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-rw-r--r--silx/math/fit/__init__.py39
-rw-r--r--silx/math/fit/bgtheories.py440
-rw-r--r--silx/math/fit/filters/filters.c20519
-rw-r--r--silx/math/fit/filters/filters.pyx412
-rw-r--r--silx/math/fit/filters/filters_wrapper.pxd71
-rw-r--r--silx/math/fit/filters/include/filters.h45
-rw-r--r--silx/math/fit/filters/src/smoothnd.c317
-rw-r--r--silx/math/fit/filters/src/snip1d.c149
-rw-r--r--silx/math/fit/filters/src/snip2d.c96
-rw-r--r--silx/math/fit/filters/src/snip3d.c186
-rw-r--r--silx/math/fit/filters/src/strip.c118
-rw-r--r--silx/math/fit/fitmanager.py1071
-rw-r--r--silx/math/fit/fittheories.py1374
-rw-r--r--silx/math/fit/fittheory.py161
-rw-r--r--silx/math/fit/functions/functions.c27541
-rw-r--r--silx/math/fit/functions/functions.pyx986
-rw-r--r--silx/math/fit/functions/functions_wrapper.pxd170
-rw-r--r--silx/math/fit/functions/include/functions.h68
-rw-r--r--silx/math/fit/functions/src/funs.c1265
-rw-r--r--silx/math/fit/leastsq.py902
-rw-r--r--silx/math/fit/peaks/include/peaks.h32
-rw-r--r--silx/math/fit/peaks/peaks.c17746
-rw-r--r--silx/math/fit/peaks/peaks.pyx176
-rw-r--r--silx/math/fit/peaks/peaks_wrapper.pxd41
-rw-r--r--silx/math/fit/peaks/src/peaks.c255
-rw-r--r--silx/math/fit/setup.py89
-rw-r--r--silx/math/fit/test/__init__.py46
-rw-r--r--silx/math/fit/test/test_bgtheories.py169
-rw-r--r--silx/math/fit/test/test_filters.py137
-rw-r--r--silx/math/fit/test/test_fit.py382
-rw-r--r--silx/math/fit/test/test_fitmanager.py498
-rw-r--r--silx/math/fit/test/test_functions.py272
-rw-r--r--silx/math/fit/test/test_peaks.py146
33 files changed, 75919 insertions, 0 deletions
diff --git a/silx/math/fit/__init__.py b/silx/math/fit/__init__.py
new file mode 100644
index 0000000..29e6a9e
--- /dev/null
+++ b/silx/math/fit/__init__.py
@@ -0,0 +1,39 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+
+from .leastsq import leastsq, chisq_alpha_beta
+from .leastsq import \
+ CFREE, CPOSITIVE, CQUOTED, CFIXED, \
+ CFACTOR, CDELTA, CSUM
+
+from .functions import *
+from .filters import *
+from .peaks import peak_search, guess_fwhm
+from .fitmanager import FitManager
+from .fittheory import FitTheory
diff --git a/silx/math/fit/bgtheories.py b/silx/math/fit/bgtheories.py
new file mode 100644
index 0000000..3cdac98
--- /dev/null
+++ b/silx/math/fit/bgtheories.py
@@ -0,0 +1,440 @@
+# coding: utf-8
+#/*##########################################################################
+#
+# Copyright (c) 2004-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+########################################################################### */
+"""This modules defines a set of background model functions and associated
+estimation functions in a format that can be imported into a
+:class:`silx.math.fit.FitManager` object.
+
+A background function is a function that you want to add to a regular fit
+function prior to fitting the sum of both functions. This is useful, for
+instance, if you need to fit multiple gaussian peaks in an array of
+measured data points when the measurement is polluted by a background signal.
+
+The models include common background models such as a constant value or a
+linear background.
+
+It also includes background computation filters - *strip* and *snip* - that
+can extract a more complex low-curvature background signal from a signal with
+peaks having higher curvatures.
+
+The source code of this module can serve as a template for defining your
+own fit background theories. The minimal skeleton of such a theory definition
+file is::
+
+ from silx.math.fit.fittheory import FitTheory
+
+ def bgfunction1(x, y0, …):
+ bg_signal = …
+ return bg_signal
+
+ def estimation_function1(x, y):
+ …
+ estimated_params = …
+ constraints = …
+ return estimated_params, constraints
+
+ THEORY = {
+ 'bg_theory_name1': FitTheory(
+ description='Description of theory 1',
+ function=bgfunction1,
+ parameters=('param name 1', 'param name 2', …),
+ estimate=estimation_function1,
+ configure=configuration_function1,
+ derivative=derivative_function1,
+ is_background=True),
+ 'theory_name_2': …,
+ }
+"""
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "16/01/2017"
+
+from collections import OrderedDict
+import numpy
+from silx.math.fit.filters import strip, snip1d,\
+ savitsky_golay
+from silx.math.fit.fittheory import FitTheory
+
+CONFIG = {
+ "SmoothingFlag": False,
+ "SmoothingWidth": 5,
+ "AnchorsFlag": False,
+ "AnchorsList": [],
+ "StripWidth": 2,
+ "StripIterations": 5000,
+ "StripThresholdFactor": 1.0,
+ "SnipWidth": 16,
+ "EstimatePolyOnStrip": True
+}
+
+# to avoid costly computations when parameters stay the same
+_BG_STRIP_OLDY = numpy.array([])
+_BG_STRIP_OLDPARS = [0, 0]
+_BG_STRIP_OLDBG = numpy.array([])
+
+_BG_SNIP_OLDY = numpy.array([])
+_BG_SNIP_OLDWIDTH = None
+_BG_SNIP_OLDBG = numpy.array([])
+
+
+_BG_OLD_ANCHORS = []
+_BG_OLD_ANCHORS_FLAG = None
+
+_BG_SMOOTH_OLDWIDTH = None
+_BG_SMOOTH_OLDFLAG = None
+
+
+def _convert_anchors_to_indices(x):
+ """Anchors stored in CONFIG["AnchorsList"] are abscissa.
+ Convert then to indices (take first index where x >= anchor),
+ then return the list of indices.
+
+ :param x: Original array of abscissa
+ :return: List of indices of anchors in x array.
+ If CONFIG['AnchorsFlag'] is False or None, or if the list
+ of indices is empty, return None.
+ """
+ # convert anchor X abscissa to index
+ if CONFIG['AnchorsFlag'] and CONFIG['AnchorsList'] is not None:
+ anchors_indices = []
+ for anchor_x in CONFIG['AnchorsList']:
+ if anchor_x <= x[0]:
+ continue
+ # take the first index where x > anchor_x
+ indices = numpy.nonzero(x >= anchor_x)[0]
+ if len(indices):
+ anchors_indices.append(min(indices))
+ if not len(anchors_indices):
+ anchors_indices = None
+ else:
+ anchors_indices = None
+
+ return anchors_indices
+
+
+def strip_bg(x, y0, width, niter):
+ """Extract and return the strip bg from y0.
+
+ Use anchors coordinates in CONFIG["AnchorsList"] if flag
+ CONFIG["AnchorsFlag"] is True. Convert anchors from x coordinate
+ to array index prior to passing it to silx.math.fit.filters.strip
+
+ :param x: Abscissa array
+ :param x: Ordinate array (data values at x positions)
+ :param width: strip width
+ :param niter: strip niter
+ """
+ global _BG_STRIP_OLDY
+ global _BG_STRIP_OLDPARS
+ global _BG_STRIP_OLDBG
+ global _BG_SMOOTH_OLDWIDTH
+ global _BG_SMOOTH_OLDFLAG
+ global _BG_OLD_ANCHORS
+ global _BG_OLD_ANCHORS_FLAG
+
+ parameters_changed =\
+ _BG_STRIP_OLDPARS != [width, niter] or\
+ _BG_SMOOTH_OLDWIDTH != CONFIG["SmoothingWidth"] or\
+ _BG_SMOOTH_OLDFLAG != CONFIG["SmoothingFlag"] or\
+ _BG_OLD_ANCHORS_FLAG != CONFIG["AnchorsFlag"] or\
+ _BG_OLD_ANCHORS != CONFIG["AnchorsList"]
+
+ # same parameters
+ if not parameters_changed:
+ # same data
+ if numpy.sum(_BG_STRIP_OLDY == y0) == len(y0):
+ # same result
+ return _BG_STRIP_OLDBG
+
+ _BG_STRIP_OLDY = y0
+ _BG_STRIP_OLDPARS = [width, niter]
+ _BG_SMOOTH_OLDWIDTH = CONFIG["SmoothingWidth"]
+ _BG_SMOOTH_OLDFLAG = CONFIG["SmoothingFlag"]
+ _BG_OLD_ANCHORS = CONFIG["AnchorsList"]
+ _BG_OLD_ANCHORS_FLAG = CONFIG["AnchorsFlag"]
+
+ y1 = savitsky_golay(y0, CONFIG["SmoothingWidth"]) if CONFIG["SmoothingFlag"] else y0
+
+ anchors_indices = _convert_anchors_to_indices(x)
+
+ background = strip(y1,
+ w=width,
+ niterations=niter,
+ factor=CONFIG["StripThresholdFactor"],
+ anchors=anchors_indices)
+
+ _BG_STRIP_OLDBG = background
+
+ return background
+
+
+def snip_bg(x, y0, width):
+ """Compute the snip bg for y0"""
+ global _BG_SNIP_OLDY
+ global _BG_SNIP_OLDWIDTH
+ global _BG_SNIP_OLDBG
+ global _BG_SMOOTH_OLDWIDTH
+ global _BG_SMOOTH_OLDFLAG
+ global _BG_OLD_ANCHORS
+ global _BG_OLD_ANCHORS_FLAG
+
+ parameters_changed =\
+ _BG_SNIP_OLDWIDTH != width or\
+ _BG_SMOOTH_OLDWIDTH != CONFIG["SmoothingWidth"] or\
+ _BG_SMOOTH_OLDFLAG != CONFIG["SmoothingFlag"] or\
+ _BG_OLD_ANCHORS_FLAG != CONFIG["AnchorsFlag"] or\
+ _BG_OLD_ANCHORS != CONFIG["AnchorsList"]
+
+ # same parameters
+ if not parameters_changed:
+ # same data
+ if numpy.sum(_BG_SNIP_OLDY == y0) == len(y0):
+ # same result
+ return _BG_SNIP_OLDBG
+
+ _BG_SNIP_OLDY = y0
+ _BG_SNIP_OLDWIDTH = width
+ _BG_SMOOTH_OLDWIDTH = CONFIG["SmoothingWidth"]
+ _BG_SMOOTH_OLDFLAG = CONFIG["SmoothingFlag"]
+ _BG_OLD_ANCHORS = CONFIG["AnchorsList"]
+ _BG_OLD_ANCHORS_FLAG = CONFIG["AnchorsFlag"]
+
+ y1 = savitsky_golay(y0, CONFIG["SmoothingWidth"]) if CONFIG["SmoothingFlag"] else y0
+
+ anchors_indices = _convert_anchors_to_indices(x)
+
+ if anchors_indices is None or not len(anchors_indices):
+ anchors_indices = [0, len(y1) - 1]
+
+ background = numpy.zeros_like(y1)
+ previous_anchor = 0
+ for anchor_index in anchors_indices:
+ if (anchor_index > previous_anchor) and (anchor_index < len(y1)):
+ background[previous_anchor:anchor_index] =\
+ snip1d(y1[previous_anchor:anchor_index],
+ width)
+ previous_anchor = anchor_index
+
+ if previous_anchor < len(y1):
+ background[previous_anchor:] = snip1d(y1[previous_anchor:],
+ width)
+
+ _BG_SNIP_OLDBG = background
+
+ return background
+
+
+def estimate_linear(x, y):
+ """
+ Estimate the linear parameters (constant, slope) of a y signal.
+
+ Strip peaks, then perform a linear regression.
+ """
+ bg = strip_bg(x, y,
+ width=CONFIG["StripWidth"],
+ niter=CONFIG["StripIterations"])
+ n = float(len(bg))
+ Sy = numpy.sum(bg)
+ Sx = float(numpy.sum(x))
+ Sxx = float(numpy.sum(x * x))
+ Sxy = float(numpy.sum(x * bg))
+
+ deno = n * Sxx - (Sx * Sx)
+ if deno != 0:
+ bg = (Sxx * Sy - Sx * Sxy) / deno
+ slope = (n * Sxy - Sx * Sy) / deno
+ else:
+ bg = 0.0
+ slope = 0.0
+ estimated_par = [bg, slope]
+ # code = 0: FREE
+ constraints = [[0, 0, 0], [0, 0, 0]]
+ return estimated_par, constraints
+
+
+def estimate_strip(x, y):
+ """Estimation function for strip parameters.
+
+ Return parameters as defined in CONFIG dict,
+ set constraints to FIXED.
+ """
+ estimated_par = [CONFIG["StripWidth"],
+ CONFIG["StripIterations"]]
+ constraints = numpy.zeros((len(estimated_par), 3), numpy.float)
+ # code = 3: FIXED
+ constraints[0][0] = 3
+ constraints[1][0] = 3
+ return estimated_par, constraints
+
+
+def estimate_snip(x, y):
+ """Estimation function for snip parameters.
+
+ Return parameters as defined in CONFIG dict,
+ set constraints to FIXED.
+ """
+ estimated_par = [CONFIG["SnipWidth"]]
+ constraints = numpy.zeros((len(estimated_par), 3), numpy.float)
+ # code = 3: FIXED
+ constraints[0][0] = 3
+ return estimated_par, constraints
+
+
+def poly(x, y, *pars):
+ """Order n polynomial.
+ The order of the polynomial is defined by the number of
+ coefficients (``*pars``).
+
+ """
+ p = numpy.poly1d(pars)
+ return p(x)
+
+
+def estimate_poly(x, y, deg=2):
+ """Estimate polynomial coefficients.
+
+ """
+ # extract bg signal with strip, to estimate polynomial on background
+ if CONFIG["EstimatePolyOnStrip"]:
+ y = strip_bg(x, y,
+ CONFIG["StripWidth"],
+ CONFIG["StripIterations"])
+ pcoeffs = numpy.polyfit(x, y, deg)
+ cons = numpy.zeros((deg + 1, 3), numpy.float)
+ return pcoeffs, cons
+
+
+def estimate_quadratic_poly(x, y):
+ """Estimate quadratic polynomial coefficients.
+ """
+ return estimate_poly(x, y, deg=2)
+
+
+def estimate_cubic_poly(x, y):
+ """Estimate cubic polynomial coefficients.
+ """
+ return estimate_poly(x, y, deg=3)
+
+
+def estimate_quartic_poly(x, y):
+ """Estimate degree 4 polynomial coefficients.
+ """
+ return estimate_poly(x, y, deg=4)
+
+
+def estimate_quintic_poly(x, y):
+ """Estimate degree 5 polynomial coefficients.
+ """
+ return estimate_poly(x, y, deg=5)
+
+
+def configure(**kw):
+ """Update the CONFIG dict
+ """
+ # inspect **kw to find known keys, update them in CONFIG
+ for key in CONFIG:
+ if key in kw:
+ CONFIG[key] = kw[key]
+
+ return CONFIG
+
+
+THEORY = OrderedDict(
+ (('No Background',
+ FitTheory(
+ description="No background function",
+ function=lambda x, y0: numpy.zeros_like(x),
+ parameters=[],
+ is_background=True)),
+ ('Constant',
+ FitTheory(
+ description='Constant background',
+ function=lambda x, y0, c: c * numpy.ones_like(x),
+ parameters=['Constant', ],
+ estimate=lambda x, y: ([min(y)], [[0, 0, 0]]),
+ is_background=True)),
+ ('Linear',
+ FitTheory(
+ description="Linear background, parameters 'Constant' and"
+ " 'Slope'",
+ function=lambda x, y0, a, b: a + b * x,
+ parameters=['Constant', 'Slope'],
+ estimate=estimate_linear,
+ configure=configure,
+ is_background=True)),
+ ('Strip',
+ FitTheory(
+ description="Compute background using a strip filter\n"
+ "Parameters 'StripWidth', 'StripIterations'",
+ function=strip_bg,
+ parameters=['StripWidth', 'StripIterations'],
+ estimate=estimate_strip,
+ configure=configure,
+ is_background=True)),
+ ('Snip',
+ FitTheory(
+ description="Compute background using a snip filter\n"
+ "Parameter 'SnipWidth'",
+ function=snip_bg,
+ parameters=['SnipWidth'],
+ estimate=estimate_snip,
+ configure=configure,
+ is_background=True)),
+ ('Degree 2 Polynomial',
+ FitTheory(
+ description="Quadratic polynomial background, Parameters "
+ "'a', 'b' and 'c'\ny = a*x^2 + b*x +c",
+ function=poly,
+ parameters=['a', 'b', 'c'],
+ estimate=estimate_quadratic_poly,
+ configure=configure,
+ is_background=True)),
+ ('Degree 3 Polynomial',
+ FitTheory(
+ description="Cubic polynomial background, Parameters "
+ "'a', 'b', 'c' and 'd'\n"
+ "y = a*x^3 + b*x^2 + c*x + d",
+ function=poly,
+ parameters=['a', 'b', 'c', 'd'],
+ estimate=estimate_cubic_poly,
+ configure=configure,
+ is_background=True)),
+ ('Degree 4 Polynomial',
+ FitTheory(
+ description="Quartic polynomial background\n"
+ "y = a*x^4 + b*x^3 + c*x^2 + d*x + e",
+ function=poly,
+ parameters=['a', 'b', 'c', 'd', 'e'],
+ estimate=estimate_quartic_poly,
+ configure=configure,
+ is_background=True)),
+ ('Degree 5 Polynomial',
+ FitTheory(
+ description="Quaintic polynomial background\n"
+ "y = a*x^5 + b*x^4 + c*x^3 + d*x^2 + e*x + f",
+ function=poly,
+ parameters=['a', 'b', 'c', 'd', 'e', 'f'],
+ estimate=estimate_quintic_poly,
+ configure=configure,
+ is_background=True))))
diff --git a/silx/math/fit/filters/filters.c b/silx/math/fit/filters/filters.c
new file mode 100644
index 0000000..fd83ee7
--- /dev/null
+++ b/silx/math/fit/filters/filters.c
@@ -0,0 +1,20519 @@
+/* Generated by Cython 0.21.1 */
+
+#define PY_SSIZE_T_CLEAN
+#ifndef CYTHON_USE_PYLONG_INTERNALS
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#else
+#include "pyconfig.h"
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 1
+#else
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#endif
+#endif
+#endif
+#include "Python.h"
+#ifndef Py_PYTHON_H
+ #error Python headers needed to compile C extensions, please install development version of Python.
+#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000)
+ #error Cython requires Python 2.6+ or Python 3.2+.
+#else
+#define CYTHON_ABI "0_21_1"
+#include <stddef.h>
+#ifndef offsetof
+#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
+#endif
+#if !defined(WIN32) && !defined(MS_WINDOWS)
+ #ifndef __stdcall
+ #define __stdcall
+ #endif
+ #ifndef __cdecl
+ #define __cdecl
+ #endif
+ #ifndef __fastcall
+ #define __fastcall
+ #endif
+#endif
+#ifndef DL_IMPORT
+ #define DL_IMPORT(t) t
+#endif
+#ifndef DL_EXPORT
+ #define DL_EXPORT(t) t
+#endif
+#ifndef PY_LONG_LONG
+ #define PY_LONG_LONG LONG_LONG
+#endif
+#ifndef Py_HUGE_VAL
+ #define Py_HUGE_VAL HUGE_VAL
+#endif
+#ifdef PYPY_VERSION
+#define CYTHON_COMPILING_IN_PYPY 1
+#define CYTHON_COMPILING_IN_CPYTHON 0
+#else
+#define CYTHON_COMPILING_IN_PYPY 0
+#define CYTHON_COMPILING_IN_CPYTHON 1
+#endif
+#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600
+#define Py_OptimizeFlag 0
+#endif
+#define __PYX_BUILD_PY_SSIZE_T "n"
+#define CYTHON_FORMAT_SSIZE_T "z"
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyClass_Type
+#else
+ #define __Pyx_BUILTIN_MODULE_NAME "builtins"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyType_Type
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define Py_TPFLAGS_CHECKTYPES 0
+ #define Py_TPFLAGS_HAVE_INDEX 0
+ #define Py_TPFLAGS_HAVE_NEWBUFFER 0
+#endif
+#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE)
+ #define Py_TPFLAGS_HAVE_FINALIZE 0
+#endif
+#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
+ #define CYTHON_PEP393_ENABLED 1
+ #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \
+ 0 : _PyUnicode_Ready((PyObject *)(op)))
+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
+ #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u)
+ #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u)
+ #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
+#else
+ #define CYTHON_PEP393_ENABLED 0
+ #define __Pyx_PyUnicode_READY(op) (0)
+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
+ #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
+ #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
+ #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
+#endif
+#if CYTHON_COMPILING_IN_PYPY
+ #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyFrozenSet_Size(s) PyObject_Size(s)
+#else
+ #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \
+ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
+ #define __Pyx_PyFrozenSet_Size(s) PySet_Size(s)
+#endif
+#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
+#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
+#else
+ #define __Pyx_PyString_Format(a, b) PyString_Format(a, b)
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBaseString_Type PyUnicode_Type
+ #define PyStringObject PyUnicodeObject
+ #define PyString_Type PyUnicode_Type
+ #define PyString_Check PyUnicode_Check
+ #define PyString_CheckExact PyUnicode_CheckExact
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
+ #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
+#else
+ #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
+ #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
+#endif
+#ifndef PySet_CheckExact
+ #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
+#endif
+#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
+#if PY_MAJOR_VERSION >= 3
+ #define PyIntObject PyLongObject
+ #define PyInt_Type PyLong_Type
+ #define PyInt_Check(op) PyLong_Check(op)
+ #define PyInt_CheckExact(op) PyLong_CheckExact(op)
+ #define PyInt_FromString PyLong_FromString
+ #define PyInt_FromUnicode PyLong_FromUnicode
+ #define PyInt_FromLong PyLong_FromLong
+ #define PyInt_FromSize_t PyLong_FromSize_t
+ #define PyInt_FromSsize_t PyLong_FromSsize_t
+ #define PyInt_AsLong PyLong_AsLong
+ #define PyInt_AS_LONG PyLong_AS_LONG
+ #define PyInt_AsSsize_t PyLong_AsSsize_t
+ #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
+ #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
+ #define PyNumber_Int PyNumber_Long
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBoolObject PyLongObject
+#endif
+#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
+ #ifndef PyUnicode_InternFromString
+ #define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
+ #endif
+#endif
+#if PY_VERSION_HEX < 0x030200A4
+ typedef long Py_hash_t;
+ #define __Pyx_PyInt_FromHash_t PyInt_FromLong
+ #define __Pyx_PyInt_AsHash_t PyInt_AsLong
+#else
+ #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
+ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
+#else
+ #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
+#endif
+#ifndef CYTHON_INLINE
+ #if defined(__GNUC__)
+ #define CYTHON_INLINE __inline__
+ #elif defined(_MSC_VER)
+ #define CYTHON_INLINE __inline
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_INLINE inline
+ #else
+ #define CYTHON_INLINE
+ #endif
+#endif
+#ifndef CYTHON_RESTRICT
+ #if defined(__GNUC__)
+ #define CYTHON_RESTRICT __restrict__
+ #elif defined(_MSC_VER) && _MSC_VER >= 1400
+ #define CYTHON_RESTRICT __restrict
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_RESTRICT restrict
+ #else
+ #define CYTHON_RESTRICT
+ #endif
+#endif
+#ifdef NAN
+#define __PYX_NAN() ((float) NAN)
+#else
+static CYTHON_INLINE float __PYX_NAN() {
+ /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and
+ a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is
+ a quiet NaN. */
+ float value;
+ memset(&value, 0xFF, sizeof(value));
+ return value;
+}
+#endif
+#ifdef __cplusplus
+template<typename T>
+void __Pyx_call_destructor(T* x) {
+ x->~T();
+}
+#endif
+
+
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y)
+#else
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y)
+#endif
+
+#ifndef __PYX_EXTERN_C
+ #ifdef __cplusplus
+ #define __PYX_EXTERN_C extern "C"
+ #else
+ #define __PYX_EXTERN_C extern
+ #endif
+#endif
+
+#if defined(WIN32) || defined(MS_WINDOWS)
+#define _USE_MATH_DEFINES
+#endif
+#include <math.h>
+#define __PYX_HAVE__filters
+#define __PYX_HAVE_API__filters
+#include "filters.h"
+#include "pythread.h"
+#include "string.h"
+#include "stdlib.h"
+#include "stdio.h"
+#include "pystate.h"
+#ifdef _OPENMP
+#include <omp.h>
+#endif /* _OPENMP */
+
+#ifdef PYREX_WITHOUT_ASSERTIONS
+#define CYTHON_WITHOUT_ASSERTIONS
+#endif
+
+#ifndef CYTHON_UNUSED
+# if defined(__GNUC__)
+# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+#endif
+typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding;
+ const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
+
+#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
+#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
+#define __PYX_DEFAULT_STRING_ENCODING ""
+#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
+#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \
+ (sizeof(type) < sizeof(Py_ssize_t)) || \
+ (sizeof(type) > sizeof(Py_ssize_t) && \
+ likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX) && \
+ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \
+ v == (type)PY_SSIZE_T_MIN))) || \
+ (sizeof(type) == sizeof(Py_ssize_t) && \
+ (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX))) )
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
+#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
+#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
+#define __Pyx_PyBytes_FromString PyBytes_FromString
+#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#else
+ #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
+#endif
+#define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s)
+#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s)
+#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s)
+#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s)
+#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s)
+#if PY_MAJOR_VERSION < 3
+static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
+{
+ const Py_UNICODE *u_end = u;
+ while (*u_end++) ;
+ return (size_t)(u_end - u - 1);
+}
+#else
+#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
+#endif
+#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
+#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
+#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
+#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
+#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
+#if CYTHON_COMPILING_IN_CPYTHON
+#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
+#else
+#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
+#endif
+#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+static int __Pyx_sys_getdefaultencoding_not_ascii;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ PyObject* ascii_chars_u = NULL;
+ PyObject* ascii_chars_b = NULL;
+ const char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ if (strcmp(default_encoding_c, "ascii") == 0) {
+ __Pyx_sys_getdefaultencoding_not_ascii = 0;
+ } else {
+ char ascii_chars[128];
+ int c;
+ for (c = 0; c < 128; c++) {
+ ascii_chars[c] = c;
+ }
+ __Pyx_sys_getdefaultencoding_not_ascii = 1;
+ ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
+ if (!ascii_chars_u) goto bad;
+ ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
+ if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
+ PyErr_Format(
+ PyExc_ValueError,
+ "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
+ default_encoding_c);
+ goto bad;
+ }
+ Py_DECREF(ascii_chars_u);
+ Py_DECREF(ascii_chars_b);
+ }
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ Py_XDECREF(ascii_chars_u);
+ Py_XDECREF(ascii_chars_b);
+ return -1;
+}
+#endif
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
+#else
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+static char* __PYX_DEFAULT_STRING_ENCODING;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
+ if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
+ strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ return -1;
+}
+#endif
+#endif
+
+
+/* Test for GCC > 2.95 */
+#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
+ #define likely(x) __builtin_expect(!!(x), 1)
+ #define unlikely(x) __builtin_expect(!!(x), 0)
+#else /* !__GNUC__ or GCC < 2.95 */
+ #define likely(x) (x)
+ #define unlikely(x) (x)
+#endif /* __GNUC__ */
+
+static PyObject *__pyx_m;
+static PyObject *__pyx_d;
+static PyObject *__pyx_b;
+static PyObject *__pyx_empty_tuple;
+static PyObject *__pyx_empty_bytes;
+static int __pyx_lineno;
+static int __pyx_clineno = 0;
+static const char * __pyx_cfilenm= __FILE__;
+static const char *__pyx_filename;
+
+
+static const char *__pyx_f[] = {
+ "filters.pyx",
+ "stringsource",
+};
+struct __pyx_memoryview_obj;
+typedef struct {
+ struct __pyx_memoryview_obj *memview;
+ char *data;
+ Py_ssize_t shape[8];
+ Py_ssize_t strides[8];
+ Py_ssize_t suboffsets[8];
+} __Pyx_memviewslice;
+
+#define IS_UNSIGNED(type) (((type) -1) > 0)
+struct __Pyx_StructField_;
+#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
+typedef struct {
+ const char* name;
+ struct __Pyx_StructField_* fields;
+ size_t size;
+ size_t arraysize[8];
+ int ndim;
+ char typegroup;
+ char is_unsigned;
+ int flags;
+} __Pyx_TypeInfo;
+typedef struct __Pyx_StructField_ {
+ __Pyx_TypeInfo* type;
+ const char* name;
+ size_t offset;
+} __Pyx_StructField;
+typedef struct {
+ __Pyx_StructField* field;
+ size_t parent_offset;
+} __Pyx_BufFmt_StackElem;
+typedef struct {
+ __Pyx_StructField root;
+ __Pyx_BufFmt_StackElem* head;
+ size_t fmt_offset;
+ size_t new_count, enc_count;
+ size_t struct_alignment;
+ int is_complex;
+ char enc_type;
+ char new_packmode;
+ char enc_packmode;
+ char is_valid_array;
+} __Pyx_BufFmt_Context;
+
+#include <pythread.h>
+#ifndef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 1
+#endif
+#define __pyx_atomic_int_type int
+#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \
+ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \
+ !defined(__i386__)
+ #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
+ #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using GNU atomics"
+ #endif
+#elif CYTHON_ATOMICS && MSC_VER
+ #include <Windows.h>
+ #define __pyx_atomic_int_type LONG
+ #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using MSVC atomics"
+ #endif
+#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
+ #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using Intel atomics"
+ #endif
+#else
+ #undef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 0
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Not using atomics"
+ #endif
+#endif
+typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
+#if CYTHON_ATOMICS
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+#else
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+#endif
+
+
+/*--- Type declarations ---*/
+struct __pyx_array_obj;
+struct __pyx_MemviewEnum_obj;
+struct __pyx_memoryview_obj;
+struct __pyx_memoryviewslice_obj;
+
+/* "View.MemoryView":99
+ *
+ * @cname("__pyx_array")
+ * cdef class array: # <<<<<<<<<<<<<<
+ *
+ * cdef:
+ */
+struct __pyx_array_obj {
+ PyObject_HEAD
+ char *data;
+ Py_ssize_t len;
+ char *format;
+ int ndim;
+ Py_ssize_t *_shape;
+ Py_ssize_t *_strides;
+ Py_ssize_t itemsize;
+ PyObject *mode;
+ PyObject *_format;
+ void (*callback_free_data)(void *);
+ int free_data;
+ int dtype_is_object;
+};
+
+
+/* "View.MemoryView":269
+ *
+ * @cname('__pyx_MemviewEnum')
+ * cdef class Enum(object): # <<<<<<<<<<<<<<
+ * cdef object name
+ * def __init__(self, name):
+ */
+struct __pyx_MemviewEnum_obj {
+ PyObject_HEAD
+ PyObject *name;
+};
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+struct __pyx_memoryview_obj {
+ PyObject_HEAD
+ struct __pyx_vtabstruct_memoryview *__pyx_vtab;
+ PyObject *obj;
+ PyObject *_size;
+ PyObject *_array_interface;
+ PyThread_type_lock lock;
+ __pyx_atomic_int acquisition_count[2];
+ __pyx_atomic_int *acquisition_count_aligned_p;
+ Py_buffer view;
+ int flags;
+ int dtype_is_object;
+ __Pyx_TypeInfo *typeinfo;
+};
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+struct __pyx_memoryviewslice_obj {
+ struct __pyx_memoryview_obj __pyx_base;
+ __Pyx_memviewslice from_slice;
+ PyObject *from_object;
+ PyObject *(*to_object_func)(char *);
+ int (*to_dtype_func)(char *, PyObject *);
+};
+
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+
+struct __pyx_vtabstruct_memoryview {
+ char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
+ PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
+};
+static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+
+struct __pyx_vtabstruct__memoryviewslice {
+ struct __pyx_vtabstruct_memoryview __pyx_base;
+};
+static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
+#ifndef CYTHON_REFNANNY
+ #define CYTHON_REFNANNY 0
+#endif
+#if CYTHON_REFNANNY
+ typedef struct {
+ void (*INCREF)(void*, PyObject*, int);
+ void (*DECREF)(void*, PyObject*, int);
+ void (*GOTREF)(void*, PyObject*, int);
+ void (*GIVEREF)(void*, PyObject*, int);
+ void* (*SetupContext)(const char*, int, const char*);
+ void (*FinishContext)(void**);
+ } __Pyx_RefNannyAPIStruct;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname);
+ #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL;
+#ifdef WITH_THREAD
+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
+ if (acquire_gil) { \
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \
+ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \
+ PyGILState_Release(__pyx_gilstate_save); \
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+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
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+ #define __Pyx_RefNannyFinishContext() \
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+ #define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GOTREF(r) __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
+ #define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
+ #define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
+ #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
+#else
+ #define __Pyx_RefNannyDeclarations
+ #define __Pyx_RefNannySetupContext(name, acquire_gil)
+ #define __Pyx_RefNannyFinishContext()
+ #define __Pyx_INCREF(r) Py_INCREF(r)
+ #define __Pyx_DECREF(r) Py_DECREF(r)
+ #define __Pyx_GOTREF(r)
+ #define __Pyx_GIVEREF(r)
+ #define __Pyx_XINCREF(r) Py_XINCREF(r)
+ #define __Pyx_XDECREF(r) Py_XDECREF(r)
+ #define __Pyx_XGOTREF(r)
+ #define __Pyx_XGIVEREF(r)
+#endif
+#define __Pyx_XDECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_XDECREF(tmp); \
+ } while (0)
+#define __Pyx_DECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_DECREF(tmp); \
+ } while (0)
+#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
+#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
+ PyTypeObject* tp = Py_TYPE(obj);
+ if (likely(tp->tp_getattro))
+ return tp->tp_getattro(obj, attr_name);
+#if PY_MAJOR_VERSION < 3
+ if (likely(tp->tp_getattr))
+ return tp->tp_getattr(obj, PyString_AS_STRING(attr_name));
+#endif
+ return PyObject_GetAttr(obj, attr_name);
+}
+#else
+#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
+#endif
+
+static PyObject *__Pyx_GetBuiltinName(PyObject *name);
+
+static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
+
+static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \
+ PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \
+ const char* function_name);
+
+static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
+ Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
+
+static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
+#else
+#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
+#endif
+
+static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
+
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
+
+static void __Pyx_RaiseBufferIndexError(int axis);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
+#endif
+
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
+
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
+ __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
+
+#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
+#define __Pyx_MEMVIEW_DIRECT 1
+#define __Pyx_MEMVIEW_PTR 2
+#define __Pyx_MEMVIEW_FULL 4
+#define __Pyx_MEMVIEW_CONTIG 8
+#define __Pyx_MEMVIEW_STRIDED 16
+#define __Pyx_MEMVIEW_FOLLOW 32
+#define __Pyx_IS_C_CONTIG 1
+#define __Pyx_IS_F_CONTIG 2
+static int __Pyx_init_memviewslice(
+ struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference);
+static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
+#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
+#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
+#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
+static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
+
+#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \
+ (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \
+ __Pyx_GetItemInt_Generic(o, to_py_func(i))))
+#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck);
+
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact);
+
+#include <string.h>
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
+
+#if PY_MAJOR_VERSION >= 3
+#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
+#else
+#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
+#endif
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */
+
+#ifndef __PYX_FORCE_INIT_THREADS
+ #define __PYX_FORCE_INIT_THREADS 0
+#endif
+
+#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))
+
+static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb);
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb);
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len)) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
+#endif
+
+static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject* none = _PyList_Extend((PyListObject*)L, v);
+ if (unlikely(!none))
+ return -1;
+ Py_DECREF(none);
+ return 0;
+#else
+ return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
+#endif
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
+#endif
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
+
+static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */
+
+static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/
+static void __Pyx_WriteUnraisable(const char *name, int clineno,
+ int lineno, const char *filename,
+ int full_traceback);
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
+#else
+#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL)
+#endif
+
+typedef struct {
+ int code_line;
+ PyCodeObject* code_object;
+} __Pyx_CodeObjectCacheEntry;
+struct __Pyx_CodeObjectCache {
+ int count;
+ int max_count;
+ __Pyx_CodeObjectCacheEntry* entries;
+};
+static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
+static PyCodeObject *__pyx_find_code_object(int code_line);
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
+
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename);
+
+typedef struct {
+ Py_ssize_t shape, strides, suboffsets;
+} __Pyx_Buf_DimInfo;
+typedef struct {
+ size_t refcount;
+ Py_buffer pybuffer;
+} __Pyx_Buffer;
+typedef struct {
+ __Pyx_Buffer *rcbuffer;
+ char *data;
+ __Pyx_Buf_DimInfo diminfo[8];
+} __Pyx_LocalBuf_ND;
+
+#if PY_MAJOR_VERSION < 3
+ static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
+ static void __Pyx_ReleaseBuffer(Py_buffer *view);
+#else
+ #define __Pyx_GetBuffer PyObject_GetBuffer
+ #define __Pyx_ReleaseBuffer PyBuffer_Release
+#endif
+
+
+static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
+static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
+
+static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
+
+static PyObject *__pyx_memview_get_double(const char *itemp);
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
+
+static PyObject *__pyx_memview_get_long(const char *itemp);
+static int __pyx_memview_set_long(const char *itemp, PyObject *obj);
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
+
+static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim);
+
+static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize);
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object);
+
+static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
+
+static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
+
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj);
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *);
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_long(PyObject *);
+
+static int __Pyx_check_binary_version(void);
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
+
+static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
+static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+
+/* Module declarations from 'cython.view' */
+
+/* Module declarations from 'cython' */
+
+/* Module declarations from 'filters_wrapper' */
+
+/* Module declarations from 'filters' */
+static PyTypeObject *__pyx_array_type = 0;
+static PyTypeObject *__pyx_MemviewEnum_type = 0;
+static PyTypeObject *__pyx_memoryview_type = 0;
+static PyTypeObject *__pyx_memoryviewslice_type = 0;
+static PyObject *generic = 0;
+static PyObject *strided = 0;
+static PyObject *indirect = 0;
+static PyObject *contiguous = 0;
+static PyObject *indirect_contiguous = 0;
+static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
+static void *__pyx_align_pointer(void *, size_t); /*proto*/
+static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
+static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
+static PyObject *_unellipsify(PyObject *, int); /*proto*/
+static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
+static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
+static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
+static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
+static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
+static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
+static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
+static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
+static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
+static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
+static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
+static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
+static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
+static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
+static __Pyx_TypeInfo __Pyx_TypeInfo_long = { "long", NULL, sizeof(long), { 0 }, 0, IS_UNSIGNED(long) ? 'U' : 'I', IS_UNSIGNED(long), 0 };
+#define __Pyx_MODULE_NAME "filters"
+int __pyx_module_is_main_filters = 0;
+
+/* Implementation of 'filters' */
+static PyObject *__pyx_builtin_TypeError;
+static PyObject *__pyx_builtin_ValueError;
+static PyObject *__pyx_builtin_MemoryError;
+static PyObject *__pyx_builtin_enumerate;
+static PyObject *__pyx_builtin_range;
+static PyObject *__pyx_builtin_Ellipsis;
+static PyObject *__pyx_builtin_xrange;
+static PyObject *__pyx_builtin_id;
+static PyObject *__pyx_builtin_IndexError;
+static PyObject *__pyx_pf_7filters_strip(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data, PyObject *__pyx_v_w, PyObject *__pyx_v_niterations, PyObject *__pyx_v_factor, PyObject *__pyx_v_anchors); /* proto */
+static PyObject *__pyx_pf_7filters_2snip1d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data, PyObject *__pyx_v_snip_width); /* proto */
+static PyObject *__pyx_pf_7filters_4snip2d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data, PyObject *__pyx_v_snip_width); /* proto */
+static PyObject *__pyx_pf_7filters_6snip3d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data, PyObject *__pyx_v_snip_width); /* proto */
+static PyObject *__pyx_pf_7filters_8savitsky_golay(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data, PyObject *__pyx_v_npoints); /* proto */
+static PyObject *__pyx_pf_7filters_10smooth1d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data); /* proto */
+static PyObject *__pyx_pf_7filters_12smooth2d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data); /* proto */
+static PyObject *__pyx_pf_7filters_14smooth3d(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_data); /* proto */
+static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
+static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
+static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
+static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
+static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
+static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
+static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static char __pyx_k_C[] = "C";
+static char __pyx_k_O[] = "O";
+static char __pyx_k_c[] = "c";
+static char __pyx_k_w[] = "w";
+static char __pyx_k_id[] = "id";
+static char __pyx_k_nx[] = "nx";
+static char __pyx_k_ny[] = "ny";
+static char __pyx_k_nz[] = "nz";
+static char __pyx_k_MIT[] = "MIT";
+static char __pyx_k_int[] = "int_";
+static char __pyx_k_len[] = "__len__";
+static char __pyx_k_obj[] = "obj";
+static char __pyx_k_base[] = "base";
+static char __pyx_k_copy[] = "copy";
+static char __pyx_k_data[] = "data";
+static char __pyx_k_date[] = "__date__";
+static char __pyx_k_main[] = "__main__";
+static char __pyx_k_mode[] = "mode";
+static char __pyx_k_name[] = "name";
+static char __pyx_k_ndim[] = "ndim";
+static char __pyx_k_pack[] = "pack";
+static char __pyx_k_size[] = "size";
+static char __pyx_k_step[] = "step";
+static char __pyx_k_stop[] = "stop";
+static char __pyx_k_test[] = "__test__";
+static char __pyx_k_array[] = "array";
+static char __pyx_k_class[] = "__class__";
+static char __pyx_k_dtype[] = "dtype";
+static char __pyx_k_empty[] = "empty";
+static char __pyx_k_error[] = "error";
+static char __pyx_k_flags[] = "flags";
+static char __pyx_k_nrows[] = "nrows";
+static char __pyx_k_numpy[] = "numpy";
+static char __pyx_k_order[] = "order";
+static char __pyx_k_range[] = "range";
+static char __pyx_k_shape[] = "shape";
+static char __pyx_k_start[] = "start";
+static char __pyx_k_strip[] = "strip";
+static char __pyx_k_data_c[] = "data_c";
+static char __pyx_k_factor[] = "factor";
+static char __pyx_k_format[] = "format";
+static char __pyx_k_import[] = "__import__";
+static char __pyx_k_logger[] = "_logger";
+static char __pyx_k_name_2[] = "__name__";
+static char __pyx_k_output[] = "output";
+static char __pyx_k_snip1d[] = "snip1d";
+static char __pyx_k_snip2d[] = "snip2d";
+static char __pyx_k_snip3d[] = "snip3d";
+static char __pyx_k_status[] = "status";
+static char __pyx_k_struct[] = "struct";
+static char __pyx_k_unpack[] = "unpack";
+static char __pyx_k_xrange[] = "xrange";
+static char __pyx_k_anchors[] = "anchors";
+static char __pyx_k_asarray[] = "asarray";
+static char __pyx_k_authors[] = "__authors__";
+static char __pyx_k_filters[] = "filters";
+static char __pyx_k_float64[] = "float64";
+static char __pyx_k_fortran[] = "fortran";
+static char __pyx_k_input_c[] = "input_c";
+static char __pyx_k_license[] = "__license__";
+static char __pyx_k_logging[] = "logging";
+static char __pyx_k_memview[] = "memview";
+static char __pyx_k_ndarray[] = "ndarray";
+static char __pyx_k_npoints[] = "npoints";
+static char __pyx_k_reshape[] = "reshape";
+static char __pyx_k_Ellipsis[] = "Ellipsis";
+static char __pyx_k_P_Knobel[] = "P. Knobel";
+static char __pyx_k_itemsize[] = "itemsize";
+static char __pyx_k_ncolumns[] = "ncolumns";
+static char __pyx_k_smooth1d[] = "smooth1d";
+static char __pyx_k_smooth2d[] = "smooth2d";
+static char __pyx_k_smooth3d[] = "smooth3d";
+static char __pyx_k_TypeError[] = "TypeError";
+static char __pyx_k_anchors_c[] = "anchors_c";
+static char __pyx_k_enumerate[] = "enumerate";
+static char __pyx_k_getLogger[] = "getLogger";
+static char __pyx_k_22_06_2016[] = "22/06/2016";
+static char __pyx_k_IndexError[] = "IndexError";
+static char __pyx_k_ValueError[] = "ValueError";
+static char __pyx_k_data_shape[] = "data_shape";
+static char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
+static char __pyx_k_snip_width[] = "snip_width";
+static char __pyx_k_MemoryError[] = "MemoryError";
+static char __pyx_k_basicConfig[] = "basicConfig";
+static char __pyx_k_len_anchors[] = "len_anchors";
+static char __pyx_k_niterations[] = "niterations";
+static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
+static char __pyx_k_savitsky_golay[] = "savitsky_golay";
+static char __pyx_k_allocate_buffer[] = "allocate_buffer";
+static char __pyx_k_dtype_is_object[] = "dtype_is_object";
+static char __pyx_k_or_a_numpy_array[] = "or a numpy array";
+static char __pyx_k_strided_and_direct[] = "<strided and direct>";
+static char __pyx_k_or_a_2D_numpy_array[] = "or a 2D numpy array";
+static char __pyx_k_or_a_3D_numpy_array[] = "or a 3D numpy array";
+static char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
+static char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
+static char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
+static char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
+static char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
+static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
+static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)";
+static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct";
+static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
+static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)";
+static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)";
+static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
+static char __pyx_k_than_3_and_smaller_than_100[] = "than 3 and smaller than 100.";
+static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
+static char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
+static char __pyx_k_This_module_provides_background[] = "This module provides background extraction functions and smoothing\nfunctions. These functions are extracted from PyMca module SpecFitFuns.\n\nIndex of background extraction functions:\n------------------------------------------\n\n - :func:`strip`\n - :func:`snip1d`\n - :func:`snip2d`\n - :func:`snip3d`\n\nSmoothing functions:\n--------------------\n\n - :func:`savitsky_golay`\n - :func:`smooth1d`\n - :func:`smooth2d`\n - :func:`smooth3d`\n\nAPI documentation:\n-------------------\n\n";
+static char __pyx_k_data_must_be_a_2D_sequence_list[] = "data must be a 2D sequence (list, tuple) ";
+static char __pyx_k_data_must_be_a_3D_sequence_list[] = "data must be a 3D sequence (list, tuple) ";
+static char __pyx_k_mntdirect__scisoft_users_tvince[] = "/mntdirect/_scisoft/users/tvincent/src/silx/silx/math/fit/filters/filters.pyx";
+static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced";
+static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
+static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
+static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions";
+static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
+static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
+static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
+static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
+static char __pyx_k_Smoothing_failed_Check_that_npoi[] = "Smoothing failed. Check that npoints is greater ";
+static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
+static char __pyx_k_data_array_must_be_2_dimensional[] = "data array must be 2-dimensional";
+static char __pyx_k_data_array_must_be_3_dimensional[] = "data array must be 3-dimensional";
+static char __pyx_k_data_must_be_a_sequence_list_tup[] = "data must be a sequence (list, tuple) ";
+static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
+static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
+static PyObject *__pyx_kp_s_22_06_2016;
+static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
+static PyObject *__pyx_n_s_C;
+static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
+static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
+static PyObject *__pyx_n_s_Ellipsis;
+static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
+static PyObject *__pyx_n_s_IndexError;
+static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
+static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
+static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
+static PyObject *__pyx_n_s_MIT;
+static PyObject *__pyx_n_s_MemoryError;
+static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
+static PyObject *__pyx_kp_s_MemoryView_of_r_object;
+static PyObject *__pyx_n_b_O;
+static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
+static PyObject *__pyx_kp_s_P_Knobel;
+static PyObject *__pyx_kp_s_Smoothing_failed_Check_that_npoi;
+static PyObject *__pyx_n_s_TypeError;
+static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
+static PyObject *__pyx_n_s_ValueError;
+static PyObject *__pyx_n_s_allocate_buffer;
+static PyObject *__pyx_n_s_anchors;
+static PyObject *__pyx_n_s_anchors_c;
+static PyObject *__pyx_n_s_array;
+static PyObject *__pyx_n_s_asarray;
+static PyObject *__pyx_n_s_authors;
+static PyObject *__pyx_n_s_base;
+static PyObject *__pyx_n_s_basicConfig;
+static PyObject *__pyx_n_s_c;
+static PyObject *__pyx_n_u_c;
+static PyObject *__pyx_n_s_class;
+static PyObject *__pyx_kp_s_contiguous_and_direct;
+static PyObject *__pyx_kp_s_contiguous_and_indirect;
+static PyObject *__pyx_n_s_copy;
+static PyObject *__pyx_n_s_data;
+static PyObject *__pyx_kp_s_data_array_must_be_2_dimensional;
+static PyObject *__pyx_kp_s_data_array_must_be_3_dimensional;
+static PyObject *__pyx_n_s_data_c;
+static PyObject *__pyx_kp_s_data_must_be_a_2D_sequence_list;
+static PyObject *__pyx_kp_s_data_must_be_a_3D_sequence_list;
+static PyObject *__pyx_kp_s_data_must_be_a_sequence_list_tup;
+static PyObject *__pyx_n_s_data_shape;
+static PyObject *__pyx_n_s_date;
+static PyObject *__pyx_n_s_dtype;
+static PyObject *__pyx_n_s_dtype_is_object;
+static PyObject *__pyx_n_s_empty;
+static PyObject *__pyx_n_s_enumerate;
+static PyObject *__pyx_n_s_error;
+static PyObject *__pyx_n_s_factor;
+static PyObject *__pyx_n_s_filters;
+static PyObject *__pyx_n_s_flags;
+static PyObject *__pyx_n_s_float64;
+static PyObject *__pyx_n_s_format;
+static PyObject *__pyx_n_s_fortran;
+static PyObject *__pyx_n_u_fortran;
+static PyObject *__pyx_n_s_getLogger;
+static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
+static PyObject *__pyx_n_s_id;
+static PyObject *__pyx_n_s_import;
+static PyObject *__pyx_n_s_input_c;
+static PyObject *__pyx_n_s_int;
+static PyObject *__pyx_n_s_itemsize;
+static PyObject *__pyx_kp_s_itemsize_0_for_cython_array;
+static PyObject *__pyx_n_s_len;
+static PyObject *__pyx_n_s_len_anchors;
+static PyObject *__pyx_n_s_license;
+static PyObject *__pyx_n_s_logger;
+static PyObject *__pyx_n_s_logging;
+static PyObject *__pyx_n_s_main;
+static PyObject *__pyx_n_s_memview;
+static PyObject *__pyx_kp_s_mntdirect__scisoft_users_tvince;
+static PyObject *__pyx_n_s_mode;
+static PyObject *__pyx_n_s_name;
+static PyObject *__pyx_n_s_name_2;
+static PyObject *__pyx_n_s_ncolumns;
+static PyObject *__pyx_n_s_ndarray;
+static PyObject *__pyx_n_s_ndim;
+static PyObject *__pyx_n_s_niterations;
+static PyObject *__pyx_n_s_npoints;
+static PyObject *__pyx_n_s_nrows;
+static PyObject *__pyx_n_s_numpy;
+static PyObject *__pyx_n_s_nx;
+static PyObject *__pyx_n_s_ny;
+static PyObject *__pyx_n_s_nz;
+static PyObject *__pyx_n_s_obj;
+static PyObject *__pyx_kp_s_or_a_2D_numpy_array;
+static PyObject *__pyx_kp_s_or_a_3D_numpy_array;
+static PyObject *__pyx_kp_s_or_a_numpy_array;
+static PyObject *__pyx_n_s_order;
+static PyObject *__pyx_n_s_output;
+static PyObject *__pyx_n_s_pack;
+static PyObject *__pyx_n_s_pyx_getbuffer;
+static PyObject *__pyx_n_s_pyx_vtable;
+static PyObject *__pyx_n_s_range;
+static PyObject *__pyx_n_s_reshape;
+static PyObject *__pyx_n_s_savitsky_golay;
+static PyObject *__pyx_n_s_shape;
+static PyObject *__pyx_n_s_size;
+static PyObject *__pyx_n_s_smooth1d;
+static PyObject *__pyx_n_s_smooth2d;
+static PyObject *__pyx_n_s_smooth3d;
+static PyObject *__pyx_n_s_snip1d;
+static PyObject *__pyx_n_s_snip2d;
+static PyObject *__pyx_n_s_snip3d;
+static PyObject *__pyx_n_s_snip_width;
+static PyObject *__pyx_n_s_start;
+static PyObject *__pyx_n_s_status;
+static PyObject *__pyx_n_s_step;
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+ int __pyx_t_2;
+ int __pyx_t_3;
+ int __pyx_lineno = 0;
+ const char *__pyx_filename = NULL;
+ int __pyx_clineno = 0;
+
+ /* "View.MemoryView":784
+ * cdef bint negative_step
+ *
+ * if not is_slice: # <<<<<<<<<<<<<<
+ *
+ * if start < 0:
+ */
+ __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":786
+ * if not is_slice:
+ *
+ * if start < 0: # <<<<<<<<<<<<<<
+ * start += shape
+ * if not 0 <= start < shape:
+ */
+ __pyx_t_1 = ((__pyx_v_start < 0) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":787
+ *
+ * if start < 0:
+ * start += shape # <<<<<<<<<<<<<<
+ * if not 0 <= start < shape:
+ * _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
+ */
+ __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
+ goto __pyx_L4;
+ }
+ __pyx_L4:;
+
+ /* "View.MemoryView":788
+ * if start < 0:
+ * start += shape
+ * if not 0 <= start < shape: # <<<<<<<<<<<<<<
+ * _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
+ * else:
+ */
+ __pyx_t_1 = (0 <= __pyx_v_start);
+ if (__pyx_t_1) {
+ __pyx_t_1 = (__pyx_v_start < __pyx_v_shape);
+ }
+ __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":789
+ * start += shape
+ * if not 0 <= start < shape:
+ * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<<
+ * else:
+ *
+ */
+ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 789; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ goto __pyx_L5;
+ }
+ __pyx_L5:;
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":792
+ * else:
+ *
+ * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<<
+ *
+ * if have_step and step == 0:
+ */
+ __pyx_t_1 = ((__pyx_v_have_step != 0) != 0);
+ if (__pyx_t_1) {
+ } else {
+ __pyx_t_2 = __pyx_t_1;
+ goto __pyx_L6_bool_binop_done;
+ }
+ __pyx_t_1 = ((__pyx_v_step < 0) != 0);
+ __pyx_t_2 = __pyx_t_1;
+ __pyx_L6_bool_binop_done:;
+ __pyx_v_negative_step = __pyx_t_2;
+
+ /* "View.MemoryView":794
+ * negative_step = have_step != 0 and step < 0
+ *
+ * if have_step and step == 0: # <<<<<<<<<<<<<<
+ * _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
+ *
+ */
+ __pyx_t_1 = (__pyx_v_have_step != 0);
+ if (__pyx_t_1) {
+ } else {
+ __pyx_t_2 = __pyx_t_1;
+ goto __pyx_L9_bool_binop_done;
+ }
+ __pyx_t_1 = ((__pyx_v_step == 0) != 0);
+ __pyx_t_2 = __pyx_t_1;
+ __pyx_L9_bool_binop_done:;
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":795
+ *
+ * if have_step and step == 0:
+ * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ goto __pyx_L8;
+ }
+ __pyx_L8:;
+
+ /* "View.MemoryView":798
+ *
+ *
+ * if have_start: # <<<<<<<<<<<<<<
+ * if start < 0:
+ * start += shape
+ */
+ __pyx_t_2 = (__pyx_v_have_start != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":799
+ *
+ * if have_start:
+ * if start < 0: # <<<<<<<<<<<<<<
+ * start += shape
+ * if start < 0:
+ */
+ __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":800
+ * if have_start:
+ * if start < 0:
+ * start += shape # <<<<<<<<<<<<<<
+ * if start < 0:
+ * start = 0
+ */
+ __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
+
+ /* "View.MemoryView":801
+ * if start < 0:
+ * start += shape
+ * if start < 0: # <<<<<<<<<<<<<<
+ * start = 0
+ * elif start >= shape:
+ */
+ __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":802
+ * start += shape
+ * if start < 0:
+ * start = 0 # <<<<<<<<<<<<<<
+ * elif start >= shape:
+ * if negative_step:
+ */
+ __pyx_v_start = 0;
+ goto __pyx_L13;
+ }
+ __pyx_L13:;
+ goto __pyx_L12;
+ }
+
+ /* "View.MemoryView":803
+ * if start < 0:
+ * start = 0
+ * elif start >= shape: # <<<<<<<<<<<<<<
+ * if negative_step:
+ * start = shape - 1
+ */
+ __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":804
+ * start = 0
+ * elif start >= shape:
+ * if negative_step: # <<<<<<<<<<<<<<
+ * start = shape - 1
+ * else:
+ */
+ __pyx_t_2 = (__pyx_v_negative_step != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":805
+ * elif start >= shape:
+ * if negative_step:
+ * start = shape - 1 # <<<<<<<<<<<<<<
+ * else:
+ * start = shape
+ */
+ __pyx_v_start = (__pyx_v_shape - 1);
+ goto __pyx_L14;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":807
+ * start = shape - 1
+ * else:
+ * start = shape # <<<<<<<<<<<<<<
+ * else:
+ * if negative_step:
+ */
+ __pyx_v_start = __pyx_v_shape;
+ }
+ __pyx_L14:;
+ goto __pyx_L12;
+ }
+ __pyx_L12:;
+ goto __pyx_L11;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":809
+ * start = shape
+ * else:
+ * if negative_step: # <<<<<<<<<<<<<<
+ * start = shape - 1
+ * else:
+ */
+ __pyx_t_2 = (__pyx_v_negative_step != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":810
+ * else:
+ * if negative_step:
+ * start = shape - 1 # <<<<<<<<<<<<<<
+ * else:
+ * start = 0
+ */
+ __pyx_v_start = (__pyx_v_shape - 1);
+ goto __pyx_L15;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":812
+ * start = shape - 1
+ * else:
+ * start = 0 # <<<<<<<<<<<<<<
+ *
+ * if have_stop:
+ */
+ __pyx_v_start = 0;
+ }
+ __pyx_L15:;
+ }
+ __pyx_L11:;
+
+ /* "View.MemoryView":814
+ * start = 0
+ *
+ * if have_stop: # <<<<<<<<<<<<<<
+ * if stop < 0:
+ * stop += shape
+ */
+ __pyx_t_2 = (__pyx_v_have_stop != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":815
+ *
+ * if have_stop:
+ * if stop < 0: # <<<<<<<<<<<<<<
+ * stop += shape
+ * if stop < 0:
+ */
+ __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":816
+ * if have_stop:
+ * if stop < 0:
+ * stop += shape # <<<<<<<<<<<<<<
+ * if stop < 0:
+ * stop = 0
+ */
+ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape);
+
+ /* "View.MemoryView":817
+ * if stop < 0:
+ * stop += shape
+ * if stop < 0: # <<<<<<<<<<<<<<
+ * stop = 0
+ * elif stop > shape:
+ */
+ __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":818
+ * stop += shape
+ * if stop < 0:
+ * stop = 0 # <<<<<<<<<<<<<<
+ * elif stop > shape:
+ * stop = shape
+ */
+ __pyx_v_stop = 0;
+ goto __pyx_L18;
+ }
+ __pyx_L18:;
+ goto __pyx_L17;
+ }
+
+ /* "View.MemoryView":819
+ * if stop < 0:
+ * stop = 0
+ * elif stop > shape: # <<<<<<<<<<<<<<
+ * stop = shape
+ * else:
+ */
+ __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":820
+ * stop = 0
+ * elif stop > shape:
+ * stop = shape # <<<<<<<<<<<<<<
+ * else:
+ * if negative_step:
+ */
+ __pyx_v_stop = __pyx_v_shape;
+ goto __pyx_L17;
+ }
+ __pyx_L17:;
+ goto __pyx_L16;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":822
+ * stop = shape
+ * else:
+ * if negative_step: # <<<<<<<<<<<<<<
+ * stop = -1
+ * else:
+ */
+ __pyx_t_2 = (__pyx_v_negative_step != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":823
+ * else:
+ * if negative_step:
+ * stop = -1 # <<<<<<<<<<<<<<
+ * else:
+ * stop = shape
+ */
+ __pyx_v_stop = -1;
+ goto __pyx_L19;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":825
+ * stop = -1
+ * else:
+ * stop = shape # <<<<<<<<<<<<<<
+ *
+ * if not have_step:
+ */
+ __pyx_v_stop = __pyx_v_shape;
+ }
+ __pyx_L19:;
+ }
+ __pyx_L16:;
+
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+ * stop = shape
+ *
+ * if not have_step: # <<<<<<<<<<<<<<
+ * step = 1
+ *
+ */
+ __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":828
+ *
+ * if not have_step:
+ * step = 1 # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_v_step = 1;
+ goto __pyx_L20;
+ }
+ __pyx_L20:;
+
+ /* "View.MemoryView":832
+ *
+ * with cython.cdivision(True):
+ * new_shape = (stop - start) // step # <<<<<<<<<<<<<<
+ *
+ * if (stop - start) - step * new_shape:
+ */
+ __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step);
+
+ /* "View.MemoryView":834
+ * new_shape = (stop - start) // step
+ *
+ * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<<
+ * new_shape += 1
+ *
+ */
+ __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":835
+ *
+ * if (stop - start) - step * new_shape:
+ * new_shape += 1 # <<<<<<<<<<<<<<
+ *
+ * if new_shape < 0:
+ */
+ __pyx_v_new_shape = (__pyx_v_new_shape + 1);
+ goto __pyx_L21;
+ }
+ __pyx_L21:;
+
+ /* "View.MemoryView":837
+ * new_shape += 1
+ *
+ * if new_shape < 0: # <<<<<<<<<<<<<<
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+ *
+ */
+ __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":838
+ *
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+ * new_shape = 0 # <<<<<<<<<<<<<<
+ *
+ *
+ */
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+ goto __pyx_L22;
+ }
+ __pyx_L22:;
+
+ /* "View.MemoryView":841
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+ *
+ * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<<
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+ * dst.suboffsets[new_ndim] = suboffset
+ */
+ (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step);
+
+ /* "View.MemoryView":842
+ *
+ * dst.strides[new_ndim] = stride * step
+ * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<<
+ * dst.suboffsets[new_ndim] = suboffset
+ *
+ */
+ (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape;
+
+ /* "View.MemoryView":843
+ * dst.strides[new_ndim] = stride * step
+ * dst.shape[new_ndim] = new_shape
+ * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset;
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":846
+ *
+ *
+ * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<<
+ * dst.data += start * stride
+ * else:
+ */
+ __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":847
+ *
+ * if suboffset_dim[0] < 0:
+ * dst.data += start * stride # <<<<<<<<<<<<<<
+ * else:
+ * dst.suboffsets[suboffset_dim[0]] += start * stride
+ */
+ __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride));
+ goto __pyx_L23;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":849
+ * dst.data += start * stride
+ * else:
+ * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<<
+ *
+ * if suboffset >= 0:
+ */
+ __pyx_t_3 = (__pyx_v_suboffset_dim[0]);
+ (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride));
+ }
+ __pyx_L23:;
+
+ /* "View.MemoryView":851
+ * dst.suboffsets[suboffset_dim[0]] += start * stride
+ *
+ * if suboffset >= 0: # <<<<<<<<<<<<<<
+ * if not is_slice:
+ * if new_ndim == 0:
+ */
+ __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":852
+ *
+ * if suboffset >= 0:
+ * if not is_slice: # <<<<<<<<<<<<<<
+ * if new_ndim == 0:
+ * dst.data = (<char **> dst.data)[0] + suboffset
+ */
+ __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":853
+ * if suboffset >= 0:
+ * if not is_slice:
+ * if new_ndim == 0: # <<<<<<<<<<<<<<
+ * dst.data = (<char **> dst.data)[0] + suboffset
+ * else:
+ */
+ __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":854
+ * if not is_slice:
+ * if new_ndim == 0:
+ * dst.data = (<char **> dst.data)[0] + suboffset # <<<<<<<<<<<<<<
+ * else:
+ * _err_dim(IndexError, "All dimensions preceding dimension %d "
+ */
+ __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset);
+ goto __pyx_L26;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":856
+ * dst.data = (<char **> dst.data)[0] + suboffset
+ * else:
+ * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<<
+ * "must be indexed and not sliced", dim)
+ * else:
+ */
+ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 856; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ }
+ __pyx_L26:;
+ goto __pyx_L25;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":859
+ * "must be indexed and not sliced", dim)
+ * else:
+ * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<<
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+ * return 0
+ */
+ (__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim;
+ }
+ __pyx_L25:;
+ goto __pyx_L24;
+ }
+ __pyx_L24:;
+
+ /* "View.MemoryView":861
+ * suboffset_dim[0] = new_ndim
+ *
+ * return 0 # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_r = 0;
+ goto __pyx_L0;
+
+ /* "View.MemoryView":764
+ *
+ * @cname('__pyx_memoryview_slice_memviewslice')
+ * cdef int slice_memviewslice( # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *dst,
+ * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
+ */
+
+ /* function exit code */
+ __pyx_L1_error:;
+ {
+ #ifdef WITH_THREAD
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
+ #endif
+ __Pyx_AddTraceback("View.MemoryView.slice_memviewslice", __pyx_clineno, __pyx_lineno, __pyx_filename);
+ #ifdef WITH_THREAD
+ PyGILState_Release(__pyx_gilstate_save);
+ #endif
+ }
+ __pyx_r = -1;
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":867
+ *
+ * @cname('__pyx_pybuffer_index')
+ * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index, # <<<<<<<<<<<<<<
+ * Py_ssize_t dim) except NULL:
+ * cdef Py_ssize_t shape, stride, suboffset = -1
+ */
+
+static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, Py_ssize_t __pyx_v_index, Py_ssize_t __pyx_v_dim) {
+ Py_ssize_t __pyx_v_shape;
+ Py_ssize_t __pyx_v_stride;
+ Py_ssize_t __pyx_v_suboffset;
+ Py_ssize_t __pyx_v_itemsize;
+ char *__pyx_v_resultp;
+ char *__pyx_r;
+ __Pyx_RefNannyDeclarations
+ Py_ssize_t __pyx_t_1;
+ int __pyx_t_2;
+ PyObject *__pyx_t_3 = NULL;
+ PyObject *__pyx_t_4 = NULL;
+ int __pyx_lineno = 0;
+ const char *__pyx_filename = NULL;
+ int __pyx_clineno = 0;
+ __Pyx_RefNannySetupContext("pybuffer_index", 0);
+
+ /* "View.MemoryView":869
+ * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index,
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+ * cdef Py_ssize_t shape, stride, suboffset = -1 # <<<<<<<<<<<<<<
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+ * cdef char *resultp
+ */
+ __pyx_v_suboffset = -1;
+
+ /* "View.MemoryView":870
+ * Py_ssize_t dim) except NULL:
+ * cdef Py_ssize_t shape, stride, suboffset = -1
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+ * cdef char *resultp
+ *
+ */
+ __pyx_t_1 = __pyx_v_view->itemsize;
+ __pyx_v_itemsize = __pyx_t_1;
+
+ /* "View.MemoryView":873
+ * cdef char *resultp
+ *
+ * if view.ndim == 0: # <<<<<<<<<<<<<<
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+ __pyx_t_2 = ((__pyx_v_view->ndim == 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":874
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+ #ifdef WITH_THREAD
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
+ #endif
+ PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero");
+ #ifdef WITH_THREAD
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+ #endif
+ {__pyx_filename = __pyx_f[1]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ #ifdef WITH_THREAD
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
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+ PyErr_SetString(PyExc_OverflowError, "value too large to perform division");
+ #ifdef WITH_THREAD
+ PyGILState_Release(__pyx_gilstate_save);
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+ {__pyx_filename = __pyx_f[1]; __pyx_lineno = 874; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+
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+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1108
+ * if (src_stride > 0 and dst_stride > 0 and
+ * <size_t> src_stride == itemsize == <size_t> dst_stride):
+ * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(dst_extent):
+ */
+ memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));
+ goto __pyx_L4;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1110
+ * memcpy(dst_data, src_data, itemsize * dst_extent)
+ * else:
+ * for i in range(dst_extent): # <<<<<<<<<<<<<<
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride
+ */
+ __pyx_t_4 = __pyx_v_dst_extent;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1111
+ * else:
+ * for i in range(dst_extent):
+ * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<<
+ * src_data += src_stride
+ * dst_data += dst_stride
+ */
+ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1112
+ * for i in range(dst_extent):
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride # <<<<<<<<<<<<<<
+ * dst_data += dst_stride
+ * else:
+ */
+ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+ /* "View.MemoryView":1113
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride
+ * dst_data += dst_stride # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(dst_extent):
+ */
+ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+ }
+ }
+ __pyx_L4:;
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1115
+ * dst_data += dst_stride
+ * else:
+ * for i in range(dst_extent): # <<<<<<<<<<<<<<
+ * _copy_strided_to_strided(src_data, src_strides + 1,
+ * dst_data, dst_strides + 1,
+ */
+ __pyx_t_4 = __pyx_v_dst_extent;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1116
+ * else:
+ * for i in range(dst_extent):
+ * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<<
+ * dst_data, dst_strides + 1,
+ * src_shape + 1, dst_shape + 1,
+ */
+ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);
+
+ /* "View.MemoryView":1120
+ * src_shape + 1, dst_shape + 1,
+ * ndim - 1, itemsize)
+ * src_data += src_stride # <<<<<<<<<<<<<<
+ * dst_data += dst_stride
+ *
+ */
+ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+ /* "View.MemoryView":1121
+ * ndim - 1, itemsize)
+ * src_data += src_stride
+ * dst_data += dst_stride # <<<<<<<<<<<<<<
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
+ */
+ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1093
+ *
+ * @cython.cdivision(True)
+ * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<<
+ * char *dst_data, Py_ssize_t *dst_strides,
+ * Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1123
+ * dst_data += dst_stride
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ */
+
+static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
+
+ /* "View.MemoryView":1126
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<<
+ * src.shape, dst.shape, ndim, itemsize)
+ *
+ */
+ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1123
+ * dst_data += dst_stride
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1130
+ *
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ */
+
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
+ int __pyx_v_i;
+ Py_ssize_t __pyx_v_size;
+ Py_ssize_t __pyx_r;
+ Py_ssize_t __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+
+ /* "View.MemoryView":1133
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<<
+ *
+ * for i in range(ndim):
+ */
+ __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
+ __pyx_v_size = __pyx_t_1;
+
+ /* "View.MemoryView":1135
+ * cdef Py_ssize_t size = src.memview.view.itemsize
+ *
+ * for i in range(ndim): # <<<<<<<<<<<<<<
+ * size *= src.shape[i]
+ *
+ */
+ __pyx_t_2 = __pyx_v_ndim;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1136
+ *
+ * for i in range(ndim):
+ * size *= src.shape[i] # <<<<<<<<<<<<<<
+ *
+ * return size
+ */
+ __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i]));
+ }
+
+ /* "View.MemoryView":1138
+ * size *= src.shape[i]
+ *
+ * return size # <<<<<<<<<<<<<<
+ *
+ * @cname('__pyx_fill_contig_strides_array')
+ */
+ __pyx_r = __pyx_v_size;
+ goto __pyx_L0;
+
+ /* "View.MemoryView":1130
+ *
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ */
+
+ /* function exit code */
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":1141
+ *
+ * @cname('__pyx_fill_contig_strides_array')
+ * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<<
+ * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
+ * int ndim, char order) nogil:
+ */
+
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
+ int __pyx_v_idx;
+ Py_ssize_t __pyx_r;
+ int __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+
+ /* "View.MemoryView":1150
+ * cdef int idx
+ *
+ * if order == 'F': # <<<<<<<<<<<<<<
+ * for idx in range(ndim):
+ * strides[idx] = stride
+ */
+ __pyx_t_1 = ((__pyx_v_order == 'F') != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1151
+ *
+ * if order == 'F':
+ * for idx in range(ndim): # <<<<<<<<<<<<<<
+ * strides[idx] = stride
+ * stride = stride * shape[idx]
+ */
+ __pyx_t_2 = __pyx_v_ndim;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_idx = __pyx_t_3;
+
+ /* "View.MemoryView":1152
+ * if order == 'F':
+ * for idx in range(ndim):
+ * strides[idx] = stride # <<<<<<<<<<<<<<
+ * stride = stride * shape[idx]
+ * else:
+ */
+ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
+
+ /* "View.MemoryView":1153
+ * for idx in range(ndim):
+ * strides[idx] = stride
+ * stride = stride * shape[idx] # <<<<<<<<<<<<<<
+ * else:
+ * for idx in range(ndim - 1, -1, -1):
+ */
+ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
+ }
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1155
+ * stride = stride * shape[idx]
+ * else:
+ * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
+ * strides[idx] = stride
+ * stride = stride * shape[idx]
+ */
+ for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) {
+ __pyx_v_idx = __pyx_t_2;
+
+ /* "View.MemoryView":1156
+ * else:
+ * for idx in range(ndim - 1, -1, -1):
+ * strides[idx] = stride # <<<<<<<<<<<<<<
+ * stride = stride * shape[idx]
+ *
+ */
+ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
+
+ /* "View.MemoryView":1157
+ * for idx in range(ndim - 1, -1, -1):
+ * strides[idx] = stride
+ * stride = stride * shape[idx] # <<<<<<<<<<<<<<
+ *
+ * return stride
+ */
+ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1159
+ * stride = stride * shape[idx]
+ *
+ * return stride # <<<<<<<<<<<<<<
+ *
+ * @cname('__pyx_memoryview_copy_data_to_temp')
+ */
+ __pyx_r = __pyx_v_stride;
+ goto __pyx_L0;
+
+ /* "View.MemoryView":1141
+ *
+ * @cname('__pyx_fill_contig_strides_array')
+ * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<<
+ * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
+ * int ndim, char order) nogil:
+ */
+
+ /* function exit code */
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":1162
+ *
+ * @cname('__pyx_memoryview_copy_data_to_temp')
+ * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *tmpslice,
+ * char order,
+ */
+
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) {
+ int __pyx_v_i;
+ void *__pyx_v_result;
+ size_t __pyx_v_itemsize;
+ size_t __pyx_v_size;
+ void *__pyx_r;
+ Py_ssize_t __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+ struct __pyx_memoryview_obj *__pyx_t_4;
+ int __pyx_t_5;
+ int __pyx_lineno = 0;
+ const char *__pyx_filename = NULL;
+ int __pyx_clineno = 0;
+
+ /* "View.MemoryView":1173
+ * cdef void *result
+ *
+ * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<<
+ * cdef size_t size = slice_get_size(src, ndim)
+ *
+ */
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+ __pyx_v_itemsize = __pyx_t_1;
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+
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+ *
+ * result = malloc(size) # <<<<<<<<<<<<<<
+ * if not result:
+ * _err(MemoryError, NULL)
+ */
+ __pyx_v_result = malloc(__pyx_v_size);
+
+ /* "View.MemoryView":1177
+ *
+ * result = malloc(size)
+ * if not result: # <<<<<<<<<<<<<<
+ * _err(MemoryError, NULL)
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+ */
+ __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1178
+ * result = malloc(size)
+ * if not result:
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+ *
+ *
+ */
+ __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ goto __pyx_L3;
+ }
+ __pyx_L3:;
+
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+ *
+ *
+ * tmpslice.data = <char *> result # <<<<<<<<<<<<<<
+ * tmpslice.memview = src.memview
+ * for i in range(ndim):
+ */
+ __pyx_v_tmpslice->data = ((char *)__pyx_v_result);
+
+ /* "View.MemoryView":1182
+ *
+ * tmpslice.data = <char *> result
+ * tmpslice.memview = src.memview # <<<<<<<<<<<<<<
+ * for i in range(ndim):
+ * tmpslice.shape[i] = src.shape[i]
+ */
+ __pyx_t_4 = __pyx_v_src->memview;
+ __pyx_v_tmpslice->memview = __pyx_t_4;
+
+ /* "View.MemoryView":1183
+ * tmpslice.data = <char *> result
+ * tmpslice.memview = src.memview
+ * for i in range(ndim): # <<<<<<<<<<<<<<
+ * tmpslice.shape[i] = src.shape[i]
+ * tmpslice.suboffsets[i] = -1
+ */
+ __pyx_t_3 = __pyx_v_ndim;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_3; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1184
+ * tmpslice.memview = src.memview
+ * for i in range(ndim):
+ * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<<
+ * tmpslice.suboffsets[i] = -1
+ *
+ */
+ (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]);
+
+ /* "View.MemoryView":1185
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+ * tmpslice.shape[i] = src.shape[i]
+ * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<<
+ *
+ * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize,
+ */
+ (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1;
+ }
+
+ /* "View.MemoryView":1187
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+ *
+ * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<<
+ * ndim, order)
+ *
+ */
+ __pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order);
+
+ /* "View.MemoryView":1191
+ *
+ *
+ * for i in range(ndim): # <<<<<<<<<<<<<<
+ * if tmpslice.shape[i] == 1:
+ * tmpslice.strides[i] = 0
+ */
+ __pyx_t_3 = __pyx_v_ndim;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_3; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1192
+ *
+ * for i in range(ndim):
+ * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<<
+ * tmpslice.strides[i] = 0
+ *
+ */
+ __pyx_t_2 = (((__pyx_v_tmpslice->shape[__pyx_v_i]) == 1) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1193
+ * for i in range(ndim):
+ * if tmpslice.shape[i] == 1:
+ * tmpslice.strides[i] = 0 # <<<<<<<<<<<<<<
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+ */
+ (__pyx_v_tmpslice->strides[__pyx_v_i]) = 0;
+ goto __pyx_L8;
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+ __pyx_L8:;
+ }
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+ /* "View.MemoryView":1195
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+ *
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+ * else:
+ */
+ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1196
+ *
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+ * memcpy(result, src.data, size) # <<<<<<<<<<<<<<
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+ */
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+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1198
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+ * else:
+ * copy_strided_to_strided(src, tmpslice, ndim, itemsize) # <<<<<<<<<<<<<<
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+ * return result
+ */
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+ __pyx_L9:;
+
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+ *
+ */
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+
+ /* "View.MemoryView":1162
+ *
+ * @cname('__pyx_memoryview_copy_data_to_temp')
+ * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
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+ */
+
+ /* function exit code */
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+/* "View.MemoryView":1205
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+ * raise ValueError("got differing extents in dimension %d (got %d and %d)" %
+ */
+
+static int __pyx_memoryview_err_extents(int __pyx_v_i, Py_ssize_t __pyx_v_extent1, Py_ssize_t __pyx_v_extent2) {
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+ int __pyx_lineno = 0;
+ const char *__pyx_filename = NULL;
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+ * (i, extent1, extent2)) # <<<<<<<<<<<<<<
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+ * if src.shape[i] == 1:
+ * broadcasting = True # <<<<<<<<<<<<<<
+ * src.strides[i] = 0
+ * else:
+ */
+ __pyx_v_broadcasting = 1;
+
+ /* "View.MemoryView":1249
+ * if src.shape[i] == 1:
+ * broadcasting = True
+ * src.strides[i] = 0 # <<<<<<<<<<<<<<
+ * else:
+ * _err_extents(i, dst.shape[i], src.shape[i])
+ */
+ (__pyx_v_src.strides[__pyx_v_i]) = 0;
+ goto __pyx_L7;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1251
+ * src.strides[i] = 0
+ * else:
+ * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<<
+ *
+ * if src.suboffsets[i] >= 0:
+ */
+ __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1251; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ }
+ __pyx_L7:;
+ goto __pyx_L6;
+ }
+ __pyx_L6:;
+
+ /* "View.MemoryView":1253
+ * _err_extents(i, dst.shape[i], src.shape[i])
+ *
+ * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<<
+ * _err_dim(ValueError, "Dimension %d is not direct", i)
+ *
+ */
+ __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1254
+ *
+ * if src.suboffsets[i] >= 0:
+ * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<<
+ *
+ * if slices_overlap(&src, &dst, ndim, itemsize):
+ */
+ __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1254; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ goto __pyx_L8;
+ }
+ __pyx_L8:;
+ }
+
+ /* "View.MemoryView":1256
+ * _err_dim(ValueError, "Dimension %d is not direct", i)
+ *
+ * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<<
+ *
+ * if not slice_is_contig(&src, order, ndim):
+ */
+ __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1258
+ * if slices_overlap(&src, &dst, ndim, itemsize):
+ *
+ * if not slice_is_contig(&src, order, ndim): # <<<<<<<<<<<<<<
+ * order = get_best_order(&dst, ndim)
+ *
+ */
+ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig((&__pyx_v_src), __pyx_v_order, __pyx_v_ndim) != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1259
+ *
+ * if not slice_is_contig(&src, order, ndim):
+ * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<<
+ *
+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ */
+ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim);
+ goto __pyx_L10;
+ }
+ __pyx_L10:;
+
+ /* "View.MemoryView":1261
+ * order = get_best_order(&dst, ndim)
+ *
+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<<
+ * src = tmp
+ *
+ */
+ __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_v_tmpdata = __pyx_t_6;
+
+ /* "View.MemoryView":1262
+ *
+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ * src = tmp # <<<<<<<<<<<<<<
+ *
+ * if not broadcasting:
+ */
+ __pyx_v_src = __pyx_v_tmp;
+ goto __pyx_L9;
+ }
+ __pyx_L9:;
+
+ /* "View.MemoryView":1264
+ * src = tmp
+ *
+ * if not broadcasting: # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1267
+ *
+ *
+ * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<<
+ * direct_copy = slice_is_contig(&dst, 'C', ndim)
+ * elif slice_is_contig(&src, 'F', ndim):
+ */
+ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1268
+ *
+ * if slice_is_contig(&src, 'C', ndim):
+ * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<<
+ * elif slice_is_contig(&src, 'F', ndim):
+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ */
+ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim);
+ goto __pyx_L12;
+ }
+
+ /* "View.MemoryView":1269
+ * if slice_is_contig(&src, 'C', ndim):
+ * direct_copy = slice_is_contig(&dst, 'C', ndim)
+ * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<<
+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ *
+ */
+ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1270
+ * direct_copy = slice_is_contig(&dst, 'C', ndim)
+ * elif slice_is_contig(&src, 'F', ndim):
+ * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<<
+ *
+ * if direct_copy:
+ */
+ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim);
+ goto __pyx_L12;
+ }
+ __pyx_L12:;
+
+ /* "View.MemoryView":1272
+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ *
+ * if direct_copy: # <<<<<<<<<<<<<<
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+ __pyx_t_2 = (__pyx_v_direct_copy != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1274
+ * if direct_copy:
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+ /* "View.MemoryView":1275
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<<
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ * free(tmpdata)
+ */
+ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim));
+
+ /* "View.MemoryView":1276
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
+ * free(tmpdata)
+ * return 0
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+ /* "View.MemoryView":1277
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ * free(tmpdata) # <<<<<<<<<<<<<<
+ * return 0
+ *
+ */
+ free(__pyx_v_tmpdata);
+
+ /* "View.MemoryView":1278
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ * free(tmpdata)
+ * return 0 # <<<<<<<<<<<<<<
+ *
+ * if order == 'F' == get_best_order(&dst, ndim):
+ */
+ __pyx_r = 0;
+ goto __pyx_L0;
+ }
+ goto __pyx_L11;
+ }
+ __pyx_L11:;
+
+ /* "View.MemoryView":1280
+ * return 0
+ *
+ * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_t_2 = (__pyx_v_order == 'F');
+ if (__pyx_t_2) {
+ __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim));
+ }
+ __pyx_t_7 = (__pyx_t_2 != 0);
+ if (__pyx_t_7) {
+
+ /* "View.MemoryView":1283
+ *
+ *
+ * transpose_memslice(&src) # <<<<<<<<<<<<<<
+ * transpose_memslice(&dst)
+ *
+ */
+ __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1283; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "View.MemoryView":1284
+ *
+ * transpose_memslice(&src)
+ * transpose_memslice(&dst) # <<<<<<<<<<<<<<
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+ __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ goto __pyx_L14;
+ }
+ __pyx_L14:;
+
+ /* "View.MemoryView":1286
+ * transpose_memslice(&dst)
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
+ * copy_strided_to_strided(&src, &dst, ndim, itemsize)
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+ /* "View.MemoryView":1287
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<<
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ *
+ */
+ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1288
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ * copy_strided_to_strided(&src, &dst, ndim, itemsize)
+ * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
+ *
+ * free(tmpdata)
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+ /* "View.MemoryView":1290
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ *
+ * free(tmpdata) # <<<<<<<<<<<<<<
+ * return 0
+ *
+ */
+ free(__pyx_v_tmpdata);
+
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+ *
+ * free(tmpdata)
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+ *
+ * @cname('__pyx_memoryview_broadcast_leading')
+ */
+ __pyx_r = 0;
+ goto __pyx_L0;
+
+ /* "View.MemoryView":1222
+ *
+ * @cname('__pyx_memoryview_copy_contents')
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+ * __Pyx_memviewslice dst,
+ * int src_ndim, int dst_ndim,
+ */
+
+ /* function exit code */
+ __pyx_L1_error:;
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+ #ifdef WITH_THREAD
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
+ #endif
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+ #ifdef WITH_THREAD
+ PyGILState_Release(__pyx_gilstate_save);
+ #endif
+ }
+ __pyx_r = -1;
+ __pyx_L0:;
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+}
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+ */
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+ int __pyx_v_offset;
+ int __pyx_t_1;
+ int __pyx_t_2;
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+ __pyx_v_i = __pyx_t_1;
+
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+ */
+ (__pyx_v_slice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->shape[__pyx_v_i]);
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+ *
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+ /* "View.MemoryView":1303
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+ * slice.strides[i + offset] = slice.strides[i]
+ * slice.suboffsets[i + offset] = slice.suboffsets[i] # <<<<<<<<<<<<<<
+ *
+ * for i in range(offset):
+ */
+ (__pyx_v_slice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_slice->suboffsets[__pyx_v_i]);
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+
+ /* "View.MemoryView":1305
+ * slice.suboffsets[i + offset] = slice.suboffsets[i]
+ *
+ * for i in range(offset): # <<<<<<<<<<<<<<
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+ * slice.strides[i] = slice.strides[0]
+ */
+ __pyx_t_1 = __pyx_v_offset;
+ for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
+ __pyx_v_i = __pyx_t_2;
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+ /* "View.MemoryView":1306
+ *
+ * for i in range(offset):
+ * slice.shape[i] = 1 # <<<<<<<<<<<<<<
+ * slice.strides[i] = slice.strides[0]
+ * slice.suboffsets[i] = -1
+ */
+ (__pyx_v_slice->shape[__pyx_v_i]) = 1;
+
+ /* "View.MemoryView":1307
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+ * slice.strides[i] = slice.strides[0] # <<<<<<<<<<<<<<
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+ *
+ */
+ (__pyx_v_slice->strides[__pyx_v_i]) = (__pyx_v_slice->strides[0]);
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+ /* "View.MemoryView":1308
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+ * slice.suboffsets[i] = -1 # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ (__pyx_v_slice->suboffsets[__pyx_v_i]) = -1;
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+
+ /* "View.MemoryView":1294
+ *
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+ * cdef void broadcast_leading(__Pyx_memviewslice *slice, # <<<<<<<<<<<<<<
+ * int ndim,
+ * int ndim_other) nogil:
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1316
+ *
+ * @cname('__pyx_memoryview_refcount_copying')
+ * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<<
+ * int ndim, bint inc) nogil:
+ *
+ */
+
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) {
+ int __pyx_t_1;
+
+ /* "View.MemoryView":1320
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+ *
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+ * dst.strides, ndim, inc)
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+ __pyx_t_1 = (__pyx_v_dtype_is_object != 0);
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+ /* "View.MemoryView":1321
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+ */
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+ goto __pyx_L3;
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1316
+ *
+ * @cname('__pyx_memoryview_refcount_copying')
+ * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<<
+ * int ndim, bint inc) nogil:
+ *
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1325
+ *
+ * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
+ * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim,
+ * bint inc) with gil:
+ */
+
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
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+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
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+
+ /* "View.MemoryView":1328
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+ * refcount_objects_in_slice(data, shape, strides, ndim, inc) # <<<<<<<<<<<<<<
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+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ */
+ __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, __pyx_v_shape, __pyx_v_strides, __pyx_v_ndim, __pyx_v_inc);
+
+ /* "View.MemoryView":1325
+ *
+ * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
+ * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
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+
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+ #ifdef WITH_THREAD
+ PyGILState_Release(__pyx_gilstate_save);
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+}
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+/* "View.MemoryView":1331
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+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim, bint inc):
+ * cdef Py_ssize_t i
+ */
+
+static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
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+ * if ndim == 1:
+ * if inc:
+ */
+ __pyx_t_1 = (__pyx_v_shape[0]);
+ for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
+ __pyx_v_i = __pyx_t_2;
+
+ /* "View.MemoryView":1336
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+ * for i in range(shape[0]):
+ * if ndim == 1: # <<<<<<<<<<<<<<
+ * if inc:
+ * Py_INCREF((<PyObject **> data)[0])
+ */
+ __pyx_t_3 = ((__pyx_v_ndim == 1) != 0);
+ if (__pyx_t_3) {
+
+ /* "View.MemoryView":1337
+ * for i in range(shape[0]):
+ * if ndim == 1:
+ * if inc: # <<<<<<<<<<<<<<
+ * Py_INCREF((<PyObject **> data)[0])
+ * else:
+ */
+ __pyx_t_3 = (__pyx_v_inc != 0);
+ if (__pyx_t_3) {
+
+ /* "View.MemoryView":1338
+ * if ndim == 1:
+ * if inc:
+ * Py_INCREF((<PyObject **> data)[0]) # <<<<<<<<<<<<<<
+ * else:
+ * Py_DECREF((<PyObject **> data)[0])
+ */
+ Py_INCREF((((PyObject **)__pyx_v_data)[0]));
+ goto __pyx_L6;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1340
+ * Py_INCREF((<PyObject **> data)[0])
+ * else:
+ * Py_DECREF((<PyObject **> data)[0]) # <<<<<<<<<<<<<<
+ * else:
+ * refcount_objects_in_slice(data, shape + 1, strides + 1,
+ */
+ Py_DECREF((((PyObject **)__pyx_v_data)[0]));
+ }
+ __pyx_L6:;
+ goto __pyx_L5;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1342
+ * Py_DECREF((<PyObject **> data)[0])
+ * else:
+ * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<<
+ * ndim - 1, inc)
+ *
+ */
+ __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc);
+ }
+ __pyx_L5:;
+
+ /* "View.MemoryView":1345
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+ *
+ * data += strides[0] # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_v_data = (__pyx_v_data + (__pyx_v_strides[0]));
+ }
+
+ /* "View.MemoryView":1331
+ *
+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim, bint inc):
+ * cdef Py_ssize_t i
+ */
+
+ /* function exit code */
+ __Pyx_RefNannyFinishContext();
+}
+
+/* "View.MemoryView":1351
+ *
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<<
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ */
+
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {
+
+ /* "View.MemoryView":1354
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ * itemsize, item)
+ */
+ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+ /* "View.MemoryView":1355
+ * bint dtype_is_object) nogil:
+ * refcount_copying(dst, dtype_is_object, ndim, False)
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<<
+ * itemsize, item)
+ * refcount_copying(dst, dtype_is_object, ndim, True)
+ */
+ __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item);
+
+ /* "View.MemoryView":1357
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ * itemsize, item)
+ * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+ /* "View.MemoryView":1351
+ *
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<<
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1361
+ *
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim,
+ * size_t itemsize, void *item) nogil:
+ */
+
+static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
+ CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+ Py_ssize_t __pyx_v_stride;
+ Py_ssize_t __pyx_v_extent;
+ int __pyx_t_1;
+ Py_ssize_t __pyx_t_2;
+ Py_ssize_t __pyx_t_3;
+
+ /* "View.MemoryView":1365
+ * size_t itemsize, void *item) nogil:
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t extent = shape[0]
+ *
+ */
+ __pyx_v_stride = (__pyx_v_strides[0]);
+
+ /* "View.MemoryView":1366
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t stride = strides[0]
+ * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<<
+ *
+ * if ndim == 1:
+ */
+ __pyx_v_extent = (__pyx_v_shape[0]);
+
+ /* "View.MemoryView":1368
+ * cdef Py_ssize_t extent = shape[0]
+ *
+ * if ndim == 1: # <<<<<<<<<<<<<<
+ * for i in range(extent):
+ * memcpy(data, item, itemsize)
+ */
+ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1369
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+ * if ndim == 1:
+ * for i in range(extent): # <<<<<<<<<<<<<<
+ * memcpy(data, item, itemsize)
+ * data += stride
+ */
+ __pyx_t_2 = __pyx_v_extent;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1370
+ * if ndim == 1:
+ * for i in range(extent):
+ * memcpy(data, item, itemsize) # <<<<<<<<<<<<<<
+ * data += stride
+ * else:
+ */
+ memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1371
+ * for i in range(extent):
+ * memcpy(data, item, itemsize)
+ * data += stride # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(extent):
+ */
+ __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+ }
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1373
+ * data += stride
+ * else:
+ * for i in range(extent): # <<<<<<<<<<<<<<
+ * _slice_assign_scalar(data, shape + 1, strides + 1,
+ * ndim - 1, itemsize, item)
+ */
+ __pyx_t_2 = __pyx_v_extent;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1374
+ * else:
+ * for i in range(extent):
+ * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<<
+ * ndim - 1, itemsize, item)
+ * data += stride
+ */
+ __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item);
+
+ /* "View.MemoryView":1376
+ * _slice_assign_scalar(data, shape + 1, strides + 1,
+ * ndim - 1, itemsize, item)
+ * data += stride # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1361
+ *
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim,
+ * size_t itemsize, void *item) nogil:
+ */
+
+ /* function exit code */
+}
+
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_array_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_array_obj *)o);
+ p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None);
+ p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None);
+ if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) {
+ Py_DECREF(o); o = 0;
+ }
+ return o;
+}
+
+static void __pyx_tp_dealloc_array(PyObject *o) {
+ struct __pyx_array_obj *p = (struct __pyx_array_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_array___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->mode);
+ Py_CLEAR(p->_format);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) {
+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_array___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
+ PyObject *v = PyObject_GenericGetAttr(o, n);
+ if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+ PyErr_Clear();
+ v = __pyx_array___getattr__(o, n);
+ }
+ return v;
+}
+
+static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
+ return get_memview(o);
+}
+
+static PyMethodDef __pyx_methods_array[] = {
+ {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_array[] = {
+ {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_array = {
+ 0, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_array, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_array = {
+ 0, /*mp_length*/
+ __pyx_array___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_array = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_array_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_array = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "filters.array", /*tp_name*/
+ sizeof(struct __pyx_array_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_array, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ 0, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_array, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_array, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ __pyx_tp_getattro_array, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_array, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
+ 0, /*tp_doc*/
+ 0, /*tp_traverse*/
+ 0, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_array, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_array, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_array, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
+ struct __pyx_MemviewEnum_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_MemviewEnum_obj *)o);
+ p->name = Py_None; Py_INCREF(Py_None);
+ return o;
+}
+
+static void __pyx_tp_dealloc_Enum(PyObject *o) {
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ Py_CLEAR(p->name);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ if (p->name) {
+ e = (*v)(p->name, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_Enum(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ tmp = ((PyObject*)p->name);
+ p->name = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ return 0;
+}
+
+static PyMethodDef __pyx_methods_Enum[] = {
+ {0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_MemviewEnum = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "filters.Enum", /*tp_name*/
+ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_Enum, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_MemviewEnum___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_Enum, /*tp_traverse*/
+ __pyx_tp_clear_Enum, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_Enum, /*tp_methods*/
+ 0, /*tp_members*/
+ 0, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ __pyx_MemviewEnum___init__, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_Enum, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
+
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryview_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryview_obj *)o);
+ p->__pyx_vtab = __pyx_vtabptr_memoryview;
+ p->obj = Py_None; Py_INCREF(Py_None);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ p->view.obj = NULL;
+ if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) {
+ Py_DECREF(o); o = 0;
+ }
+ return o;
+}
+
+static void __pyx_tp_dealloc_memoryview(PyObject *o) {
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryview___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->obj);
+ Py_CLEAR(p->_size);
+ Py_CLEAR(p->_array_interface);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ if (p->obj) {
+ e = (*v)(p->obj, a); if (e) return e;
+ }
+ if (p->_size) {
+ e = (*v)(p->_size, a); if (e) return e;
+ }
+ if (p->_array_interface) {
+ e = (*v)(p->_array_interface, a); if (e) return e;
+ }
+ if (p->view.obj) {
+ e = (*v)(p->view.obj, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_memoryview(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ tmp = ((PyObject*)p->obj);
+ p->obj = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_size);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_array_interface);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ Py_CLEAR(p->view.obj);
+ return 0;
+}
+static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_memoryview___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_transpose(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview__get__base(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_shape(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_strides(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_suboffsets(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_ndim(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_itemsize(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_nbytes(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_size(o);
+}
+
+static PyMethodDef __pyx_methods_memoryview[] = {
+ {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
+ {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
+ {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
+ {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_memoryview[] = {
+ {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0},
+ {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0},
+ {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0},
+ {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0},
+ {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0},
+ {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0},
+ {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0},
+ {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0},
+ {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
+ __pyx_memoryview___len__, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_memoryview, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
+ __pyx_memoryview___len__, /*mp_length*/
+ __pyx_memoryview___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_memoryview_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_memoryview = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "filters.memoryview", /*tp_name*/
+ sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_memoryview___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ __pyx_memoryview___str__, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_memoryview, /*tp_traverse*/
+ __pyx_tp_clear_memoryview, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_memoryview, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_memoryview, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_memoryview, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;
+
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryviewslice_obj *p;
+ PyObject *o = __pyx_tp_new_memoryview(t, a, k);
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryviewslice_obj *)o);
+ p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ p->from_slice.memview = NULL;
+ return o;
+}
+
+static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryviewslice___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->from_object);
+ PyObject_GC_Track(o);
+ __pyx_tp_dealloc_memoryview(o);
+}
+
+static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
+ if (p->from_object) {
+ e = (*v)(p->from_object, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ __pyx_tp_clear_memoryview(o);
+ tmp = ((PyObject*)p->from_object);
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
+ return 0;
+}
+
+static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryviewslice__get__base(o);
+}
+
+static PyMethodDef __pyx_methods__memoryviewslice[] = {
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
+ {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_memoryviewslice = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "filters._memoryviewslice", /*tp_name*/
+ sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___repr__, /*tp_repr*/
+ #else
+ 0, /*tp_repr*/
+ #endif
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___str__, /*tp_str*/
+ #else
+ 0, /*tp_str*/
+ #endif
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ "Internal class for passing memoryview slices to Python", /*tp_doc*/
+ __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
+ __pyx_tp_clear__memoryviewslice, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods__memoryviewslice, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets__memoryviewslice, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new__memoryviewslice, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyMethodDef __pyx_methods[] = {
+ {0, 0, 0, 0}
+};
+
+#if PY_MAJOR_VERSION >= 3
+static struct PyModuleDef __pyx_moduledef = {
+ #if PY_VERSION_HEX < 0x03020000
+ { PyObject_HEAD_INIT(NULL) NULL, 0, NULL },
+ #else
+ PyModuleDef_HEAD_INIT,
+ #endif
+ "filters",
+ __pyx_k_This_module_provides_background, /* m_doc */
+ -1, /* m_size */
+ __pyx_methods /* m_methods */,
+ NULL, /* m_reload */
+ NULL, /* m_traverse */
+ NULL, /* m_clear */
+ NULL /* m_free */
+};
+#endif
+
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+ __Pyx_GOTREF(__pyx_t_1);
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+ __Pyx_GIVEREF(__pyx_t_1);
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+ /* "View.MemoryView":282
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+ __Pyx_GOTREF(__pyx_t_1);
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+ __Pyx_GOTREF(__pyx_t_1);
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+ __Pyx_GOTREF(__pyx_t_1);
+ if (PyDict_SetItem(__pyx_memoryviewslice_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 953; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ PyType_Modified(__pyx_memoryviewslice_type);
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+ /* "View.MemoryView":1361
+ *
+ * @cname('__pyx_memoryview__slice_assign_scalar')
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+ /*--- Wrapped vars code ---*/
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+ goto __pyx_L0;
+ __pyx_L1_error:;
+ __Pyx_XDECREF(__pyx_t_1);
+ __Pyx_XDECREF(__pyx_t_2);
+ __Pyx_XDECREF(__pyx_t_3);
+ __Pyx_XDECREF(__pyx_t_4);
+ __Pyx_XDECREF(__pyx_t_5);
+ if (__pyx_m) {
+ if (__pyx_d) {
+ __Pyx_AddTraceback("init filters", __pyx_clineno, __pyx_lineno, __pyx_filename);
+ }
+ Py_DECREF(__pyx_m); __pyx_m = 0;
+ } else if (!PyErr_Occurred()) {
+ PyErr_SetString(PyExc_ImportError, "init filters");
+ }
+ __pyx_L0:;
+ __Pyx_RefNannyFinishContext();
+ #if PY_MAJOR_VERSION < 3
+ return;
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+ return __pyx_m;
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+}
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+/* Runtime support code */
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+static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
+ PyObject *m = NULL, *p = NULL;
+ void *r = NULL;
+ m = PyImport_ImportModule((char *)modname);
+ if (!m) goto end;
+ p = PyObject_GetAttrString(m, (char *)"RefNannyAPI");
+ if (!p) goto end;
+ r = PyLong_AsVoidPtr(p);
+end:
+ Py_XDECREF(p);
+ Py_XDECREF(m);
+ return (__Pyx_RefNannyAPIStruct *)r;
+}
+#endif
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+static PyObject *__Pyx_GetBuiltinName(PyObject *name) {
+ PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name);
+ if (unlikely(!result)) {
+ PyErr_Format(PyExc_NameError,
+#if PY_MAJOR_VERSION >= 3
+ "name '%U' is not defined", name);
+#else
+ "name '%.200s' is not defined", PyString_AS_STRING(name));
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+ }
+ return result;
+}
+
+static void __Pyx_RaiseDoubleKeywordsError(
+ const char* func_name,
+ PyObject* kw_name)
+{
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION >= 3
+ "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
+ #else
+ "%s() got multiple values for keyword argument '%s'", func_name,
+ PyString_AsString(kw_name));
+ #endif
+}
+
+static int __Pyx_ParseOptionalKeywords(
+ PyObject *kwds,
+ PyObject **argnames[],
+ PyObject *kwds2,
+ PyObject *values[],
+ Py_ssize_t num_pos_args,
+ const char* function_name)
+{
+ PyObject *key = 0, *value = 0;
+ Py_ssize_t pos = 0;
+ PyObject*** name;
+ PyObject*** first_kw_arg = argnames + num_pos_args;
+ while (PyDict_Next(kwds, &pos, &key, &value)) {
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+ if (*name) {
+ values[name-argnames] = value;
+ continue;
+ }
+ name = first_kw_arg;
+ #if PY_MAJOR_VERSION < 3
+ if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
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+ && _PyString_Eq(**name, key)) {
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+ else {
+ PyObject*** argname = argnames;
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+ (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
+ && _PyString_Eq(**argname, key))) {
+ goto arg_passed_twice;
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+ argname++;
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+ #endif
+ if (likely(PyUnicode_Check(key))) {
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+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
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+ }
+ name++;
+ }
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+ else {
+ PyObject*** argname = argnames;
+ while (argname != first_kw_arg) {
+ int cmp = (**argname == key) ? 0 :
+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
+ #endif
+ PyUnicode_Compare(**argname, key);
+ if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+ if (cmp == 0) goto arg_passed_twice;
+ argname++;
+ }
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+ } else
+ goto invalid_keyword_type;
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+ } else {
+ goto invalid_keyword;
+ }
+ }
+ return 0;
+arg_passed_twice:
+ __Pyx_RaiseDoubleKeywordsError(function_name, key);
+ goto bad;
+invalid_keyword_type:
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() keywords must be strings", function_name);
+ goto bad;
+invalid_keyword:
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION < 3
+ "%.200s() got an unexpected keyword argument '%.200s'",
+ function_name, PyString_AsString(key));
+ #else
+ "%s() got an unexpected keyword argument '%U'",
+ function_name, key);
+ #endif
+bad:
+ return -1;
+}
+
+static void __Pyx_RaiseArgtupleInvalid(
+ const char* func_name,
+ int exact,
+ Py_ssize_t num_min,
+ Py_ssize_t num_max,
+ Py_ssize_t num_found)
+{
+ Py_ssize_t num_expected;
+ const char *more_or_less;
+ if (num_found < num_min) {
+ num_expected = num_min;
+ more_or_less = "at least";
+ } else {
+ num_expected = num_max;
+ more_or_less = "at most";
+ }
+ if (exact) {
+ more_or_less = "exactly";
+ }
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
+ func_name, more_or_less, num_expected,
+ (num_expected == 1) ? "" : "s", num_found);
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
+ PyObject *result;
+#if CYTHON_COMPILING_IN_CPYTHON
+ result = PyDict_GetItem(__pyx_d, name);
+ if (likely(result)) {
+ Py_INCREF(result);
+ } else {
+#else
+ result = PyObject_GetItem(__pyx_d, name);
+ if (!result) {
+ PyErr_Clear();
+#endif
+ result = __Pyx_GetBuiltinName(name);
+ }
+ return result;
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) {
+ PyObject *result;
+ ternaryfunc call = func->ob_type->tp_call;
+ if (unlikely(!call))
+ return PyObject_Call(func, arg, kw);
+ if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+ return NULL;
+ result = (*call)(func, arg, kw);
+ Py_LeaveRecursiveCall();
+ if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+ PyErr_SetString(
+ PyExc_SystemError,
+ "NULL result without error in PyObject_Call");
+ }
+ return result;
+}
+#endif
+
+static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->curexc_type;
+ tmp_value = tstate->curexc_value;
+ tmp_tb = tstate->curexc_traceback;
+ tstate->curexc_type = type;
+ tstate->curexc_value = value;
+ tstate->curexc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_Restore(type, value, tb);
+#endif
+}
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->curexc_type;
+ *value = tstate->curexc_value;
+ *tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(type, value, tb);
+#endif
+}
+
+#if PY_MAJOR_VERSION < 3
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
+ CYTHON_UNUSED PyObject *cause) {
+ Py_XINCREF(type);
+ if (!value || value == Py_None)
+ value = NULL;
+ else
+ Py_INCREF(value);
+ if (!tb || tb == Py_None)
+ tb = NULL;
+ else {
+ Py_INCREF(tb);
+ if (!PyTraceBack_Check(tb)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: arg 3 must be a traceback or None");
+ goto raise_error;
+ }
+ }
+ if (PyType_Check(type)) {
+#if CYTHON_COMPILING_IN_PYPY
+ if (!value) {
+ Py_INCREF(Py_None);
+ value = Py_None;
+ }
+#endif
+ PyErr_NormalizeException(&type, &value, &tb);
+ } else {
+ if (value) {
+ PyErr_SetString(PyExc_TypeError,
+ "instance exception may not have a separate value");
+ goto raise_error;
+ }
+ value = type;
+ type = (PyObject*) Py_TYPE(type);
+ Py_INCREF(type);
+ if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: exception class must be a subclass of BaseException");
+ goto raise_error;
+ }
+ }
+ __Pyx_ErrRestore(type, value, tb);
+ return;
+raise_error:
+ Py_XDECREF(value);
+ Py_XDECREF(type);
+ Py_XDECREF(tb);
+ return;
+}
+#else
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
+ PyObject* owned_instance = NULL;
+ if (tb == Py_None) {
+ tb = 0;
+ } else if (tb && !PyTraceBack_Check(tb)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: arg 3 must be a traceback or None");
+ goto bad;
+ }
+ if (value == Py_None)
+ value = 0;
+ if (PyExceptionInstance_Check(type)) {
+ if (value) {
+ PyErr_SetString(PyExc_TypeError,
+ "instance exception may not have a separate value");
+ goto bad;
+ }
+ value = type;
+ type = (PyObject*) Py_TYPE(value);
+ } else if (PyExceptionClass_Check(type)) {
+ PyObject *instance_class = NULL;
+ if (value && PyExceptionInstance_Check(value)) {
+ instance_class = (PyObject*) Py_TYPE(value);
+ if (instance_class != type) {
+ if (PyObject_IsSubclass(instance_class, type)) {
+ type = instance_class;
+ } else {
+ instance_class = NULL;
+ }
+ }
+ }
+ if (!instance_class) {
+ PyObject *args;
+ if (!value)
+ args = PyTuple_New(0);
+ else if (PyTuple_Check(value)) {
+ Py_INCREF(value);
+ args = value;
+ } else
+ args = PyTuple_Pack(1, value);
+ if (!args)
+ goto bad;
+ owned_instance = PyObject_Call(type, args, NULL);
+ Py_DECREF(args);
+ if (!owned_instance)
+ goto bad;
+ value = owned_instance;
+ if (!PyExceptionInstance_Check(value)) {
+ PyErr_Format(PyExc_TypeError,
+ "calling %R should have returned an instance of "
+ "BaseException, not %R",
+ type, Py_TYPE(value));
+ goto bad;
+ }
+ }
+ } else {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: exception class must be a subclass of BaseException");
+ goto bad;
+ }
+#if PY_VERSION_HEX >= 0x03030000
+ if (cause) {
+#else
+ if (cause && cause != Py_None) {
+#endif
+ PyObject *fixed_cause;
+ if (cause == Py_None) {
+ fixed_cause = NULL;
+ } else if (PyExceptionClass_Check(cause)) {
+ fixed_cause = PyObject_CallObject(cause, NULL);
+ if (fixed_cause == NULL)
+ goto bad;
+ } else if (PyExceptionInstance_Check(cause)) {
+ fixed_cause = cause;
+ Py_INCREF(fixed_cause);
+ } else {
+ PyErr_SetString(PyExc_TypeError,
+ "exception causes must derive from "
+ "BaseException");
+ goto bad;
+ }
+ PyException_SetCause(value, fixed_cause);
+ }
+ PyErr_SetObject(type, value);
+ if (tb) {
+#if CYTHON_COMPILING_IN_PYPY
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyErr_Fetch(tmp_type, tmp_value, tmp_tb);
+ Py_INCREF(tb);
+ PyErr_Restore(tmp_type, tmp_value, tb);
+ Py_XDECREF(tmp_tb);
+#else
+ PyThreadState *tstate = PyThreadState_GET();
+ PyObject* tmp_tb = tstate->curexc_traceback;
+ if (tb != tmp_tb) {
+ Py_INCREF(tb);
+ tstate->curexc_traceback = tb;
+ Py_XDECREF(tmp_tb);
+ }
+#endif
+ }
+bad:
+ Py_XDECREF(owned_instance);
+ return;
+}
+#endif
+
+static void __Pyx_RaiseBufferIndexError(int axis) {
+ PyErr_Format(PyExc_IndexError,
+ "Out of bounds on buffer access (axis %d)", axis);
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
+ PyObject *self, *result;
+ PyCFunction cfunc;
+ cfunc = PyCFunction_GET_FUNCTION(func);
+ self = PyCFunction_GET_SELF(func);
+ if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+ return NULL;
+ result = cfunc(self, arg);
+ Py_LeaveRecursiveCall();
+ if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+ PyErr_SetString(
+ PyExc_SystemError,
+ "NULL result without error in PyObject_Call");
+ }
+ return result;
+}
+#endif
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+ PyObject *result;
+ PyObject *args = PyTuple_New(1);
+ if (unlikely(!args)) return NULL;
+ Py_INCREF(arg);
+ PyTuple_SET_ITEM(args, 0, arg);
+ result = __Pyx_PyObject_Call(func, args, NULL);
+ Py_DECREF(args);
+ return result;
+}
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+#ifdef __Pyx_CyFunction_USED
+ if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
+#else
+ if (likely(PyCFunction_Check(func))) {
+#endif
+ if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
+ return __Pyx_PyObject_CallMethO(func, arg);
+ }
+ }
+ return __Pyx__PyObject_CallOneArg(func, arg);
+}
+#else
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+ PyObject* args = PyTuple_Pack(1, arg);
+ return (likely(args)) ? __Pyx_PyObject_Call(func, args, NULL) : NULL;
+}
+#endif
+
+static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
+ unsigned int n = 1;
+ return *(unsigned char*)(&n) != 0;
+}
+static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
+ __Pyx_BufFmt_StackElem* stack,
+ __Pyx_TypeInfo* type) {
+ stack[0].field = &ctx->root;
+ stack[0].parent_offset = 0;
+ ctx->root.type = type;
+ ctx->root.name = "buffer dtype";
+ ctx->root.offset = 0;
+ ctx->head = stack;
+ ctx->head->field = &ctx->root;
+ ctx->fmt_offset = 0;
+ ctx->head->parent_offset = 0;
+ ctx->new_packmode = '@';
+ ctx->enc_packmode = '@';
+ ctx->new_count = 1;
+ ctx->enc_count = 0;
+ ctx->enc_type = 0;
+ ctx->is_complex = 0;
+ ctx->is_valid_array = 0;
+ ctx->struct_alignment = 0;
+ while (type->typegroup == 'S') {
+ ++ctx->head;
+ ctx->head->field = type->fields;
+ ctx->head->parent_offset = 0;
+ type = type->fields->type;
+ }
+}
+static int __Pyx_BufFmt_ParseNumber(const char** ts) {
+ int count;
+ const char* t = *ts;
+ if (*t < '0' || *t > '9') {
+ return -1;
+ } else {
+ count = *t++ - '0';
+ while (*t >= '0' && *t < '9') {
+ count *= 10;
+ count += *t++ - '0';
+ }
+ }
+ *ts = t;
+ return count;
+}
+static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
+ int number = __Pyx_BufFmt_ParseNumber(ts);
+ if (number == -1)
+ PyErr_Format(PyExc_ValueError,\
+ "Does not understand character buffer dtype format string ('%c')", **ts);
+ return number;
+}
+static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
+ PyErr_Format(PyExc_ValueError,
+ "Unexpected format string character: '%c'", ch);
+}
+static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
+ switch (ch) {
+ case 'c': return "'char'";
+ case 'b': return "'signed char'";
+ case 'B': return "'unsigned char'";
+ case 'h': return "'short'";
+ case 'H': return "'unsigned short'";
+ case 'i': return "'int'";
+ case 'I': return "'unsigned int'";
+ case 'l': return "'long'";
+ case 'L': return "'unsigned long'";
+ case 'q': return "'long long'";
+ case 'Q': return "'unsigned long long'";
+ case 'f': return (is_complex ? "'complex float'" : "'float'");
+ case 'd': return (is_complex ? "'complex double'" : "'double'");
+ case 'g': return (is_complex ? "'complex long double'" : "'long double'");
+ case 'T': return "a struct";
+ case 'O': return "Python object";
+ case 'P': return "a pointer";
+ case 's': case 'p': return "a string";
+ case 0: return "end";
+ default: return "unparseable format string";
+ }
+}
+static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return 2;
+ case 'i': case 'I': case 'l': case 'L': return 4;
+ case 'q': case 'Q': return 8;
+ case 'f': return (is_complex ? 8 : 4);
+ case 'd': return (is_complex ? 16 : 8);
+ case 'g': {
+ PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
+ return 0;
+ }
+ case 'O': case 'P': return sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
+ switch (ch) {
+ case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(short);
+ case 'i': case 'I': return sizeof(int);
+ case 'l': case 'L': return sizeof(long);
+ #ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(PY_LONG_LONG);
+ #endif
+ case 'f': return sizeof(float) * (is_complex ? 2 : 1);
+ case 'd': return sizeof(double) * (is_complex ? 2 : 1);
+ case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
+ case 'O': case 'P': return sizeof(void*);
+ default: {
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+ }
+}
+typedef struct { char c; short x; } __Pyx_st_short;
+typedef struct { char c; int x; } __Pyx_st_int;
+typedef struct { char c; long x; } __Pyx_st_long;
+typedef struct { char c; float x; } __Pyx_st_float;
+typedef struct { char c; double x; } __Pyx_st_double;
+typedef struct { char c; long double x; } __Pyx_st_longdouble;
+typedef struct { char c; void *x; } __Pyx_st_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
+ case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
+ case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
+#endif
+ case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
+ case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
+ case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
+ case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+/* These are for computing the padding at the end of the struct to align
+ on the first member of the struct. This will probably the same as above,
+ but we don't have any guarantees.
+ */
+typedef struct { short x; char c; } __Pyx_pad_short;
+typedef struct { int x; char c; } __Pyx_pad_int;
+typedef struct { long x; char c; } __Pyx_pad_long;
+typedef struct { float x; char c; } __Pyx_pad_float;
+typedef struct { double x; char c; } __Pyx_pad_double;
+typedef struct { long double x; char c; } __Pyx_pad_longdouble;
+typedef struct { void *x; char c; } __Pyx_pad_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
+ case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
+ case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
+#endif
+ case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
+ case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
+ case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
+ case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
+ switch (ch) {
+ case 'c':
+ return 'H';
+ case 'b': case 'h': case 'i':
+ case 'l': case 'q': case 's': case 'p':
+ return 'I';
+ case 'B': case 'H': case 'I': case 'L': case 'Q':
+ return 'U';
+ case 'f': case 'd': case 'g':
+ return (is_complex ? 'C' : 'R');
+ case 'O':
+ return 'O';
+ case 'P':
+ return 'P';
+ default: {
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+ }
+}
+static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
+ if (ctx->head == NULL || ctx->head->field == &ctx->root) {
+ const char* expected;
+ const char* quote;
+ if (ctx->head == NULL) {
+ expected = "end";
+ quote = "";
+ } else {
+ expected = ctx->head->field->type->name;
+ quote = "'";
+ }
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected %s%s%s but got %s",
+ quote, expected, quote,
+ __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
+ } else {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_StructField* parent = (ctx->head - 1)->field;
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
+ field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
+ parent->type->name, field->name);
+ }
+}
+static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
+ char group;
+ size_t size, offset, arraysize = 1;
+ if (ctx->enc_type == 0) return 0;
+ if (ctx->head->field->type->arraysize[0]) {
+ int i, ndim = 0;
+ if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
+ ctx->is_valid_array = ctx->head->field->type->ndim == 1;
+ ndim = 1;
+ if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
+ PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %zu",
+ ctx->head->field->type->arraysize[0], ctx->enc_count);
+ return -1;
+ }
+ }
+ if (!ctx->is_valid_array) {
+ PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
+ ctx->head->field->type->ndim, ndim);
+ return -1;
+ }
+ for (i = 0; i < ctx->head->field->type->ndim; i++) {
+ arraysize *= ctx->head->field->type->arraysize[i];
+ }
+ ctx->is_valid_array = 0;
+ ctx->enc_count = 1;
+ }
+ group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
+ do {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_TypeInfo* type = field->type;
+ if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
+ size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
+ } else {
+ size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
+ }
+ if (ctx->enc_packmode == '@') {
+ size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
+ size_t align_mod_offset;
+ if (align_at == 0) return -1;
+ align_mod_offset = ctx->fmt_offset % align_at;
+ if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
+ if (ctx->struct_alignment == 0)
+ ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
+ ctx->is_complex);
+ }
+ if (type->size != size || type->typegroup != group) {
+ if (type->typegroup == 'C' && type->fields != NULL) {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ ++ctx->head;
+ ctx->head->field = type->fields;
+ ctx->head->parent_offset = parent_offset;
+ continue;
+ }
+ if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
+ } else {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ }
+ offset = ctx->head->parent_offset + field->offset;
+ if (ctx->fmt_offset != offset) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
+ (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
+ return -1;
+ }
+ ctx->fmt_offset += size;
+ if (arraysize)
+ ctx->fmt_offset += (arraysize - 1) * size;
+ --ctx->enc_count;
+ while (1) {
+ if (field == &ctx->root) {
+ ctx->head = NULL;
+ if (ctx->enc_count != 0) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ break;
+ }
+ ctx->head->field = ++field;
+ if (field->type == NULL) {
+ --ctx->head;
+ field = ctx->head->field;
+ continue;
+ } else if (field->type->typegroup == 'S') {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ if (field->type->fields->type == NULL) continue;
+ field = field->type->fields;
+ ++ctx->head;
+ ctx->head->field = field;
+ ctx->head->parent_offset = parent_offset;
+ break;
+ } else {
+ break;
+ }
+ }
+ } while (ctx->enc_count);
+ ctx->enc_type = 0;
+ ctx->is_complex = 0;
+ return 0;
+}
+static CYTHON_INLINE PyObject *
+__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
+{
+ const char *ts = *tsp;
+ int i = 0, number;
+ int ndim = ctx->head->field->type->ndim;
+;
+ ++ts;
+ if (ctx->new_count != 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Cannot handle repeated arrays in format string");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ while (*ts && *ts != ')') {
+ switch (*ts) {
+ case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
+ default: break;
+ }
+ number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %d",
+ ctx->head->field->type->arraysize[i], number);
+ if (*ts != ',' && *ts != ')')
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a comma in format string, got '%c'", *ts);
+ if (*ts == ',') ts++;
+ i++;
+ }
+ if (i != ndim)
+ return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
+ ctx->head->field->type->ndim, i);
+ if (!*ts) {
+ PyErr_SetString(PyExc_ValueError,
+ "Unexpected end of format string, expected ')'");
+ return NULL;
+ }
+ ctx->is_valid_array = 1;
+ ctx->new_count = 1;
+ *tsp = ++ts;
+ return Py_None;
+}
+static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
+ int got_Z = 0;
+ while (1) {
+ switch(*ts) {
+ case 0:
+ if (ctx->enc_type != 0 && ctx->head == NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ if (ctx->head != NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ return ts;
+ case ' ':
+ case '\r':
+ case '\n':
+ ++ts;
+ break;
+ case '<':
+ if (!__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '>':
+ case '!':
+ if (__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '=':
+ case '@':
+ case '^':
+ ctx->new_packmode = *ts++;
+ break;
+ case 'T':
+ {
+ const char* ts_after_sub;
+ size_t i, struct_count = ctx->new_count;
+ size_t struct_alignment = ctx->struct_alignment;
+ ctx->new_count = 1;
+ ++ts;
+ if (*ts != '{') {
+ PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ ctx->enc_count = 0;
+ ctx->struct_alignment = 0;
+ ++ts;
+ ts_after_sub = ts;
+ for (i = 0; i != struct_count; ++i) {
+ ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
+ if (!ts_after_sub) return NULL;
+ }
+ ts = ts_after_sub;
+ if (struct_alignment) ctx->struct_alignment = struct_alignment;
+ }
+ break;
+ case '}':
+ {
+ size_t alignment = ctx->struct_alignment;
+ ++ts;
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ if (alignment && ctx->fmt_offset % alignment) {
+ ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
+ }
+ }
+ return ts;
+ case 'x':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->fmt_offset += ctx->new_count;
+ ctx->new_count = 1;
+ ctx->enc_count = 0;
+ ctx->enc_type = 0;
+ ctx->enc_packmode = ctx->new_packmode;
+ ++ts;
+ break;
+ case 'Z':
+ got_Z = 1;
+ ++ts;
+ if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
+ __Pyx_BufFmt_RaiseUnexpectedChar('Z');
+ return NULL;
+ }
+ case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
+ case 'l': case 'L': case 'q': case 'Q':
+ case 'f': case 'd': case 'g':
+ case 'O': case 'p':
+ if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
+ ctx->enc_packmode == ctx->new_packmode) {
+ ctx->enc_count += ctx->new_count;
+ ctx->new_count = 1;
+ got_Z = 0;
+ ++ts;
+ break;
+ }
+ case 's':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_count = ctx->new_count;
+ ctx->enc_packmode = ctx->new_packmode;
+ ctx->enc_type = *ts;
+ ctx->is_complex = got_Z;
+ ++ts;
+ ctx->new_count = 1;
+ got_Z = 0;
+ break;
+ case ':':
+ ++ts;
+ while(*ts != ':') ++ts;
+ ++ts;
+ break;
+ case '(':
+ if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
+ break;
+ default:
+ {
+ int number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ ctx->new_count = (size_t)number;
+ }
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
+ buf->buf = NULL;
+ buf->obj = NULL;
+ buf->strides = __Pyx_zeros;
+ buf->shape = __Pyx_zeros;
+ buf->suboffsets = __Pyx_minusones;
+}
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
+ Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
+ int nd, int cast, __Pyx_BufFmt_StackElem* stack)
+{
+ if (obj == Py_None || obj == NULL) {
+ __Pyx_ZeroBuffer(buf);
+ return 0;
+ }
+ buf->buf = NULL;
+ if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
+ if (buf->ndim != nd) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ nd, buf->ndim);
+ goto fail;
+ }
+ if (!cast) {
+ __Pyx_BufFmt_Context ctx;
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned)buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
+ buf->itemsize, (buf->itemsize > 1) ? "s" : "",
+ dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
+ return 0;
+fail:;
+ __Pyx_ZeroBuffer(buf);
+ return -1;
+}
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
+ if (info->buf == NULL) return;
+ if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
+ __Pyx_ReleaseBuffer(info);
+}
+
+static int
+__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference)
+{
+ __Pyx_RefNannyDeclarations
+ int i, retval=-1;
+ Py_buffer *buf = &memview->view;
+ __Pyx_RefNannySetupContext("init_memviewslice", 0);
+ if (!buf) {
+ PyErr_SetString(PyExc_ValueError,
+ "buf is NULL.");
+ goto fail;
+ } else if (memviewslice->memview || memviewslice->data) {
+ PyErr_SetString(PyExc_ValueError,
+ "memviewslice is already initialized!");
+ goto fail;
+ }
+ if (buf->strides) {
+ for (i = 0; i < ndim; i++) {
+ memviewslice->strides[i] = buf->strides[i];
+ }
+ } else {
+ Py_ssize_t stride = buf->itemsize;
+ for (i = ndim - 1; i >= 0; i--) {
+ memviewslice->strides[i] = stride;
+ stride *= buf->shape[i];
+ }
+ }
+ for (i = 0; i < ndim; i++) {
+ memviewslice->shape[i] = buf->shape[i];
+ if (buf->suboffsets) {
+ memviewslice->suboffsets[i] = buf->suboffsets[i];
+ } else {
+ memviewslice->suboffsets[i] = -1;
+ }
+ }
+ memviewslice->memview = memview;
+ memviewslice->data = (char *)buf->buf;
+ if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
+ Py_INCREF(memview);
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ memviewslice->memview = 0;
+ memviewslice->data = 0;
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
+ va_list vargs;
+ char msg[200];
+ va_start(vargs, fmt);
+#ifdef HAVE_STDARG_PROTOTYPES
+ va_start(vargs, fmt);
+#else
+ va_start(vargs);
+#endif
+ vsnprintf(msg, 200, fmt, vargs);
+ Py_FatalError(msg);
+ va_end(vargs);
+}
+static CYTHON_INLINE int
+__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)++;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE int
+__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)--;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE void
+__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
+{
+ int first_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview || (PyObject *) memview == Py_None)
+ return;
+ if (__pyx_get_slice_count(memview) < 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ first_time = __pyx_add_acquisition_count(memview) == 0;
+ if (first_time) {
+ if (have_gil) {
+ Py_INCREF((PyObject *) memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_INCREF((PyObject *) memview);
+ PyGILState_Release(_gilstate);
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
+ int have_gil, int lineno) {
+ int last_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview ) {
+ return;
+ } else if ((PyObject *) memview == Py_None) {
+ memslice->memview = NULL;
+ return;
+ }
+ if (__pyx_get_slice_count(memview) <= 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ last_time = __pyx_sub_acquisition_count(memview) == 1;
+ memslice->data = NULL;
+ if (last_time) {
+ if (have_gil) {
+ Py_CLEAR(memslice->memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_CLEAR(memslice->memview);
+ PyGILState_Release(_gilstate);
+ }
+ } else {
+ memslice->memview = NULL;
+ }
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
+ PyObject *r;
+ if (!j) return NULL;
+ r = PyObject_GetItem(o, j);
+ Py_DECREF(j);
+ return r;
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
+ PyObject *r = PyList_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (is_list || PyList_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
+ if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
+ PyObject *r = PyList_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ }
+ else if (PyTuple_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ } else {
+ PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
+ if (likely(m && m->sq_item)) {
+ if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
+ Py_ssize_t l = m->sq_length(o);
+ if (likely(l >= 0)) {
+ i += l;
+ } else {
+ if (PyErr_ExceptionMatches(PyExc_OverflowError))
+ PyErr_Clear();
+ else
+ return NULL;
+ }
+ }
+ return m->sq_item(o, i);
+ }
+ }
+#else
+ if (is_list || PySequence_Check(o)) {
+ return PySequence_GetItem(o, i);
+ }
+#endif
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+}
+
+static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
+ PyErr_Format(PyExc_TypeError,
+ "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
+ name, type->tp_name, Py_TYPE(obj)->tp_name);
+}
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact)
+{
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (none_allowed && obj == Py_None) return 1;
+ else if (exact) {
+ if (likely(Py_TYPE(obj) == type)) return 1;
+ #if PY_MAJOR_VERSION == 2
+ else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
+ #endif
+ }
+ else {
+ if (likely(PyObject_TypeCheck(obj, type))) return 1;
+ }
+ __Pyx_RaiseArgumentTypeInvalid(name, obj, type);
+ return 0;
+}
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+ if (s1 == s2) {
+ return (equals == Py_EQ);
+ } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
+ const char *ps1, *ps2;
+ Py_ssize_t length = PyBytes_GET_SIZE(s1);
+ if (length != PyBytes_GET_SIZE(s2))
+ return (equals == Py_NE);
+ ps1 = PyBytes_AS_STRING(s1);
+ ps2 = PyBytes_AS_STRING(s2);
+ if (ps1[0] != ps2[0]) {
+ return (equals == Py_NE);
+ } else if (length == 1) {
+ return (equals == Py_EQ);
+ } else {
+ int result = memcmp(ps1, ps2, (size_t)length);
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
+ return (equals == Py_NE);
+ } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
+ return (equals == Py_NE);
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+#endif
+}
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+#if PY_MAJOR_VERSION < 3
+ PyObject* owned_ref = NULL;
+#endif
+ int s1_is_unicode, s2_is_unicode;
+ if (s1 == s2) {
+ goto return_eq;
+ }
+ s1_is_unicode = PyUnicode_CheckExact(s1);
+ s2_is_unicode = PyUnicode_CheckExact(s2);
+#if PY_MAJOR_VERSION < 3
+ if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
+ owned_ref = PyUnicode_FromObject(s2);
+ if (unlikely(!owned_ref))
+ return -1;
+ s2 = owned_ref;
+ s2_is_unicode = 1;
+ } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
+ owned_ref = PyUnicode_FromObject(s1);
+ if (unlikely(!owned_ref))
+ return -1;
+ s1 = owned_ref;
+ s1_is_unicode = 1;
+ } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
+ return __Pyx_PyBytes_Equals(s1, s2, equals);
+ }
+#endif
+ if (s1_is_unicode & s2_is_unicode) {
+ Py_ssize_t length;
+ int kind;
+ void *data1, *data2;
+ if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
+ return -1;
+ length = __Pyx_PyUnicode_GET_LENGTH(s1);
+ if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
+ goto return_ne;
+ }
+ kind = __Pyx_PyUnicode_KIND(s1);
+ if (kind != __Pyx_PyUnicode_KIND(s2)) {
+ goto return_ne;
+ }
+ data1 = __Pyx_PyUnicode_DATA(s1);
+ data2 = __Pyx_PyUnicode_DATA(s2);
+ if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
+ goto return_ne;
+ } else if (length == 1) {
+ goto return_eq;
+ } else {
+ int result = memcmp(data1, data2, (size_t)(length * kind));
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & s2_is_unicode) {
+ goto return_ne;
+ } else if ((s2 == Py_None) & s1_is_unicode) {
+ goto return_ne;
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+return_eq:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ);
+return_ne:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_NE);
+#endif
+}
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
+ Py_ssize_t q = a / b;
+ Py_ssize_t r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
+#if CYTHON_COMPILING_IN_CPYTHON
+#if PY_MAJOR_VERSION >= 3
+ if (likely(PyUnicode_Check(n)))
+#else
+ if (likely(PyString_Check(n)))
+#endif
+ return __Pyx_PyObject_GetAttrStr(o, n);
+#endif
+ return PyObject_GetAttr(o, n);
+}
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
+ Py_ssize_t length;
+ if (unlikely((start < 0) | (stop < 0))) {
+ length = strlen(cstring);
+ if (start < 0) {
+ start += length;
+ if (start < 0)
+ start = 0;
+ }
+ if (stop < 0)
+ stop += length;
+ }
+ length = stop - start;
+ if (unlikely(length <= 0))
+ return PyUnicode_FromUnicode(NULL, 0);
+ cstring += start;
+ if (decode_func) {
+ return decode_func(cstring, length, errors);
+ } else {
+ return PyUnicode_Decode(cstring, length, encoding, errors);
+ }
+}
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
+ PyErr_Format(PyExc_ValueError,
+ "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
+ PyErr_Format(PyExc_ValueError,
+ "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
+ index, (index == 1) ? "" : "s");
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
+ PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
+}
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (likely(PyObject_TypeCheck(obj, type)))
+ return 1;
+ PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
+ Py_TYPE(obj)->tp_name, type->tp_name);
+ return 0;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->exc_type;
+ *value = tstate->exc_value;
+ *tb = tstate->exc_traceback;
+ Py_XINCREF(*type);
+ Py_XINCREF(*value);
+ Py_XINCREF(*tb);
+#else
+ PyErr_GetExcInfo(type, value, tb);
+#endif
+}
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = type;
+ tstate->exc_value = value;
+ tstate->exc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(type, value, tb);
+#endif
+}
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *local_type, *local_value, *local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ local_type = tstate->curexc_type;
+ local_value = tstate->curexc_value;
+ local_tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(&local_type, &local_value, &local_tb);
+#endif
+ PyErr_NormalizeException(&local_type, &local_value, &local_tb);
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (unlikely(tstate->curexc_type))
+#else
+ if (unlikely(PyErr_Occurred()))
+#endif
+ goto bad;
+ #if PY_MAJOR_VERSION >= 3
+ if (local_tb) {
+ if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
+ goto bad;
+ }
+ #endif
+ Py_XINCREF(local_tb);
+ Py_XINCREF(local_type);
+ Py_XINCREF(local_value);
+ *type = local_type;
+ *value = local_value;
+ *tb = local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = local_type;
+ tstate->exc_value = local_value;
+ tstate->exc_traceback = local_tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(local_type, local_value, local_tb);
+#endif
+ return 0;
+bad:
+ *type = 0;
+ *value = 0;
+ *tb = 0;
+ Py_XDECREF(local_type);
+ Py_XDECREF(local_value);
+ Py_XDECREF(local_tb);
+ return -1;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = *type;
+ tstate->exc_value = *value;
+ tstate->exc_traceback = *tb;
+#else
+ PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
+ PyErr_SetExcInfo(*type, *value, *tb);
+#endif
+ *type = tmp_type;
+ *value = tmp_value;
+ *tb = tmp_tb;
+}
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
+ PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
+}
+
+static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
+ long q = a / b;
+ long r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
+ CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
+ int full_traceback) {
+ PyObject *old_exc, *old_val, *old_tb;
+ PyObject *ctx;
+ __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
+ if (full_traceback) {
+ Py_XINCREF(old_exc);
+ Py_XINCREF(old_val);
+ Py_XINCREF(old_tb);
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ PyErr_PrintEx(1);
+ }
+ #if PY_MAJOR_VERSION < 3
+ ctx = PyString_FromString(name);
+ #else
+ ctx = PyUnicode_FromString(name);
+ #endif
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ if (!ctx) {
+ PyErr_WriteUnraisable(Py_None);
+ } else {
+ PyErr_WriteUnraisable(ctx);
+ Py_DECREF(ctx);
+ }
+}
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
+#if PY_VERSION_HEX >= 0x02070000
+ PyObject *ob = PyCapsule_New(vtable, 0, 0);
+#else
+ PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
+#endif
+ if (!ob)
+ goto bad;
+ if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
+ goto bad;
+ Py_DECREF(ob);
+ return 0;
+bad:
+ Py_XDECREF(ob);
+ return -1;
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
+#ifdef __Pyx_CyFunction_USED
+ if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
+#else
+ if (likely(PyCFunction_Check(func))) {
+#endif
+ if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
+ return __Pyx_PyObject_CallMethO(func, NULL);
+ }
+ }
+ return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
+}
+#endif
+
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
+ int start = 0, mid = 0, end = count - 1;
+ if (end >= 0 && code_line > entries[end].code_line) {
+ return count;
+ }
+ while (start < end) {
+ mid = (start + end) / 2;
+ if (code_line < entries[mid].code_line) {
+ end = mid;
+ } else if (code_line > entries[mid].code_line) {
+ start = mid + 1;
+ } else {
+ return mid;
+ }
+ }
+ if (code_line <= entries[mid].code_line) {
+ return mid;
+ } else {
+ return mid + 1;
+ }
+}
+static PyCodeObject *__pyx_find_code_object(int code_line) {
+ PyCodeObject* code_object;
+ int pos;
+ if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
+ return NULL;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
+ return NULL;
+ }
+ code_object = __pyx_code_cache.entries[pos].code_object;
+ Py_INCREF(code_object);
+ return code_object;
+}
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
+ int pos, i;
+ __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
+ if (unlikely(!code_line)) {
+ return;
+ }
+ if (unlikely(!entries)) {
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (likely(entries)) {
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = 64;
+ __pyx_code_cache.count = 1;
+ entries[0].code_line = code_line;
+ entries[0].code_object = code_object;
+ Py_INCREF(code_object);
+ }
+ return;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
+ PyCodeObject* tmp = entries[pos].code_object;
+ entries[pos].code_object = code_object;
+ Py_DECREF(tmp);
+ return;
+ }
+ if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
+ int new_max = __pyx_code_cache.max_count + 64;
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
+ __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (unlikely(!entries)) {
+ return;
+ }
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = new_max;
+ }
+ for (i=__pyx_code_cache.count; i>pos; i--) {
+ entries[i] = entries[i-1];
+ }
+ entries[pos].code_line = code_line;
+ entries[pos].code_object = code_object;
+ __pyx_code_cache.count++;
+ Py_INCREF(code_object);
+}
+
+#include "compile.h"
+#include "frameobject.h"
+#include "traceback.h"
+static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
+ const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyObject *py_srcfile = 0;
+ PyObject *py_funcname = 0;
+ #if PY_MAJOR_VERSION < 3
+ py_srcfile = PyString_FromString(filename);
+ #else
+ py_srcfile = PyUnicode_FromString(filename);
+ #endif
+ if (!py_srcfile) goto bad;
+ if (c_line) {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #else
+ py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #endif
+ }
+ else {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromString(funcname);
+ #else
+ py_funcname = PyUnicode_FromString(funcname);
+ #endif
+ }
+ if (!py_funcname) goto bad;
+ py_code = __Pyx_PyCode_New(
+ 0,
+ 0,
+ 0,
+ 0,
+ 0,
+ __pyx_empty_bytes, /*PyObject *code,*/
+ __pyx_empty_tuple, /*PyObject *consts,*/
+ __pyx_empty_tuple, /*PyObject *names,*/
+ __pyx_empty_tuple, /*PyObject *varnames,*/
+ __pyx_empty_tuple, /*PyObject *freevars,*/
+ __pyx_empty_tuple, /*PyObject *cellvars,*/
+ py_srcfile, /*PyObject *filename,*/
+ py_funcname, /*PyObject *name,*/
+ py_line,
+ __pyx_empty_bytes /*PyObject *lnotab*/
+ );
+ Py_DECREF(py_srcfile);
+ Py_DECREF(py_funcname);
+ return py_code;
+bad:
+ Py_XDECREF(py_srcfile);
+ Py_XDECREF(py_funcname);
+ return NULL;
+}
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyFrameObject *py_frame = 0;
+ py_code = __pyx_find_code_object(c_line ? c_line : py_line);
+ if (!py_code) {
+ py_code = __Pyx_CreateCodeObjectForTraceback(
+ funcname, c_line, py_line, filename);
+ if (!py_code) goto bad;
+ __pyx_insert_code_object(c_line ? c_line : py_line, py_code);
+ }
+ py_frame = PyFrame_New(
+ PyThreadState_GET(), /*PyThreadState *tstate,*/
+ py_code, /*PyCodeObject *code,*/
+ __pyx_d, /*PyObject *globals,*/
+ 0 /*PyObject *locals*/
+ );
+ if (!py_frame) goto bad;
+ py_frame->f_lineno = py_line;
+ PyTraceBack_Here(py_frame);
+bad:
+ Py_XDECREF(py_code);
+ Py_XDECREF(py_frame);
+}
+
+#if PY_MAJOR_VERSION < 3
+static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
+ if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
+ PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
+ return -1;
+}
+static void __Pyx_ReleaseBuffer(Py_buffer *view) {
+ PyObject *obj = view->obj;
+ if (!obj) return;
+ if (PyObject_CheckBuffer(obj)) {
+ PyBuffer_Release(view);
+ return;
+ }
+ Py_DECREF(obj);
+ view->obj = NULL;
+}
+#endif
+
+
+ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
+ PyObject *empty_list = 0;
+ PyObject *module = 0;
+ PyObject *global_dict = 0;
+ PyObject *empty_dict = 0;
+ PyObject *list;
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_import;
+ py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
+ if (!py_import)
+ goto bad;
+ #endif
+ if (from_list)
+ list = from_list;
+ else {
+ empty_list = PyList_New(0);
+ if (!empty_list)
+ goto bad;
+ list = empty_list;
+ }
+ global_dict = PyModule_GetDict(__pyx_m);
+ if (!global_dict)
+ goto bad;
+ empty_dict = PyDict_New();
+ if (!empty_dict)
+ goto bad;
+ {
+ #if PY_MAJOR_VERSION >= 3
+ if (level == -1) {
+ if (strchr(__Pyx_MODULE_NAME, '.')) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(1);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, 1);
+ #endif
+ if (!module) {
+ if (!PyErr_ExceptionMatches(PyExc_ImportError))
+ goto bad;
+ PyErr_Clear();
+ }
+ }
+ level = 0;
+ }
+ #endif
+ if (!module) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(level);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, level);
+ #endif
+ }
+ }
+bad:
+ #if PY_VERSION_HEX < 0x03030000
+ Py_XDECREF(py_import);
+ #endif
+ Py_XDECREF(empty_list);
+ Py_XDECREF(empty_dict);
+ return module;
+}
+
+static PyObject *__pyx_memview_get_double(const char *itemp) {
+ return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
+}
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
+ double value = __pyx_PyFloat_AsDouble(obj);
+ if ((value == (double)-1) && PyErr_Occurred())
+ return 0;
+ *(double *) itemp = value;
+ return 1;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(long) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(long) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(long),
+ little, !is_unsigned);
+ }
+}
+
+#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \
+ { \
+ func_type value = func_value; \
+ if (sizeof(target_type) < sizeof(func_type)) { \
+ if (unlikely(value != (func_type) (target_type) value)) { \
+ func_type zero = 0; \
+ if (is_unsigned && unlikely(value < zero)) \
+ goto raise_neg_overflow; \
+ else \
+ goto raise_overflow; \
+ } \
+ } \
+ return (target_type) value; \
+ }
+
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ #include "longintrepr.h"
+ #endif
+#endif
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(long) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (long) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(long) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(long) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x))
+ } else if (sizeof(long) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ long val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (long) -1;
+ }
+ } else {
+ long val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (long) -1;
+ val = __Pyx_PyInt_As_long(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to long");
+ return (long) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to long");
+ return (long) -1;
+}
+
+static PyObject *__pyx_memview_get_long(const char *itemp) {
+ return (PyObject *) __Pyx_PyInt_From_long(*(long *) itemp);
+}
+static int __pyx_memview_set_long(const char *itemp, PyObject *obj) {
+ long value = __Pyx_PyInt_As_long(obj);
+ if ((value == (long)-1) && PyErr_Occurred())
+ return 0;
+ *(long *) itemp = value;
+ return 1;
+}
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(int) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (int) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(int) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(int) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x))
+ } else if (sizeof(int) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ int val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (int) -1;
+ }
+ } else {
+ int val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (int) -1;
+ val = __Pyx_PyInt_As_int(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to int");
+ return (int) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to int");
+ return (int) -1;
+}
+
+static int
+__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim)
+{
+ int i, index, step, start;
+ Py_ssize_t itemsize = mvs->memview->view.itemsize;
+ if (order == 'F') {
+ step = 1;
+ start = 0;
+ } else {
+ step = -1;
+ start = ndim - 1;
+ }
+ for (i = 0; i < ndim; i++) {
+ index = start + step * i;
+ if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize)
+ return 0;
+ itemsize *= mvs->shape[index];
+ }
+ return 1;
+}
+
+static void
+__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
+ void **out_start, void **out_end,
+ int ndim, size_t itemsize)
+{
+ char *start, *end;
+ int i;
+ start = end = slice->data;
+ for (i = 0; i < ndim; i++) {
+ Py_ssize_t stride = slice->strides[i];
+ Py_ssize_t extent = slice->shape[i];
+ if (extent == 0) {
+ *out_start = *out_end = start;
+ return;
+ } else {
+ if (stride > 0)
+ end += stride * (extent - 1);
+ else
+ start += stride * (extent - 1);
+ }
+ }
+ *out_start = start;
+ *out_end = end + itemsize;
+}
+static int
+__pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize)
+{
+ void *start1, *end1, *start2, *end2;
+ __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
+ __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
+ return (start1 < end2) && (start2 < end1);
+}
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object)
+{
+ __Pyx_RefNannyDeclarations
+ int i;
+ __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
+ struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
+ Py_buffer *buf = &from_memview->view;
+ PyObject *shape_tuple = NULL;
+ PyObject *temp_int = NULL;
+ struct __pyx_array_obj *array_obj = NULL;
+ struct __pyx_memoryview_obj *memview_obj = NULL;
+ __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
+ for (i = 0; i < ndim; i++) {
+ if (from_mvs->suboffsets[i] >= 0) {
+ PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
+ "indirect dimensions (axis %d)", i);
+ goto fail;
+ }
+ }
+ shape_tuple = PyTuple_New(ndim);
+ if (unlikely(!shape_tuple)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(shape_tuple);
+ for(i = 0; i < ndim; i++) {
+ temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
+ if(unlikely(!temp_int)) {
+ goto fail;
+ } else {
+ PyTuple_SET_ITEM(shape_tuple, i, temp_int);
+ temp_int = NULL;
+ }
+ }
+ array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
+ if (unlikely(!array_obj)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(array_obj);
+ memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ (PyObject *) array_obj, contig_flag,
+ dtype_is_object,
+ from_mvs->memview->typeinfo);
+ if (unlikely(!memview_obj))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
+ goto fail;
+ if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
+ dtype_is_object) < 0))
+ goto fail;
+ goto no_fail;
+fail:
+ __Pyx_XDECREF(new_mvs.memview);
+ new_mvs.memview = NULL;
+ new_mvs.data = NULL;
+no_fail:
+ __Pyx_XDECREF(shape_tuple);
+ __Pyx_XDECREF(temp_int);
+ __Pyx_XDECREF(array_obj);
+ __Pyx_RefNannyFinishContext();
+ return new_mvs;
+}
+
+static CYTHON_INLINE PyObject *
+__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
+{
+ PyObject *cobj;
+#if PY_VERSION_HEX >= 0x02070000
+ cobj = PyCapsule_New(p, sig, NULL);
+#else
+ cobj = PyCObject_FromVoidPtr(p, NULL);
+#endif
+ return cobj;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(int) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(int) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(int),
+ little, !is_unsigned);
+ }
+}
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
+ const char neg_one = (char) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(char) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (char) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(char) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(char) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(char) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x))
+ } else if (sizeof(char) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ char val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (char) -1;
+ }
+ } else {
+ char val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (char) -1;
+ val = __Pyx_PyInt_As_char(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to char");
+ return (char) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to char");
+ return (char) -1;
+}
+
+static int
+__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
+{
+ int i;
+ if (!a || !b)
+ return 0;
+ if (a == b)
+ return 1;
+ if (a->size != b->size || a->typegroup != b->typegroup ||
+ a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
+ if (a->typegroup == 'H' || b->typegroup == 'H') {
+ return a->size == b->size;
+ } else {
+ return 0;
+ }
+ }
+ if (a->ndim) {
+ for (i = 0; i < a->ndim; i++)
+ if (a->arraysize[i] != b->arraysize[i])
+ return 0;
+ }
+ if (a->typegroup == 'S') {
+ if (a->flags != b->flags)
+ return 0;
+ if (a->fields || b->fields) {
+ if (!(a->fields && b->fields))
+ return 0;
+ for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
+ __Pyx_StructField *field_a = a->fields + i;
+ __Pyx_StructField *field_b = b->fields + i;
+ if (field_a->offset != field_b->offset ||
+ !__pyx_typeinfo_cmp(field_a->type, field_b->type))
+ return 0;
+ }
+ return !a->fields[i].type && !b->fields[i].type;
+ }
+ }
+ return 1;
+}
+
+static int
+__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
+{
+ if (buf->shape[dim] <= 1)
+ return 1;
+ if (buf->strides) {
+ if (spec & __Pyx_MEMVIEW_CONTIG) {
+ if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
+ if (buf->strides[dim] != sizeof(void *)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly contiguous "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ } else if (buf->strides[dim] != buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_FOLLOW) {
+ Py_ssize_t stride = buf->strides[dim];
+ if (stride < 0)
+ stride = -stride;
+ if (stride < buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ } else {
+ if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not contiguous in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (spec & (__Pyx_MEMVIEW_PTR)) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not indirect in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (buf->suboffsets) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer exposes suboffsets but no strides");
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
+{
+ if (spec & __Pyx_MEMVIEW_DIRECT) {
+ if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer not compatible with direct access "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_PTR) {
+ if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly accessible "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
+{
+ int i;
+ if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = 0; i < ndim; i++) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1)
+ {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not fortran contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = ndim - 1; i >- 1; i--) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not C contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj)
+{
+ struct __pyx_memoryview_obj *memview, *new_memview;
+ __Pyx_RefNannyDeclarations
+ Py_buffer *buf;
+ int i, spec = 0, retval = -1;
+ __Pyx_BufFmt_Context ctx;
+ int from_memoryview = __pyx_memoryview_check(original_obj);
+ __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
+ if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
+ original_obj)->typeinfo)) {
+ memview = (struct __pyx_memoryview_obj *) original_obj;
+ new_memview = NULL;
+ } else {
+ memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ original_obj, buf_flags, 0, dtype);
+ new_memview = memview;
+ if (unlikely(!memview))
+ goto fail;
+ }
+ buf = &memview->view;
+ if (buf->ndim != ndim) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ ndim, buf->ndim);
+ goto fail;
+ }
+ if (new_memview) {
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned) buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
+ "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
+ buf->itemsize,
+ (buf->itemsize > 1) ? "s" : "",
+ dtype->name,
+ dtype->size,
+ (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ for (i = 0; i < ndim; i++) {
+ spec = axes_specs[i];
+ if (!__pyx_check_strides(buf, i, ndim, spec))
+ goto fail;
+ if (!__pyx_check_suboffsets(buf, i, ndim, spec))
+ goto fail;
+ }
+ if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
+ new_memview != NULL) == -1)) {
+ goto fail;
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ Py_XDECREF(new_memview);
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *obj) {
+ __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+ __Pyx_BufFmt_StackElem stack[1];
+ int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+ int retcode;
+ if (obj == Py_None) {
+ result.memview = (struct __pyx_memoryview_obj *) Py_None;
+ return result;
+ }
+ retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+ (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
+ &__Pyx_TypeInfo_double, stack,
+ &result, obj);
+ if (unlikely(retcode == -1))
+ goto __pyx_fail;
+ return result;
+__pyx_fail:
+ result.memview = NULL;
+ result.data = NULL;
+ return result;
+}
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_long(PyObject *obj) {
+ __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+ __Pyx_BufFmt_StackElem stack[1];
+ int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+ int retcode;
+ if (obj == Py_None) {
+ result.memview = (struct __pyx_memoryview_obj *) Py_None;
+ return result;
+ }
+ retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+ (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
+ &__Pyx_TypeInfo_long, stack,
+ &result, obj);
+ if (unlikely(retcode == -1))
+ goto __pyx_fail;
+ return result;
+__pyx_fail:
+ result.memview = NULL;
+ result.data = NULL;
+ return result;
+}
+
+static int __Pyx_check_binary_version(void) {
+ char ctversion[4], rtversion[4];
+ PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
+ PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
+ if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
+ char message[200];
+ PyOS_snprintf(message, sizeof(message),
+ "compiletime version %s of module '%.100s' "
+ "does not match runtime version %s",
+ ctversion, __Pyx_MODULE_NAME, rtversion);
+ return PyErr_WarnEx(NULL, message, 1);
+ }
+ return 0;
+}
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
+ while (t->p) {
+ #if PY_MAJOR_VERSION < 3
+ if (t->is_unicode) {
+ *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
+ } else if (t->intern) {
+ *t->p = PyString_InternFromString(t->s);
+ } else {
+ *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
+ }
+ #else
+ if (t->is_unicode | t->is_str) {
+ if (t->intern) {
+ *t->p = PyUnicode_InternFromString(t->s);
+ } else if (t->encoding) {
+ *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
+ } else {
+ *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
+ }
+ } else {
+ *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
+ }
+ #endif
+ if (!*t->p)
+ return -1;
+ ++t;
+ }
+ return 0;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
+ return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
+ Py_ssize_t ignore;
+ return __Pyx_PyObject_AsStringAndSize(o, &ignore);
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+ if (
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ __Pyx_sys_getdefaultencoding_not_ascii &&
+#endif
+ PyUnicode_Check(o)) {
+#if PY_VERSION_HEX < 0x03030000
+ char* defenc_c;
+ PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
+ if (!defenc) return NULL;
+ defenc_c = PyBytes_AS_STRING(defenc);
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ {
+ char* end = defenc_c + PyBytes_GET_SIZE(defenc);
+ char* c;
+ for (c = defenc_c; c < end; c++) {
+ if ((unsigned char) (*c) >= 128) {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+ }
+ }
+#endif
+ *length = PyBytes_GET_SIZE(defenc);
+ return defenc_c;
+#else
+ if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ if (PyUnicode_IS_ASCII(o)) {
+ *length = PyUnicode_GET_LENGTH(o);
+ return PyUnicode_AsUTF8(o);
+ } else {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+#else
+ return PyUnicode_AsUTF8AndSize(o, length);
+#endif
+#endif
+ } else
+#endif
+#if !CYTHON_COMPILING_IN_PYPY
+ if (PyByteArray_Check(o)) {
+ *length = PyByteArray_GET_SIZE(o);
+ return PyByteArray_AS_STRING(o);
+ } else
+#endif
+ {
+ char* result;
+ int r = PyBytes_AsStringAndSize(o, &result, length);
+ if (unlikely(r < 0)) {
+ return NULL;
+ } else {
+ return result;
+ }
+ }
+}
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
+ int is_true = x == Py_True;
+ if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
+ else return PyObject_IsTrue(x);
+}
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
+ PyNumberMethods *m;
+ const char *name = NULL;
+ PyObject *res = NULL;
+#if PY_MAJOR_VERSION < 3
+ if (PyInt_Check(x) || PyLong_Check(x))
+#else
+ if (PyLong_Check(x))
+#endif
+ return Py_INCREF(x), x;
+ m = Py_TYPE(x)->tp_as_number;
+#if PY_MAJOR_VERSION < 3
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Int(x);
+ }
+ else if (m && m->nb_long) {
+ name = "long";
+ res = PyNumber_Long(x);
+ }
+#else
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Long(x);
+ }
+#endif
+ if (res) {
+#if PY_MAJOR_VERSION < 3
+ if (!PyInt_Check(res) && !PyLong_Check(res)) {
+#else
+ if (!PyLong_Check(res)) {
+#endif
+ PyErr_Format(PyExc_TypeError,
+ "__%.4s__ returned non-%.4s (type %.200s)",
+ name, name, Py_TYPE(res)->tp_name);
+ Py_DECREF(res);
+ return NULL;
+ }
+ }
+ else if (!PyErr_Occurred()) {
+ PyErr_SetString(PyExc_TypeError,
+ "an integer is required");
+ }
+ return res;
+}
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
+ Py_ssize_t ival;
+ PyObject *x;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_CheckExact(b)))
+ return PyInt_AS_LONG(b);
+#endif
+ if (likely(PyLong_CheckExact(b))) {
+ #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(b)) {
+ case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0];
+ case 0: return 0;
+ case 1: return ((PyLongObject*)b)->ob_digit[0];
+ }
+ #endif
+ #endif
+ return PyLong_AsSsize_t(b);
+ }
+ x = PyNumber_Index(b);
+ if (!x) return -1;
+ ival = PyInt_AsSsize_t(x);
+ Py_DECREF(x);
+ return ival;
+}
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
+ return PyInt_FromSize_t(ival);
+}
+
+
+#endif /* Py_PYTHON_H */
diff --git a/silx/math/fit/filters/filters.pyx b/silx/math/fit/filters/filters.pyx
new file mode 100644
index 0000000..9887ad7
--- /dev/null
+++ b/silx/math/fit/filters/filters.pyx
@@ -0,0 +1,412 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+"""This module provides background extraction functions and smoothing
+functions. These functions are extracted from PyMca module SpecFitFuns.
+
+Index of background extraction functions:
+------------------------------------------
+
+ - :func:`strip`
+ - :func:`snip1d`
+ - :func:`snip2d`
+ - :func:`snip3d`
+
+Smoothing functions:
+--------------------
+
+ - :func:`savitsky_golay`
+ - :func:`smooth1d`
+ - :func:`smooth2d`
+ - :func:`smooth3d`
+
+API documentation:
+-------------------
+
+"""
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+import logging
+import numpy
+
+logging.basicConfig()
+_logger = logging.getLogger(__name__)
+
+cimport cython
+cimport filters_wrapper
+
+
+def strip(data, w=1, niterations=1000, factor=1.0, anchors=None):
+ """Extract background from data using the strip algorithm, as explained at
+ http://pymca.sourceforge.net/stripbackground.html.
+
+ In its simplest implementation it is just as an iterative procedure
+ depending on two parameters. These parameters are the strip background
+ width ``w``, and the number of iterations. At each iteration, if the
+ contents of channel ``i``, ``y(i)``, is above the average of the contents
+ of the channels at ``w`` channels of distance, ``y(i-w)`` and
+ ``y(i+w)``, ``y(i)`` is replaced by the average.
+ At the end of the process we are left with something that resembles a spectrum
+ in which the peaks have been stripped.
+
+ :param data: Data array
+ :type data: numpy.ndarray
+ :param w: Strip width
+ :param niterations: number of iterations
+ :param factor: scaling factor applied to the average of ``y(i-w)`` and
+ ``y(i+w)`` before comparing to ``y(i)``
+ :param anchors: Array of anchors, indices of points that will not be
+ modified during the stripping procedure.
+ :return: Data with peaks stripped away
+ """
+ cdef:
+ double[::1] input_c
+ double[::1] output
+ long[::1] anchors_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__"):
+ raise TypeError("data must be a sequence (list, tuple) " +
+ "or a numpy array")
+ data_shape = (len(data), )
+ else:
+ data_shape = data.shape
+
+ input_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ output = numpy.empty(shape=(input_c.size,),
+ dtype=numpy.float64)
+
+ if anchors is not None and len(anchors):
+ # numpy.int_ is the same as C long (http://docs.scipy.org/doc/numpy/user/basics.types.html)
+ anchors_c = numpy.array(anchors,
+ copy=False,
+ dtype=numpy.int_,
+ order='C')
+ len_anchors = anchors_c.size
+ else:
+ # Make a dummy length-1 array, because if I use shape=(0,) I get the error
+ # IndexError: Out of bounds on buffer access (axis 0)
+ anchors_c = numpy.empty(shape=(1,),
+ dtype=numpy.int_)
+ len_anchors = 0
+
+
+ status = filters_wrapper.strip(&input_c[0], input_c.size,
+ factor, niterations, w,
+ &anchors_c[0], len_anchors, &output[0])
+
+ return numpy.asarray(output).reshape(data_shape)
+
+
+def snip1d(data, snip_width):
+ """Estimate the baseline (background) of a 1D data vector by clipping peaks.
+
+ Implementation of the algorithm SNIP in 1D is described in *Miroslav
+ Morhac et al. Nucl. Instruments and Methods in Physics Research A401
+ (1997) 113-132*.
+
+ The original idea for 1D and the low-statistics-digital-filter (lsdf) come
+ from *C.G. Ryan et al. Nucl. Instruments and Methods in Physics Research
+ B34 (1988) 396-402*.
+
+ :param data: Data array, preferably 1D and of type *numpy.float64*.
+ Else, the data array will be flattened and converted to
+ *dtype=numpy.float64* prior to applying the snip filter.
+ :type data: numpy.ndarray
+ :param snip_width: Width of the snip operator, in number of samples.
+ A sample will be iteratively compared to it's neighbors up to a
+ distance of ``snip_width`` samples. This parameters has a direct
+ influence on the speed of the algorithm.
+ :type width: int
+ :return: Baseline of the input array, as an array of the same shape.
+ :rtype: numpy.ndarray
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__"):
+ raise TypeError("data must be a sequence (list, tuple) " +
+ "or a numpy array")
+ data_shape = (len(data), )
+ else:
+ data_shape = data.shape
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.snip1d(&data_c[0], data_c.size, snip_width)
+
+ return numpy.asarray(data_c).reshape(data_shape)
+
+
+def snip2d(data, snip_width):
+ """Estimate the baseline (background) of a 2D data signal by clipping peaks.
+
+ Implementation of the algorithm SNIP in 2D described in
+ *Miroslav Morhac et al. Nucl. Instruments and Methods in Physics Research
+ A401 (1997) 113-132.*
+
+ :param data: 2D array
+ :type data: numpy.ndarray
+ :param width: Width of the snip operator, in number of samples. A wider
+ snip operator will result in a smoother result (lower frequency peaks
+ will be clipped), and a longer computation time.
+ :type width: int
+ :return: Baseline of the input array, as an array of the same shape.
+ :rtype: numpy.ndarray
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__") or not hasattr(data[0], "__len__"):
+ raise TypeError("data must be a 2D sequence (list, tuple) " +
+ "or a 2D numpy array")
+ nrows = len(data)
+ ncolumns = len(data[0])
+ data_shape = (len(data), len(data[0]))
+
+ else:
+ data_shape = data.shape
+ nrows = data_shape[0]
+ if len(data_shape) == 2:
+ ncolumns = data_shape[1]
+ else:
+ raise TypeError("data array must be 2-dimensional")
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.snip2d(&data_c[0], nrows, ncolumns, snip_width)
+
+ return numpy.asarray(data_c).reshape(data_shape)
+
+
+def snip3d(data, snip_width):
+ """Estimate the baseline (background) of a 3D data signal by clipping peaks.
+
+ Implementation of the algorithm SNIP in 2D described in
+ *Miroslav Morhac et al. Nucl. Instruments and Methods in Physics Research
+ A401 (1997) 113-132.*
+
+ :param data: 3D array
+ :type data: numpy.ndarray
+ :param width: Width of the snip operator, in number of samples. A wider
+ snip operator will result in a smoother result (lower frequency peaks
+ will be clipped), and a longer computation time.
+ :type width: int
+
+ :return: Baseline of the input array, as an array of the same shape.
+ :rtype: numpy.ndarray
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__") or not hasattr(data[0], "__len__") or\
+ not hasattr(data[0][0], "__len__"):
+ raise TypeError("data must be a 3D sequence (list, tuple) " +
+ "or a 3D numpy array")
+ nx = len(data)
+ ny = len(data[0])
+ nz = len(data[0][0])
+ data_shape = (len(data), len(data[0]), len(data[0][0]))
+ else:
+ data_shape = data.shape
+ nrows = data_shape[0]
+ if len(data_shape) == 3:
+ nx = data_shape[0]
+ ny = data_shape[1]
+ nz = data_shape[2]
+ else:
+ raise TypeError("data array must be 3-dimensional")
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.snip3d(&data_c[0], nx, ny, nz, snip_width)
+
+ return numpy.asarray(data_c).reshape(data_shape)
+
+
+def savitsky_golay(data, npoints=5):
+ """Smooth a curve using a Savitsky-Golay filter.
+
+ :param data: Input data
+ :type data: 1D numpy array
+ :param npoints: Size of the smoothing operator in number of samples
+ Must be between 3 and 100.
+ :return: Smoothed data
+ """
+ cdef:
+ double[::1] data_c
+ double[::1] output
+
+ data_c = numpy.array(data,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ output = numpy.empty(shape=(data_c.size,),
+ dtype=numpy.float64)
+
+ status = filters_wrapper.SavitskyGolay(&data_c[0], data_c.size,
+ npoints, &output[0])
+
+ if status:
+ _logger.error("Smoothing failed. Check that npoints is greater " +
+ "than 3 and smaller than 100.")
+
+ return numpy.asarray(output).reshape(data.shape)
+
+
+def smooth1d(data):
+ """Simple smoothing for 1D data.
+
+ For a data array :math:`y` of length :math:`n`, the smoothed array
+ :math:`ys` is calculated as a weighted average of neighboring samples:
+
+ :math:`ys_0 = 0.75 y_0 + 0.25 y_1`
+
+ :math:`ys_i = 0.25 (y_{i-1} + 2 y_i + y_{i+1})` for :math:`0 < i < n-1`
+
+ :math:`ys_{n-1} = 0.25 y_{n-2} + 0.75 y_{n-1}`
+
+
+ :param data: 1D data array
+ :type data: numpy.ndarray
+ :return: Smoothed data
+ :rtype: numpy.ndarray(dtype=numpy.float64)
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__"):
+ raise TypeError("data must be a sequence (list, tuple) " +
+ "or a numpy array")
+ data_shape = (len(data), )
+ else:
+ data_shape = data.shape
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.smooth1d(&data_c[0], data_c.size)
+
+ return numpy.asarray(data_c).reshape(data_shape)
+
+
+def smooth2d(data):
+ """Simple smoothing for 2D data:
+ :func:`smooth1d` is applied succesively along both axis
+
+ :param data: 2D data array
+ :type data: numpy.ndarray
+ :return: Smoothed data
+ :rtype: numpy.ndarray(dtype=numpy.float64)
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__") or not hasattr(data[0], "__len__"):
+ raise TypeError("data must be a 2D sequence (list, tuple) " +
+ "or a 2D numpy array")
+ nrows = len(data)
+ ncolumns = len(data[0])
+ data_shape = (len(data), len(data[0]))
+
+ else:
+ data_shape = data.shape
+ nrows = data_shape[0]
+ if len(data_shape) == 2:
+ ncolumns = data_shape[1]
+ else:
+ raise TypeError("data array must be 2-dimensional")
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.smooth2d(&data_c[0], nrows, ncolumns)
+
+ return numpy.asarray(data_c).reshape(data_shape)
+
+
+def smooth3d(data):
+ """Simple smoothing for 3D data:
+ :func:`smooth2d` is applied on each 2D slice of the data volume along all
+ 3 axis
+
+ :param data: 2D data array
+ :type data: numpy.ndarray
+ :return: Smoothed data
+ :rtype: numpy.ndarray(dtype=numpy.float64)
+ """
+ cdef:
+ double[::1] data_c
+
+ if not isinstance(data, numpy.ndarray):
+ if not hasattr(data, "__len__") or not hasattr(data[0], "__len__") or\
+ not hasattr(data[0][0], "__len__"):
+ raise TypeError("data must be a 3D sequence (list, tuple) " +
+ "or a 3D numpy array")
+ nx = len(data)
+ ny = len(data[0])
+ nz = len(data[0][0])
+ data_shape = (len(data), len(data[0]), len(data[0][0]))
+ else:
+ data_shape = data.shape
+ nrows = data_shape[0]
+ if len(data_shape) == 3:
+ nx = data_shape[0]
+ ny = data_shape[1]
+ nz = data_shape[2]
+ else:
+ raise TypeError("data array must be 3-dimensional")
+
+ data_c = numpy.array(data,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+
+ filters_wrapper.smooth3d(&data_c[0], nx, ny, nz)
+
+ return numpy.asarray(data_c).reshape(data_shape)
diff --git a/silx/math/fit/filters/filters_wrapper.pxd b/silx/math/fit/filters/filters_wrapper.pxd
new file mode 100644
index 0000000..e4f7c72
--- /dev/null
+++ b/silx/math/fit/filters/filters_wrapper.pxd
@@ -0,0 +1,71 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+cimport cython
+
+cdef extern from "filters.h":
+ void snip1d(double *data,
+ int size,
+ int width)
+
+ void snip2d(double *data,
+ int nrows,
+ int ncolumns,
+ int width)
+
+ void snip3d(double *data,
+ int nx,
+ int ny,
+ int nz,
+ int width)
+
+ int strip(double* input,
+ long len_input,
+ double c,
+ long niter,
+ int deltai,
+ long* anchors,
+ long len_anchors,
+ double* output)
+
+ int SavitskyGolay(double* input,
+ long len_input,
+ int npoints,
+ double* output)
+
+ void smooth1d(double *data,
+ int size)
+
+ void smooth2d(double *data,
+ int size0,
+ int size1)
+
+ void smooth3d(double *data,
+ int size0,
+ int size1,
+ int size2)
diff --git a/silx/math/fit/filters/include/filters.h b/silx/math/fit/filters/include/filters.h
new file mode 100644
index 0000000..48e7e52
--- /dev/null
+++ b/silx/math/fit/filters/include/filters.h
@@ -0,0 +1,45 @@
+/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+#ifndef FITFILTERSH
+#define FITFILTERS_H
+
+/* Background functions */
+void snip1d(double *data, int size, int width);
+//void snip1d_multiple(double *data, int n_channels, int snip_width, int n_spectra);
+void snip2d(double *data, int nrows, int ncolumns, int width);
+void snip3d(double *data, int nx, int ny, int nz, int width);
+
+int strip(double* input, long len_input, double c, long niter, int deltai,
+ long* anchors, long len_anchors, double* output);
+
+/* Smoothing functions */
+
+int SavitskyGolay(double* input, long len_input, int npoints, double* output);
+
+void smooth1d(double *data, int size);
+void smooth2d(double *data, int size0, int size1);
+void smooth3d(double *data, int size0, int size1, int size2);
+
+
+#endif /* #define FITFILTERS_H */
diff --git a/silx/math/fit/filters/src/smoothnd.c b/silx/math/fit/filters/src/smoothnd.c
new file mode 100644
index 0000000..cb96961
--- /dev/null
+++ b/silx/math/fit/filters/src/smoothnd.c
@@ -0,0 +1,317 @@
+#/*##########################################################################
+#
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+#define MAX_SAVITSKY_GOLAY_WIDTH 101
+#define MIN_SAVITSKY_GOLAY_WIDTH 3
+
+/* Wrapped functions */
+void smooth1d(double *data, int size);
+void smooth2d(double *data, int size0, int size1);
+void smooth3d(double *data, int size0, int size1, int size2);
+int SavitskyGolay(double* input, long len_input, int npoints, double* output);
+
+/* Internal functions */
+long index2d(long row_idx, long col_idx, long ncols);
+long index3d(long x_idx, long y_idx, long z_idx, long ny, long nz);
+void smooth1d_rows(double *data, long nrows, long ncols);
+void smooth1d_cols(double *data, long nrows, long ncols);
+void smooth1d_x(double *data, long nx, long ny, long nz);
+void smooth1d_y(double *data, long nx, long ny, long nz);
+void smooth1d_z(double *data, long nx, long ny, long nz);
+void smooth2d_yzslice(double *data, long nx, long ny, long nz);
+void smooth2d_xzslice(double *data, long nx, long ny, long nz);
+void smooth2d_xyslice(double *data, long nx, long ny, long nz);
+
+
+/* Simple smoothing of a 1D array */
+void smooth1d(double *data, int size)
+{
+ long i;
+ double prev_sample;
+ double next_sample;
+
+ if (size < 3)
+ {
+ return;
+ }
+ prev_sample = data[0];
+ for (i=0; i<(size-1); i++)
+ {
+ next_sample = 0.25 * (prev_sample + 2 * data[i] + data[i+1]);
+ prev_sample = data[i];
+ data[i] = next_sample;
+ }
+ data[size-1] = 0.25 * prev_sample + 0.75 * data[size-1];
+ return;
+}
+
+/* Smoothing of a 2D array*/
+void smooth2d(double *data, int nrows, int ncols)
+{
+ /* smooth the first dimension (rows) */
+ smooth1d_rows(data, nrows, ncols);
+
+ /* smooth the 2nd dimension */
+ smooth1d_cols(data, nrows, ncols);
+}
+
+/* Smoothing of a 3D array */
+void smooth3d(double *data, int nx, int ny, int nz)
+{
+ smooth2d_xyslice(data, nx, ny, nz);
+ smooth2d_xzslice(data, nx, ny, nz);
+ smooth2d_yzslice(data, nx, ny, nz);
+}
+
+/* 1D Savitsky-Golay smoothing */
+int SavitskyGolay(double* input, long len_input, int npoints, double* output)
+{
+
+ //double dpoints = 5.;
+ double coeff[MAX_SAVITSKY_GOLAY_WIDTH];
+ int i, j, m;
+ double dhelp, den;
+ double *data;
+
+ memcpy(output, input, len_input * sizeof(double));
+
+ if (!(npoints % 2)) npoints +=1;
+
+ if((npoints < MIN_SAVITSKY_GOLAY_WIDTH) || (len_input < npoints) || \
+ (npoints > MAX_SAVITSKY_GOLAY_WIDTH))
+ {
+ /* do not smooth data */
+ return 1;
+ }
+
+ /* calculate the coefficients */
+ m = (int) (npoints/2);
+ den = (double) ((2*m-1) * (2*m+1) * (2*m + 3));
+ for (i=0; i<= m; i++){
+ coeff[m+i] = (double) (3 * (3*m*m + 3*m - 1 - 5*i*i ));
+ coeff[m-i] = coeff[m+i];
+ }
+
+ /* simple smoothing at the beginning */
+ for (j=0; j<=(int)(npoints/3); j++)
+ {
+ smooth1d(output, m);
+ }
+
+ /* simple smoothing at the end */
+ for (j=0; j<=(int)(npoints/3); j++)
+ {
+ smooth1d((output+len_input-m-1), m);
+ }
+
+ /*one does not need the whole spectrum buffer, but code is clearer */
+ data = (double *) malloc(len_input * sizeof(double));
+ memcpy(data, output, len_input * sizeof(double));
+
+ /* the actual SG smoothing in the middle */
+ for (i=m; i<(len_input-m); i++){
+ dhelp = 0;
+ for (j=-m;j<=m;j++) {
+ dhelp += coeff[m+j] * (*(data+i+j));
+ }
+ if(dhelp > 0.0){
+ *(output+i) = dhelp / den;
+ }
+ }
+ free(data);
+ return (0);
+}
+
+/*********************/
+/* Utility functions */
+/*********************/
+
+long index2d(long row_idx, long col_idx, long ncols)
+{
+ return (row_idx*ncols+col_idx);
+}
+
+/* Apply smooth 1d on all rows in a 2D array*/
+void smooth1d_rows(double *data, long nrows, long ncols)
+{
+ long row_idx;
+
+ for (row_idx=0; row_idx < nrows; row_idx++)
+ {
+ smooth1d(&data[row_idx * ncols], ncols);
+ }
+}
+
+/* Apply smooth 1d on all columns in a 2D array*/
+void smooth1d_cols(double *data, long nrows, long ncols)
+{
+ long row_idx, col_idx;
+ long this_idx2d, next_idx2d;
+ double prev_sample;
+ double next_sample;
+
+ for (col_idx=0; col_idx < ncols; col_idx++)
+ {
+ prev_sample = data[index2d(0, col_idx, ncols)];
+ for (row_idx=0; row_idx<(nrows-1); row_idx++)
+ {
+ this_idx2d = index2d(row_idx, col_idx, ncols);
+ next_idx2d = index2d(row_idx+1, col_idx, ncols);
+
+ next_sample = 0.25 * (prev_sample + \
+ 2 * data[this_idx2d] + \
+ data[next_idx2d]);
+ prev_sample = data[this_idx2d];
+ data[this_idx2d] = next_sample;
+ }
+
+ this_idx2d = index2d(nrows-1, col_idx, ncols);
+ data[this_idx2d] = 0.25 * prev_sample + 0.75 * data[this_idx2d];
+ }
+}
+
+long index3d(long x_idx, long y_idx, long z_idx, long ny, long nz)
+{
+ return ((x_idx*ny + y_idx) * nz + z_idx);
+}
+
+/* Apply smooth 1d along first dimension in a 3D array*/
+void smooth1d_x(double *data, long nx, long ny, long nz)
+{
+ long x_idx, y_idx, z_idx;
+ long this_idx3d, next_idx3d;
+ double prev_sample;
+ double next_sample;
+
+ for (y_idx=0; y_idx < ny; y_idx++)
+ {
+ for (z_idx=0; z_idx < nz; z_idx++)
+ {
+ prev_sample = data[index3d(0, y_idx, z_idx, ny, nz)];
+ for (x_idx=0; x_idx<(nx-1); x_idx++)
+ {
+ this_idx3d = index3d(x_idx, y_idx, z_idx, ny, nz);
+ next_idx3d = index3d(x_idx+1, y_idx, z_idx, ny, nz);
+
+ next_sample = 0.25 * (prev_sample + \
+ 2 * data[this_idx3d] + \
+ data[next_idx3d]);
+ prev_sample = data[this_idx3d];
+ data[this_idx3d] = next_sample;
+ }
+
+ this_idx3d = index3d(nx-1, y_idx, z_idx, ny, nz);
+ data[this_idx3d] = 0.25 * prev_sample + 0.75 * data[this_idx3d];
+ }
+ }
+}
+
+/* Apply smooth 1d along second dimension in a 3D array*/
+void smooth1d_y(double *data, long nx, long ny, long nz)
+{
+ long x_idx, y_idx, z_idx;
+ long this_idx3d, next_idx3d;
+ double prev_sample;
+ double next_sample;
+
+ for (x_idx=0; x_idx < nx; x_idx++)
+ {
+ for (z_idx=0; z_idx < nz; z_idx++)
+ {
+ prev_sample = data[index3d(x_idx, 0, z_idx, ny, nz)];
+ for (y_idx=0; y_idx<(ny-1); y_idx++)
+ {
+ this_idx3d = index3d(x_idx, y_idx, z_idx, ny, nz);
+ next_idx3d = index3d(x_idx, y_idx+1, z_idx, ny, nz);
+
+ next_sample = 0.25 * (prev_sample + \
+ 2 * data[this_idx3d] + \
+ data[next_idx3d]);
+ prev_sample = data[this_idx3d];
+ data[this_idx3d] = next_sample;
+ }
+
+ this_idx3d = index3d(x_idx, ny-1, z_idx, ny, nz);
+ data[this_idx3d] = 0.25 * prev_sample + 0.75 * data[this_idx3d];
+ }
+ }
+}
+
+/* Apply smooth 1d along third dimension in a 3D array*/
+void smooth1d_z(double *data, long nx, long ny, long nz)
+{
+ long x_idx, y_idx;
+ long idx3d_first_sample;
+
+ for (x_idx=0; x_idx < nx; x_idx++)
+ {
+ for (y_idx=0; y_idx < ny; y_idx++)
+ {
+ idx3d_first_sample = index3d(x_idx, y_idx, 0, ny, nz);
+ /*We can use regular 1D smoothing function because z samples
+ are contiguous in memory*/
+ smooth1d(&data[idx3d_first_sample], nz);
+ }
+ }
+}
+
+/* 2D smoothing of a YZ slice in a 3D volume*/
+void smooth2d_yzslice(double *data, long nx, long ny, long nz)
+{
+ long x_idx;
+ long slice_size = ny * nz;
+
+ /* a YZ slice is a "normal" 2D array of memory-contiguous data*/
+ for (x_idx=0; x_idx < nx; x_idx++)
+ {
+ smooth2d(&data[x_idx*slice_size], ny, nz);
+ }
+}
+
+/* 2D smoothing of a XZ slice in a 3D volume*/
+void smooth2d_xzslice(double *data, long nx, long ny, long nz)
+{
+
+ /* smooth along the first dimension */
+ smooth1d_x(data, nx, ny, nz);
+
+ /* smooth along the third dimension */
+ smooth1d_z(data, nx, ny, nz);
+}
+
+/* 2D smoothing of a XY slice in a 3D volume*/
+void smooth2d_xyslice(double *data, long nx, long ny, long nz)
+{
+ /* smooth along the first dimension */
+ smooth1d_x(data, nx, ny, nz);
+
+ /* smooth along the second dimension */
+ smooth1d_y(data, nx, ny, nz);
+}
+
diff --git a/silx/math/fit/filters/src/snip1d.c b/silx/math/fit/filters/src/snip1d.c
new file mode 100644
index 0000000..994a272
--- /dev/null
+++ b/silx/math/fit/filters/src/snip1d.c
@@ -0,0 +1,149 @@
+#/*##########################################################################
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+/*
+ Implementation of the algorithm SNIP in 1D described in
+ Miroslav Morhac et al. Nucl. Instruments and Methods in Physics Research A401 (1997) 113-132.
+
+ The original idea for 1D and the low-statistics-digital-filter (lsdf) come from
+ C.G. Ryan et al. Nucl. Instruments and Methods in Physics Research B34 (1988) 396-402.
+*/
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+void lls(double *data, int size);
+void lls_inv(double *data, int size);
+void snip1d(double *data, int n_channels, int snip_width);
+void snip1d_multiple(double *data, int n_channels, int snip_width, int n_spectra);
+void lsdf(double *data, int size, int fwhm, double f, double A, double M, double ratio);
+
+void lls(double *data, int size)
+{
+ int i;
+ for (i=0; i< size; i++)
+ {
+ data[i] = log(log(sqrt(data[i]+1.0)+1.0)+1.0);
+ }
+}
+
+void lls_inv(double *data, int size)
+{
+ int i;
+ double tmp;
+ for (i=0; i< size; i++)
+ {
+ /* slightly different than the published formula because
+ with the original formula:
+
+ tmp = exp(exp(data[i]-1.0)-1.0);
+ data[i] = tmp * tmp - 1.0;
+
+ one does not recover the original data */
+
+ tmp = exp(exp(data[i])-1.0)-1.0;
+ data[i] = tmp * tmp - 1.0;
+ }
+}
+
+void lsdf(double *data, int size, int fwhm, double f, double A, double M, double ratio)
+{
+ int channel, i, j;
+ double L, R, S;
+ int width;
+ double dhelp;
+
+ width = (int) (f * fwhm);
+ for (channel=width; channel<(size-width); channel++)
+ {
+ i = width;
+ while(i>0)
+ {
+ L=0;
+ R=0;
+ for(j=channel-i; j<channel; j++)
+ {
+ L += data[j];
+ }
+ for(j=channel+1; j<channel+i; j++)
+ {
+ R += data[j];
+ }
+ S = data[channel] + L + R;
+ if (S<M)
+ {
+ data[channel] = S /(2*i+1);
+ break;
+ }
+ dhelp = (R+1)/(L+1);
+ if ((dhelp < ratio) && (dhelp > (1/ratio)))
+ {
+ if (S<(A*sqrt(data[channel])))
+ {
+ data[channel] = S /(2*i+1);
+ break;
+ }
+ }
+ i=i-1;
+ }
+ }
+}
+
+
+void snip1d(double *data, int n_channels, int snip_width)
+{
+ snip1d_multiple(data, n_channels, snip_width, 1);
+}
+
+void snip1d_multiple(double *data, int n_channels, int snip_width, int n_spectra)
+{
+ int i;
+ int j;
+ int p;
+ int offset;
+ double *w;
+
+ i = (int) (0.5 * snip_width);
+ /* lsdf(data, size, i, 1.5, 75., 10., 1.3); */
+
+ w = (double *) malloc(n_channels * sizeof(double));
+
+ for (j=0; j < n_spectra; j++)
+ {
+ offset = j * n_channels;
+ for (p = snip_width; p > 0; p--)
+ {
+ for (i=p; i<(n_channels - p); i++)
+ {
+ w[i] = MIN(data[i + offset], 0.5*(data[i + offset - p] + data[ i + offset + p]));
+ }
+ for (i=p; i<(n_channels - p); i++)
+ {
+ data[i+offset] = w[i];
+ }
+ }
+ }
+ free(w);
+}
diff --git a/silx/math/fit/filters/src/snip2d.c b/silx/math/fit/filters/src/snip2d.c
new file mode 100644
index 0000000..235759c
--- /dev/null
+++ b/silx/math/fit/filters/src/snip2d.c
@@ -0,0 +1,96 @@
+#/*##########################################################################
+#
+# The PyMca X-Ray Fluorescence Toolkit
+#
+# Copyright (c) 2004-2014 European Synchrotron Radiation Facility
+#
+# This file is part of the PyMca X-ray Fluorescence Toolkit developed at
+# the ESRF by the Software group.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+/*
+ Implementation of the algorithm SNIP in 2D described in
+ Miroslav Morhac et al. Nucl. Instruments and Methods in Physics Research A401 (1997) 113-132.
+*/
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+void lls(double *data, int size);
+void lls_inv(double *data, int size);
+
+void snip2d(double *data, int nrows, int ncolumns, int width)
+{
+ int i, j;
+ int p;
+ int size;
+ double *w;
+ double P1, P2, P3, P4;
+ double S1, S2, S3, S4;
+ double dhelp;
+ int iminuspxncolumns; /* (i-p) * ncolumns */
+ int ixncolumns; /* i * ncolumns */
+ int ipluspxncolumns; /* (i+p) * ncolumns */
+
+ size = nrows * ncolumns;
+ w = (double *) malloc(size * sizeof(double));
+
+ for (p=width; p > 0; p--)
+ {
+ for (i=p; i<(nrows-p); i++)
+ {
+ iminuspxncolumns = (i-p) * ncolumns;
+ ixncolumns = i * ncolumns;
+ ipluspxncolumns = (i+p) * ncolumns;
+ for (j=p; j<(ncolumns-p); j++)
+ {
+ P4 = data[ iminuspxncolumns + (j-p)]; /* P4 = data[i-p][j-p] */
+ S4 = data[ iminuspxncolumns + j]; /* S4 = data[i-p][j] */
+ P2 = data[ iminuspxncolumns + (j+p)]; /* P2 = data[i-p][j+p] */
+ S3 = data[ ixncolumns + (j-p)]; /* S3 = data[i][j-p] */
+ S2 = data[ ixncolumns + (j+p)]; /* S2 = data[i][j+p] */
+ P3 = data[ ipluspxncolumns + (j-p)]; /* P3 = data[i+p][j-p] */
+ S1 = data[ ipluspxncolumns + j]; /* S1 = data[i+p][j] */
+ P1 = data[ ipluspxncolumns + (j+p)]; /* P1 = data[i+p][j+p] */
+ dhelp = 0.5*(P1+P3);
+ S1 = MAX(S1, dhelp) - dhelp;
+ dhelp = 0.5*(P1+P2);
+ S2 = MAX(S2, dhelp) - dhelp;
+ dhelp = 0.5*(P3+P4);
+ S3 = MAX(S3, dhelp) - dhelp;
+ dhelp = 0.5*(P2+P4);
+ S4 = MAX(S4, dhelp) - dhelp;
+ w[ixncolumns + j] = MIN(data[ixncolumns + j], 0.5 * (S1+S2+S3+S4) + 0.25 * (P1+P2+P3+P4));
+ }
+ }
+ for (i=p; i<(nrows-p); i++)
+ {
+ ixncolumns = i * ncolumns;
+ for (j=p; j<(ncolumns-p); j++)
+ {
+ data[ixncolumns + j] = w[ixncolumns + j];
+ }
+ }
+ }
+ free(w);
+}
diff --git a/silx/math/fit/filters/src/snip3d.c b/silx/math/fit/filters/src/snip3d.c
new file mode 100644
index 0000000..cf48ee4
--- /dev/null
+++ b/silx/math/fit/filters/src/snip3d.c
@@ -0,0 +1,186 @@
+#/*##########################################################################
+#
+# The PyMca X-Ray Fluorescence Toolkit
+#
+# Copyright (c) 2004-2014 European Synchrotron Radiation Facility
+#
+# This file is part of the PyMca X-ray Fluorescence Toolkit developed at
+# the ESRF by the Software group.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+/*
+ Implementation of the algorithm SNIP in 3D described in
+ Miroslav Morhac et al. Nucl. Instruments and Methods in Physics Research A401 (1997) 113-132.
+*/
+
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+void lls(double *data, int size);
+void lls_inv(double *data, int size);
+
+void snip3d(double *data, int nx, int ny, int nz, int width)
+{
+ int i, j, k;
+ int p;
+ int size;
+ double *w;
+ double P1, P2, P3, P4, P5, P6, P7, P8;
+ double R1, R2, R3, R4, R5, R6;
+ double S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12;
+ double dhelp;
+ long ioffset;
+ long iplus;
+ long imin;
+ long joffset;
+ long jplus;
+ long jmin;
+
+ size = nx * ny * nz;
+ w = (double *) malloc(size * sizeof(double));
+
+ for (p=width; p > 0; p--)
+ {
+ for (i=p; i<(nx-p); i++)
+ {
+ ioffset = i * ny * nz;
+ iplus = (i + p) * ny * nz;
+ imin = (i - p) * ny * nz;
+ for (j=p; j<(ny-p); j++)
+ {
+ joffset = j * nz;
+ jplus = (j + p) * nz;
+ jmin = (j - p) * nz;
+ for (k=p; k<(nz-p); k++)
+ {
+ P1 = data[iplus + jplus + k-p]; /* P1 = data[i+p][j+p][k-p] */
+ P2 = data[imin + jplus + k-p]; /* P2 = data[i-p][j+p][k-p] */
+ P3 = data[iplus + jmin + k-p]; /* P3 = data[i+p][j-p][k-p] */
+ P4 = data[imin + jmin + k-p]; /* P4 = data[i-p][j-p][k-p] */
+ P5 = data[iplus + jplus + k+p]; /* P5 = data[i+p][j+p][k+p] */
+ P6 = data[imin + jplus + k+p]; /* P6 = data[i-p][j+p][k+p] */
+ P7 = data[imin + jmin + k+p]; /* P7 = data[i-p][j-p][k+p] */
+ P8 = data[iplus + jmin + k+p]; /* P8 = data[i+p][j-p][k+p] */
+
+ S1 = data[iplus + joffset + k-p]; /* S1 = data[i+p][j][k-p] */
+ S2 = data[ioffset + jmin + k-p]; /* S2 = data[i][j+p][k-p] */
+ S3 = data[imin + joffset + k-p]; /* S3 = data[i-p][j][k-p] */
+ S4 = data[ioffset + jmin + k-p]; /* S4 = data[i][j-p][k-p] */
+ S5 = data[imin + joffset + k+p]; /* S5 = data[i-p][j][k+p] */
+ S6 = data[ioffset + jplus + k+p]; /* S6 = data[i][j+p][k+p] */
+ S7 = data[imin + joffset + k+p]; /* S7 = data[i-p][j][k+p] */
+ S8 = data[ioffset + jmin + k+p]; /* S8 = data[i][j-p][k+p] */
+ S9 = data[imin + jplus + k]; /* S9 = data[i-p][j+p][k] */
+ S10 = data[imin + jmin + k]; /* S10 = data[i-p][j-p][k] */
+ S11 = data[iplus + jmin + k]; /* S11 = data[i+p][j-p][k] */
+ S12 = data[iplus + jplus + k]; /* S12 = data[i+p][j+p][k] */
+
+ R1 = data[ioffset + joffset + k-p]; /* R1 = data[i][j][k-p] */
+ R2 = data[ioffset + joffset + k+p]; /* R2 = data[i][j][k+p] */
+ R3 = data[imin + joffset + k]; /* R3 = data[i-p][j][k] */
+ R4 = data[iplus + joffset + k]; /* R4 = data[i+p][j][k] */
+ R5 = data[ioffset + jplus + k]; /* R5 = data[i][j+p][k] */
+ R6 = data[ioffset + jmin + k]; /* R6 = data[i][j-p][k] */
+
+ dhelp = 0.5*(P1+P3);
+ S1 = MAX(S1, dhelp) - dhelp;
+
+ dhelp = 0.5*(P1+P2);
+ S2 = MAX(S2, dhelp) - dhelp;
+
+ dhelp = 0.5*(P2+P4);
+ S3 = MAX(S3, dhelp) - dhelp;
+
+ dhelp = 0.5*(P3+P4);
+ S4 = MAX(S4, dhelp) - dhelp;
+
+ dhelp = 0.5*(P5+P8); /* Different from paper (P5+P7) but according to drawing */
+ S5 = MAX(S5, dhelp) - dhelp;
+
+ dhelp = 0.5*(P5+P6);
+ S6 = MAX(S6, dhelp) - dhelp;
+
+ dhelp = 0.5*(P6+P7); /* Different from paper (P6+P8) but according to drawing */
+ S7 = MAX(S7, dhelp) - dhelp;
+
+ dhelp = 0.5*(P7+P8);
+ S8 = MAX(S8, dhelp) - dhelp;
+
+ dhelp = 0.5*(P2+P6);
+ S9 = MAX(S9, dhelp) - dhelp;
+
+ dhelp = 0.5*(P4+P7); /* Different from paper (P4+P8) but according to drawing */
+ S10 = MAX(S10, dhelp) - dhelp;
+
+ dhelp = 0.5*(P3+P8); /* Different from paper (P1+P5) but according to drawing */
+ S11 = MAX(S11, dhelp) - dhelp;
+
+ dhelp = 0.5*(P1+P5); /* Different from paper (P3+P7) but according to drawing */
+ S12 = MAX(S12, dhelp) - dhelp;
+
+ /* The published formulae correspond to have:
+ P7 and P8 interchanged, and S11 and S12 interchanged
+ with respect to the published drawing */
+
+ dhelp = 0.5 * (S1+S2+S3+S4) + 0.25 * (P1+P2+P3+P4);
+ R1 = MAX(R1, dhelp) - dhelp;
+
+ dhelp = 0.5 * (S5+S6+S7+S8) + 0.25 * (P5+P6+P7+P8);
+ R2 = MAX(R2, dhelp) - dhelp;
+
+ dhelp = 0.5 * (S3+S7+S9+S10) + 0.25 * (P2+P4+P6+P7); /* Again same P7 and P8 change */
+ R3 = MAX(R3, dhelp) - dhelp;
+
+ dhelp = 0.5 * (S1+S5+S11+S12) + 0.25 * (P1+P3+P5+P8); /* Again same P7 and P8 change */
+ R4 = MAX(R4, dhelp) - dhelp;
+
+ dhelp = 0.5 * (S2+S6+S9+S12) + 0.25 * (P1+P2+P5+P6); /* Again same S11 and S12 change */
+ R5 = MAX(R5, dhelp) - dhelp;
+
+ dhelp = 0.5 * (S4+S8+S10+S11) + 0.25 * (P3+P4+P7+P8); /* Again same S11 and S12 change */
+ R6 = MAX(R6, dhelp) - dhelp;
+
+ dhelp = 0.5 * (R1 + R2 + R3 + R4 + R5 + R6) +\
+ 0.25 * (S1 + S2 + S3 + S4 + S5 + S6) +\
+ 0.25 * (S7 + S8 + S9 + S10 + S11 + S12) +\
+ 0.125 * (P1 + P2 + P3 + P4 + P5 + P6 + P7 + P8);
+ w[ioffset + joffset + k] = MIN(data[ioffset + joffset + k], dhelp);
+ }
+ }
+ }
+ for (i=p; i<(nx-p); i++)
+ {
+ ioffset = i * ny * nz;
+ for (j=p; j<(ny-p); j++)
+ {
+ joffset = j * nz;
+ for (k=p; k<(nz-p); j++)
+ {
+ data[ioffset + joffset + k] = w[ioffset + joffset + k];
+ }
+ }
+ }
+ }
+ free(w);
+}
diff --git a/silx/math/fit/filters/src/strip.c b/silx/math/fit/filters/src/strip.c
new file mode 100644
index 0000000..dec0742
--- /dev/null
+++ b/silx/math/fit/filters/src/strip.c
@@ -0,0 +1,118 @@
+#/*##########################################################################
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+/*
+ This file provides a background strip function, to isolate low frequency
+ background signal from a spectrum (and later substact it from the signal
+ to be left only with the peaks to be fitted).
+
+ It is adapted from PyMca source file "SpecFitFuns.c". The main difference
+ with the original code is that this code does not handle the python
+ wrapping, which is done elsewhere using cython.
+
+ Authors: V.A. Sole, P. Knobel
+ License: MIT
+ Last modified: 17/06/2016
+*/
+
+#include <string.h>
+
+#include <stdio.h>
+
+/* strip(double* input, double c, long niter, double* output)
+
+ The strip background is probably PyMca's most popular background model.
+
+ In its simplest implementation it is just as an iterative procedure depending
+ on two parameters. These parameters are the strip background width w, and the
+ strip background number of iterations. At each iteration, if the contents of
+ channel i, y(i), is above the average of the contents of the channels at w
+ channels of distance, y(i-w) and y(i+w), y(i) is replaced by the average.
+ At the end of the process we are left with something that resembles a spectrum
+ in which the peaks have been "stripped".
+
+ Parameters:
+
+ - input: Input data array
+ - c: scaling factor applied to the average of y(i-w) and y(i+w) before
+ comparing to y(i)
+ - niter: number of iterations
+ - deltai: operator width (in number of channels)
+ - anchors: Array of anchors, indices of points that will not be
+ modified during the stripping procedure.
+ - output: output array
+
+*/
+int strip(double* input, long len_input,
+ double c, long niter, int deltai,
+ long* anchors, long len_anchors,
+ double* output)
+{
+ long iter_index, array_index, anchor_index, anchor;
+ int anchor_nearby_flag;
+ double t_mean;
+
+ memcpy(output, input, len_input * sizeof(double));
+
+ if (deltai <=0) deltai = 1;
+
+ if (len_input < (2*deltai+1)) return(-1);
+
+ if (len_anchors > 0) {
+ for (iter_index = 0; iter_index < niter; iter_index++) {
+ for (array_index = deltai; array_index < len_input - deltai; array_index++) {
+ /* if index is within +- deltai of an anchor, don't do anything */
+ anchor_nearby_flag = 0;
+ for (anchor_index=0; anchor_index<len_anchors; anchor_index++)
+ {
+ anchor = anchors[anchor_index];
+ if (array_index > (anchor - deltai) && array_index < (anchor + deltai))
+ {
+ anchor_nearby_flag = 1;
+ break;
+ }
+ }
+ /* skip this array_index index */
+ if (anchor_nearby_flag) {
+ continue;
+ }
+
+ t_mean = 0.5 * (input[array_index-deltai] + input[array_index+deltai]);
+ if (input[array_index] > (t_mean * c))
+ output[array_index] = t_mean;
+ }
+ memcpy(input, output, len_input * sizeof(double));
+ }
+ }
+ else {
+ for (iter_index = 0; iter_index < niter; iter_index++) {
+ for (array_index=deltai; array_index < len_input - deltai; array_index++) {
+ t_mean = 0.5 * (input[array_index-deltai] + input[array_index+deltai]);
+
+ if (input[array_index] > (t_mean * c))
+ output[array_index] = t_mean;
+ }
+ memcpy(input, output, len_input * sizeof(double));
+ }
+ }
+ return(0);
+}
diff --git a/silx/math/fit/fitmanager.py b/silx/math/fit/fitmanager.py
new file mode 100644
index 0000000..4a12a24
--- /dev/null
+++ b/silx/math/fit/fitmanager.py
@@ -0,0 +1,1071 @@
+# coding: utf-8
+# /*#########################################################################
+#
+# Copyright (c) 2004-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ##########################################################################*/
+"""
+This module provides a tool to perform advanced fitting. The actual fit relies
+on :func:`silx.math.fit.leastsq`.
+
+This module deals with:
+
+ - handling of the model functions (using a set of default functions or
+ loading custom user functions)
+ - handling of estimation function, that are used to determine the number
+ of parameters to be fitted for functions with unknown number of
+ parameters (such as the sum of a variable number of gaussian curves),
+ and find reasonable initial parameters for input to the iterative
+ fitting algorithm
+ - handling of custom derivative functions that can be passed as a
+ parameter to :func:`silx.math.fit.leastsq`
+ - providing different background models
+
+"""
+from collections import OrderedDict
+import logging
+import numpy
+from numpy.linalg.linalg import LinAlgError
+import os
+import sys
+
+from .filters import strip, smooth1d
+from .leastsq import leastsq
+from .fittheory import FitTheory
+from . import bgtheories
+
+
+__authors__ = ["V.A. Sole", "P. Knobel"]
+__license__ = "MIT"
+__date__ = "16/01/2017"
+
+_logger = logging.getLogger(__name__)
+
+
+class FitManager(object):
+ """
+ Fit functions manager
+
+ :param x: Abscissa data. If ``None``, :attr:`xdata` is set to
+ ``numpy.array([0.0, 1.0, 2.0, ..., len(y)-1])``
+ :type x: Sequence or numpy array or None
+ :param y: The dependant data ``y = f(x)``. ``y`` must have the same
+ shape as ``x`` if ``x`` is not ``None``.
+ :type y: Sequence or numpy array or None
+ :param sigmay: The uncertainties in the ``ydata`` array. These can be
+ used as weights in the least-squares problem, if ``weight_flag``
+ is ``True``.
+ If ``None``, the uncertainties are assumed to be 1, unless
+ ``weight_flag`` is ``True``, in which case the square-root
+ of ``y`` is used.
+ :type sigmay: Sequence or numpy array or None
+ :param weight_flag: If this parameter is ``True`` and ``sigmay``
+ uncertainties are not specified, the square root of ``y`` is used
+ as weights in the least-squares problem. If ``False``, the
+ uncertainties are set to 1.
+ :type weight_flag: boolean
+ """
+ def __init__(self, x=None, y=None, sigmay=None, weight_flag=False):
+ """
+ """
+ self.fitconfig = {
+ 'WeightFlag': weight_flag,
+ 'fitbkg': 'No Background',
+ 'fittheory': None,
+ # Next few parameters are defined for compatibility with legacy theories
+ # which take the background as argument for their estimation function
+ 'StripWidth': 2,
+ 'StripIterations': 5000,
+ 'StripThresholdFactor': 1.0,
+ 'SmoothingFlag': False
+ }
+ """Dictionary of fit configuration parameters.
+ These parameters can be modified using the :meth:`configure` method.
+
+ Keys are:
+
+ - 'fitbkg': name of the function used for fitting a low frequency
+ background signal
+ - 'FwhmPoints': default full width at half maximum value for the
+ peaks'.
+ - 'Sensitivity': Sensitivity parameter for the peak detection
+ algorithm (:func:`silx.math.fit.peak_search`)
+ """
+
+ self.theories = OrderedDict()
+ """Dictionary of fit theories, defining functions to be fitted
+ to individual peaks.
+
+ Keys are descriptive theory names (e.g "Gaussians" or "Step up").
+ Values are :class:`silx.math.fit.fittheory.FitTheory` objects with
+ the following attributes:
+
+ - *"function"* is the fit function for an individual peak
+ - *"parameters"* is a sequence of parameter names
+ - *"estimate"* is the parameter estimation function
+ - *"configure"* is the function returning the configuration dict
+ for the theory in the format described in the :attr:` fitconfig`
+ documentation
+ - *"derivative"* (optional) is a custom derivative function, whose
+ signature is described in the documentation of
+ :func:`silx.math.fit.leastsq.leastsq`
+ (``model_deriv(xdata, parameters, index)``).
+ - *"description"* is a description string
+ """
+
+ self.selectedtheory = None
+ """Name of currently selected theory. This name matches a key in
+ :attr:`theories`."""
+
+ self.bgtheories = OrderedDict()
+ """Dictionary of background theories.
+
+ See :attr:`theories` for documentation on theories.
+ """
+
+ # Load default theories (constant, linear, strip)
+ self.loadbgtheories(bgtheories)
+
+ self.selectedbg = 'No Background'
+ """Name of currently selected background theory. This name must be
+ an existing key in :attr:`bgtheories`."""
+
+ self.fit_results = []
+ """This list stores detailed information about all fit parameters.
+ It is initialized in :meth:`estimate` and completed with final fit
+ values in :meth:`runfit`.
+
+ Each fit parameter is stored as a dictionary with following fields:
+
+ - 'name': Parameter name.
+ - 'estimation': Estimated value.
+ - 'group': Group number. Group 0 corresponds to the background
+ function parameters. Group ``n`` (for ``n>0``) corresponds to
+ the fit function parameters for the n-th peak.
+ - 'code': Constraint code
+
+ - 0 - FREE
+ - 1 - POSITIVE
+ - 2 - QUOTED
+ - 3 - FIXED
+ - 4 - FACTOR
+ - 5 - DELTA
+ - 6 - SUM
+
+ - 'cons1':
+
+ - Ignored if 'code' is FREE, POSITIVE or FIXED.
+ - Min value of the parameter if code is QUOTED
+ - Index of fitted parameter to which 'cons2' is related
+ if code is FACTOR, DELTA or SUM.
+
+ - 'cons2':
+
+ - Ignored if 'code' is FREE, POSITIVE or FIXED.
+ - Max value of the parameter if QUOTED
+ - Factor to apply to related parameter with index 'cons1' if
+ 'code' is FACTOR
+ - Difference with parameter with index 'cons1' if
+ 'code' is DELTA
+ - Sum obtained when adding parameter with index 'cons1' if
+ 'code' is SUM
+
+ - 'fitresult': Fitted value.
+ - 'sigma': Standard deviation for the parameter estimate
+ - 'xmin': Lower limit of the ``x`` data range on which the fit
+ was performed
+ - 'xmax': Upeer limit of the ``x`` data range on which the fit
+ was performed
+ """
+
+ self.parameter_names = []
+ """This list stores all fit parameter names: background function
+ parameters and fit function parameters for every peak. It is filled
+ in :meth:`estimate`.
+
+ It is the responsibility of the estimate function defined in
+ :attr:`theories` to determine how many parameters are needed,
+ based on how many peaks are detected and how many parameters are needed
+ to fit an individual peak.
+ """
+
+ self.setdata(x, y, sigmay)
+
+ ##################
+ # Public methods #
+ ##################
+ def addbackground(self, bgname, bgtheory):
+ """Add a new background theory to dictionary :attr:`bgtheories`.
+
+ :param bgname: String with the name describing the function
+ :param bgtheory: :class:`FitTheory` object
+ :type bgtheory: :class:`silx.math.fit.fittheory.FitTheory`
+ """
+ self.bgtheories[bgname] = bgtheory
+
+ def addtheory(self, name, theory=None,
+ function=None, parameters=None,
+ estimate=None, configure=None, derivative=None,
+ description=None, pymca_legacy=False):
+ """Add a new theory to dictionary :attr:`theories`.
+
+ You can pass a name and a :class:`FitTheory` object as arguments, or
+ alternatively provide all arguments necessary to instantiate a new
+ :class:`FitTheory` object.
+
+ See :meth:`loadtheories` for more information on estimation functions,
+ configuration functions and custom derivative functions.
+
+ :param name: String with the name describing the function
+ :param theory: :class:`FitTheory` object, defining a fit function and
+ associated information (estimation function, description…).
+ If this parameter is provided, all other parameters, except for
+ ``name``, are ignored.
+ :type theory: :class:`silx.math.fit.fittheory.FitTheory`
+ :param function function: Mandatory argument if ``theory`` is not provided.
+ See documentation for :attr:`silx.math.fit.fittheory.FitTheory.function`.
+ :param list[str] parameters: Mandatory argument if ``theory`` is not provided.
+ See documentation for :attr:`silx.math.fit.fittheory.FitTheory.parameters`.
+ :param function estimate: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.estimate`
+ :param function configure: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.configure`
+ :param function derivative: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.derivative`
+ :param str description: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.description`
+ :param config_widget: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.config_widget`
+ :param bool pymca_legacy: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.pymca_legacy`
+ """
+ if theory is not None:
+ self.theories[name] = theory
+
+ elif function is not None and parameters is not None:
+ self.theories[name] = FitTheory(
+ description=description,
+ function=function,
+ parameters=parameters,
+ estimate=estimate,
+ configure=configure,
+ derivative=derivative,
+ pymca_legacy=pymca_legacy
+ )
+
+ else:
+ raise TypeError("You must supply a FitTheory object or define " +
+ "a fit function and its parameters.")
+
+ def addbgtheory(self, name, theory=None,
+ function=None, parameters=None,
+ estimate=None, configure=None,
+ derivative=None, description=None):
+ """Add a new theory to dictionary :attr:`bgtheories`.
+
+ You can pass a name and a :class:`FitTheory` object as arguments, or
+ alternatively provide all arguments necessary to instantiate a new
+ :class:`FitTheory` object.
+
+ :param name: String with the name describing the function
+ :param theory: :class:`FitTheory` object, defining a fit function and
+ associated information (estimation function, description…).
+ If this parameter is provided, all other parameters, except for
+ ``name``, are ignored.
+ :type theory: :class:`silx.math.fit.fittheory.FitTheory`
+ :param function function: Mandatory argument if ``theory`` is not provided.
+ See documentation for :attr:`silx.math.fit.fittheory.FitTheory.function`.
+ :param list[str] parameters: Mandatory argument if ``theory`` is not provided.
+ See documentation for :attr:`silx.math.fit.fittheory.FitTheory.parameters`.
+ :param function estimate: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.estimate`
+ :param function configure: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.configure`
+ :param function derivative: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.derivative`
+ :param str description: See documentation for
+ :attr:`silx.math.fit.fittheory.FitTheory.description`
+ """
+ if theory is not None:
+ self.bgtheories[name] = theory
+
+ elif function is not None and parameters is not None:
+ self.bgtheories[name] = FitTheory(
+ description=description,
+ function=function,
+ parameters=parameters,
+ estimate=estimate,
+ configure=configure,
+ derivative=derivative,
+ is_background=True
+ )
+
+ else:
+ raise TypeError("You must supply a FitTheory object or define " +
+ "a background function and its parameters.")
+
+ def configure(self, **kw):
+ """Configure the current theory by filling or updating the
+ :attr:`fitconfig` dictionary.
+ Call the custom configuration function, if any. This allows the user
+ to modify the behavior of the custom fit function or the custom
+ estimate function.
+
+ This methods accepts only named parameters. All ``**kw`` parameters
+ are expected to be fields of :attr:`fitconfig` to be updated, unless
+ they have a special meaning for the custom configuration function
+ of the currently selected theory..
+
+ This method returns the modified config dictionary returned by the
+ custom configuration function.
+ """
+ # inspect **kw to find known keys, update them in self.fitconfig
+ for key in self.fitconfig:
+ if key in kw:
+ self.fitconfig[key] = kw[key]
+
+ # initialize dict with existing config dict
+ result = {}
+ result.update(self.fitconfig)
+
+ if "WeightFlag" in kw:
+ if kw["WeightFlag"]:
+ self.enableweight()
+ else:
+ self.disableweight()
+
+ if self.selectedtheory is None:
+ return result
+
+ # Apply custom configuration function
+ custom_config_fun = self.theories[self.selectedtheory].configure
+ if custom_config_fun is not None:
+ result.update(custom_config_fun(**kw))
+
+ custom_bg_config_fun = self.bgtheories[self.selectedbg].configure
+ if custom_bg_config_fun is not None:
+ result.update(custom_bg_config_fun(**kw))
+
+ # Update self.fitconfig with custom config
+ for key in self.fitconfig:
+ if key in result:
+ self.fitconfig[key] = result[key]
+
+ result.update(self.fitconfig)
+ return result
+
+ def estimate(self, callback=None):
+ """
+ Fill :attr:`fit_results` with an estimation of the fit parameters.
+
+ At first, the background parameters are estimated, if a background
+ model has been specified.
+ Then, a custom estimation function related to the model function is
+ called.
+
+ This process determines the number of needed fit parameters and
+ provides an initial estimation for them, to serve as an input for the
+ actual iterative fitting performed in :meth:`runfit`.
+
+ :param callback: Optional callback function, conforming to the
+ signature ``callback(data)`` with ``data`` being a dictionary.
+ This callback function is called before and after the estimation
+ process, and is given a dictionary containing the values of
+ :attr:`state` (``'Estimate in progress'`` or ``'Ready to Fit'``)
+ and :attr:`chisq`.
+ This is used for instance in :mod:`silx.gui.fit.FitWidget` to
+ update a widget displaying a status message.
+ :return: Estimated parameters
+ """
+ self.state = 'Estimate in progress'
+ self.chisq = None
+
+ if callback is not None:
+ callback(data={'chisq': self.chisq,
+ 'status': self.state})
+
+ CONS = {0: 'FREE',
+ 1: 'POSITIVE',
+ 2: 'QUOTED',
+ 3: 'FIXED',
+ 4: 'FACTOR',
+ 5: 'DELTA',
+ 6: 'SUM',
+ 7: 'IGNORE'}
+
+ xwork = self.xdata
+ ywork = self.ydata
+
+ # estimate the background
+ bg_params, bg_constraints = self.estimate_bkg(xwork, ywork)
+
+ # estimate the function
+ try:
+ fun_params, fun_constraints = self.estimate_fun(xwork, ywork)
+ except LinAlgError:
+ self.state = 'Estimate failed'
+ if callback is not None:
+ callback(data={'status': self.state})
+ raise
+
+ # build the names
+ self.parameter_names = []
+
+ for bg_param_name in self.bgtheories[self.selectedbg].parameters:
+ self.parameter_names.append(bg_param_name)
+
+ fun_param_names = self.theories[self.selectedtheory].parameters
+ param_index, peak_index = 0, 0
+ while param_index < len(fun_params):
+ peak_index += 1
+ for fun_param_name in fun_param_names:
+ self.parameter_names.append(fun_param_name + "%d" % peak_index)
+ param_index += 1
+
+ self.fit_results = []
+ nb_fun_params_per_group = len(fun_param_names)
+ group_number = 0
+ xmin = min(xwork)
+ xmax = max(xwork)
+ nb_bg_params = len(bg_params)
+ for (pindex, pname) in enumerate(self.parameter_names):
+ # First come background parameters
+ if pindex < nb_bg_params:
+ estimation_value = bg_params[pindex]
+ constraint_code = CONS[int(bg_constraints[pindex][0])]
+ cons1 = bg_constraints[pindex][1]
+ cons2 = bg_constraints[pindex][2]
+ # then come peak function parameters
+ else:
+ fun_param_index = pindex - nb_bg_params
+
+ # increment group_number for each new fitted peak
+ if (fun_param_index % nb_fun_params_per_group) == 0:
+ group_number += 1
+
+ estimation_value = fun_params[fun_param_index]
+ constraint_code = CONS[int(fun_constraints[fun_param_index][0])]
+ # cons1 is the index of another fit parameter. In the global
+ # fit_results, we must adjust the index to account for the bg
+ # params added to the start of the list.
+ cons1 = fun_constraints[fun_param_index][1]
+ if constraint_code in ["FACTOR", "DELTA", "SUM"]:
+ cons1 += nb_bg_params
+ cons2 = fun_constraints[fun_param_index][2]
+
+ self.fit_results.append({'name': pname,
+ 'estimation': estimation_value,
+ 'group': group_number,
+ 'code': constraint_code,
+ 'cons1': cons1,
+ 'cons2': cons2,
+ 'fitresult': 0.0,
+ 'sigma': 0.0,
+ 'xmin': xmin,
+ 'xmax': xmax})
+
+ self.state = 'Ready to Fit'
+ self.chisq = None
+ self.niter = 0
+
+ if callback is not None:
+ callback(data={'chisq': self.chisq,
+ 'status': self.state})
+ return numpy.append(bg_params, fun_params)
+
+ def fit(self):
+ """Convenience method to call :meth:`estimate` followed by :meth:`runfit`.
+
+ :return: Output of :meth:`runfit`"""
+ self.estimate()
+ return self.runfit()
+
+ def gendata(self, x=None, paramlist=None, estimated=False):
+ """Return a data array using the currently selected fit function
+ and the fitted parameters.
+
+ :param x: Independent variable where the function is calculated.
+ If ``None``, use :attr:`xdata`.
+ :param paramlist: List of dictionaries, each dictionary item being a
+ fit parameter. The dictionary's format is documented in
+ :attr:`fit_results`.
+ If ``None`` (default), use parameters from :attr:`fit_results`.
+ :param estimated: If *True*, use estimated parameters.
+ :return: :meth:`fitfunction` calculated for parameters whose code is
+ not set to ``"IGNORE"``.
+
+ This calculates :meth:`fitfunction` on `x` data using fit parameters
+ from a list of parameter dictionaries, if field ``code`` is not set
+ to ``"IGNORE"``.
+ """
+ if x is None:
+ x = self.xdata
+ if paramlist is None:
+ paramlist = self.fit_results
+ active_params = []
+ for param in paramlist:
+ if param['code'] not in ['IGNORE', 7]:
+ if not estimated:
+ active_params.append(param['fitresult'])
+ else:
+ active_params.append(param['estimation'])
+
+ newdata = self.fitfunction(numpy.array(x), *active_params)
+ return newdata
+
+ def get_estimation(self):
+ """Return the list of fit parameter names."""
+ if self.state not in ["Ready to fit", "Fit in progress", "Ready"]:
+ _logger.warning("get_estimation() called before estimate() completed")
+ return [param["estimation"] for param in self.fit_results]
+
+ def get_names(self):
+ """Return the list of fit parameter estimations."""
+ if self.state not in ["Ready to fit", "Fit in progress", "Ready"]:
+ msg = "get_names() called before estimate() completed, "
+ msg += "names are not populated at this stage"
+ _logger.warning(msg)
+ return [param["name"] for param in self.fit_results]
+
+ def get_fitted_parameters(self):
+ """Return the list of fitted parameters."""
+ if self.state not in ["Ready"]:
+ msg = "get_fitted_parameters() called before runfit() completed, "
+ msg += "results are not available a this stage"
+ _logger.warning(msg)
+ return [param["fitresult"] for param in self.fit_results]
+
+ def loadtheories(self, theories):
+ """Import user defined fit functions defined in an external Python
+ source file, and save them in :attr:`theories`.
+
+ An example of such a file can be found in the sources of
+ :mod:`silx.math.fit.fittheories`. It must contain a
+ dictionary named ``THEORY`` with the following structure::
+
+ THEORY = {
+ 'theory_name_1':
+ FitTheory(description='Description of theory 1',
+ function=fitfunction1,
+ parameters=('param name 1', 'param name 2', …),
+ estimate=estimation_function1,
+ configure=configuration_function1,
+ derivative=derivative_function1),
+ 'theory_name_2':
+ FitTheory(…),
+ }
+
+ See documentation of :mod:`silx.math.fit.fittheories` and
+ :mod:`silx.math.fit.fittheory` for more
+ information on designing your fit functions file.
+
+ This method can also load user defined functions in the legacy
+ format used in *PyMca*.
+
+ :param theories: Name of python source file, or module containing the
+ definition of fit functions.
+ :raise: ImportError if theories cannot be imported
+ """
+ from types import ModuleType
+ if isinstance(theories, ModuleType):
+ theories_module = theories
+ else:
+ # if theories is not a module, it must be a string
+ string_types = (basestring,) if sys.version_info[0] == 2 else (str,) # noqa
+ if not isinstance(theories, string_types):
+ raise ImportError("theory must be a python module, a module" +
+ "name or a python filename")
+ # if theories is a filename
+ if os.path.isfile(theories):
+ sys.path.append(os.path.dirname(theories))
+ f = os.path.basename(os.path.splitext(theories)[0])
+ theories_module = __import__(f)
+ # if theories is a module name
+ else:
+ theories_module = __import__(theories)
+
+ if hasattr(theories_module, "INIT"):
+ theories.INIT()
+
+ if not hasattr(theories_module, "THEORY"):
+ msg = "File %s does not contain a THEORY dictionary" % theories
+ raise ImportError(msg)
+
+ elif isinstance(theories_module.THEORY, dict):
+ # silx format for theory definition
+ for theory_name, fittheory in list(theories_module.THEORY.items()):
+ self.addtheory(theory_name, fittheory)
+ else:
+ self._load_legacy_theories(theories_module)
+
+ def loadbgtheories(self, theories):
+ """Import user defined background functions defined in an external Python
+ module (source file), and save them in :attr:`theories`.
+
+ An example of such a file can be found in the sources of
+ :mod:`silx.math.fit.fittheories`. It must contain a
+ dictionary named ``THEORY`` with the following structure::
+
+ THEORY = {
+ 'theory_name_1':
+ FitTheory(description='Description of theory 1',
+ function=fitfunction1,
+ parameters=('param name 1', 'param name 2', …),
+ estimate=estimation_function1,
+ configure=configuration_function1,
+ 'theory_name_2':
+ FitTheory(…),
+ }
+
+ See documentation of :mod:`silx.math.fit.bgtheories` and
+ :mod:`silx.math.fit.fittheory` for more
+ information on designing your background functions file.
+
+ :param theories: Module or name of python source file containing the
+ definition of background functions.
+ :raise: ImportError if theories cannot be imported
+ """
+ from types import ModuleType
+ if isinstance(theories, ModuleType):
+ theories_module = theories
+ else:
+ # if theories is not a module, it must be a string
+ string_types = (basestring,) if sys.version_info[0] == 2 else (str,) # noqa
+ if not isinstance(theories, string_types):
+ raise ImportError("theory must be a python module, a module" +
+ "name or a python filename")
+ # if theories is a filename
+ if os.path.isfile(theories):
+ sys.path.append(os.path.dirname(theories))
+ f = os.path.basename(os.path.splitext(theories)[0])
+ theories_module = __import__(f)
+ # if theories is a module name
+ else:
+ theories_module = __import__(theories)
+
+ if hasattr(theories_module, "INIT"):
+ theories.INIT()
+
+ if not hasattr(theories_module, "THEORY"):
+ msg = "File %s does not contain a THEORY dictionary" % theories
+ raise ImportError(msg)
+
+ elif isinstance(theories_module.THEORY, dict):
+ # silx format for theory definition
+ for theory_name, fittheory in list(theories_module.THEORY.items()):
+ self.addbgtheory(theory_name, fittheory)
+
+ def setbackground(self, theory):
+ """Choose a background type from within :attr:`bgtheories`.
+
+ This updates :attr:`selectedbg`.
+
+ :param theory: The name of the background to be used.
+ :raise: KeyError if ``theory`` is not a key of :attr:`bgtheories``.
+ """
+ if theory in self.bgtheories:
+ self.selectedbg = theory
+ else:
+ msg = "No theory with name %s in bgtheories.\n" % theory
+ msg += "Available theories: %s\n" % self.bgtheories.keys()
+ raise KeyError(msg)
+
+ # run configure to apply our fitconfig to the selected theory
+ # through its custom config function
+ self.configure(**self.fitconfig)
+
+ def setdata(self, x, y, sigmay=None, xmin=None, xmax=None):
+ """Set data attributes:
+
+ - ``xdata0``, ``ydata0`` and ``sigmay0`` store the initial data
+ and uncertainties. These attributes are not modified after
+ initialization.
+ - ``xdata``, ``ydata`` and ``sigmay`` store the data after
+ removing values where ``xdata < xmin`` or ``xdata > xmax``.
+ These attributes may be modified at a latter stage by filters.
+
+ :param x: Abscissa data. If ``None``, :attr:`xdata`` is set to
+ ``numpy.array([0.0, 1.0, 2.0, ..., len(y)-1])``
+ :type x: Sequence or numpy array or None
+ :param y: The dependant data ``y = f(x)``. ``y`` must have the same
+ shape as ``x`` if ``x`` is not ``None``.
+ :type y: Sequence or numpy array or None
+ :param sigmay: The uncertainties in the ``ydata`` array. These are
+ used as weights in the least-squares problem.
+ If ``None``, the uncertainties are assumed to be 1.
+ :type sigmay: Sequence or numpy array or None
+ :param xmin: Lower value of x values to use for fitting
+ :param xmax: Upper value of x values to use for fitting
+ """
+ if y is None:
+ self.xdata0 = numpy.array([], numpy.float)
+ self.ydata0 = numpy.array([], numpy.float)
+ # self.sigmay0 = numpy.array([], numpy.float)
+ self.xdata = numpy.array([], numpy.float)
+ self.ydata = numpy.array([], numpy.float)
+ # self.sigmay = numpy.array([], numpy.float)
+
+ else:
+ self.ydata0 = numpy.array(y)
+ self.ydata = numpy.array(y)
+ if x is None:
+ self.xdata0 = numpy.arange(len(self.ydata0))
+ self.xdata = numpy.arange(len(self.ydata0))
+ else:
+ self.xdata0 = numpy.array(x)
+ self.xdata = numpy.array(x)
+
+ # default weight
+ if sigmay is None:
+ self.sigmay0 = None
+ self.sigmay = numpy.sqrt(self.ydata) if self.fitconfig["WeightFlag"] else None
+ else:
+ self.sigmay0 = numpy.array(sigmay)
+ self.sigmay = numpy.array(sigmay) if self.fitconfig["WeightFlag"] else None
+
+ # take the data between limits, using boolean array indexing
+ if (xmin is not None or xmax is not None) and len(self.xdata):
+ xmin = xmin if xmin is not None else min(self.xdata)
+ xmax = xmax if xmax is not None else max(self.xdata)
+ bool_array = (self.xdata >= xmin) & (self.xdata <= xmax)
+ self.xdata = self.xdata[bool_array]
+ self.ydata = self.ydata[bool_array]
+ self.sigmay = self.sigmay[bool_array] if sigmay is not None else None
+
+ def enableweight(self):
+ """This method can be called to set :attr:`sigmay`. If :attr:`sigmay0` was filled with
+ actual uncertainties in :meth:`setdata`, use these values.
+ Else, use ``sqrt(self.ydata)``.
+ """
+ if self.sigmay0 is None:
+ self.sigmay = numpy.sqrt(self.ydata) if self.fitconfig["WeightFlag"] else None
+ else:
+ self.sigmay = self.sigmay0
+
+ def disableweight(self):
+ """This method can be called to set :attr:`sigmay` equal to ``None``.
+ As a result, :func:`leastsq` will consider that the weights in the
+ least square problem are 1 for all samples."""
+ self.sigmay = None
+
+ def settheory(self, theory):
+ """Pick a theory from :attr:`theories`.
+
+ :param theory: Name of the theory to be used.
+ :raise: KeyError if ``theory`` is not a key of :attr:`theories`.
+ """
+ if theory is None:
+ self.selectedtheory = None
+ elif theory in self.theories:
+ self.selectedtheory = theory
+ else:
+ msg = "No theory with name %s in theories.\n" % theory
+ msg += "Available theories: %s\n" % self.theories.keys()
+ raise KeyError(msg)
+
+ # run configure to apply our fitconfig to the selected theory
+ # through its custom config function
+ self.configure(**self.fitconfig)
+
+ def runfit(self, callback=None):
+ """Run the actual fitting and fill :attr:`fit_results` with fit results.
+
+ Before running this method, :attr:`fit_results` must already be
+ populated with a list of all parameters and their estimated values.
+ For this, run :meth:`estimate` beforehand.
+
+ :param callback: Optional callback function, conforming to the
+ signature ``callback(data)`` with ``data`` being a dictionary.
+ This callback function is called before and after the estimation
+ process, and is given a dictionary containing the values of
+ :attr:`state` (``'Fit in progress'`` or ``'Ready'``)
+ and :attr:`chisq`.
+ This is used for instance in :mod:`silx.gui.fit.FitWidget` to
+ update a widget displaying a status message.
+ :return: Tuple ``(fitted parameters, uncertainties, infodict)``.
+ *infodict* is the dictionary returned by
+ :func:`silx.math.fit.leastsq` when called with option
+ ``full_output=True``. Uncertainties is a sequence of uncertainty
+ values associated with each fitted parameter.
+ """
+ # self.dataupdate()
+
+ self.state = 'Fit in progress'
+ self.chisq = None
+
+ if callback is not None:
+ callback(data={'chisq': self.chisq,
+ 'status': self.state})
+
+ param_val = []
+ param_constraints = []
+ # Initial values are set to the ones computed in estimate()
+ for param in self.fit_results:
+ param_val.append(param['estimation'])
+ param_constraints.append([param['code'], param['cons1'], param['cons2']])
+
+ ywork = self.ydata
+
+
+ try:
+ params, covariance_matrix, infodict = leastsq(
+ self.fitfunction, # bg + actual model function
+ self.xdata, ywork, param_val,
+ sigma=self.sigmay,
+ constraints=param_constraints,
+ model_deriv=self.theories[self.selectedtheory].derivative,
+ full_output=True, left_derivative=True)
+ except LinAlgError:
+ self.state = 'Fit failed'
+ callback(data={'status': self.state})
+ raise
+
+ sigmas = infodict['uncertainties']
+
+ for i, param in enumerate(self.fit_results):
+ if param['code'] != 'IGNORE':
+ param['fitresult'] = params[i]
+ param['sigma'] = sigmas[i]
+
+ self.chisq = infodict["reduced_chisq"]
+ self.niter = infodict["niter"]
+ self.state = 'Ready'
+
+ if callback is not None:
+ callback(data={'chisq': self.chisq,
+ 'status': self.state})
+
+ return params, sigmas, infodict
+
+ ###################
+ # Private methods #
+ ###################
+ def fitfunction(self, x, *pars):
+ """Function to be fitted.
+
+ This is the sum of the selected background function plus
+ the selected fit model function.
+
+ :param x: Independent variable where the function is calculated.
+ :param pars: Sequence of all fit parameters. The first few parameters
+ are background parameters, then come the peak function parameters.
+ :return: Output of the fit function with ``x`` as input and ``pars``
+ as fit parameters.
+ """
+ result = numpy.zeros(numpy.shape(x), numpy.float)
+
+ if self.selectedbg is not None:
+ bg_pars_list = self.bgtheories[self.selectedbg].parameters
+ nb_bg_pars = len(bg_pars_list)
+
+ bgfun = self.bgtheories[self.selectedbg].function
+ result += bgfun(x, self.ydata, *pars[0:nb_bg_pars])
+ else:
+ nb_bg_pars = 0
+
+ selectedfun = self.theories[self.selectedtheory].function
+ result += selectedfun(x, *pars[nb_bg_pars:])
+
+ return result
+
+ def estimate_bkg(self, x, y):
+ """Estimate background parameters using the function defined in
+ the current fit configuration.
+
+ To change the selected background model, attribute :attr:`selectdbg`
+ must be changed using method :meth:`setbackground`.
+
+ The actual background function to be used is
+ referenced in :attr:`bgtheories`
+
+ :param x: Sequence of x data
+ :param y: sequence of y data
+ :return: Tuple of two sequences and one data array
+ ``(estimated_param, constraints, bg_data)``:
+
+ - ``estimated_param`` is a list of estimated values for each
+ background parameter.
+ - ``constraints`` is a 2D sequence of dimension ``(n_parameters, 3)``
+
+ - ``constraints[i][0]``: Constraint code.
+ See explanation about codes in :attr:`fit_results`
+
+ - ``constraints[i][1]``
+ See explanation about 'cons1' in :attr:`fit_results`
+ documentation.
+
+ - ``constraints[i][2]``
+ See explanation about 'cons2' in :attr:`fit_results`
+ documentation.
+ """
+ background_estimate_function = self.bgtheories[self.selectedbg].estimate
+ if background_estimate_function is not None:
+ return background_estimate_function(x, y)
+ else:
+ return [], []
+
+ def estimate_fun(self, x, y):
+ """Estimate fit parameters using the function defined in
+ the current fit configuration.
+
+ :param x: Sequence of x data
+ :param y: sequence of y data
+ :param bg: Background signal, to be subtracted from ``y`` before fitting.
+ :return: Tuple of two sequences ``(estimated_param, constraints)``:
+
+ - ``estimated_param`` is a list of estimated values for each
+ background parameter.
+ - ``constraints`` is a 2D sequence of dimension (n_parameters, 3)
+
+ - ``constraints[i][0]``: Constraint code.
+ See explanation about codes in :attr:`fit_results`
+
+ - ``constraints[i][1]``
+ See explanation about 'cons1' in :attr:`fit_results`
+ documentation.
+
+ - ``constraints[i][2]``
+ See explanation about 'cons2' in :attr:`fit_results`
+ documentation.
+ :raise: ``TypeError`` if estimation function is not callable
+
+ """
+ estimatefunction = self.theories[self.selectedtheory].estimate
+ if hasattr(estimatefunction, '__call__'):
+ if not self.theories[self.selectedtheory].pymca_legacy:
+ return estimatefunction(x, y)
+ else:
+ # legacy pymca estimate functions have a different signature
+ if self.fitconfig["fitbkg"] == "No Background":
+ bg = numpy.zeros_like(y)
+ else:
+ if self.fitconfig["SmoothingFlag"]:
+ y = smooth1d(y)
+ bg = strip(y,
+ w=self.fitconfig["StripWidth"],
+ niterations=self.fitconfig["StripIterations"],
+ factor=self.fitconfig["StripThresholdFactor"])
+ # fitconfig can be filled by user defined config function
+ xscaling = self.fitconfig.get('Xscaling', 1.0)
+ yscaling = self.fitconfig.get('Yscaling', 1.0)
+ return estimatefunction(x, y, bg, xscaling, yscaling)
+ else:
+ raise TypeError("Estimation function in attribute " +
+ "theories[%s]" % self.selectedtheory +
+ " must be callable.")
+
+ def _load_legacy_theories(self, theories_module):
+ """Load theories from a custom module in the old PyMca format.
+
+ See PyMca5.PyMcaMath.fitting.SpecfitFunctions for an example.
+ """
+ mandatory_attributes = ["THEORY", "PARAMETERS",
+ "FUNCTION", "ESTIMATE"]
+ err_msg = "Custom fit function file must define: "
+ err_msg += ", ".join(mandatory_attributes)
+ for attr in mandatory_attributes:
+ if not hasattr(theories_module, attr):
+ raise ImportError(err_msg)
+
+ derivative = theories_module.DERIVATIVE if hasattr(theories_module, "DERIVATIVE") else None
+ configure = theories_module.CONFIGURE if hasattr(theories_module, "CONFIGURE") else None
+ estimate = theories_module.ESTIMATE if hasattr(theories_module, "ESTIMATE") else None
+ if isinstance(theories_module.THEORY, (list, tuple)):
+ # multiple fit functions
+ for i in range(len(theories_module.THEORY)):
+ deriv = derivative[i] if derivative is not None else None
+ config = configure[i] if configure is not None else None
+ estim = estimate[i] if estimate is not None else None
+ self.addtheory(theories_module.THEORY[i],
+ FitTheory(
+ theories_module.FUNCTION[i],
+ theories_module.PARAMETERS[i],
+ estim,
+ config,
+ deriv,
+ pymca_legacy=True))
+ else:
+ # single fit function
+ self.addtheory(theories_module.THEORY,
+ FitTheory(
+ theories_module.FUNCTION,
+ theories_module.PARAMETERS,
+ estimate,
+ configure,
+ derivative,
+ pymca_legacy=True))
+
+
+def test():
+ from .functions import sum_gauss
+ from . import fittheories
+ from . import bgtheories
+
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(1000).astype(numpy.float)
+
+ p = [1000, 100., 250,
+ 255, 690., 45,
+ 1500, 800.5, 95]
+ y = 0.5 * x + 13 + sum_gauss(x, *p)
+
+ # Fitting
+ fit = FitManager()
+ # more sensitivity necessary to resolve
+ # overlapping peaks at x=690 and x=800.5
+ fit.setdata(x=x, y=y)
+ fit.loadtheories(fittheories)
+ fit.settheory('Gaussians')
+ fit.loadbgtheories(bgtheories)
+ fit.setbackground('Linear')
+ fit.estimate()
+ fit.runfit()
+
+ print("Searched parameters = ", p)
+ print("Obtained parameters : ")
+ dummy_list = []
+ for param in fit.fit_results:
+ print(param['name'], ' = ', param['fitresult'])
+ dummy_list.append(param['fitresult'])
+ print("chisq = ", fit.chisq)
+
+ # Plot
+ constant, slope = dummy_list[:2]
+ p1 = dummy_list[2:]
+ print(p1)
+ y2 = slope * x + constant + sum_gauss(x, *p1)
+
+ try:
+ from silx.gui import qt
+ from silx.gui.plot.PlotWindow import PlotWindow
+ app = qt.QApplication([])
+ pw = PlotWindow(control=True)
+ pw.addCurve(x, y, "Original")
+ pw.addCurve(x, y2, "Fit result")
+ pw.legendsDockWidget.show()
+ pw.show()
+ app.exec_()
+ except ImportError:
+ _logger.warning("Could not import qt to display fit result as curve")
+
+
+if __name__ == "__main__":
+ test()
diff --git a/silx/math/fit/fittheories.py b/silx/math/fit/fittheories.py
new file mode 100644
index 0000000..bd3e1ce
--- /dev/null
+++ b/silx/math/fit/fittheories.py
@@ -0,0 +1,1374 @@
+# coding: utf-8
+#/*##########################################################################
+#
+# Copyright (c) 2004-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+########################################################################### */
+"""This modules provides a set of fit functions and associated
+estimation functions in a format that can be imported into a
+:class:`silx.math.fit.FitManager` instance.
+
+These functions are well suited for fitting multiple gaussian shaped peaks
+typically found in spectroscopy data. The estimation functions are designed
+to detect how many peaks are present in the data, and provide an initial
+estimate for their height, their center location and their full-width
+at half maximum (fwhm).
+
+The limitation of these estimation algorithms is that only gaussians having a
+similar fwhm can be detected by the peak search algorithm.
+This *search fwhm* can be defined by the user, if
+he knows the characteristics of his data, or can be automatically estimated
+based on the fwhm of the largest peak in the data.
+
+The source code of this module can serve as template for defining your own
+fit functions.
+
+The functions to be imported by :meth:`FitManager.loadtheories` are defined by
+a dictionary :const:`THEORY`: with the following structure::
+
+ from silx.math.fit.fittheory import FitTheory
+
+ THEORY = {
+ 'theory_name_1': FitTheory(
+ description='Description of theory 1',
+ function=fitfunction1,
+ parameters=('param name 1', 'param name 2', …),
+ estimate=estimation_function1,
+ configure=configuration_function1,
+ derivative=derivative_function1),
+
+ 'theory_name_2': FitTheory(…),
+ }
+
+.. note::
+
+ Consider using an OrderedDict instead of a regular dictionary, when
+ defining your own theory dictionary, if the order matters to you.
+ This will likely be the case if you intend to load a selection of
+ functions in a GUI such as :class:`silx.gui.fit.FitManager`.
+
+Theory names can be customized (e.g. ``gauss, lorentz, splitgauss``…).
+
+The mandatory parameters for :class:`FitTheory` are ``function`` and
+``parameters``.
+
+You can also define an ``INIT`` function that will be executed by
+:meth:`FitManager.loadtheories`.
+
+See the documentation of :class:`silx.math.fit.fittheory.FitTheory`
+for more information.
+
+Module members:
+---------------
+"""
+import numpy
+from collections import OrderedDict
+import logging
+
+from silx.math.fit import functions
+from silx.math.fit.peaks import peak_search, guess_fwhm
+from silx.math.fit.filters import strip, savitsky_golay
+from silx.math.fit.leastsq import leastsq
+from silx.math.fit.fittheory import FitTheory
+
+logging.basicConfig()
+_logger = logging.getLogger(__name__)
+
+__authors__ = ["V.A. Sole", "P. Knobel"]
+__license__ = "MIT"
+__date__ = "06/01/2017"
+
+
+DEFAULT_CONFIG = {
+ 'NoConstraintsFlag': False,
+ 'PositiveFwhmFlag': True,
+ 'PositiveHeightAreaFlag': True,
+ 'SameFwhmFlag': False,
+ 'QuotedPositionFlag': False, # peak not outside data range
+ 'QuotedEtaFlag': False, # force 0 < eta < 1
+ # Peak detection
+ 'AutoScaling': False,
+ 'Yscaling': 1.0,
+ 'FwhmPoints': 8,
+ 'AutoFwhm': True,
+ 'Sensitivity': 2.5,
+ 'ForcePeakPresence': True,
+ # Hypermet
+ 'HypermetTails': 15,
+ 'QuotedFwhmFlag': 0,
+ 'MaxFwhm2InputRatio': 1.5,
+ 'MinFwhm2InputRatio': 0.4,
+ # short tail parameters
+ 'MinGaussArea4ShortTail': 50000.,
+ 'InitialShortTailAreaRatio': 0.050,
+ 'MaxShortTailAreaRatio': 0.100,
+ 'MinShortTailAreaRatio': 0.0010,
+ 'InitialShortTailSlopeRatio': 0.70,
+ 'MaxShortTailSlopeRatio': 2.00,
+ 'MinShortTailSlopeRatio': 0.50,
+ # long tail parameters
+ 'MinGaussArea4LongTail': 1000.0,
+ 'InitialLongTailAreaRatio': 0.050,
+ 'MaxLongTailAreaRatio': 0.300,
+ 'MinLongTailAreaRatio': 0.010,
+ 'InitialLongTailSlopeRatio': 20.0,
+ 'MaxLongTailSlopeRatio': 50.0,
+ 'MinLongTailSlopeRatio': 5.0,
+ # step tail
+ 'MinGaussHeight4StepTail': 5000.,
+ 'InitialStepTailHeightRatio': 0.002,
+ 'MaxStepTailHeightRatio': 0.0100,
+ 'MinStepTailHeightRatio': 0.0001,
+ # Hypermet constraints
+ # position in range [estimated position +- estimated fwhm/2]
+ 'HypermetQuotedPositionFlag': True,
+ 'DeltaPositionFwhmUnits': 0.5,
+ 'SameSlopeRatioFlag': 1,
+ 'SameAreaRatioFlag': 1,
+ # Strip bg removal
+ 'StripBackgroundFlag': True,
+ 'SmoothingFlag': True,
+ 'SmoothingWidth': 5,
+ 'StripWidth': 2,
+ 'StripIterations': 5000,
+ 'StripThresholdFactor': 1.0}
+"""This dictionary defines default configuration parameters that have effects
+on fit functions and estimation functions, mainly on fit constraints.
+This dictionary is accessible as attribute :attr:`FitTheories.config`,
+which can be modified by configuration functions defined in
+:const:`CONFIGURE`.
+"""
+
+CFREE = 0
+CPOSITIVE = 1
+CQUOTED = 2
+CFIXED = 3
+CFACTOR = 4
+CDELTA = 5
+CSUM = 6
+CIGNORED = 7
+
+
+class FitTheories(object):
+ """Class wrapping functions from :class:`silx.math.fit.functions`
+ and providing estimate functions for all of these fit functions."""
+ def __init__(self, config=None):
+ if config is None:
+ self.config = DEFAULT_CONFIG
+ else:
+ self.config = config
+
+ def ahypermet(self, x, *pars):
+ """
+ Wrapping of :func:`silx.math.fit.functions.sum_ahypermet` without
+ the tail flags in the function signature.
+
+ Depending on the value of `self.config['HypermetTails']`, one can
+ activate or deactivate the various terms of the hypermet function.
+
+ `self.config['HypermetTails']` must be an integer between 0 and 15.
+ It is a set of 4 binary flags, one for activating each one of the
+ hypermet terms: *gaussian function, short tail, long tail, step*.
+
+ For example, 15 can be expressed as ``1111`` in base 2, so a flag of
+ 15 means all terms are active.
+ """
+ g_term = self.config['HypermetTails'] & 1
+ st_term = (self.config['HypermetTails'] >> 1) & 1
+ lt_term = (self.config['HypermetTails'] >> 2) & 1
+ step_term = (self.config['HypermetTails'] >> 3) & 1
+ return functions.sum_ahypermet(x, *pars,
+ gaussian_term=g_term, st_term=st_term,
+ lt_term=lt_term, step_term=step_term)
+
+ def poly(self, x, *pars):
+ """Order n polynomial.
+ The order of the polynomial is defined by the number of
+ coefficients (``*pars``).
+
+ """
+ p = numpy.poly1d(pars)
+ return p(x)
+
+ @staticmethod
+ def estimate_poly(x, y, n=2):
+ """Estimate polynomial coefficients for a degree n polynomial.
+
+ """
+ pcoeffs = numpy.polyfit(x, y, n)
+ constraints = numpy.zeros((n + 1, 3), numpy.float)
+ return pcoeffs, constraints
+
+ def estimate_quadratic(self, x, y):
+ """Estimate quadratic coefficients
+
+ """
+ return self.estimate_poly(x, y, n=2)
+
+ def estimate_cubic(self, x, y):
+ """Estimate coefficients for a degree 3 polynomial
+
+ """
+ return self.estimate_poly(x, y, n=3)
+
+ def estimate_quartic(self, x, y):
+ """Estimate coefficients for a degree 4 polynomial
+
+ """
+ return self.estimate_poly(x, y, n=4)
+
+ def estimate_quintic(self, x, y):
+ """Estimate coefficients for a degree 5 polynomial
+
+ """
+ return self.estimate_poly(x, y, n=5)
+
+ def strip_bg(self, y):
+ """Return the strip background of y, using parameters from
+ :attr:`config` dictionary (*StripBackgroundFlag, StripWidth,
+ StripIterations, StripThresholdFactor*)"""
+ remove_strip_bg = self.config.get('StripBackgroundFlag', False)
+ if remove_strip_bg:
+ if self.config['SmoothingFlag']:
+ y = savitsky_golay(y, self.config['SmoothingWidth'])
+ strip_width = self.config['StripWidth']
+ strip_niterations = self.config['StripIterations']
+ strip_thr_factor = self.config['StripThresholdFactor']
+ return strip(y, w=strip_width,
+ niterations=strip_niterations,
+ factor=strip_thr_factor)
+ else:
+ return numpy.zeros_like(y)
+
+ def guess_yscaling(self, y):
+ """Estimate scaling for y prior to peak search.
+ A smoothing filter is applied to y to estimate the noise level
+ (chi-squared)
+
+ :param y: Data array
+ :return: Scaling factor
+ """
+ # ensure y is an array
+ yy = numpy.array(y, copy=False)
+
+ # smooth
+ convolution_kernel = numpy.ones(shape=(3,)) / 3.
+ ysmooth = numpy.convolve(y, convolution_kernel, mode="same")
+
+ # remove zeros
+ idx_array = numpy.fabs(y) > 0.0
+ yy = yy[idx_array]
+ ysmooth = ysmooth[idx_array]
+
+ # compute scaling factor
+ chisq = numpy.mean((yy - ysmooth)**2 / numpy.fabs(yy))
+ if chisq > 0:
+ return 1. / chisq
+ else:
+ return 1.0
+
+ def peak_search(self, y, fwhm, sensitivity):
+ """Search for peaks in y array, after padding the array and
+ multiplying its value by a scaling factor.
+
+ :param y: 1-D data array
+ :param int fwhm: Typical full width at half maximum for peaks,
+ in number of points. This parameter is used for to discriminate between
+ true peaks and background fluctuations.
+ :param float sensitivity: Sensitivity parameter. This is a threshold factor
+ for peak detection. Only peaks larger than the standard deviation
+ of the noise multiplied by this sensitivity parameter are detected.
+ :return: List of peak indices
+ """
+ # add padding
+ ysearch = numpy.ones((len(y) + 2 * fwhm,), numpy.float)
+ ysearch[0:fwhm] = y[0]
+ ysearch[-1:-fwhm - 1:-1] = y[len(y)-1]
+ ysearch[fwhm:fwhm + len(y)] = y[:]
+
+ scaling = self.guess_yscaling(y) if self.config["AutoScaling"] else self.config["Yscaling"]
+
+ if len(ysearch) > 1.5 * fwhm:
+ peaks = peak_search(scaling * ysearch,
+ fwhm=fwhm, sensitivity=sensitivity)
+ return [peak_index - fwhm for peak_index in peaks
+ if 0 <= peak_index - fwhm < len(y)]
+ else:
+ return []
+
+ def estimate_height_position_fwhm(self, x, y):
+ """Estimation of *Height, Position, FWHM* of peaks, for gaussian-like
+ curves.
+
+ This functions finds how many parameters are needed, based on the
+ number of peaks detected. Then it estimates the fit parameters
+ with a few iterations of fitting gaussian functions.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Height, Position, FWHM*.
+ Fit constraints depend on :attr:`config`.
+ """
+ fittedpar = []
+
+ bg = self.strip_bg(y)
+
+ if self.config['AutoFwhm']:
+ search_fwhm = guess_fwhm(y)
+ else:
+ search_fwhm = int(float(self.config['FwhmPoints']))
+ search_sens = float(self.config['Sensitivity'])
+
+ if search_fwhm < 3:
+ _logger.warning("Setting peak fwhm to 3 (lower limit)")
+ search_fwhm = 3
+ self.config['FwhmPoints'] = 3
+
+ if search_sens < 1:
+ _logger.warning("Setting peak search sensitivity to 1. " +
+ "(lower limit to filter out noise peaks)")
+ search_sens = 1
+ self.config['Sensitivity'] = 1
+
+ npoints = len(y)
+
+ # Find indices of peaks in data array
+ peaks = self.peak_search(y,
+ fwhm=search_fwhm,
+ sensitivity=search_sens)
+
+ if not len(peaks):
+ forcepeak = int(float(self.config.get('ForcePeakPresence', 0)))
+ if forcepeak:
+ delta = y - bg
+ # get index of global maximum
+ # (first one if several samples are equal to this value)
+ peaks = [numpy.nonzero(delta == delta.max())[0][0]]
+
+ # Find index of largest peak in peaks array
+ index_largest_peak = 0
+ if len(peaks) > 0:
+ # estimate fwhm as 5 * sampling interval
+ sig = 5 * abs(x[npoints - 1] - x[0]) / npoints
+ peakpos = x[int(peaks[0])]
+ if abs(peakpos) < 1.0e-16:
+ peakpos = 0.0
+ param = numpy.array(
+ [y[int(peaks[0])] - bg[int(peaks[0])], peakpos, sig])
+ height_largest_peak = param[0]
+ peak_index = 1
+ for i in peaks[1:]:
+ param2 = numpy.array(
+ [y[int(i)] - bg[int(i)], x[int(i)], sig])
+ param = numpy.concatenate((param, param2))
+ if param2[0] > height_largest_peak:
+ height_largest_peak = param2[0]
+ index_largest_peak = peak_index
+ peak_index += 1
+
+ # Subtract background
+ xw = x
+ yw = y - bg
+
+ cons = numpy.zeros((len(param), 3), numpy.float)
+
+ # peak height must be positive
+ cons[0:len(param):3, 0] = CPOSITIVE
+ # force peaks to stay around their position
+ cons[1:len(param):3, 0] = CQUOTED
+
+ # set possible peak range to estimated peak +- guessed fwhm
+ if len(xw) > search_fwhm:
+ fwhmx = numpy.fabs(xw[int(search_fwhm)] - xw[0])
+ cons[1:len(param):3, 1] = param[1:len(param):3] - 0.5 * fwhmx
+ cons[1:len(param):3, 2] = param[1:len(param):3] + 0.5 * fwhmx
+ else:
+ cons[1:len(param):3, 1] = min(xw) * numpy.ones(
+ (param[1:len(param):3]),
+ numpy.float)
+ cons[1:len(param):3, 2] = max(xw) * numpy.ones(
+ (param[1:len(param):3]),
+ numpy.float)
+
+ # ensure fwhm is positive
+ cons[2:len(param):3, 0] = CPOSITIVE
+
+ # run a quick iterative fit (4 iterations) to improve
+ # estimations
+ fittedpar, _, _ = leastsq(functions.sum_gauss, xw, yw, param,
+ max_iter=4, constraints=cons.tolist(),
+ full_output=True)
+
+ # set final constraints based on config parameters
+ cons = numpy.zeros((len(fittedpar), 3), numpy.float)
+ peak_index = 0
+ for i in range(len(peaks)):
+ # Setup height area constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['PositiveHeightAreaFlag']:
+ cons[peak_index, 0] = CPOSITIVE
+ cons[peak_index, 1] = 0
+ cons[peak_index, 2] = 0
+ peak_index += 1
+
+ # Setup position constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['QuotedPositionFlag']:
+ cons[peak_index, 0] = CQUOTED
+ cons[peak_index, 1] = min(x)
+ cons[peak_index, 2] = max(x)
+ peak_index += 1
+
+ # Setup positive FWHM constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['PositiveFwhmFlag']:
+ cons[peak_index, 0] = CPOSITIVE
+ cons[peak_index, 1] = 0
+ cons[peak_index, 2] = 0
+ if self.config['SameFwhmFlag']:
+ if i != index_largest_peak:
+ cons[peak_index, 0] = CFACTOR
+ cons[peak_index, 1] = 3 * index_largest_peak + 2
+ cons[peak_index, 2] = 1.0
+ peak_index += 1
+
+ return fittedpar, cons
+
+ def estimate_agauss(self, x, y):
+ """Estimation of *Area, Position, FWHM* of peaks, for gaussian-like
+ curves.
+
+ This functions uses :meth:`estimate_height_position_fwhm`, then
+ converts the height parameters to area under the curve with the
+ formula ``area = sqrt(2*pi) * height * fwhm / (2 * sqrt(2 * log(2))``
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Area, Position, FWHM*.
+ Fit constraints depend on :attr:`config`.
+ """
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ # get the number of found peaks
+ npeaks = len(fittedpar) // 3
+ for i in range(npeaks):
+ height = fittedpar[3 * i]
+ fwhm = fittedpar[3 * i + 2]
+ # Replace height with area in fittedpar
+ fittedpar[3 * i] = numpy.sqrt(2 * numpy.pi) * height * fwhm / (
+ 2.0 * numpy.sqrt(2 * numpy.log(2)))
+ return fittedpar, cons
+
+ def estimate_alorentz(self, x, y):
+ """Estimation of *Area, Position, FWHM* of peaks, for Lorentzian
+ curves.
+
+ This functions uses :meth:`estimate_height_position_fwhm`, then
+ converts the height parameters to area under the curve with the
+ formula ``area = height * fwhm * 0.5 * pi``
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Area, Position, FWHM*.
+ Fit constraints depend on :attr:`config`.
+ """
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ # get the number of found peaks
+ npeaks = len(fittedpar) // 3
+ for i in range(npeaks):
+ height = fittedpar[3 * i]
+ fwhm = fittedpar[3 * i + 2]
+ # Replace height with area in fittedpar
+ fittedpar[3 * i] = (height * fwhm * 0.5 * numpy.pi)
+ return fittedpar, cons
+
+ def estimate_splitgauss(self, x, y):
+ """Estimation of *Height, Position, FWHM1, FWHM2* of peaks, for
+ asymmetric gaussian-like curves.
+
+ This functions uses :meth:`estimate_height_position_fwhm`, then
+ adds a second (identical) estimation of FWHM to the fit parameters
+ for each peak, and the corresponding constraint.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Height, Position, FWHM1, FWHM2*.
+ Fit constraints depend on :attr:`config`.
+ """
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ # get the number of found peaks
+ npeaks = len(fittedpar) // 3
+ estimated_parameters = []
+ estimated_constraints = numpy.zeros((4 * npeaks, 3), numpy.float)
+ for i in range(npeaks):
+ for j in range(3):
+ estimated_parameters.append(fittedpar[3 * i + j])
+ # fwhm2 estimate = fwhm1
+ estimated_parameters.append(fittedpar[3 * i + 2])
+ # height
+ estimated_constraints[4 * i, 0] = cons[3 * i, 0]
+ estimated_constraints[4 * i, 1] = cons[3 * i, 1]
+ estimated_constraints[4 * i, 2] = cons[3 * i, 2]
+ # position
+ estimated_constraints[4 * i + 1, 0] = cons[3 * i + 1, 0]
+ estimated_constraints[4 * i + 1, 1] = cons[3 * i + 1, 1]
+ estimated_constraints[4 * i + 1, 2] = cons[3 * i + 1, 2]
+ # fwhm1
+ estimated_constraints[4 * i + 2, 0] = cons[3 * i + 2, 0]
+ estimated_constraints[4 * i + 2, 1] = cons[3 * i + 2, 1]
+ estimated_constraints[4 * i + 2, 2] = cons[3 * i + 2, 2]
+ # fwhm2
+ estimated_constraints[4 * i + 3, 0] = cons[3 * i + 2, 0]
+ estimated_constraints[4 * i + 3, 1] = cons[3 * i + 2, 1]
+ estimated_constraints[4 * i + 3, 2] = cons[3 * i + 2, 2]
+ if cons[3 * i + 2, 0] == CFACTOR:
+ # convert indices of related parameters
+ # (this happens if SameFwhmFlag == True)
+ estimated_constraints[4 * i + 2, 1] = \
+ int(cons[3 * i + 2, 1] / 3) * 4 + 2
+ estimated_constraints[4 * i + 3, 1] = \
+ int(cons[3 * i + 2, 1] / 3) * 4 + 3
+ return estimated_parameters, estimated_constraints
+
+ def estimate_pvoigt(self, x, y):
+ """Estimation of *Height, Position, FWHM, eta* of peaks, for
+ pseudo-Voigt curves.
+
+ Pseudo-Voigt are a sum of a gaussian curve *G(x)* and a lorentzian
+ curve *L(x)* with the same height, center, fwhm parameters:
+ ``y(x) = eta * G(x) + (1-eta) * L(x)``
+
+ This functions uses :meth:`estimate_height_position_fwhm`, then
+ adds a constant estimation of *eta* (0.5) to the fit parameters
+ for each peak, and the corresponding constraint.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Height, Position, FWHM, eta*.
+ Constraint for the eta parameter can be set to QUOTED (0.--1.)
+ by setting :attr:`config`['QuotedEtaFlag'] to ``True``.
+ If this is not the case, the constraint code is set to FREE.
+ """
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ npeaks = len(fittedpar) // 3
+ newpar = []
+ newcons = numpy.zeros((4 * npeaks, 3), numpy.float)
+ # find out related parameters proper index
+ if not self.config['NoConstraintsFlag']:
+ if self.config['SameFwhmFlag']:
+ j = 0
+ # get the index of the free FWHM
+ for i in range(npeaks):
+ if cons[3 * i + 2, 0] != 4:
+ j = i
+ for i in range(npeaks):
+ if i != j:
+ cons[3 * i + 2, 1] = 4 * j + 2
+ for i in range(npeaks):
+ newpar.append(fittedpar[3 * i])
+ newpar.append(fittedpar[3 * i + 1])
+ newpar.append(fittedpar[3 * i + 2])
+ newpar.append(0.5)
+ # height
+ newcons[4 * i, 0] = cons[3 * i, 0]
+ newcons[4 * i, 1] = cons[3 * i, 1]
+ newcons[4 * i, 2] = cons[3 * i, 2]
+ # position
+ newcons[4 * i + 1, 0] = cons[3 * i + 1, 0]
+ newcons[4 * i + 1, 1] = cons[3 * i + 1, 1]
+ newcons[4 * i + 1, 2] = cons[3 * i + 1, 2]
+ # fwhm
+ newcons[4 * i + 2, 0] = cons[3 * i + 2, 0]
+ newcons[4 * i + 2, 1] = cons[3 * i + 2, 1]
+ newcons[4 * i + 2, 2] = cons[3 * i + 2, 2]
+ # Eta constrains
+ newcons[4 * i + 3, 0] = CFREE
+ newcons[4 * i + 3, 1] = 0
+ newcons[4 * i + 3, 2] = 0
+ if self.config['QuotedEtaFlag']:
+ newcons[4 * i + 3, 0] = CQUOTED
+ newcons[4 * i + 3, 1] = 0.0
+ newcons[4 * i + 3, 2] = 1.0
+ return newpar, newcons
+
+ def estimate_splitpvoigt(self, x, y):
+ """Estimation of *Height, Position, FWHM1, FWHM2, eta* of peaks, for
+ asymmetric pseudo-Voigt curves.
+
+ This functions uses :meth:`estimate_height_position_fwhm`, then
+ adds an identical FWHM2 parameter and a constant estimation of
+ *eta* (0.5) to the fit parameters for each peak, and the corresponding
+ constraints.
+
+ Constraint for the eta parameter can be set to QUOTED (0.--1.)
+ by setting :attr:`config`['QuotedEtaFlag'] to ``True``.
+ If this is not the case, the constraint code is set to FREE.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Height, Position, FWHM1, FWHM2, eta*.
+ """
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ npeaks = len(fittedpar) // 3
+ newpar = []
+ newcons = numpy.zeros((5 * npeaks, 3), numpy.float)
+ # find out related parameters proper index
+ if not self.config['NoConstraintsFlag']:
+ if self.config['SameFwhmFlag']:
+ j = 0
+ # get the index of the free FWHM
+ for i in range(npeaks):
+ if cons[3 * i + 2, 0] != 4:
+ j = i
+ for i in range(npeaks):
+ if i != j:
+ cons[3 * i + 2, 1] = 4 * j + 2
+ for i in range(npeaks):
+ # height
+ newpar.append(fittedpar[3 * i])
+ # position
+ newpar.append(fittedpar[3 * i + 1])
+ # fwhm1
+ newpar.append(fittedpar[3 * i + 2])
+ # fwhm2 estimate equal to fwhm1
+ newpar.append(fittedpar[3 * i + 2])
+ # eta
+ newpar.append(0.5)
+ # constraint codes
+ # ----------------
+ # height
+ newcons[5 * i, 0] = cons[3 * i, 0]
+ # position
+ newcons[5 * i + 1, 0] = cons[3 * i + 1, 0]
+ # fwhm1
+ newcons[5 * i + 2, 0] = cons[3 * i + 2, 0]
+ # fwhm2
+ newcons[5 * i + 3, 0] = cons[3 * i + 2, 0]
+ # cons 1
+ # ------
+ newcons[5 * i, 1] = cons[3 * i, 1]
+ newcons[5 * i + 1, 1] = cons[3 * i + 1, 1]
+ newcons[5 * i + 2, 1] = cons[3 * i + 2, 1]
+ newcons[5 * i + 3, 1] = cons[3 * i + 2, 1]
+ # cons 2
+ # ------
+ newcons[5 * i, 2] = cons[3 * i, 2]
+ newcons[5 * i + 1, 2] = cons[3 * i + 1, 2]
+ newcons[5 * i + 2, 2] = cons[3 * i + 2, 2]
+ newcons[5 * i + 3, 2] = cons[3 * i + 2, 2]
+
+ if cons[3 * i + 2, 0] == CFACTOR:
+ # fwhm2 connstraint depends on fwhm1
+ newcons[5 * i + 3, 1] = newcons[5 * i + 2, 1] + 1
+ # eta constraints
+ newcons[5 * i + 4, 0] = CFREE
+ newcons[5 * i + 4, 1] = 0
+ newcons[5 * i + 4, 2] = 0
+ if self.config['QuotedEtaFlag']:
+ newcons[5 * i + 4, 0] = CQUOTED
+ newcons[5 * i + 4, 1] = 0.0
+ newcons[5 * i + 4, 2] = 1.0
+ return newpar, newcons
+
+ def estimate_apvoigt(self, x, y):
+ """Estimation of *Area, Position, FWHM1, eta* of peaks, for
+ pseudo-Voigt curves.
+
+ This functions uses :meth:`estimate_pvoigt`, then converts the height
+ parameter to area.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *Area, Position, FWHM, eta*.
+ """
+ fittedpar, cons = self.estimate_pvoigt(x, y)
+ npeaks = len(fittedpar) // 4
+ # Assume 50% of the area is determined by the gaussian and 50% by
+ # the Lorentzian.
+ for i in range(npeaks):
+ height = fittedpar[4 * i]
+ fwhm = fittedpar[4 * i + 2]
+ fittedpar[4 * i] = 0.5 * (height * fwhm * 0.5 * numpy.pi) +\
+ 0.5 * (height * fwhm / (2.0 * numpy.sqrt(2 * numpy.log(2)))
+ ) * numpy.sqrt(2 * numpy.pi)
+ return fittedpar, cons
+
+ def estimate_ahypermet(self, x, y):
+ """Estimation of *area, position, fwhm, st_area_r, st_slope_r,
+ lt_area_r, lt_slope_r, step_height_r* of peaks, for hypermet curves.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each peak are:
+ *area, position, fwhm, st_area_r, st_slope_r,
+ lt_area_r, lt_slope_r, step_height_r* .
+ """
+ yscaling = self.config.get('Yscaling', 1.0)
+ if yscaling == 0:
+ yscaling = 1.0
+ fittedpar, cons = self.estimate_height_position_fwhm(x, y)
+ npeaks = len(fittedpar) // 3
+ newpar = []
+ newcons = numpy.zeros((8 * npeaks, 3), numpy.float)
+ main_peak = 0
+ # find out related parameters proper index
+ if not self.config['NoConstraintsFlag']:
+ if self.config['SameFwhmFlag']:
+ j = 0
+ # get the index of the free FWHM
+ for i in range(npeaks):
+ if cons[3 * i + 2, 0] != 4:
+ j = i
+ for i in range(npeaks):
+ if i != j:
+ cons[3 * i + 2, 1] = 8 * j + 2
+ main_peak = j
+ for i in range(npeaks):
+ if fittedpar[3 * i] > fittedpar[3 * main_peak]:
+ main_peak = i
+
+ for i in range(npeaks):
+ height = fittedpar[3 * i]
+ position = fittedpar[3 * i + 1]
+ fwhm = fittedpar[3 * i + 2]
+ area = (height * fwhm / (2.0 * numpy.sqrt(2 * numpy.log(2)))
+ ) * numpy.sqrt(2 * numpy.pi)
+ # the gaussian parameters
+ newpar.append(area)
+ newpar.append(position)
+ newpar.append(fwhm)
+ # print "area, pos , fwhm = ",area,position,fwhm
+ # Avoid zero derivatives because of not calculating contribution
+ g_term = 1
+ st_term = 1
+ lt_term = 1
+ step_term = 1
+ if self.config['HypermetTails'] != 0:
+ g_term = self.config['HypermetTails'] & 1
+ st_term = (self.config['HypermetTails'] >> 1) & 1
+ lt_term = (self.config['HypermetTails'] >> 2) & 1
+ step_term = (self.config['HypermetTails'] >> 3) & 1
+ if g_term == 0:
+ # fix the gaussian parameters
+ newcons[8 * i, 0] = CFIXED
+ newcons[8 * i + 1, 0] = CFIXED
+ newcons[8 * i + 2, 0] = CFIXED
+ # the short tail parameters
+ if ((area * yscaling) <
+ self.config['MinGaussArea4ShortTail']) | \
+ (st_term == 0):
+ newpar.append(0.0)
+ newpar.append(0.0)
+ newcons[8 * i + 3, 0] = CFIXED
+ newcons[8 * i + 3, 1] = 0.0
+ newcons[8 * i + 3, 2] = 0.0
+ newcons[8 * i + 4, 0] = CFIXED
+ newcons[8 * i + 4, 1] = 0.0
+ newcons[8 * i + 4, 2] = 0.0
+ else:
+ newpar.append(self.config['InitialShortTailAreaRatio'])
+ newpar.append(self.config['InitialShortTailSlopeRatio'])
+ newcons[8 * i + 3, 0] = CQUOTED
+ newcons[8 * i + 3, 1] = self.config['MinShortTailAreaRatio']
+ newcons[8 * i + 3, 2] = self.config['MaxShortTailAreaRatio']
+ newcons[8 * i + 4, 0] = CQUOTED
+ newcons[8 * i + 4, 1] = self.config['MinShortTailSlopeRatio']
+ newcons[8 * i + 4, 2] = self.config['MaxShortTailSlopeRatio']
+ # the long tail parameters
+ if ((area * yscaling) <
+ self.config['MinGaussArea4LongTail']) | \
+ (lt_term == 0):
+ newpar.append(0.0)
+ newpar.append(0.0)
+ newcons[8 * i + 5, 0] = CFIXED
+ newcons[8 * i + 5, 1] = 0.0
+ newcons[8 * i + 5, 2] = 0.0
+ newcons[8 * i + 6, 0] = CFIXED
+ newcons[8 * i + 6, 1] = 0.0
+ newcons[8 * i + 6, 2] = 0.0
+ else:
+ newpar.append(self.config['InitialLongTailAreaRatio'])
+ newpar.append(self.config['InitialLongTailSlopeRatio'])
+ newcons[8 * i + 5, 0] = CQUOTED
+ newcons[8 * i + 5, 1] = self.config['MinLongTailAreaRatio']
+ newcons[8 * i + 5, 2] = self.config['MaxLongTailAreaRatio']
+ newcons[8 * i + 6, 0] = CQUOTED
+ newcons[8 * i + 6, 1] = self.config['MinLongTailSlopeRatio']
+ newcons[8 * i + 6, 2] = self.config['MaxLongTailSlopeRatio']
+ # the step parameters
+ if ((height * yscaling) <
+ self.config['MinGaussHeight4StepTail']) | \
+ (step_term == 0):
+ newpar.append(0.0)
+ newcons[8 * i + 7, 0] = CFIXED
+ newcons[8 * i + 7, 1] = 0.0
+ newcons[8 * i + 7, 2] = 0.0
+ else:
+ newpar.append(self.config['InitialStepTailHeightRatio'])
+ newcons[8 * i + 7, 0] = CQUOTED
+ newcons[8 * i + 7, 1] = self.config['MinStepTailHeightRatio']
+ newcons[8 * i + 7, 2] = self.config['MaxStepTailHeightRatio']
+ # if self.config['NoConstraintsFlag'] == 1:
+ # newcons=numpy.zeros((8*npeaks, 3),numpy.float)
+ if npeaks > 0:
+ if g_term:
+ if self.config['PositiveHeightAreaFlag']:
+ for i in range(npeaks):
+ newcons[8 * i, 0] = CPOSITIVE
+ if self.config['PositiveFwhmFlag']:
+ for i in range(npeaks):
+ newcons[8 * i + 2, 0] = CPOSITIVE
+ if self.config['SameFwhmFlag']:
+ for i in range(npeaks):
+ if i != main_peak:
+ newcons[8 * i + 2, 0] = CFACTOR
+ newcons[8 * i + 2, 1] = 8 * main_peak + 2
+ newcons[8 * i + 2, 2] = 1.0
+ if self.config['HypermetQuotedPositionFlag']:
+ for i in range(npeaks):
+ delta = self.config['DeltaPositionFwhmUnits'] * fwhm
+ newcons[8 * i + 1, 0] = CQUOTED
+ newcons[8 * i + 1, 1] = newpar[8 * i + 1] - delta
+ newcons[8 * i + 1, 2] = newpar[8 * i + 1] + delta
+ if self.config['SameSlopeRatioFlag']:
+ for i in range(npeaks):
+ if i != main_peak:
+ newcons[8 * i + 4, 0] = CFACTOR
+ newcons[8 * i + 4, 1] = 8 * main_peak + 4
+ newcons[8 * i + 4, 2] = 1.0
+ newcons[8 * i + 6, 0] = CFACTOR
+ newcons[8 * i + 6, 1] = 8 * main_peak + 6
+ newcons[8 * i + 6, 2] = 1.0
+ if self.config['SameAreaRatioFlag']:
+ for i in range(npeaks):
+ if i != main_peak:
+ newcons[8 * i + 3, 0] = CFACTOR
+ newcons[8 * i + 3, 1] = 8 * main_peak + 3
+ newcons[8 * i + 3, 2] = 1.0
+ newcons[8 * i + 5, 0] = CFACTOR
+ newcons[8 * i + 5, 1] = 8 * main_peak + 5
+ newcons[8 * i + 5, 2] = 1.0
+ return newpar, newcons
+
+ def estimate_stepdown(self, x, y):
+ """Estimation of parameters for stepdown curves.
+
+ The functions estimates gaussian parameters for the derivative of
+ the data, takes the largest gaussian peak and uses its estimated
+ parameters to define the center of the step and its fwhm. The
+ estimated amplitude returned is simply ``max(y) - min(y)``.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit newconstraints.
+ Parameters to be estimated for each stepdown are:
+ *height, centroid, fwhm* .
+ """
+ crappyfilter = [-0.25, -0.75, 0.0, 0.75, 0.25]
+ cutoff = len(crappyfilter) // 2
+ y_deriv = numpy.convolve(y,
+ crappyfilter,
+ mode="valid")
+
+ # make the derivative's peak have the same amplitude as the step
+ if max(y_deriv) > 0:
+ y_deriv = y_deriv * max(y) / max(y_deriv)
+
+ fittedpar, newcons = self.estimate_height_position_fwhm(
+ x[cutoff:-cutoff], y_deriv)
+
+ data_amplitude = max(y) - min(y)
+
+ # use parameters from largest gaussian found
+ if len(fittedpar):
+ npeaks = len(fittedpar) // 3
+ largest_index = 0
+ largest = [data_amplitude,
+ fittedpar[3 * largest_index + 1],
+ fittedpar[3 * largest_index + 2]]
+ for i in range(npeaks):
+ if fittedpar[3 * i] > largest[0]:
+ largest_index = i
+ largest = [data_amplitude,
+ fittedpar[3 * largest_index + 1],
+ fittedpar[3 * largest_index + 2]]
+ else:
+ # no peak was found
+ largest = [data_amplitude, # height
+ x[len(x)//2], # center: middle of x range
+ self.config["FwhmPoints"] * (x[1] - x[0])] # fwhm: default value
+
+ # Setup constrains
+ newcons = numpy.zeros((3, 3), numpy.float)
+ if not self.config['NoConstraintsFlag']:
+ # Setup height constrains
+ if self.config['PositiveHeightAreaFlag']:
+ newcons[0, 0] = CPOSITIVE
+ newcons[0, 1] = 0
+ newcons[0, 2] = 0
+
+ # Setup position constrains
+ if self.config['QuotedPositionFlag']:
+ newcons[1, 0] = CQUOTED
+ newcons[1, 1] = min(x)
+ newcons[1, 2] = max(x)
+
+ # Setup positive FWHM constrains
+ if self.config['PositiveFwhmFlag']:
+ newcons[2, 0] = CPOSITIVE
+ newcons[2, 1] = 0
+ newcons[2, 2] = 0
+
+ return largest, newcons
+
+ def estimate_slit(self, x, y):
+ """Estimation of parameters for slit curves.
+
+ The functions estimates stepup and stepdown parameters for the largest
+ steps, and uses them for calculating the center (middle between stepup
+ and stepdown), the height (maximum amplitude in data), the fwhm
+ (distance between the up- and down-step centers) and the beamfwhm
+ (average of FWHM for up- and down-step).
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each slit are:
+ *height, position, fwhm, beamfwhm* .
+ """
+ largestup, cons = self.estimate_stepup(x, y)
+ largestdown, cons = self.estimate_stepdown(x, y)
+ fwhm = numpy.fabs(largestdown[1] - largestup[1])
+ beamfwhm = 0.5 * (largestup[2] + largestdown[1])
+ beamfwhm = min(beamfwhm, fwhm / 10.0)
+ beamfwhm = max(beamfwhm, (max(x) - min(x)) * 3.0 / len(x))
+
+ y_minus_bg = y - self.strip_bg(y)
+ height = max(y_minus_bg)
+
+ i1 = numpy.nonzero(y_minus_bg >= 0.5 * height)[0]
+ xx = numpy.take(x, i1)
+ position = (xx[0] + xx[-1]) / 2.0
+ fwhm = xx[-1] - xx[0]
+ largest = [height, position, fwhm, beamfwhm]
+ cons = numpy.zeros((4, 3), numpy.float)
+ # Setup constrains
+ if not self.config['NoConstraintsFlag']:
+ # Setup height constrains
+ if self.config['PositiveHeightAreaFlag']:
+ cons[0, 0] = CPOSITIVE
+ cons[0, 1] = 0
+ cons[0, 2] = 0
+
+ # Setup position constrains
+ if self.config['QuotedPositionFlag']:
+ cons[1, 0] = CQUOTED
+ cons[1, 1] = min(x)
+ cons[1, 2] = max(x)
+
+ # Setup positive FWHM constrains
+ if self.config['PositiveFwhmFlag']:
+ cons[2, 0] = CPOSITIVE
+ cons[2, 1] = 0
+ cons[2, 2] = 0
+
+ # Setup positive FWHM constrains
+ if self.config['PositiveFwhmFlag']:
+ cons[3, 0] = CPOSITIVE
+ cons[3, 1] = 0
+ cons[3, 2] = 0
+ return largest, cons
+
+ def estimate_stepup(self, x, y):
+ """Estimation of parameters for a single step up curve.
+
+ The functions estimates gaussian parameters for the derivative of
+ the data, takes the largest gaussian peak and uses its estimated
+ parameters to define the center of the step and its fwhm. The
+ estimated amplitude returned is simply ``max(y) - min(y)``.
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ Parameters to be estimated for each stepup are:
+ *height, centroid, fwhm* .
+ """
+ crappyfilter = [0.25, 0.75, 0.0, -0.75, -0.25]
+ cutoff = len(crappyfilter) // 2
+ y_deriv = numpy.convolve(y, crappyfilter, mode="valid")
+ if max(y_deriv) > 0:
+ y_deriv = y_deriv * max(y) / max(y_deriv)
+
+ fittedpar, cons = self.estimate_height_position_fwhm(
+ x[cutoff:-cutoff], y_deriv)
+
+ # for height, use the data amplitude after removing the background
+ data_amplitude = max(y) - min(y)
+
+ # find params of the largest gaussian found
+ if len(fittedpar):
+ npeaks = len(fittedpar) // 3
+ largest_index = 0
+ largest = [data_amplitude,
+ fittedpar[3 * largest_index + 1],
+ fittedpar[3 * largest_index + 2]]
+ for i in range(npeaks):
+ if fittedpar[3 * i] > largest[0]:
+ largest_index = i
+ largest = [fittedpar[3 * largest_index],
+ fittedpar[3 * largest_index + 1],
+ fittedpar[3 * largest_index + 2]]
+ else:
+ # no peak was found
+ largest = [data_amplitude, # height
+ x[len(x)//2], # center: middle of x range
+ self.config["FwhmPoints"] * (x[1] - x[0])] # fwhm: default value
+
+ newcons = numpy.zeros((3, 3), numpy.float)
+ # Setup constrains
+ if not self.config['NoConstraintsFlag']:
+ # Setup height constraints
+ if self.config['PositiveHeightAreaFlag']:
+ newcons[0, 0] = CPOSITIVE
+ newcons[0, 1] = 0
+ newcons[0, 2] = 0
+
+ # Setup position constraints
+ if self.config['QuotedPositionFlag']:
+ newcons[1, 0] = CQUOTED
+ newcons[1, 1] = min(x)
+ newcons[1, 2] = max(x)
+
+ # Setup positive FWHM constraints
+ if self.config['PositiveFwhmFlag']:
+ newcons[2, 0] = CPOSITIVE
+ newcons[2, 1] = 0
+ newcons[2, 2] = 0
+
+ return largest, newcons
+
+ def estimate_periodic_gauss(self, x, y):
+ """Estimation of parameters for periodic gaussian curves:
+ *number of peaks, distance between peaks, height, position of the
+ first peak, fwhm*
+
+ The functions detects all peaks, then computes the parameters the
+ following way:
+
+ - *distance*: average of distances between detected peaks
+ - *height*: average height of detected peaks
+ - *fwhm*: fwhm of the highest peak (in number of samples) if
+ field ``'AutoFwhm'`` in :attr:`config` is ``True``, else take
+ the default value (field ``'FwhmPoints'`` in :attr:`config`)
+
+ :param x: Array of abscissa values
+ :param y: Array of ordinate values (``y = f(x)``)
+ :return: Tuple of estimated fit parameters and fit constraints.
+ """
+ yscaling = self.config.get('Yscaling', 1.0)
+ if yscaling == 0:
+ yscaling = 1.0
+
+ bg = self.strip_bg(y)
+
+ if self.config['AutoFwhm']:
+ search_fwhm = guess_fwhm(y)
+ else:
+ search_fwhm = int(float(self.config['FwhmPoints']))
+ search_sens = float(self.config['Sensitivity'])
+
+ if search_fwhm < 3:
+ search_fwhm = 3
+
+ if search_sens < 1:
+ search_sens = 1
+
+ if len(y) > 1.5 * search_fwhm:
+ peaks = peak_search(yscaling * y, fwhm=search_fwhm,
+ sensitivity=search_sens)
+ else:
+ peaks = []
+ npeaks = len(peaks)
+ if not npeaks:
+ fittedpar = []
+ cons = numpy.zeros((len(fittedpar), 3), numpy.float)
+ return fittedpar, cons
+
+ fittedpar = [0.0, 0.0, 0.0, 0.0, 0.0]
+
+ # The number of peaks
+ fittedpar[0] = npeaks
+
+ # The separation between peaks in x units
+ delta = 0.0
+ height = 0.0
+ for i in range(npeaks):
+ height += y[int(peaks[i])] - bg[int(peaks[i])]
+ if i != npeaks - 1:
+ delta += (x[int(peaks[i + 1])] - x[int(peaks[i])])
+
+ # delta between peaks
+ if npeaks > 1:
+ fittedpar[1] = delta / (npeaks - 1)
+
+ # starting height
+ fittedpar[2] = height / npeaks
+
+ # position of the first peak
+ fittedpar[3] = x[int(peaks[0])]
+
+ # Estimate the fwhm
+ fittedpar[4] = search_fwhm
+
+ # setup constraints
+ cons = numpy.zeros((5, 3), numpy.float)
+ cons[0, 0] = CFIXED # the number of gaussians
+ if npeaks == 1:
+ cons[1, 0] = CFIXED # the delta between peaks
+ else:
+ cons[1, 0] = CFREE
+ j = 2
+ # Setup height area constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['PositiveHeightAreaFlag']:
+ # POSITIVE = 1
+ cons[j, 0] = CPOSITIVE
+ cons[j, 1] = 0
+ cons[j, 2] = 0
+ j += 1
+
+ # Setup position constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['QuotedPositionFlag']:
+ # QUOTED = 2
+ cons[j, 0] = CQUOTED
+ cons[j, 1] = min(x)
+ cons[j, 2] = max(x)
+ j += 1
+
+ # Setup positive FWHM constrains
+ if not self.config['NoConstraintsFlag']:
+ if self.config['PositiveFwhmFlag']:
+ # POSITIVE=1
+ cons[j, 0] = CPOSITIVE
+ cons[j, 1] = 0
+ cons[j, 2] = 0
+ j += 1
+ return fittedpar, cons
+
+ def configure(self, **kw):
+ """Add new / unknown keyword arguments to :attr:`config`,
+ update entries in :attr:`config` if the parameter name is a existing
+ key.
+
+ :param kw: Dictionary of keyword arguments.
+ :return: Configuration dictionary :attr:`config`
+ """
+ if not kw.keys():
+ return self.config
+ for key in kw.keys():
+ notdone = 1
+ # take care of lower / upper case problems ...
+ for config_key in self.config.keys():
+ if config_key.lower() == key.lower():
+ self.config[config_key] = kw[key]
+ notdone = 0
+ if notdone:
+ self.config[key] = kw[key]
+ return self.config
+
+fitfuns = FitTheories()
+
+THEORY = OrderedDict((
+ ('Gaussians',
+ FitTheory(description='Gaussian functions',
+ function=functions.sum_gauss,
+ parameters=('Height', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_height_position_fwhm,
+ configure=fitfuns.configure)),
+ ('Lorentz',
+ FitTheory(description='Lorentzian functions',
+ function=functions.sum_lorentz,
+ parameters=('Height', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_height_position_fwhm,
+ configure=fitfuns.configure)),
+ ('Area Gaussians',
+ FitTheory(description='Gaussian functions (area)',
+ function=functions.sum_agauss,
+ parameters=('Area', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_agauss,
+ configure=fitfuns.configure)),
+ ('Area Lorentz',
+ FitTheory(description='Lorentzian functions (area)',
+ function=functions.sum_alorentz,
+ parameters=('Area', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_alorentz,
+ configure=fitfuns.configure)),
+ ('Pseudo-Voigt Line',
+ FitTheory(description='Pseudo-Voigt functions',
+ function=functions.sum_pvoigt,
+ parameters=('Height', 'Position', 'FWHM', 'Eta'),
+ estimate=fitfuns.estimate_pvoigt,
+ configure=fitfuns.configure)),
+ ('Area Pseudo-Voigt',
+ FitTheory(description='Pseudo-Voigt functions (area)',
+ function=functions.sum_apvoigt,
+ parameters=('Area', 'Position', 'FWHM', 'Eta'),
+ estimate=fitfuns.estimate_apvoigt,
+ configure=fitfuns.configure)),
+ ('Split Gaussian',
+ FitTheory(description='Asymmetric gaussian functions',
+ function=functions.sum_splitgauss,
+ parameters=('Height', 'Position', 'LowFWHM',
+ 'HighFWHM'),
+ estimate=fitfuns.estimate_splitgauss,
+ configure=fitfuns.configure)),
+ ('Split Lorentz',
+ FitTheory(description='Asymmetric lorentzian functions',
+ function=functions.sum_splitlorentz,
+ parameters=('Height', 'Position', 'LowFWHM', 'HighFWHM'),
+ estimate=fitfuns.estimate_splitgauss,
+ configure=fitfuns.configure)),
+ ('Split Pseudo-Voigt',
+ FitTheory(description='Asymmetric pseudo-Voigt functions',
+ function=functions.sum_splitpvoigt,
+ parameters=('Height', 'Position', 'LowFWHM',
+ 'HighFWHM', 'Eta'),
+ estimate=fitfuns.estimate_splitpvoigt,
+ configure=fitfuns.configure)),
+ ('Step Down',
+ FitTheory(description='Step down function',
+ function=functions.sum_stepdown,
+ parameters=('Height', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_stepdown,
+ configure=fitfuns.configure)),
+ ('Step Up',
+ FitTheory(description='Step up function',
+ function=functions.sum_stepup,
+ parameters=('Height', 'Position', 'FWHM'),
+ estimate=fitfuns.estimate_stepup,
+ configure=fitfuns.configure)),
+ ('Slit',
+ FitTheory(description='Slit function',
+ function=functions.sum_slit,
+ parameters=('Height', 'Position', 'FWHM', 'BeamFWHM'),
+ estimate=fitfuns.estimate_slit,
+ configure=fitfuns.configure)),
+ ('Atan',
+ FitTheory(description='Arctan step up function',
+ function=functions.atan_stepup,
+ parameters=('Height', 'Position', 'Width'),
+ estimate=fitfuns.estimate_stepup,
+ configure=fitfuns.configure)),
+ ('Hypermet',
+ FitTheory(description='Hypermet functions',
+ function=fitfuns.ahypermet, # customized version of functions.sum_ahypermet
+ parameters=('G_Area', 'Position', 'FWHM', 'ST_Area',
+ 'ST_Slope', 'LT_Area', 'LT_Slope', 'Step_H'),
+ estimate=fitfuns.estimate_ahypermet,
+ configure=fitfuns.configure)),
+ # ('Periodic Gaussians',
+ # FitTheory(description='Periodic gaussian functions',
+ # function=functions.periodic_gauss,
+ # parameters=('N', 'Delta', 'Height', 'Position', 'FWHM'),
+ # estimate=fitfuns.estimate_periodic_gauss,
+ # configure=fitfuns.configure))
+ ('Degree 2 Polynomial',
+ FitTheory(description='Degree 2 polynomial'
+ '\ny = a*x^2 + b*x +c',
+ function=fitfuns.poly,
+ parameters=['a', 'b', 'c'],
+ estimate=fitfuns.estimate_quadratic)),
+ ('Degree 3 Polynomial',
+ FitTheory(description='Degree 3 polynomial'
+ '\ny = a*x^3 + b*x^2 + c*x + d',
+ function=fitfuns.poly,
+ parameters=['a', 'b', 'c', 'd'],
+ estimate=fitfuns.estimate_cubic)),
+ ('Degree 4 Polynomial',
+ FitTheory(description='Degree 4 polynomial'
+ '\ny = a*x^4 + b*x^3 + c*x^2 + d*x + e',
+ function=fitfuns.poly,
+ parameters=['a', 'b', 'c', 'd', 'e'],
+ estimate=fitfuns.estimate_quartic)),
+ ('Degree 5 Polynomial',
+ FitTheory(description='Degree 5 polynomial'
+ '\ny = a*x^5 + b*x^4 + c*x^3 + d*x^2 + e*x + f',
+ function=fitfuns.poly,
+ parameters=['a', 'b', 'c', 'd', 'e', 'f'],
+ estimate=fitfuns.estimate_quintic)),
+))
+"""Dictionary of fit theories: fit functions and their associated estimation
+function, parameters list, configuration function and description.
+"""
+
+
+def test(a):
+ from silx.math.fit import fitmanager
+ x = numpy.arange(1000).astype(numpy.float)
+ p = [1500, 100., 50.0,
+ 1500, 700., 50.0]
+ y_synthetic = functions.sum_gauss(x, *p) + 1
+
+ fit = fitmanager.FitManager(x, y_synthetic)
+ fit.addtheory('Gaussians', functions.sum_gauss, ['Height', 'Position', 'FWHM'],
+ a.estimate_height_position_fwhm)
+ fit.settheory('Gaussians')
+ fit.setbackground('Linear')
+
+ fit.estimate()
+ fit.runfit()
+
+ y_fit = fit.gendata()
+
+ print("Fit parameter names: %s" % str(fit.get_names()))
+ print("Theoretical parameters: %s" % str(numpy.append([1, 0], p)))
+ print("Fitted parameters: %s" % str(fit.get_fitted_parameters()))
+
+ try:
+ from silx.gui import qt
+ from silx.gui.plot import plot1D
+ app = qt.QApplication([])
+
+ # Offset of 1 to see the difference in log scale
+ plot1D(x, (y_synthetic + 1, y_fit), "Input data + 1, Fit")
+
+ app.exec_()
+ except ImportError:
+ _logger.warning("Unable to load qt binding, can't plot results.")
+
+
+if __name__ == "__main__":
+ test(fitfuns)
diff --git a/silx/math/fit/fittheory.py b/silx/math/fit/fittheory.py
new file mode 100644
index 0000000..17441ac
--- /dev/null
+++ b/silx/math/fit/fittheory.py
@@ -0,0 +1,161 @@
+# coding: utf-8
+#/*##########################################################################
+#
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+########################################################################### */
+"""
+This module defines the :class:`FitTheory` object that is used by
+:class:`silx.math.fit.FitManager` to define fit functions and background
+models.
+"""
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "09/08/2016"
+
+
+class FitTheory(object):
+ """This class defines a fit theory, which consists of:
+
+ - a model function, the actual function to be fitted
+ - parameters names
+ - an estimation function, that return the estimated initial parameters
+ that serve as input for :func:`silx.math.fit.leastsq`
+ - an optional configuration function, that can be used to modify
+ configuration parameters to alter the behavior of the fit function
+ and the estimation function
+ - an optional derivative function, that replaces the default model
+ derivative used in :func:`silx.math.fit.leastsq`
+ """
+ def __init__(self, function, parameters,
+ estimate=None, configure=None, derivative=None,
+ description=None, pymca_legacy=False, is_background=False):
+ """
+ :param function function: Actual function. See documentation for
+ :attr:`function`.
+ :param list[str] parameters: List of parameter names for the function.
+ See documentation for :attr:`parameters`.
+ :param function estimate: Optional estimation function.
+ See documentation for :attr:`estimate`
+ :param function configure: Optional configuration function.
+ See documentation for :attr:`configure`
+ :param function derivative: Optional custom derivative function.
+ See documentation for :attr:`derivative`
+ :param str description: Optional description string.
+ See documentation for :attr:`description`
+ :param bool pymca_legacy: Flag to indicate that the theory is a PyMca
+ legacy theory. See documentation for :attr:`pymca_legacy`
+ :param bool is_background: Flag to indicate that the theory is a
+ background theory. This has implications regarding the function's
+ signature, as explained in the documentation for :attr:`function`.
+ """
+ self.function = function
+ """Regular fit functions must have the signature *f(x, \*params) -> y*,
+ where *x* is a 1D array of values for the independent variable,
+ *params* are the parameters to be fitted and *y* is the output array
+ that we want to have the best fit to a series of data points.
+
+ Background functions used by :class:`FitManager` must have a slightly
+ different signature: *f(x, y0, \*params) -> bg*, where *y0* is the
+ array of original data points and *bg* is the background signal that
+ we want to subtract from the data array prior to fitting the regular
+ fit function.
+
+ The number of parameters must be the same as in :attr:`parameters`, or
+ a multiple of this number if the function is defined as a sum of a
+ variable number of base functions and if :attr:`estimate` is designed
+ to be able to estimate the number of needed base functions.
+ """
+
+ self.parameters = parameters
+ """List of parameters names.
+
+ This list can contain the minimum number of parameters, if the
+ function takes a variable number of parameters,
+ and if the estimation function is responsible for finding the number
+ of required parameters """
+
+ self.estimate = estimate
+ """The estimation function should have the following signature::
+
+ f(x, y) -> (estimated_param, constraints)
+
+ Parameters:
+
+ - ``x`` is a sequence of values for the independent variable
+ - ``y`` is a sequence of the same length as ``x`` containing the
+ data to be fitted
+
+ Return values:
+
+ - ``estimated_param`` is a sequence of estimated fit parameters to
+ be used as initial values for an iterative fit.
+ - ``constraints`` is a sequence of shape *(n, 3)*, where *n* is the
+ number of estimated parameters, containing the constraints for each
+ parameter to be fitted. See :func:`silx.math.fit.leastsq` for more
+ explanations about constraints."""
+ if estimate is None:
+ self.estimate = self.default_estimate
+
+ self.configure = configure
+ """The optional configuration function must conform to the signature
+ ``f(**kw) -> dict`` (i.e it must accept any named argument and
+ return a dictionary).
+ It can be used to modify configuration parameters to alter the
+ behavior of the fit function and the estimation function."""
+
+ self.derivative = derivative
+ """The optional derivative function must conform to the signature
+ ``model_deriv(xdata, parameters, index)``, where parameters is a
+ sequence with the current values of the fitting parameters, index is
+ the fitting parameter index for which the the derivative has to be
+ provided in the supplied array of xdata points."""
+
+ self.description = description
+ """Optional description string for this particular fit theory."""
+
+ self.pymca_legacy = pymca_legacy
+ """This attribute can be set to *True* to indicate that the theory
+ is a PyMca legacy theory.
+
+ This tells :mod:`silx.math.fit.fitmanager` that the signature of
+ the estimate function is::
+
+ f(x, y, bg, xscaling, yscaling) -> (estimated_param, constraints)
+ """
+
+ self.is_background = is_background
+ """Flag to indicate that the theory is background theory.
+
+ A background function is an secondary function that needs to be added
+ to the main fit function to better fit the original data.
+ If this flag is set to *True*, modules using this theory are informed
+ that :attr:`function` has the signature *f(x, y0, \*params) -> bg*,
+ instead of the usual fit function signature."""
+
+ def default_estimate(self, x=None, y=None, bg=None):
+ """Default estimate function. Return an array of *ones* as the
+ initial estimated parameters, and set all constraints to zero
+ (FREE)"""
+ estimated_parameters = [1. for _ in self.parameters]
+ estimated_constraints = [[0, 0, 0] for _ in self.parameters]
+ return estimated_parameters, estimated_constraints
diff --git a/silx/math/fit/functions/functions.c b/silx/math/fit/functions/functions.c
new file mode 100644
index 0000000..21c6911
--- /dev/null
+++ b/silx/math/fit/functions/functions.c
@@ -0,0 +1,27541 @@
+/* Generated by Cython 0.21.1 */
+
+#define PY_SSIZE_T_CLEAN
+#ifndef CYTHON_USE_PYLONG_INTERNALS
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#else
+#include "pyconfig.h"
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 1
+#else
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#endif
+#endif
+#endif
+#include "Python.h"
+#ifndef Py_PYTHON_H
+ #error Python headers needed to compile C extensions, please install development version of Python.
+#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000)
+ #error Cython requires Python 2.6+ or Python 3.2+.
+#else
+#define CYTHON_ABI "0_21_1"
+#include <stddef.h>
+#ifndef offsetof
+#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
+#endif
+#if !defined(WIN32) && !defined(MS_WINDOWS)
+ #ifndef __stdcall
+ #define __stdcall
+ #endif
+ #ifndef __cdecl
+ #define __cdecl
+ #endif
+ #ifndef __fastcall
+ #define __fastcall
+ #endif
+#endif
+#ifndef DL_IMPORT
+ #define DL_IMPORT(t) t
+#endif
+#ifndef DL_EXPORT
+ #define DL_EXPORT(t) t
+#endif
+#ifndef PY_LONG_LONG
+ #define PY_LONG_LONG LONG_LONG
+#endif
+#ifndef Py_HUGE_VAL
+ #define Py_HUGE_VAL HUGE_VAL
+#endif
+#ifdef PYPY_VERSION
+#define CYTHON_COMPILING_IN_PYPY 1
+#define CYTHON_COMPILING_IN_CPYTHON 0
+#else
+#define CYTHON_COMPILING_IN_PYPY 0
+#define CYTHON_COMPILING_IN_CPYTHON 1
+#endif
+#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600
+#define Py_OptimizeFlag 0
+#endif
+#define __PYX_BUILD_PY_SSIZE_T "n"
+#define CYTHON_FORMAT_SSIZE_T "z"
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyClass_Type
+#else
+ #define __Pyx_BUILTIN_MODULE_NAME "builtins"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyType_Type
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define Py_TPFLAGS_CHECKTYPES 0
+ #define Py_TPFLAGS_HAVE_INDEX 0
+ #define Py_TPFLAGS_HAVE_NEWBUFFER 0
+#endif
+#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE)
+ #define Py_TPFLAGS_HAVE_FINALIZE 0
+#endif
+#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
+ #define CYTHON_PEP393_ENABLED 1
+ #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \
+ 0 : _PyUnicode_Ready((PyObject *)(op)))
+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
+ #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u)
+ #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u)
+ #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
+#else
+ #define CYTHON_PEP393_ENABLED 0
+ #define __Pyx_PyUnicode_READY(op) (0)
+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
+ #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
+ #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
+ #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
+#endif
+#if CYTHON_COMPILING_IN_PYPY
+ #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyFrozenSet_Size(s) PyObject_Size(s)
+#else
+ #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \
+ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
+ #define __Pyx_PyFrozenSet_Size(s) PySet_Size(s)
+#endif
+#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
+#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
+#else
+ #define __Pyx_PyString_Format(a, b) PyString_Format(a, b)
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBaseString_Type PyUnicode_Type
+ #define PyStringObject PyUnicodeObject
+ #define PyString_Type PyUnicode_Type
+ #define PyString_Check PyUnicode_Check
+ #define PyString_CheckExact PyUnicode_CheckExact
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
+ #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
+#else
+ #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
+ #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
+#endif
+#ifndef PySet_CheckExact
+ #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
+#endif
+#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
+#if PY_MAJOR_VERSION >= 3
+ #define PyIntObject PyLongObject
+ #define PyInt_Type PyLong_Type
+ #define PyInt_Check(op) PyLong_Check(op)
+ #define PyInt_CheckExact(op) PyLong_CheckExact(op)
+ #define PyInt_FromString PyLong_FromString
+ #define PyInt_FromUnicode PyLong_FromUnicode
+ #define PyInt_FromLong PyLong_FromLong
+ #define PyInt_FromSize_t PyLong_FromSize_t
+ #define PyInt_FromSsize_t PyLong_FromSsize_t
+ #define PyInt_AsLong PyLong_AsLong
+ #define PyInt_AS_LONG PyLong_AS_LONG
+ #define PyInt_AsSsize_t PyLong_AsSsize_t
+ #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
+ #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
+ #define PyNumber_Int PyNumber_Long
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBoolObject PyLongObject
+#endif
+#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
+ #ifndef PyUnicode_InternFromString
+ #define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
+ #endif
+#endif
+#if PY_VERSION_HEX < 0x030200A4
+ typedef long Py_hash_t;
+ #define __Pyx_PyInt_FromHash_t PyInt_FromLong
+ #define __Pyx_PyInt_AsHash_t PyInt_AsLong
+#else
+ #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
+ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
+#else
+ #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
+#endif
+#ifndef CYTHON_INLINE
+ #if defined(__GNUC__)
+ #define CYTHON_INLINE __inline__
+ #elif defined(_MSC_VER)
+ #define CYTHON_INLINE __inline
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_INLINE inline
+ #else
+ #define CYTHON_INLINE
+ #endif
+#endif
+#ifndef CYTHON_RESTRICT
+ #if defined(__GNUC__)
+ #define CYTHON_RESTRICT __restrict__
+ #elif defined(_MSC_VER) && _MSC_VER >= 1400
+ #define CYTHON_RESTRICT __restrict
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_RESTRICT restrict
+ #else
+ #define CYTHON_RESTRICT
+ #endif
+#endif
+#ifdef NAN
+#define __PYX_NAN() ((float) NAN)
+#else
+static CYTHON_INLINE float __PYX_NAN() {
+ /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and
+ a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is
+ a quiet NaN. */
+ float value;
+ memset(&value, 0xFF, sizeof(value));
+ return value;
+}
+#endif
+#ifdef __cplusplus
+template<typename T>
+void __Pyx_call_destructor(T* x) {
+ x->~T();
+}
+#endif
+
+
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y)
+#else
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y)
+#endif
+
+#ifndef __PYX_EXTERN_C
+ #ifdef __cplusplus
+ #define __PYX_EXTERN_C extern "C"
+ #else
+ #define __PYX_EXTERN_C extern
+ #endif
+#endif
+
+#if defined(WIN32) || defined(MS_WINDOWS)
+#define _USE_MATH_DEFINES
+#endif
+#include <math.h>
+#define __PYX_HAVE__functions
+#define __PYX_HAVE_API__functions
+#include "functions.h"
+#include "pythread.h"
+#include "string.h"
+#include "stdlib.h"
+#include "stdio.h"
+#include "pystate.h"
+#ifdef _OPENMP
+#include <omp.h>
+#endif /* _OPENMP */
+
+#ifdef PYREX_WITHOUT_ASSERTIONS
+#define CYTHON_WITHOUT_ASSERTIONS
+#endif
+
+#ifndef CYTHON_UNUSED
+# if defined(__GNUC__)
+# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+#endif
+typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding;
+ const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
+
+#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
+#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
+#define __PYX_DEFAULT_STRING_ENCODING ""
+#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
+#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \
+ (sizeof(type) < sizeof(Py_ssize_t)) || \
+ (sizeof(type) > sizeof(Py_ssize_t) && \
+ likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX) && \
+ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \
+ v == (type)PY_SSIZE_T_MIN))) || \
+ (sizeof(type) == sizeof(Py_ssize_t) && \
+ (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX))) )
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
+#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
+#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
+#define __Pyx_PyBytes_FromString PyBytes_FromString
+#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#else
+ #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
+#endif
+#define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s)
+#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s)
+#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s)
+#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s)
+#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s)
+#if PY_MAJOR_VERSION < 3
+static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
+{
+ const Py_UNICODE *u_end = u;
+ while (*u_end++) ;
+ return (size_t)(u_end - u - 1);
+}
+#else
+#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
+#endif
+#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
+#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
+#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
+#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
+#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
+#if CYTHON_COMPILING_IN_CPYTHON
+#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
+#else
+#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
+#endif
+#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+static int __Pyx_sys_getdefaultencoding_not_ascii;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ PyObject* ascii_chars_u = NULL;
+ PyObject* ascii_chars_b = NULL;
+ const char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ if (strcmp(default_encoding_c, "ascii") == 0) {
+ __Pyx_sys_getdefaultencoding_not_ascii = 0;
+ } else {
+ char ascii_chars[128];
+ int c;
+ for (c = 0; c < 128; c++) {
+ ascii_chars[c] = c;
+ }
+ __Pyx_sys_getdefaultencoding_not_ascii = 1;
+ ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
+ if (!ascii_chars_u) goto bad;
+ ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
+ if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
+ PyErr_Format(
+ PyExc_ValueError,
+ "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
+ default_encoding_c);
+ goto bad;
+ }
+ Py_DECREF(ascii_chars_u);
+ Py_DECREF(ascii_chars_b);
+ }
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ Py_XDECREF(ascii_chars_u);
+ Py_XDECREF(ascii_chars_b);
+ return -1;
+}
+#endif
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
+#else
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+static char* __PYX_DEFAULT_STRING_ENCODING;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
+ if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
+ strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ return -1;
+}
+#endif
+#endif
+
+
+/* Test for GCC > 2.95 */
+#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
+ #define likely(x) __builtin_expect(!!(x), 1)
+ #define unlikely(x) __builtin_expect(!!(x), 0)
+#else /* !__GNUC__ or GCC < 2.95 */
+ #define likely(x) (x)
+ #define unlikely(x) (x)
+#endif /* __GNUC__ */
+
+static PyObject *__pyx_m;
+static PyObject *__pyx_d;
+static PyObject *__pyx_b;
+static PyObject *__pyx_empty_tuple;
+static PyObject *__pyx_empty_bytes;
+static int __pyx_lineno;
+static int __pyx_clineno = 0;
+static const char * __pyx_cfilenm= __FILE__;
+static const char *__pyx_filename;
+
+
+static const char *__pyx_f[] = {
+ "functions.pyx",
+ "stringsource",
+};
+struct __pyx_memoryview_obj;
+typedef struct {
+ struct __pyx_memoryview_obj *memview;
+ char *data;
+ Py_ssize_t shape[8];
+ Py_ssize_t strides[8];
+ Py_ssize_t suboffsets[8];
+} __Pyx_memviewslice;
+
+#define IS_UNSIGNED(type) (((type) -1) > 0)
+struct __Pyx_StructField_;
+#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
+typedef struct {
+ const char* name;
+ struct __Pyx_StructField_* fields;
+ size_t size;
+ size_t arraysize[8];
+ int ndim;
+ char typegroup;
+ char is_unsigned;
+ int flags;
+} __Pyx_TypeInfo;
+typedef struct __Pyx_StructField_ {
+ __Pyx_TypeInfo* type;
+ const char* name;
+ size_t offset;
+} __Pyx_StructField;
+typedef struct {
+ __Pyx_StructField* field;
+ size_t parent_offset;
+} __Pyx_BufFmt_StackElem;
+typedef struct {
+ __Pyx_StructField root;
+ __Pyx_BufFmt_StackElem* head;
+ size_t fmt_offset;
+ size_t new_count, enc_count;
+ size_t struct_alignment;
+ int is_complex;
+ char enc_type;
+ char new_packmode;
+ char enc_packmode;
+ char is_valid_array;
+} __Pyx_BufFmt_Context;
+
+#include <pythread.h>
+#ifndef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 1
+#endif
+#define __pyx_atomic_int_type int
+#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \
+ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \
+ !defined(__i386__)
+ #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
+ #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using GNU atomics"
+ #endif
+#elif CYTHON_ATOMICS && MSC_VER
+ #include <Windows.h>
+ #define __pyx_atomic_int_type LONG
+ #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using MSVC atomics"
+ #endif
+#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
+ #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using Intel atomics"
+ #endif
+#else
+ #undef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 0
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Not using atomics"
+ #endif
+#endif
+typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
+#if CYTHON_ATOMICS
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+#else
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+#endif
+
+
+/*--- Type declarations ---*/
+struct __pyx_array_obj;
+struct __pyx_MemviewEnum_obj;
+struct __pyx_memoryview_obj;
+struct __pyx_memoryviewslice_obj;
+
+/* "View.MemoryView":99
+ *
+ * @cname("__pyx_array")
+ * cdef class array: # <<<<<<<<<<<<<<
+ *
+ * cdef:
+ */
+struct __pyx_array_obj {
+ PyObject_HEAD
+ char *data;
+ Py_ssize_t len;
+ char *format;
+ int ndim;
+ Py_ssize_t *_shape;
+ Py_ssize_t *_strides;
+ Py_ssize_t itemsize;
+ PyObject *mode;
+ PyObject *_format;
+ void (*callback_free_data)(void *);
+ int free_data;
+ int dtype_is_object;
+};
+
+
+/* "View.MemoryView":269
+ *
+ * @cname('__pyx_MemviewEnum')
+ * cdef class Enum(object): # <<<<<<<<<<<<<<
+ * cdef object name
+ * def __init__(self, name):
+ */
+struct __pyx_MemviewEnum_obj {
+ PyObject_HEAD
+ PyObject *name;
+};
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+struct __pyx_memoryview_obj {
+ PyObject_HEAD
+ struct __pyx_vtabstruct_memoryview *__pyx_vtab;
+ PyObject *obj;
+ PyObject *_size;
+ PyObject *_array_interface;
+ PyThread_type_lock lock;
+ __pyx_atomic_int acquisition_count[2];
+ __pyx_atomic_int *acquisition_count_aligned_p;
+ Py_buffer view;
+ int flags;
+ int dtype_is_object;
+ __Pyx_TypeInfo *typeinfo;
+};
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+struct __pyx_memoryviewslice_obj {
+ struct __pyx_memoryview_obj __pyx_base;
+ __Pyx_memviewslice from_slice;
+ PyObject *from_object;
+ PyObject *(*to_object_func)(char *);
+ int (*to_dtype_func)(char *, PyObject *);
+};
+
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+
+struct __pyx_vtabstruct_memoryview {
+ char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
+ PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
+};
+static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+
+struct __pyx_vtabstruct__memoryviewslice {
+ struct __pyx_vtabstruct_memoryview __pyx_base;
+};
+static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
+#ifndef CYTHON_REFNANNY
+ #define CYTHON_REFNANNY 0
+#endif
+#if CYTHON_REFNANNY
+ typedef struct {
+ void (*INCREF)(void*, PyObject*, int);
+ void (*DECREF)(void*, PyObject*, int);
+ void (*GOTREF)(void*, PyObject*, int);
+ void (*GIVEREF)(void*, PyObject*, int);
+ void* (*SetupContext)(const char*, int, const char*);
+ void (*FinishContext)(void**);
+ } __Pyx_RefNannyAPIStruct;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname);
+ #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL;
+#ifdef WITH_THREAD
+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
+ if (acquire_gil) { \
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \
+ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \
+ PyGILState_Release(__pyx_gilstate_save); \
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+ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \
+ }
+#else
+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
+ __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__)
+#endif
+ #define __Pyx_RefNannyFinishContext() \
+ __Pyx_RefNanny->FinishContext(&__pyx_refnanny)
+ #define __Pyx_INCREF(r) __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GOTREF(r) __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
+ #define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
+ #define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
+ #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
+#else
+ #define __Pyx_RefNannyDeclarations
+ #define __Pyx_RefNannySetupContext(name, acquire_gil)
+ #define __Pyx_RefNannyFinishContext()
+ #define __Pyx_INCREF(r) Py_INCREF(r)
+ #define __Pyx_DECREF(r) Py_DECREF(r)
+ #define __Pyx_GOTREF(r)
+ #define __Pyx_GIVEREF(r)
+ #define __Pyx_XINCREF(r) Py_XINCREF(r)
+ #define __Pyx_XDECREF(r) Py_XDECREF(r)
+ #define __Pyx_XGOTREF(r)
+ #define __Pyx_XGIVEREF(r)
+#endif
+#define __Pyx_XDECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_XDECREF(tmp); \
+ } while (0)
+#define __Pyx_DECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_DECREF(tmp); \
+ } while (0)
+#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
+#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
+ PyTypeObject* tp = Py_TYPE(obj);
+ if (likely(tp->tp_getattro))
+ return tp->tp_getattro(obj, attr_name);
+#if PY_MAJOR_VERSION < 3
+ if (likely(tp->tp_getattr))
+ return tp->tp_getattr(obj, PyString_AS_STRING(attr_name));
+#endif
+ return PyObject_GetAttr(obj, attr_name);
+}
+#else
+#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
+#endif
+
+static PyObject *__Pyx_GetBuiltinName(PyObject *name);
+
+static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
+#else
+#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
+#endif
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
+#endif
+
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
+
+static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
+
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
+
+static void __Pyx_RaiseBufferIndexError(int axis);
+
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
+ __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
+
+#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
+#define __Pyx_MEMVIEW_DIRECT 1
+#define __Pyx_MEMVIEW_PTR 2
+#define __Pyx_MEMVIEW_FULL 4
+#define __Pyx_MEMVIEW_CONTIG 8
+#define __Pyx_MEMVIEW_STRIDED 16
+#define __Pyx_MEMVIEW_FOLLOW 32
+#define __Pyx_IS_C_CONTIG 1
+#define __Pyx_IS_F_CONTIG 2
+static int __Pyx_init_memviewslice(
+ struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference);
+static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
+#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
+#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
+#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
+static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
+
+static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
+
+static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \
+ PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \
+ const char* function_name);
+
+static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
+ Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
+
+#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \
+ (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \
+ __Pyx_GetItemInt_Generic(o, to_py_func(i))))
+#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck);
+
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact);
+
+#include <string.h>
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
+
+#if PY_MAJOR_VERSION >= 3
+#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
+#else
+#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
+#endif
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */
+
+#ifndef __PYX_FORCE_INIT_THREADS
+ #define __PYX_FORCE_INIT_THREADS 0
+#endif
+
+#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))
+
+static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb);
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb);
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len)) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
+#endif
+
+static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject* none = _PyList_Extend((PyListObject*)L, v);
+ if (unlikely(!none))
+ return -1;
+ Py_DECREF(none);
+ return 0;
+#else
+ return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
+#endif
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
+#endif
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
+
+static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */
+
+static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/
+static void __Pyx_WriteUnraisable(const char *name, int clineno,
+ int lineno, const char *filename,
+ int full_traceback);
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
+#else
+#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL)
+#endif
+
+typedef struct {
+ int code_line;
+ PyCodeObject* code_object;
+} __Pyx_CodeObjectCacheEntry;
+struct __Pyx_CodeObjectCache {
+ int count;
+ int max_count;
+ __Pyx_CodeObjectCacheEntry* entries;
+};
+static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
+static PyCodeObject *__pyx_find_code_object(int code_line);
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
+
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename);
+
+typedef struct {
+ Py_ssize_t shape, strides, suboffsets;
+} __Pyx_Buf_DimInfo;
+typedef struct {
+ size_t refcount;
+ Py_buffer pybuffer;
+} __Pyx_Buffer;
+typedef struct {
+ __Pyx_Buffer *rcbuffer;
+ char *data;
+ __Pyx_Buf_DimInfo diminfo[8];
+} __Pyx_LocalBuf_ND;
+
+#if PY_MAJOR_VERSION < 3
+ static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
+ static void __Pyx_ReleaseBuffer(Py_buffer *view);
+#else
+ #define __Pyx_GetBuffer PyObject_GetBuffer
+ #define __Pyx_ReleaseBuffer PyBuffer_Release
+#endif
+
+
+static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
+static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
+
+static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
+
+static PyObject *__pyx_memview_get_double(const char *itemp);
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj);
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
+
+static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim);
+
+static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize);
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object);
+
+static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
+
+static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
+
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj);
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *);
+
+static int __Pyx_check_binary_version(void);
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
+
+static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
+static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+
+/* Module declarations from 'cython.view' */
+
+/* Module declarations from 'cython' */
+
+/* Module declarations from 'functions_wrapper' */
+
+/* Module declarations from 'functions' */
+static PyTypeObject *__pyx_array_type = 0;
+static PyTypeObject *__pyx_MemviewEnum_type = 0;
+static PyTypeObject *__pyx_memoryview_type = 0;
+static PyTypeObject *__pyx_memoryviewslice_type = 0;
+static PyObject *generic = 0;
+static PyObject *strided = 0;
+static PyObject *indirect = 0;
+static PyObject *contiguous = 0;
+static PyObject *indirect_contiguous = 0;
+static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
+static void *__pyx_align_pointer(void *, size_t); /*proto*/
+static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
+static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
+static PyObject *_unellipsify(PyObject *, int); /*proto*/
+static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
+static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
+static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
+static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
+static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
+static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
+static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
+static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
+static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
+static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
+static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
+static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
+static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
+static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
+#define __Pyx_MODULE_NAME "functions"
+int __pyx_module_is_main_functions = 0;
+
+/* Implementation of 'functions' */
+static PyObject *__pyx_builtin_IndexError;
+static PyObject *__pyx_builtin_range;
+static PyObject *__pyx_builtin_ValueError;
+static PyObject *__pyx_builtin_MemoryError;
+static PyObject *__pyx_builtin_enumerate;
+static PyObject *__pyx_builtin_Ellipsis;
+static PyObject *__pyx_builtin_TypeError;
+static PyObject *__pyx_builtin_xrange;
+static PyObject *__pyx_builtin_id;
+static PyObject *__pyx_pf_9functions_erf(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x); /* proto */
+static PyObject *__pyx_pf_9functions_2erfc(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x); /* proto */
+static PyObject *__pyx_pf_9functions_4sum_gauss(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_6sum_agauss(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_8sum_fastagauss(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_10sum_splitgauss(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_12sum_apvoigt(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_14sum_pvoigt(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_16sum_splitpvoigt(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_18sum_lorentz(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_20sum_alorentz(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_22sum_splitlorentz(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_24sum_stepdown(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_26sum_stepup(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_28sum_slit(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_30sum_ahypermet(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_gaussian_term, PyObject *__pyx_v_st_term, PyObject *__pyx_v_lt_term, PyObject *__pyx_v_step_term, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_32sum_fastahypermet(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_gaussian_term, PyObject *__pyx_v_st_term, PyObject *__pyx_v_lt_term, PyObject *__pyx_v_step_term, PyObject *__pyx_v_params); /* proto */
+static PyObject *__pyx_pf_9functions_34atan_stepup(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c); /* proto */
+static PyObject *__pyx_pf_9functions_36periodic_gauss(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x, PyObject *__pyx_v_pars); /* proto */
+static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
+static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
+static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
+static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
+static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
+static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
+static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static char __pyx_k_C[] = "C";
+static char __pyx_k_O[] = "O";
+static char __pyx_k_a[] = "a";
+static char __pyx_k_b[] = "b";
+static char __pyx_k_c[] = "c";
+static char __pyx_k_i[] = "i";
+static char __pyx_k_x[] = "x";
+static char __pyx_k_id[] = "id";
+static char __pyx_k_pi[] = "pi";
+static char __pyx_k_MIT[] = "MIT";
+static char __pyx_k_erf[] = "erf";
+static char __pyx_k_obj[] = "obj";
+static char __pyx_k_x_c[] = "x_c";
+static char __pyx_k_y_c[] = "y_c";
+static char __pyx_k_base[] = "base";
+static char __pyx_k_copy[] = "copy";
+static char __pyx_k_date[] = "__date__";
+static char __pyx_k_erfc[] = "erfc";
+static char __pyx_k_main[] = "__main__";
+static char __pyx_k_mode[] = "mode";
+static char __pyx_k_name[] = "name";
+static char __pyx_k_ndim[] = "ndim";
+static char __pyx_k_pack[] = "pack";
+static char __pyx_k_pars[] = "pars";
+static char __pyx_k_size[] = "size";
+static char __pyx_k_step[] = "step";
+static char __pyx_k_stop[] = "stop";
+static char __pyx_k_test[] = "__test__";
+static char __pyx_k_array[] = "array";
+static char __pyx_k_class[] = "__class__";
+static char __pyx_k_dtype[] = "dtype";
+static char __pyx_k_empty[] = "empty";
+static char __pyx_k_error[] = "error";
+static char __pyx_k_flags[] = "flags";
+static char __pyx_k_float[] = "float";
+static char __pyx_k_numpy[] = "numpy";
+static char __pyx_k_order[] = "order";
+static char __pyx_k_range[] = "range";
+static char __pyx_k_shape[] = "shape";
+static char __pyx_k_start[] = "start";
+static char __pyx_k_zeros[] = "zeros";
+static char __pyx_k_arctan[] = "arctan";
+static char __pyx_k_format[] = "format";
+static char __pyx_k_import[] = "__import__";
+static char __pyx_k_logger[] = "_logger";
+static char __pyx_k_name_2[] = "__name__";
+static char __pyx_k_params[] = "params";
+static char __pyx_k_status[] = "status";
+static char __pyx_k_struct[] = "struct";
+static char __pyx_k_unpack[] = "unpack";
+static char __pyx_k_xrange[] = "xrange";
+static char __pyx_k_asarray[] = "asarray";
+static char __pyx_k_authors[] = "__authors__";
+static char __pyx_k_float64[] = "float64";
+static char __pyx_k_fortran[] = "fortran";
+static char __pyx_k_len_dim[] = "len_dim";
+static char __pyx_k_license[] = "__license__";
+static char __pyx_k_logging[] = "logging";
+static char __pyx_k_lt_term[] = "lt_term";
+static char __pyx_k_memview[] = "memview";
+static char __pyx_k_newpars[] = "newpars";
+static char __pyx_k_reshape[] = "reshape";
+static char __pyx_k_st_term[] = "st_term";
+static char __pyx_k_Ellipsis[] = "Ellipsis";
+static char __pyx_k_P_Knobel[] = "P. Knobel";
+static char __pyx_k_itemsize[] = "itemsize";
+static char __pyx_k_params_c[] = "params_c";
+static char __pyx_k_sum_slit[] = "sum_slit";
+static char __pyx_k_TypeError[] = "TypeError";
+static char __pyx_k_enumerate[] = "enumerate";
+static char __pyx_k_functions[] = "functions";
+static char __pyx_k_getLogger[] = "getLogger";
+static char __pyx_k_step_term[] = "step_term";
+static char __pyx_k_sum_gauss[] = "sum_gauss";
+static char __pyx_k_17_06_2016[] = "17/06/2016";
+static char __pyx_k_IndexError[] = "IndexError";
+static char __pyx_k_ValueError[] = "ValueError";
+static char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
+static char __pyx_k_sum_agauss[] = "sum_agauss";
+static char __pyx_k_sum_pvoigt[] = "sum_pvoigt";
+static char __pyx_k_sum_stepup[] = "sum_stepup";
+static char __pyx_k_tail_flags[] = "tail_flags";
+static char __pyx_k_MemoryError[] = "MemoryError";
+static char __pyx_k_atan_stepup[] = "atan_stepup";
+static char __pyx_k_basicConfig[] = "basicConfig";
+static char __pyx_k_sum_apvoigt[] = "sum_apvoigt";
+static char __pyx_k_sum_lorentz[] = "sum_lorentz";
+static char __pyx_k_sum_alorentz[] = "sum_alorentz";
+static char __pyx_k_sum_stepdown[] = "sum_stepdown";
+static char __pyx_k_gaussian_term[] = "gaussian_term";
+static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
+static char __pyx_k_sum_ahypermet[] = "sum_ahypermet";
+static char __pyx_k_periodic_gauss[] = "periodic_gauss";
+static char __pyx_k_sum_fastagauss[] = "sum_fastagauss";
+static char __pyx_k_sum_splitgauss[] = "sum_splitgauss";
+static char __pyx_k_allocate_buffer[] = "allocate_buffer";
+static char __pyx_k_dtype_is_object[] = "dtype_is_object";
+static char __pyx_k_sum_splitpvoigt[] = "sum_splitpvoigt";
+static char __pyx_k_sum_splitlorentz[] = "sum_splitlorentz";
+static char __pyx_k_sum_fastahypermet[] = "sum_fastahypermet";
+static char __pyx_k_strided_and_direct[] = "<strided and direct>";
+static char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
+static char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
+static char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
+static char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
+static char __pyx_k_No_parameters_specified[] = "No parameters specified. ";
+static char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
+static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
+static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)";
+static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct";
+static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
+static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)";
+static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)";
+static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
+static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
+static char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
+static char __pyx_k_Cannot_compute_erf_for_an_empty[] = "Cannot compute erf for an empty array";
+static char __pyx_k_mntdirect__scisoft_users_tvince[] = "/mntdirect/_scisoft/users/tvincent/src/silx/silx/math/fit/functions/functions.pyx";
+static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced";
+static char __pyx_k_At_least_3_parameters_are_requir[] = "At least 3 parameters are required.";
+static char __pyx_k_At_least_4_parameters_are_requir[] = "At least 4 parameters are required.";
+static char __pyx_k_At_least_5_parameters_are_requir[] = "At least 5 parameters are required.";
+static char __pyx_k_At_least_8_parameters_are_requir[] = "At least 8 parameters are required.";
+static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
+static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
+static char __pyx_k_Cannot_compute_erfc_for_an_empty[] = "Cannot compute erfc for an empty array";
+static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions";
+static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
+static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
+static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
+static char __pyx_k_No_gaussian_parameters_specified[] = "No gaussian parameters specified. ";
+static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
+static char __pyx_k_This_module_provides_fit_functio[] = "This module provides fit functions.\n\nList of fit functions:\n-----------------------\n\n - :func:`sum_gauss`\n - :func:`sum_agauss`\n - :func:`sum_splitgauss`\n - :func:`sum_fastagauss`\n\n - :func:`sum_apvoigt`\n - :func:`sum_pvoigt`\n - :func:`sum_splitpvoigt`\n\n - :func:`sum_lorentz`\n - :func:`sum_alorentz`\n - :func:`sum_splitlorentz`\n\n - :func:`sum_stepdown`\n - :func:`sum_stepup`\n - :func:`sum_slit`\n\n - :func:`sum_ahypermet`\n - :func:`sum_fastahypermet`\n\nFull documentation:\n-------------------\n\n";
+static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
+static char __pyx_k_Wrong_number_of_parameters_for_f[] = "Wrong number of parameters for function";
+static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
+static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
+static PyObject *__pyx_kp_s_17_06_2016;
+static PyObject *__pyx_kp_s_At_least_3_parameters_are_requir;
+static PyObject *__pyx_kp_s_At_least_4_parameters_are_requir;
+static PyObject *__pyx_kp_s_At_least_5_parameters_are_requir;
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+static PyObject *__pyx_kp_s_Cannot_compute_erfc_for_an_empty;
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+static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
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+static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
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+static PyObject *__pyx_n_s_MemoryError;
+static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
+static PyObject *__pyx_kp_s_MemoryView_of_r_object;
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+static PyObject *__pyx_kp_s_No_parameters_specified;
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+static PyObject *__pyx_kp_s_P_Knobel;
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+static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
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+static PyObject *__pyx_kp_s_Wrong_number_of_parameters_for_f;
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+static PyObject *__pyx_n_s_logging;
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+static PyObject *__pyx_kp_s_mntdirect__scisoft_users_tvince;
+static PyObject *__pyx_n_s_mode;
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+
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+ __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+ if (__pyx_t_2) {
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+ * start = 0
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+ __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
+
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+ * start += shape
+ * if start < 0: # <<<<<<<<<<<<<<
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+ * elif start >= shape:
+ */
+ __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":802
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+ * if start < 0:
+ * start = 0 # <<<<<<<<<<<<<<
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+ * if negative_step:
+ */
+ __pyx_v_start = 0;
+ goto __pyx_L13;
+ }
+ __pyx_L13:;
+ goto __pyx_L12;
+ }
+
+ /* "View.MemoryView":803
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+ * start = 0
+ * elif start >= shape: # <<<<<<<<<<<<<<
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+ * start = shape - 1
+ */
+ __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":804
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+ * if negative_step: # <<<<<<<<<<<<<<
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+ * else:
+ */
+ __pyx_t_2 = (__pyx_v_negative_step != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":805
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+ * if negative_step:
+ * start = shape - 1 # <<<<<<<<<<<<<<
+ * else:
+ * start = shape
+ */
+ __pyx_v_start = (__pyx_v_shape - 1);
+ goto __pyx_L14;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":807
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+ * else:
+ * start = shape # <<<<<<<<<<<<<<
+ * else:
+ * if negative_step:
+ */
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+ __pyx_L14:;
+ goto __pyx_L12;
+ }
+ __pyx_L12:;
+ goto __pyx_L11;
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+ if (__pyx_t_2) {
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+ /* "View.MemoryView":810
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+ * else:
+ * start = 0
+ */
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+ goto __pyx_L15;
+ }
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+
+ /* "View.MemoryView":812
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+ * else:
+ * start = 0 # <<<<<<<<<<<<<<
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+ * if have_stop:
+ */
+ __pyx_v_start = 0;
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+ __pyx_L15:;
+ }
+ __pyx_L11:;
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+ */
+ __pyx_t_2 = (__pyx_v_have_stop != 0);
+ if (__pyx_t_2) {
+
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+ * if stop < 0: # <<<<<<<<<<<<<<
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+ * if stop < 0:
+ */
+ __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+ if (__pyx_t_2) {
+
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+ * stop = 0
+ */
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+
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+ * stop += shape
+ * if stop < 0: # <<<<<<<<<<<<<<
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+ * elif stop > shape:
+ */
+ __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":818
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+ * if stop < 0:
+ * stop = 0 # <<<<<<<<<<<<<<
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+ * stop = shape
+ */
+ __pyx_v_stop = 0;
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+ }
+ __pyx_L18:;
+ goto __pyx_L17;
+ }
+
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+ * elif stop > shape: # <<<<<<<<<<<<<<
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+ * else:
+ */
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+ if (__pyx_t_2) {
+
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+ */
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+ */
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+ __pyx_L16:;
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+ __pyx_L20:;
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+
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+ __pyx_L25:;
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+ #ifdef WITH_THREAD
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+ Py_ssize_t __pyx_v_suboffset;
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+ * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<<
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+ * src_shape + 1, dst_shape + 1,
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+
+ /* "View.MemoryView":1120
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+ *
+ */
+ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+ /* "View.MemoryView":1121
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+ * src_data += src_stride
+ * dst_data += dst_stride # <<<<<<<<<<<<<<
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+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
+ */
+ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1093
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+ * @cython.cdivision(True)
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+ * Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+ /* function exit code */
+}
+
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+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
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+ */
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+ */
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+ int __pyx_v_i;
+ Py_ssize_t __pyx_v_size;
+ Py_ssize_t __pyx_r;
+ Py_ssize_t __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
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+ __pyx_v_size = __pyx_t_1;
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+ int __pyx_t_1;
+ int __pyx_t_2;
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+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1258
+ * if slices_overlap(&src, &dst, ndim, itemsize):
+ *
+ * if not slice_is_contig(&src, order, ndim): # <<<<<<<<<<<<<<
+ * order = get_best_order(&dst, ndim)
+ *
+ */
+ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig((&__pyx_v_src), __pyx_v_order, __pyx_v_ndim) != 0)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1259
+ *
+ * if not slice_is_contig(&src, order, ndim):
+ * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<<
+ *
+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ */
+ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim);
+ goto __pyx_L10;
+ }
+ __pyx_L10:;
+
+ /* "View.MemoryView":1261
+ * order = get_best_order(&dst, ndim)
+ *
+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<<
+ * src = tmp
+ *
+ */
+ __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 1261; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_v_tmpdata = __pyx_t_6;
+
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+ * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ * src = tmp # <<<<<<<<<<<<<<
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+ * if not broadcasting:
+ */
+ __pyx_v_src = __pyx_v_tmp;
+ goto __pyx_L9;
+ }
+ __pyx_L9:;
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+ *
+ * if not broadcasting: # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0);
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+ *
+ *
+ * if slice_is_contig(&src, 'C', ndim): # <<<<<<<<<<<<<<
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+ * elif slice_is_contig(&src, 'F', ndim):
+ */
+ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0);
+ if (__pyx_t_2) {
+
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+ *
+ * if slice_is_contig(&src, 'C', ndim):
+ * direct_copy = slice_is_contig(&dst, 'C', ndim) # <<<<<<<<<<<<<<
+ * elif slice_is_contig(&src, 'F', ndim):
+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ */
+ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim);
+ goto __pyx_L12;
+ }
+
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+ * if slice_is_contig(&src, 'C', ndim):
+ * direct_copy = slice_is_contig(&dst, 'C', ndim)
+ * elif slice_is_contig(&src, 'F', ndim): # <<<<<<<<<<<<<<
+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ *
+ */
+ __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1270
+ * direct_copy = slice_is_contig(&dst, 'C', ndim)
+ * elif slice_is_contig(&src, 'F', ndim):
+ * direct_copy = slice_is_contig(&dst, 'F', ndim) # <<<<<<<<<<<<<<
+ *
+ * if direct_copy:
+ */
+ __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim);
+ goto __pyx_L12;
+ }
+ __pyx_L12:;
+
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+ * direct_copy = slice_is_contig(&dst, 'F', ndim)
+ *
+ * if direct_copy: # <<<<<<<<<<<<<<
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+ __pyx_t_2 = (__pyx_v_direct_copy != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1274
+ * if direct_copy:
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+ /* "View.MemoryView":1275
+ *
+ * refcount_copying(&dst, dtype_is_object, ndim, False)
+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<<
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+ * free(tmpdata)
+ */
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+
+ /* "View.MemoryView":1276
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+ * memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
+ * free(tmpdata)
+ * return 0
+ */
+ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+ /* "View.MemoryView":1277
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+ * refcount_copying(&dst, dtype_is_object, ndim, True)
+ * free(tmpdata) # <<<<<<<<<<<<<<
+ * return 0
+ *
+ */
+ free(__pyx_v_tmpdata);
+
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+ * free(tmpdata)
+ * return 0 # <<<<<<<<<<<<<<
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+ * if order == 'F' == get_best_order(&dst, ndim):
+ */
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+ }
+ goto __pyx_L11;
+ }
+ __pyx_L11:;
+
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+ *
+ * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<<
+ *
+ *
+ */
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+ __pyx_t_7 = (__pyx_t_2 != 0);
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+ *
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+ *
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+
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+ * transpose_memslice(&dst) # <<<<<<<<<<<<<<
+ *
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+/* "View.MemoryView":1351
+ *
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<<
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ */
+
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {
+
+ /* "View.MemoryView":1354
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ * itemsize, item)
+ */
+ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+ /* "View.MemoryView":1355
+ * bint dtype_is_object) nogil:
+ * refcount_copying(dst, dtype_is_object, ndim, False)
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<<
+ * itemsize, item)
+ * refcount_copying(dst, dtype_is_object, ndim, True)
+ */
+ __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item);
+
+ /* "View.MemoryView":1357
+ * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ * itemsize, item)
+ * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+ /* "View.MemoryView":1351
+ *
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<<
+ * size_t itemsize, void *item,
+ * bint dtype_is_object) nogil:
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1361
+ *
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim,
+ * size_t itemsize, void *item) nogil:
+ */
+
+static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
+ CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+ Py_ssize_t __pyx_v_stride;
+ Py_ssize_t __pyx_v_extent;
+ int __pyx_t_1;
+ Py_ssize_t __pyx_t_2;
+ Py_ssize_t __pyx_t_3;
+
+ /* "View.MemoryView":1365
+ * size_t itemsize, void *item) nogil:
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t extent = shape[0]
+ *
+ */
+ __pyx_v_stride = (__pyx_v_strides[0]);
+
+ /* "View.MemoryView":1366
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t stride = strides[0]
+ * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<<
+ *
+ * if ndim == 1:
+ */
+ __pyx_v_extent = (__pyx_v_shape[0]);
+
+ /* "View.MemoryView":1368
+ * cdef Py_ssize_t extent = shape[0]
+ *
+ * if ndim == 1: # <<<<<<<<<<<<<<
+ * for i in range(extent):
+ * memcpy(data, item, itemsize)
+ */
+ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1369
+ *
+ * if ndim == 1:
+ * for i in range(extent): # <<<<<<<<<<<<<<
+ * memcpy(data, item, itemsize)
+ * data += stride
+ */
+ __pyx_t_2 = __pyx_v_extent;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1370
+ * if ndim == 1:
+ * for i in range(extent):
+ * memcpy(data, item, itemsize) # <<<<<<<<<<<<<<
+ * data += stride
+ * else:
+ */
+ memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1371
+ * for i in range(extent):
+ * memcpy(data, item, itemsize)
+ * data += stride # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(extent):
+ */
+ __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+ }
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1373
+ * data += stride
+ * else:
+ * for i in range(extent): # <<<<<<<<<<<<<<
+ * _slice_assign_scalar(data, shape + 1, strides + 1,
+ * ndim - 1, itemsize, item)
+ */
+ __pyx_t_2 = __pyx_v_extent;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1374
+ * else:
+ * for i in range(extent):
+ * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<<
+ * ndim - 1, itemsize, item)
+ * data += stride
+ */
+ __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item);
+
+ /* "View.MemoryView":1376
+ * _slice_assign_scalar(data, shape + 1, strides + 1,
+ * ndim - 1, itemsize, item)
+ * data += stride # <<<<<<<<<<<<<<
+ *
+ *
+ */
+ __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1361
+ *
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
+ * Py_ssize_t *strides, int ndim,
+ * size_t itemsize, void *item) nogil:
+ */
+
+ /* function exit code */
+}
+
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_array_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_array_obj *)o);
+ p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None);
+ p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None);
+ if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) {
+ Py_DECREF(o); o = 0;
+ }
+ return o;
+}
+
+static void __pyx_tp_dealloc_array(PyObject *o) {
+ struct __pyx_array_obj *p = (struct __pyx_array_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_array___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->mode);
+ Py_CLEAR(p->_format);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) {
+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_array___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
+ PyObject *v = PyObject_GenericGetAttr(o, n);
+ if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+ PyErr_Clear();
+ v = __pyx_array___getattr__(o, n);
+ }
+ return v;
+}
+
+static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
+ return get_memview(o);
+}
+
+static PyMethodDef __pyx_methods_array[] = {
+ {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_array[] = {
+ {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_array = {
+ 0, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_array, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_array = {
+ 0, /*mp_length*/
+ __pyx_array___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_array = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_array_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_array = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "functions.array", /*tp_name*/
+ sizeof(struct __pyx_array_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_array, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ 0, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_array, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_array, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ __pyx_tp_getattro_array, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_array, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
+ 0, /*tp_doc*/
+ 0, /*tp_traverse*/
+ 0, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_array, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_array, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_array, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
+ struct __pyx_MemviewEnum_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_MemviewEnum_obj *)o);
+ p->name = Py_None; Py_INCREF(Py_None);
+ return o;
+}
+
+static void __pyx_tp_dealloc_Enum(PyObject *o) {
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ Py_CLEAR(p->name);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ if (p->name) {
+ e = (*v)(p->name, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_Enum(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ tmp = ((PyObject*)p->name);
+ p->name = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ return 0;
+}
+
+static PyMethodDef __pyx_methods_Enum[] = {
+ {0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_MemviewEnum = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "functions.Enum", /*tp_name*/
+ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_Enum, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_MemviewEnum___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_Enum, /*tp_traverse*/
+ __pyx_tp_clear_Enum, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_Enum, /*tp_methods*/
+ 0, /*tp_members*/
+ 0, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ __pyx_MemviewEnum___init__, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_Enum, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
+
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryview_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryview_obj *)o);
+ p->__pyx_vtab = __pyx_vtabptr_memoryview;
+ p->obj = Py_None; Py_INCREF(Py_None);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ p->view.obj = NULL;
+ if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) {
+ Py_DECREF(o); o = 0;
+ }
+ return o;
+}
+
+static void __pyx_tp_dealloc_memoryview(PyObject *o) {
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryview___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->obj);
+ Py_CLEAR(p->_size);
+ Py_CLEAR(p->_array_interface);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ if (p->obj) {
+ e = (*v)(p->obj, a); if (e) return e;
+ }
+ if (p->_size) {
+ e = (*v)(p->_size, a); if (e) return e;
+ }
+ if (p->_array_interface) {
+ e = (*v)(p->_array_interface, a); if (e) return e;
+ }
+ if (p->view.obj) {
+ e = (*v)(p->view.obj, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_memoryview(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ tmp = ((PyObject*)p->obj);
+ p->obj = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_size);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_array_interface);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ Py_CLEAR(p->view.obj);
+ return 0;
+}
+static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_memoryview___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_transpose(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview__get__base(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_shape(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_strides(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_suboffsets(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_ndim(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_itemsize(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_nbytes(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_size(o);
+}
+
+static PyMethodDef __pyx_methods_memoryview[] = {
+ {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
+ {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
+ {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
+ {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_memoryview[] = {
+ {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0},
+ {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0},
+ {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0},
+ {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0},
+ {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0},
+ {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0},
+ {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0},
+ {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0},
+ {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
+ __pyx_memoryview___len__, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_memoryview, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
+ __pyx_memoryview___len__, /*mp_length*/
+ __pyx_memoryview___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_memoryview_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_memoryview = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "functions.memoryview", /*tp_name*/
+ sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_memoryview___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ __pyx_memoryview___str__, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_memoryview, /*tp_traverse*/
+ __pyx_tp_clear_memoryview, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_memoryview, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_memoryview, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_memoryview, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;
+
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryviewslice_obj *p;
+ PyObject *o = __pyx_tp_new_memoryview(t, a, k);
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryviewslice_obj *)o);
+ p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ p->from_slice.memview = NULL;
+ return o;
+}
+
+static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryviewslice___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->from_object);
+ PyObject_GC_Track(o);
+ __pyx_tp_dealloc_memoryview(o);
+}
+
+static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
+ if (p->from_object) {
+ e = (*v)(p->from_object, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ __pyx_tp_clear_memoryview(o);
+ tmp = ((PyObject*)p->from_object);
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
+ return 0;
+}
+
+static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryviewslice__get__base(o);
+}
+
+static PyMethodDef __pyx_methods__memoryviewslice[] = {
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
+ {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_memoryviewslice = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "functions._memoryviewslice", /*tp_name*/
+ sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___repr__, /*tp_repr*/
+ #else
+ 0, /*tp_repr*/
+ #endif
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___str__, /*tp_str*/
+ #else
+ 0, /*tp_str*/
+ #endif
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ "Internal class for passing memoryview slices to Python", /*tp_doc*/
+ __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
+ __pyx_tp_clear__memoryviewslice, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods__memoryviewslice, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets__memoryviewslice, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new__memoryviewslice, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyMethodDef __pyx_methods[] = {
+ {0, 0, 0, 0}
+};
+
+#if PY_MAJOR_VERSION >= 3
+static struct PyModuleDef __pyx_moduledef = {
+ #if PY_VERSION_HEX < 0x03020000
+ { PyObject_HEAD_INIT(NULL) NULL, 0, NULL },
+ #else
+ PyModuleDef_HEAD_INIT,
+ #endif
+ "functions",
+ __pyx_k_This_module_provides_fit_functio, /* m_doc */
+ -1, /* m_size */
+ __pyx_methods /* m_methods */,
+ NULL, /* m_reload */
+ NULL, /* m_traverse */
+ NULL, /* m_clear */
+ NULL /* m_free */
+};
+#endif
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+ *
+ */
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+ __Pyx_GOTREF(__pyx_tuple__63);
+ __Pyx_GIVEREF(__pyx_tuple__63);
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+
+ /* "functions.pyx":98
+ *
+ *
+ * def erfc(x): # <<<<<<<<<<<<<<
+ * """Return the gaussian complementary error function
+ *
+ */
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+ __Pyx_GOTREF(__pyx_tuple__65);
+ __Pyx_GIVEREF(__pyx_tuple__65);
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+
+ /* "functions.pyx":128
+ *
+ *
+ * def sum_gauss(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of gaussian functions defined by *(height, centroid, fwhm)*,
+ * where:
+ */
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+ __Pyx_GOTREF(__pyx_tuple__67);
+ __Pyx_GIVEREF(__pyx_tuple__67);
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+
+ /* "functions.pyx":176
+ *
+ *
+ * def sum_agauss(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of gaussian functions defined by *(area, centroid, fwhm)*,
+ * where:
+ */
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+ __Pyx_GOTREF(__pyx_tuple__69);
+ __Pyx_GIVEREF(__pyx_tuple__69);
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+
+ /* "functions.pyx":222
+ *
+ *
+ * def sum_fastagauss(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of gaussian functions defined by *(area, centroid, fwhm)*,
+ * where:
+ */
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+ __Pyx_GOTREF(__pyx_tuple__71);
+ __Pyx_GIVEREF(__pyx_tuple__71);
+ __pyx_codeobj__72 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__71, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_fastagauss, 222, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__72)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 222; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":272
+ *
+ *
+ * def sum_splitgauss(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of gaussian functions defined by *(area, centroid, fwhm1, fwhm2)*,
+ * where:
+ */
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+ __Pyx_GOTREF(__pyx_tuple__73);
+ __Pyx_GIVEREF(__pyx_tuple__73);
+ __pyx_codeobj__74 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__73, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_splitgauss, 272, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__74)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 272; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":321
+ *
+ *
+ * def sum_apvoigt(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of pseudo-Voigt functions, defined by *(area, centroid, fwhm,
+ * eta)*.
+ */
+ __pyx_tuple__75 = PyTuple_Pack(6, __pyx_n_s_x, __pyx_n_s_params, __pyx_n_s_x_c, __pyx_n_s_params_c, __pyx_n_s_y_c, __pyx_n_s_status); if (unlikely(!__pyx_tuple__75)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 321; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_tuple__75);
+ __Pyx_GIVEREF(__pyx_tuple__75);
+ __pyx_codeobj__76 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__75, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_apvoigt, 321, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__76)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 321; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":371
+ *
+ *
+ * def sum_pvoigt(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of pseudo-Voigt functions, defined by *(height, centroid,
+ * fwhm, eta)*.
+ */
+ __pyx_tuple__77 = PyTuple_Pack(6, __pyx_n_s_x, __pyx_n_s_params, __pyx_n_s_x_c, __pyx_n_s_params_c, __pyx_n_s_y_c, __pyx_n_s_status); if (unlikely(!__pyx_tuple__77)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 371; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_tuple__77);
+ __Pyx_GIVEREF(__pyx_tuple__77);
+ __pyx_codeobj__78 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__77, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_pvoigt, 371, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__78)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 371; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":422
+ *
+ *
+ * def sum_splitpvoigt(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of split pseudo-Voigt functions, defined by *(height,
+ * centroid, fwhm1, fwhm2, eta)*.
+ */
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+ __Pyx_GOTREF(__pyx_tuple__79);
+ __Pyx_GIVEREF(__pyx_tuple__79);
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+
+ /* "functions.pyx":477
+ *
+ *
+ * def sum_lorentz(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of Lorentz distributions, also known as Cauchy distribution,
+ * defined by *(height, centroid, fwhm)*.
+ */
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+ __Pyx_GOTREF(__pyx_tuple__81);
+ __Pyx_GIVEREF(__pyx_tuple__81);
+ __pyx_codeobj__82 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__81, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_lorentz, 477, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__82)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 477; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":524
+ *
+ *
+ * def sum_alorentz(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of Lorentz distributions, also known as Cauchy distribution,
+ * defined by *(area, centroid, fwhm)*.
+ */
+ __pyx_tuple__83 = PyTuple_Pack(6, __pyx_n_s_x, __pyx_n_s_params, __pyx_n_s_x_c, __pyx_n_s_params_c, __pyx_n_s_y_c, __pyx_n_s_status); if (unlikely(!__pyx_tuple__83)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 524; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_tuple__83);
+ __Pyx_GIVEREF(__pyx_tuple__83);
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+
+ /* "functions.pyx":571
+ *
+ *
+ * def sum_splitlorentz(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of split Lorentz distributions,
+ * defined by *(height, centroid, fwhm1, fwhm2)*.
+ */
+ __pyx_tuple__85 = PyTuple_Pack(6, __pyx_n_s_x, __pyx_n_s_params, __pyx_n_s_x_c, __pyx_n_s_params_c, __pyx_n_s_y_c, __pyx_n_s_status); if (unlikely(!__pyx_tuple__85)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 571; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_tuple__85);
+ __Pyx_GIVEREF(__pyx_tuple__85);
+ __pyx_codeobj__86 = (PyObject*)__Pyx_PyCode_New(1, 0, 6, 0, CO_VARARGS, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__85, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_mntdirect__scisoft_users_tvince, __pyx_n_s_sum_splitlorentz, 571, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__86)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 571; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+
+ /* "functions.pyx":619
+ *
+ *
+ * def sum_stepdown(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of stepdown functions.
+ * defined by *(height, centroid, fwhm)*.
+ */
+ __pyx_tuple__87 = PyTuple_Pack(6, __pyx_n_s_x, __pyx_n_s_params, __pyx_n_s_x_c, __pyx_n_s_params_c, __pyx_n_s_y_c, __pyx_n_s_status); if (unlikely(!__pyx_tuple__87)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 619; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_tuple__87);
+ __Pyx_GIVEREF(__pyx_tuple__87);
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+
+ /* "functions.pyx":667
+ *
+ *
+ * def sum_stepup(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of stepup functions.
+ * defined by *(height, centroid, fwhm)*.
+ */
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+ __Pyx_GOTREF(__pyx_tuple__89);
+ __Pyx_GIVEREF(__pyx_tuple__89);
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+
+ /* "functions.pyx":716
+ *
+ *
+ * def sum_slit(x, *params): # <<<<<<<<<<<<<<
+ * """Return a sum of slit functions.
+ * defined by *(height, position, fwhm, beamfwhm)*.
+ */
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+ __Pyx_GOTREF(__pyx_tuple__91);
+ __Pyx_GIVEREF(__pyx_tuple__91);
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+
+ /* "functions.pyx":767
+ *
+ *
+ * def sum_ahypermet(x, *params, # <<<<<<<<<<<<<<
+ * gaussian_term=True, st_term=True, lt_term=True, step_term=True):
+ * """Return a sum of ahypermet functions.
+ */
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+ __Pyx_GOTREF(__pyx_tuple__93);
+ __Pyx_GIVEREF(__pyx_tuple__93);
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+
+ /* "functions.pyx":849
+ *
+ *
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+ * gaussian_term=True, st_term=True,
+ * lt_term=True, step_term=True):
+ */
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+ __Pyx_GOTREF(__pyx_tuple__95);
+ __Pyx_GIVEREF(__pyx_tuple__95);
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+
+ /* "functions.pyx":942
+ *
+ *
+ * def atan_stepup(x, a, b, c): # <<<<<<<<<<<<<<
+ * """
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+ */
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+}
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+}
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+}
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+}
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+}
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+ PyThreadState *tstate = PyThreadState_GET();
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+ tmp_tb = tstate->curexc_traceback;
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+ tstate->curexc_traceback = tb;
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+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_Restore(type, value, tb);
+#endif
+}
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+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
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+ *value = tstate->curexc_value;
+ *tb = tstate->curexc_traceback;
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+ tstate->curexc_value = 0;
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+ PyErr_Fetch(type, value, tb);
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+}
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+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
+ CYTHON_UNUSED PyObject *cause) {
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+ tb = NULL;
+ else {
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+ PyErr_SetString(PyExc_TypeError,
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+ goto raise_error;
+ }
+ }
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+ if (!value) {
+ Py_INCREF(Py_None);
+ value = Py_None;
+ }
+#endif
+ PyErr_NormalizeException(&type, &value, &tb);
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+ PyErr_SetString(PyExc_TypeError,
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+ }
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+ if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: exception class must be a subclass of BaseException");
+ goto raise_error;
+ }
+ }
+ __Pyx_ErrRestore(type, value, tb);
+ return;
+raise_error:
+ Py_XDECREF(value);
+ Py_XDECREF(type);
+ Py_XDECREF(tb);
+ return;
+}
+#else
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
+ PyObject* owned_instance = NULL;
+ if (tb == Py_None) {
+ tb = 0;
+ } else if (tb && !PyTraceBack_Check(tb)) {
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+ value = 0;
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+ goto bad;
+ owned_instance = PyObject_Call(type, args, NULL);
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+ goto bad;
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+ }
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+ PyErr_Fetch(tmp_type, tmp_value, tmp_tb);
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+}
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+}
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+}
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+ ctx->struct_alignment = 0;
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+ }
+}
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+ const char* t = *ts;
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+ count = *t++ - '0';
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+}
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+}
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+}
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+}
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+}
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+ case 'h': case 'H': return sizeof(short);
+ case 'i': case 'I': return sizeof(int);
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+ case 'q': case 'Q': return sizeof(PY_LONG_LONG);
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+ case 'f': return sizeof(float) * (is_complex ? 2 : 1);
+ case 'd': return sizeof(double) * (is_complex ? 2 : 1);
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+}
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+typedef struct { char c; int x; } __Pyx_st_int;
+typedef struct { char c; long x; } __Pyx_st_long;
+typedef struct { char c; float x; } __Pyx_st_float;
+typedef struct { char c; double x; } __Pyx_st_double;
+typedef struct { char c; long double x; } __Pyx_st_longdouble;
+typedef struct { char c; void *x; } __Pyx_st_void_p;
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+ case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
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+ case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
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+}
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+typedef struct { double x; char c; } __Pyx_pad_double;
+typedef struct { long double x; char c; } __Pyx_pad_longdouble;
+typedef struct { void *x; char c; } __Pyx_pad_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
+ case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
+ case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
+#endif
+ case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
+ case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
+ case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
+ case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
+ switch (ch) {
+ case 'c':
+ return 'H';
+ case 'b': case 'h': case 'i':
+ case 'l': case 'q': case 's': case 'p':
+ return 'I';
+ case 'B': case 'H': case 'I': case 'L': case 'Q':
+ return 'U';
+ case 'f': case 'd': case 'g':
+ return (is_complex ? 'C' : 'R');
+ case 'O':
+ return 'O';
+ case 'P':
+ return 'P';
+ default: {
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+ }
+}
+static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
+ if (ctx->head == NULL || ctx->head->field == &ctx->root) {
+ const char* expected;
+ const char* quote;
+ if (ctx->head == NULL) {
+ expected = "end";
+ quote = "";
+ } else {
+ expected = ctx->head->field->type->name;
+ quote = "'";
+ }
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected %s%s%s but got %s",
+ quote, expected, quote,
+ __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
+ } else {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_StructField* parent = (ctx->head - 1)->field;
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
+ field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
+ parent->type->name, field->name);
+ }
+}
+static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
+ char group;
+ size_t size, offset, arraysize = 1;
+ if (ctx->enc_type == 0) return 0;
+ if (ctx->head->field->type->arraysize[0]) {
+ int i, ndim = 0;
+ if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
+ ctx->is_valid_array = ctx->head->field->type->ndim == 1;
+ ndim = 1;
+ if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
+ PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %zu",
+ ctx->head->field->type->arraysize[0], ctx->enc_count);
+ return -1;
+ }
+ }
+ if (!ctx->is_valid_array) {
+ PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
+ ctx->head->field->type->ndim, ndim);
+ return -1;
+ }
+ for (i = 0; i < ctx->head->field->type->ndim; i++) {
+ arraysize *= ctx->head->field->type->arraysize[i];
+ }
+ ctx->is_valid_array = 0;
+ ctx->enc_count = 1;
+ }
+ group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
+ do {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_TypeInfo* type = field->type;
+ if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
+ size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
+ } else {
+ size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
+ }
+ if (ctx->enc_packmode == '@') {
+ size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
+ size_t align_mod_offset;
+ if (align_at == 0) return -1;
+ align_mod_offset = ctx->fmt_offset % align_at;
+ if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
+ if (ctx->struct_alignment == 0)
+ ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
+ ctx->is_complex);
+ }
+ if (type->size != size || type->typegroup != group) {
+ if (type->typegroup == 'C' && type->fields != NULL) {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ ++ctx->head;
+ ctx->head->field = type->fields;
+ ctx->head->parent_offset = parent_offset;
+ continue;
+ }
+ if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
+ } else {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ }
+ offset = ctx->head->parent_offset + field->offset;
+ if (ctx->fmt_offset != offset) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
+ (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
+ return -1;
+ }
+ ctx->fmt_offset += size;
+ if (arraysize)
+ ctx->fmt_offset += (arraysize - 1) * size;
+ --ctx->enc_count;
+ while (1) {
+ if (field == &ctx->root) {
+ ctx->head = NULL;
+ if (ctx->enc_count != 0) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ break;
+ }
+ ctx->head->field = ++field;
+ if (field->type == NULL) {
+ --ctx->head;
+ field = ctx->head->field;
+ continue;
+ } else if (field->type->typegroup == 'S') {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ if (field->type->fields->type == NULL) continue;
+ field = field->type->fields;
+ ++ctx->head;
+ ctx->head->field = field;
+ ctx->head->parent_offset = parent_offset;
+ break;
+ } else {
+ break;
+ }
+ }
+ } while (ctx->enc_count);
+ ctx->enc_type = 0;
+ ctx->is_complex = 0;
+ return 0;
+}
+static CYTHON_INLINE PyObject *
+__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
+{
+ const char *ts = *tsp;
+ int i = 0, number;
+ int ndim = ctx->head->field->type->ndim;
+;
+ ++ts;
+ if (ctx->new_count != 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Cannot handle repeated arrays in format string");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ while (*ts && *ts != ')') {
+ switch (*ts) {
+ case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
+ default: break;
+ }
+ number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %d",
+ ctx->head->field->type->arraysize[i], number);
+ if (*ts != ',' && *ts != ')')
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a comma in format string, got '%c'", *ts);
+ if (*ts == ',') ts++;
+ i++;
+ }
+ if (i != ndim)
+ return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
+ ctx->head->field->type->ndim, i);
+ if (!*ts) {
+ PyErr_SetString(PyExc_ValueError,
+ "Unexpected end of format string, expected ')'");
+ return NULL;
+ }
+ ctx->is_valid_array = 1;
+ ctx->new_count = 1;
+ *tsp = ++ts;
+ return Py_None;
+}
+static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
+ int got_Z = 0;
+ while (1) {
+ switch(*ts) {
+ case 0:
+ if (ctx->enc_type != 0 && ctx->head == NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ if (ctx->head != NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ return ts;
+ case ' ':
+ case '\r':
+ case '\n':
+ ++ts;
+ break;
+ case '<':
+ if (!__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '>':
+ case '!':
+ if (__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '=':
+ case '@':
+ case '^':
+ ctx->new_packmode = *ts++;
+ break;
+ case 'T':
+ {
+ const char* ts_after_sub;
+ size_t i, struct_count = ctx->new_count;
+ size_t struct_alignment = ctx->struct_alignment;
+ ctx->new_count = 1;
+ ++ts;
+ if (*ts != '{') {
+ PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ ctx->enc_count = 0;
+ ctx->struct_alignment = 0;
+ ++ts;
+ ts_after_sub = ts;
+ for (i = 0; i != struct_count; ++i) {
+ ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
+ if (!ts_after_sub) return NULL;
+ }
+ ts = ts_after_sub;
+ if (struct_alignment) ctx->struct_alignment = struct_alignment;
+ }
+ break;
+ case '}':
+ {
+ size_t alignment = ctx->struct_alignment;
+ ++ts;
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ if (alignment && ctx->fmt_offset % alignment) {
+ ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
+ }
+ }
+ return ts;
+ case 'x':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->fmt_offset += ctx->new_count;
+ ctx->new_count = 1;
+ ctx->enc_count = 0;
+ ctx->enc_type = 0;
+ ctx->enc_packmode = ctx->new_packmode;
+ ++ts;
+ break;
+ case 'Z':
+ got_Z = 1;
+ ++ts;
+ if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
+ __Pyx_BufFmt_RaiseUnexpectedChar('Z');
+ return NULL;
+ }
+ case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
+ case 'l': case 'L': case 'q': case 'Q':
+ case 'f': case 'd': case 'g':
+ case 'O': case 'p':
+ if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
+ ctx->enc_packmode == ctx->new_packmode) {
+ ctx->enc_count += ctx->new_count;
+ ctx->new_count = 1;
+ got_Z = 0;
+ ++ts;
+ break;
+ }
+ case 's':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_count = ctx->new_count;
+ ctx->enc_packmode = ctx->new_packmode;
+ ctx->enc_type = *ts;
+ ctx->is_complex = got_Z;
+ ++ts;
+ ctx->new_count = 1;
+ got_Z = 0;
+ break;
+ case ':':
+ ++ts;
+ while(*ts != ':') ++ts;
+ ++ts;
+ break;
+ case '(':
+ if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
+ break;
+ default:
+ {
+ int number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ ctx->new_count = (size_t)number;
+ }
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
+ buf->buf = NULL;
+ buf->obj = NULL;
+ buf->strides = __Pyx_zeros;
+ buf->shape = __Pyx_zeros;
+ buf->suboffsets = __Pyx_minusones;
+}
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
+ Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
+ int nd, int cast, __Pyx_BufFmt_StackElem* stack)
+{
+ if (obj == Py_None || obj == NULL) {
+ __Pyx_ZeroBuffer(buf);
+ return 0;
+ }
+ buf->buf = NULL;
+ if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
+ if (buf->ndim != nd) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ nd, buf->ndim);
+ goto fail;
+ }
+ if (!cast) {
+ __Pyx_BufFmt_Context ctx;
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned)buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
+ buf->itemsize, (buf->itemsize > 1) ? "s" : "",
+ dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
+ return 0;
+fail:;
+ __Pyx_ZeroBuffer(buf);
+ return -1;
+}
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
+ if (info->buf == NULL) return;
+ if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
+ __Pyx_ReleaseBuffer(info);
+}
+
+static int
+__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference)
+{
+ __Pyx_RefNannyDeclarations
+ int i, retval=-1;
+ Py_buffer *buf = &memview->view;
+ __Pyx_RefNannySetupContext("init_memviewslice", 0);
+ if (!buf) {
+ PyErr_SetString(PyExc_ValueError,
+ "buf is NULL.");
+ goto fail;
+ } else if (memviewslice->memview || memviewslice->data) {
+ PyErr_SetString(PyExc_ValueError,
+ "memviewslice is already initialized!");
+ goto fail;
+ }
+ if (buf->strides) {
+ for (i = 0; i < ndim; i++) {
+ memviewslice->strides[i] = buf->strides[i];
+ }
+ } else {
+ Py_ssize_t stride = buf->itemsize;
+ for (i = ndim - 1; i >= 0; i--) {
+ memviewslice->strides[i] = stride;
+ stride *= buf->shape[i];
+ }
+ }
+ for (i = 0; i < ndim; i++) {
+ memviewslice->shape[i] = buf->shape[i];
+ if (buf->suboffsets) {
+ memviewslice->suboffsets[i] = buf->suboffsets[i];
+ } else {
+ memviewslice->suboffsets[i] = -1;
+ }
+ }
+ memviewslice->memview = memview;
+ memviewslice->data = (char *)buf->buf;
+ if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
+ Py_INCREF(memview);
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ memviewslice->memview = 0;
+ memviewslice->data = 0;
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
+ va_list vargs;
+ char msg[200];
+ va_start(vargs, fmt);
+#ifdef HAVE_STDARG_PROTOTYPES
+ va_start(vargs, fmt);
+#else
+ va_start(vargs);
+#endif
+ vsnprintf(msg, 200, fmt, vargs);
+ Py_FatalError(msg);
+ va_end(vargs);
+}
+static CYTHON_INLINE int
+__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)++;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE int
+__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)--;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE void
+__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
+{
+ int first_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview || (PyObject *) memview == Py_None)
+ return;
+ if (__pyx_get_slice_count(memview) < 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ first_time = __pyx_add_acquisition_count(memview) == 0;
+ if (first_time) {
+ if (have_gil) {
+ Py_INCREF((PyObject *) memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_INCREF((PyObject *) memview);
+ PyGILState_Release(_gilstate);
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
+ int have_gil, int lineno) {
+ int last_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview ) {
+ return;
+ } else if ((PyObject *) memview == Py_None) {
+ memslice->memview = NULL;
+ return;
+ }
+ if (__pyx_get_slice_count(memview) <= 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ last_time = __pyx_sub_acquisition_count(memview) == 1;
+ memslice->data = NULL;
+ if (last_time) {
+ if (have_gil) {
+ Py_CLEAR(memslice->memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_CLEAR(memslice->memview);
+ PyGILState_Release(_gilstate);
+ }
+ } else {
+ memslice->memview = NULL;
+ }
+}
+
+static void __Pyx_RaiseDoubleKeywordsError(
+ const char* func_name,
+ PyObject* kw_name)
+{
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION >= 3
+ "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
+ #else
+ "%s() got multiple values for keyword argument '%s'", func_name,
+ PyString_AsString(kw_name));
+ #endif
+}
+
+static int __Pyx_ParseOptionalKeywords(
+ PyObject *kwds,
+ PyObject **argnames[],
+ PyObject *kwds2,
+ PyObject *values[],
+ Py_ssize_t num_pos_args,
+ const char* function_name)
+{
+ PyObject *key = 0, *value = 0;
+ Py_ssize_t pos = 0;
+ PyObject*** name;
+ PyObject*** first_kw_arg = argnames + num_pos_args;
+ while (PyDict_Next(kwds, &pos, &key, &value)) {
+ name = first_kw_arg;
+ while (*name && (**name != key)) name++;
+ if (*name) {
+ values[name-argnames] = value;
+ continue;
+ }
+ name = first_kw_arg;
+ #if PY_MAJOR_VERSION < 3
+ if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
+ while (*name) {
+ if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
+ && _PyString_Eq(**name, key)) {
+ values[name-argnames] = value;
+ break;
+ }
+ name++;
+ }
+ if (*name) continue;
+ else {
+ PyObject*** argname = argnames;
+ while (argname != first_kw_arg) {
+ if ((**argname == key) || (
+ (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
+ && _PyString_Eq(**argname, key))) {
+ goto arg_passed_twice;
+ }
+ argname++;
+ }
+ }
+ } else
+ #endif
+ if (likely(PyUnicode_Check(key))) {
+ while (*name) {
+ int cmp = (**name == key) ? 0 :
+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
+ #endif
+ PyUnicode_Compare(**name, key);
+ if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+ if (cmp == 0) {
+ values[name-argnames] = value;
+ break;
+ }
+ name++;
+ }
+ if (*name) continue;
+ else {
+ PyObject*** argname = argnames;
+ while (argname != first_kw_arg) {
+ int cmp = (**argname == key) ? 0 :
+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
+ #endif
+ PyUnicode_Compare(**argname, key);
+ if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+ if (cmp == 0) goto arg_passed_twice;
+ argname++;
+ }
+ }
+ } else
+ goto invalid_keyword_type;
+ if (kwds2) {
+ if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
+ } else {
+ goto invalid_keyword;
+ }
+ }
+ return 0;
+arg_passed_twice:
+ __Pyx_RaiseDoubleKeywordsError(function_name, key);
+ goto bad;
+invalid_keyword_type:
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() keywords must be strings", function_name);
+ goto bad;
+invalid_keyword:
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION < 3
+ "%.200s() got an unexpected keyword argument '%.200s'",
+ function_name, PyString_AsString(key));
+ #else
+ "%s() got an unexpected keyword argument '%U'",
+ function_name, key);
+ #endif
+bad:
+ return -1;
+}
+
+static void __Pyx_RaiseArgtupleInvalid(
+ const char* func_name,
+ int exact,
+ Py_ssize_t num_min,
+ Py_ssize_t num_max,
+ Py_ssize_t num_found)
+{
+ Py_ssize_t num_expected;
+ const char *more_or_less;
+ if (num_found < num_min) {
+ num_expected = num_min;
+ more_or_less = "at least";
+ } else {
+ num_expected = num_max;
+ more_or_less = "at most";
+ }
+ if (exact) {
+ more_or_less = "exactly";
+ }
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
+ func_name, more_or_less, num_expected,
+ (num_expected == 1) ? "" : "s", num_found);
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
+ PyObject *r;
+ if (!j) return NULL;
+ r = PyObject_GetItem(o, j);
+ Py_DECREF(j);
+ return r;
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
+ PyObject *r = PyList_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (is_list || PyList_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
+ if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
+ PyObject *r = PyList_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ }
+ else if (PyTuple_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ } else {
+ PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
+ if (likely(m && m->sq_item)) {
+ if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
+ Py_ssize_t l = m->sq_length(o);
+ if (likely(l >= 0)) {
+ i += l;
+ } else {
+ if (PyErr_ExceptionMatches(PyExc_OverflowError))
+ PyErr_Clear();
+ else
+ return NULL;
+ }
+ }
+ return m->sq_item(o, i);
+ }
+ }
+#else
+ if (is_list || PySequence_Check(o)) {
+ return PySequence_GetItem(o, i);
+ }
+#endif
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+}
+
+static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
+ PyErr_Format(PyExc_TypeError,
+ "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
+ name, type->tp_name, Py_TYPE(obj)->tp_name);
+}
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact)
+{
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (none_allowed && obj == Py_None) return 1;
+ else if (exact) {
+ if (likely(Py_TYPE(obj) == type)) return 1;
+ #if PY_MAJOR_VERSION == 2
+ else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
+ #endif
+ }
+ else {
+ if (likely(PyObject_TypeCheck(obj, type))) return 1;
+ }
+ __Pyx_RaiseArgumentTypeInvalid(name, obj, type);
+ return 0;
+}
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+ if (s1 == s2) {
+ return (equals == Py_EQ);
+ } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
+ const char *ps1, *ps2;
+ Py_ssize_t length = PyBytes_GET_SIZE(s1);
+ if (length != PyBytes_GET_SIZE(s2))
+ return (equals == Py_NE);
+ ps1 = PyBytes_AS_STRING(s1);
+ ps2 = PyBytes_AS_STRING(s2);
+ if (ps1[0] != ps2[0]) {
+ return (equals == Py_NE);
+ } else if (length == 1) {
+ return (equals == Py_EQ);
+ } else {
+ int result = memcmp(ps1, ps2, (size_t)length);
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
+ return (equals == Py_NE);
+ } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
+ return (equals == Py_NE);
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+#endif
+}
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+#if PY_MAJOR_VERSION < 3
+ PyObject* owned_ref = NULL;
+#endif
+ int s1_is_unicode, s2_is_unicode;
+ if (s1 == s2) {
+ goto return_eq;
+ }
+ s1_is_unicode = PyUnicode_CheckExact(s1);
+ s2_is_unicode = PyUnicode_CheckExact(s2);
+#if PY_MAJOR_VERSION < 3
+ if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
+ owned_ref = PyUnicode_FromObject(s2);
+ if (unlikely(!owned_ref))
+ return -1;
+ s2 = owned_ref;
+ s2_is_unicode = 1;
+ } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
+ owned_ref = PyUnicode_FromObject(s1);
+ if (unlikely(!owned_ref))
+ return -1;
+ s1 = owned_ref;
+ s1_is_unicode = 1;
+ } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
+ return __Pyx_PyBytes_Equals(s1, s2, equals);
+ }
+#endif
+ if (s1_is_unicode & s2_is_unicode) {
+ Py_ssize_t length;
+ int kind;
+ void *data1, *data2;
+ if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
+ return -1;
+ length = __Pyx_PyUnicode_GET_LENGTH(s1);
+ if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
+ goto return_ne;
+ }
+ kind = __Pyx_PyUnicode_KIND(s1);
+ if (kind != __Pyx_PyUnicode_KIND(s2)) {
+ goto return_ne;
+ }
+ data1 = __Pyx_PyUnicode_DATA(s1);
+ data2 = __Pyx_PyUnicode_DATA(s2);
+ if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
+ goto return_ne;
+ } else if (length == 1) {
+ goto return_eq;
+ } else {
+ int result = memcmp(data1, data2, (size_t)(length * kind));
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & s2_is_unicode) {
+ goto return_ne;
+ } else if ((s2 == Py_None) & s1_is_unicode) {
+ goto return_ne;
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+return_eq:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ);
+return_ne:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_NE);
+#endif
+}
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
+ Py_ssize_t q = a / b;
+ Py_ssize_t r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
+#if CYTHON_COMPILING_IN_CPYTHON
+#if PY_MAJOR_VERSION >= 3
+ if (likely(PyUnicode_Check(n)))
+#else
+ if (likely(PyString_Check(n)))
+#endif
+ return __Pyx_PyObject_GetAttrStr(o, n);
+#endif
+ return PyObject_GetAttr(o, n);
+}
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
+ Py_ssize_t length;
+ if (unlikely((start < 0) | (stop < 0))) {
+ length = strlen(cstring);
+ if (start < 0) {
+ start += length;
+ if (start < 0)
+ start = 0;
+ }
+ if (stop < 0)
+ stop += length;
+ }
+ length = stop - start;
+ if (unlikely(length <= 0))
+ return PyUnicode_FromUnicode(NULL, 0);
+ cstring += start;
+ if (decode_func) {
+ return decode_func(cstring, length, errors);
+ } else {
+ return PyUnicode_Decode(cstring, length, encoding, errors);
+ }
+}
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
+ PyErr_Format(PyExc_ValueError,
+ "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
+ PyErr_Format(PyExc_ValueError,
+ "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
+ index, (index == 1) ? "" : "s");
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
+ PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
+}
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (likely(PyObject_TypeCheck(obj, type)))
+ return 1;
+ PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
+ Py_TYPE(obj)->tp_name, type->tp_name);
+ return 0;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->exc_type;
+ *value = tstate->exc_value;
+ *tb = tstate->exc_traceback;
+ Py_XINCREF(*type);
+ Py_XINCREF(*value);
+ Py_XINCREF(*tb);
+#else
+ PyErr_GetExcInfo(type, value, tb);
+#endif
+}
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = type;
+ tstate->exc_value = value;
+ tstate->exc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(type, value, tb);
+#endif
+}
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *local_type, *local_value, *local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ local_type = tstate->curexc_type;
+ local_value = tstate->curexc_value;
+ local_tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(&local_type, &local_value, &local_tb);
+#endif
+ PyErr_NormalizeException(&local_type, &local_value, &local_tb);
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (unlikely(tstate->curexc_type))
+#else
+ if (unlikely(PyErr_Occurred()))
+#endif
+ goto bad;
+ #if PY_MAJOR_VERSION >= 3
+ if (local_tb) {
+ if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
+ goto bad;
+ }
+ #endif
+ Py_XINCREF(local_tb);
+ Py_XINCREF(local_type);
+ Py_XINCREF(local_value);
+ *type = local_type;
+ *value = local_value;
+ *tb = local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = local_type;
+ tstate->exc_value = local_value;
+ tstate->exc_traceback = local_tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(local_type, local_value, local_tb);
+#endif
+ return 0;
+bad:
+ *type = 0;
+ *value = 0;
+ *tb = 0;
+ Py_XDECREF(local_type);
+ Py_XDECREF(local_value);
+ Py_XDECREF(local_tb);
+ return -1;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = *type;
+ tstate->exc_value = *value;
+ tstate->exc_traceback = *tb;
+#else
+ PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
+ PyErr_SetExcInfo(*type, *value, *tb);
+#endif
+ *type = tmp_type;
+ *value = tmp_value;
+ *tb = tmp_tb;
+}
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
+ PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
+}
+
+static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
+ long q = a / b;
+ long r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
+ CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
+ int full_traceback) {
+ PyObject *old_exc, *old_val, *old_tb;
+ PyObject *ctx;
+ __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
+ if (full_traceback) {
+ Py_XINCREF(old_exc);
+ Py_XINCREF(old_val);
+ Py_XINCREF(old_tb);
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ PyErr_PrintEx(1);
+ }
+ #if PY_MAJOR_VERSION < 3
+ ctx = PyString_FromString(name);
+ #else
+ ctx = PyUnicode_FromString(name);
+ #endif
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ if (!ctx) {
+ PyErr_WriteUnraisable(Py_None);
+ } else {
+ PyErr_WriteUnraisable(ctx);
+ Py_DECREF(ctx);
+ }
+}
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
+#if PY_VERSION_HEX >= 0x02070000
+ PyObject *ob = PyCapsule_New(vtable, 0, 0);
+#else
+ PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
+#endif
+ if (!ob)
+ goto bad;
+ if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
+ goto bad;
+ Py_DECREF(ob);
+ return 0;
+bad:
+ Py_XDECREF(ob);
+ return -1;
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
+#ifdef __Pyx_CyFunction_USED
+ if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
+#else
+ if (likely(PyCFunction_Check(func))) {
+#endif
+ if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
+ return __Pyx_PyObject_CallMethO(func, NULL);
+ }
+ }
+ return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
+}
+#endif
+
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
+ int start = 0, mid = 0, end = count - 1;
+ if (end >= 0 && code_line > entries[end].code_line) {
+ return count;
+ }
+ while (start < end) {
+ mid = (start + end) / 2;
+ if (code_line < entries[mid].code_line) {
+ end = mid;
+ } else if (code_line > entries[mid].code_line) {
+ start = mid + 1;
+ } else {
+ return mid;
+ }
+ }
+ if (code_line <= entries[mid].code_line) {
+ return mid;
+ } else {
+ return mid + 1;
+ }
+}
+static PyCodeObject *__pyx_find_code_object(int code_line) {
+ PyCodeObject* code_object;
+ int pos;
+ if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
+ return NULL;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
+ return NULL;
+ }
+ code_object = __pyx_code_cache.entries[pos].code_object;
+ Py_INCREF(code_object);
+ return code_object;
+}
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
+ int pos, i;
+ __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
+ if (unlikely(!code_line)) {
+ return;
+ }
+ if (unlikely(!entries)) {
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (likely(entries)) {
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = 64;
+ __pyx_code_cache.count = 1;
+ entries[0].code_line = code_line;
+ entries[0].code_object = code_object;
+ Py_INCREF(code_object);
+ }
+ return;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
+ PyCodeObject* tmp = entries[pos].code_object;
+ entries[pos].code_object = code_object;
+ Py_DECREF(tmp);
+ return;
+ }
+ if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
+ int new_max = __pyx_code_cache.max_count + 64;
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
+ __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (unlikely(!entries)) {
+ return;
+ }
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = new_max;
+ }
+ for (i=__pyx_code_cache.count; i>pos; i--) {
+ entries[i] = entries[i-1];
+ }
+ entries[pos].code_line = code_line;
+ entries[pos].code_object = code_object;
+ __pyx_code_cache.count++;
+ Py_INCREF(code_object);
+}
+
+#include "compile.h"
+#include "frameobject.h"
+#include "traceback.h"
+static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
+ const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyObject *py_srcfile = 0;
+ PyObject *py_funcname = 0;
+ #if PY_MAJOR_VERSION < 3
+ py_srcfile = PyString_FromString(filename);
+ #else
+ py_srcfile = PyUnicode_FromString(filename);
+ #endif
+ if (!py_srcfile) goto bad;
+ if (c_line) {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #else
+ py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #endif
+ }
+ else {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromString(funcname);
+ #else
+ py_funcname = PyUnicode_FromString(funcname);
+ #endif
+ }
+ if (!py_funcname) goto bad;
+ py_code = __Pyx_PyCode_New(
+ 0,
+ 0,
+ 0,
+ 0,
+ 0,
+ __pyx_empty_bytes, /*PyObject *code,*/
+ __pyx_empty_tuple, /*PyObject *consts,*/
+ __pyx_empty_tuple, /*PyObject *names,*/
+ __pyx_empty_tuple, /*PyObject *varnames,*/
+ __pyx_empty_tuple, /*PyObject *freevars,*/
+ __pyx_empty_tuple, /*PyObject *cellvars,*/
+ py_srcfile, /*PyObject *filename,*/
+ py_funcname, /*PyObject *name,*/
+ py_line,
+ __pyx_empty_bytes /*PyObject *lnotab*/
+ );
+ Py_DECREF(py_srcfile);
+ Py_DECREF(py_funcname);
+ return py_code;
+bad:
+ Py_XDECREF(py_srcfile);
+ Py_XDECREF(py_funcname);
+ return NULL;
+}
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyFrameObject *py_frame = 0;
+ py_code = __pyx_find_code_object(c_line ? c_line : py_line);
+ if (!py_code) {
+ py_code = __Pyx_CreateCodeObjectForTraceback(
+ funcname, c_line, py_line, filename);
+ if (!py_code) goto bad;
+ __pyx_insert_code_object(c_line ? c_line : py_line, py_code);
+ }
+ py_frame = PyFrame_New(
+ PyThreadState_GET(), /*PyThreadState *tstate,*/
+ py_code, /*PyCodeObject *code,*/
+ __pyx_d, /*PyObject *globals,*/
+ 0 /*PyObject *locals*/
+ );
+ if (!py_frame) goto bad;
+ py_frame->f_lineno = py_line;
+ PyTraceBack_Here(py_frame);
+bad:
+ Py_XDECREF(py_code);
+ Py_XDECREF(py_frame);
+}
+
+#if PY_MAJOR_VERSION < 3
+static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
+ if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
+ PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
+ return -1;
+}
+static void __Pyx_ReleaseBuffer(Py_buffer *view) {
+ PyObject *obj = view->obj;
+ if (!obj) return;
+ if (PyObject_CheckBuffer(obj)) {
+ PyBuffer_Release(view);
+ return;
+ }
+ Py_DECREF(obj);
+ view->obj = NULL;
+}
+#endif
+
+
+ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
+ PyObject *empty_list = 0;
+ PyObject *module = 0;
+ PyObject *global_dict = 0;
+ PyObject *empty_dict = 0;
+ PyObject *list;
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_import;
+ py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
+ if (!py_import)
+ goto bad;
+ #endif
+ if (from_list)
+ list = from_list;
+ else {
+ empty_list = PyList_New(0);
+ if (!empty_list)
+ goto bad;
+ list = empty_list;
+ }
+ global_dict = PyModule_GetDict(__pyx_m);
+ if (!global_dict)
+ goto bad;
+ empty_dict = PyDict_New();
+ if (!empty_dict)
+ goto bad;
+ {
+ #if PY_MAJOR_VERSION >= 3
+ if (level == -1) {
+ if (strchr(__Pyx_MODULE_NAME, '.')) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(1);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, 1);
+ #endif
+ if (!module) {
+ if (!PyErr_ExceptionMatches(PyExc_ImportError))
+ goto bad;
+ PyErr_Clear();
+ }
+ }
+ level = 0;
+ }
+ #endif
+ if (!module) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(level);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, level);
+ #endif
+ }
+ }
+bad:
+ #if PY_VERSION_HEX < 0x03030000
+ Py_XDECREF(py_import);
+ #endif
+ Py_XDECREF(empty_list);
+ Py_XDECREF(empty_dict);
+ return module;
+}
+
+static PyObject *__pyx_memview_get_double(const char *itemp) {
+ return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
+}
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
+ double value = __pyx_PyFloat_AsDouble(obj);
+ if ((value == (double)-1) && PyErr_Occurred())
+ return 0;
+ *(double *) itemp = value;
+ return 1;
+}
+
+#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \
+ { \
+ func_type value = func_value; \
+ if (sizeof(target_type) < sizeof(func_type)) { \
+ if (unlikely(value != (func_type) (target_type) value)) { \
+ func_type zero = 0; \
+ if (is_unsigned && unlikely(value < zero)) \
+ goto raise_neg_overflow; \
+ else \
+ goto raise_overflow; \
+ } \
+ } \
+ return (target_type) value; \
+ }
+
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ #include "longintrepr.h"
+ #endif
+#endif
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(int) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (int) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(int) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(int) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x))
+ } else if (sizeof(int) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ int val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (int) -1;
+ }
+ } else {
+ int val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (int) -1;
+ val = __Pyx_PyInt_As_int(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to int");
+ return (int) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to int");
+ return (int) -1;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(long) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(long) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(long),
+ little, !is_unsigned);
+ }
+}
+
+static int
+__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim)
+{
+ int i, index, step, start;
+ Py_ssize_t itemsize = mvs->memview->view.itemsize;
+ if (order == 'F') {
+ step = 1;
+ start = 0;
+ } else {
+ step = -1;
+ start = ndim - 1;
+ }
+ for (i = 0; i < ndim; i++) {
+ index = start + step * i;
+ if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize)
+ return 0;
+ itemsize *= mvs->shape[index];
+ }
+ return 1;
+}
+
+static void
+__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
+ void **out_start, void **out_end,
+ int ndim, size_t itemsize)
+{
+ char *start, *end;
+ int i;
+ start = end = slice->data;
+ for (i = 0; i < ndim; i++) {
+ Py_ssize_t stride = slice->strides[i];
+ Py_ssize_t extent = slice->shape[i];
+ if (extent == 0) {
+ *out_start = *out_end = start;
+ return;
+ } else {
+ if (stride > 0)
+ end += stride * (extent - 1);
+ else
+ start += stride * (extent - 1);
+ }
+ }
+ *out_start = start;
+ *out_end = end + itemsize;
+}
+static int
+__pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize)
+{
+ void *start1, *end1, *start2, *end2;
+ __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
+ __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
+ return (start1 < end2) && (start2 < end1);
+}
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object)
+{
+ __Pyx_RefNannyDeclarations
+ int i;
+ __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
+ struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
+ Py_buffer *buf = &from_memview->view;
+ PyObject *shape_tuple = NULL;
+ PyObject *temp_int = NULL;
+ struct __pyx_array_obj *array_obj = NULL;
+ struct __pyx_memoryview_obj *memview_obj = NULL;
+ __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
+ for (i = 0; i < ndim; i++) {
+ if (from_mvs->suboffsets[i] >= 0) {
+ PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
+ "indirect dimensions (axis %d)", i);
+ goto fail;
+ }
+ }
+ shape_tuple = PyTuple_New(ndim);
+ if (unlikely(!shape_tuple)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(shape_tuple);
+ for(i = 0; i < ndim; i++) {
+ temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
+ if(unlikely(!temp_int)) {
+ goto fail;
+ } else {
+ PyTuple_SET_ITEM(shape_tuple, i, temp_int);
+ temp_int = NULL;
+ }
+ }
+ array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
+ if (unlikely(!array_obj)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(array_obj);
+ memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ (PyObject *) array_obj, contig_flag,
+ dtype_is_object,
+ from_mvs->memview->typeinfo);
+ if (unlikely(!memview_obj))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
+ goto fail;
+ if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
+ dtype_is_object) < 0))
+ goto fail;
+ goto no_fail;
+fail:
+ __Pyx_XDECREF(new_mvs.memview);
+ new_mvs.memview = NULL;
+ new_mvs.data = NULL;
+no_fail:
+ __Pyx_XDECREF(shape_tuple);
+ __Pyx_XDECREF(temp_int);
+ __Pyx_XDECREF(array_obj);
+ __Pyx_RefNannyFinishContext();
+ return new_mvs;
+}
+
+static CYTHON_INLINE PyObject *
+__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
+{
+ PyObject *cobj;
+#if PY_VERSION_HEX >= 0x02070000
+ cobj = PyCapsule_New(p, sig, NULL);
+#else
+ cobj = PyCObject_FromVoidPtr(p, NULL);
+#endif
+ return cobj;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(int) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(int) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(int),
+ little, !is_unsigned);
+ }
+}
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
+ const char neg_one = (char) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(char) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (char) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(char) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(char) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(char) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x))
+ } else if (sizeof(char) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ char val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (char) -1;
+ }
+ } else {
+ char val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (char) -1;
+ val = __Pyx_PyInt_As_char(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to char");
+ return (char) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to char");
+ return (char) -1;
+}
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(long) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (long) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(long) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(long) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x))
+ } else if (sizeof(long) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ long val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (long) -1;
+ }
+ } else {
+ long val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (long) -1;
+ val = __Pyx_PyInt_As_long(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to long");
+ return (long) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to long");
+ return (long) -1;
+}
+
+static int
+__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
+{
+ int i;
+ if (!a || !b)
+ return 0;
+ if (a == b)
+ return 1;
+ if (a->size != b->size || a->typegroup != b->typegroup ||
+ a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
+ if (a->typegroup == 'H' || b->typegroup == 'H') {
+ return a->size == b->size;
+ } else {
+ return 0;
+ }
+ }
+ if (a->ndim) {
+ for (i = 0; i < a->ndim; i++)
+ if (a->arraysize[i] != b->arraysize[i])
+ return 0;
+ }
+ if (a->typegroup == 'S') {
+ if (a->flags != b->flags)
+ return 0;
+ if (a->fields || b->fields) {
+ if (!(a->fields && b->fields))
+ return 0;
+ for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
+ __Pyx_StructField *field_a = a->fields + i;
+ __Pyx_StructField *field_b = b->fields + i;
+ if (field_a->offset != field_b->offset ||
+ !__pyx_typeinfo_cmp(field_a->type, field_b->type))
+ return 0;
+ }
+ return !a->fields[i].type && !b->fields[i].type;
+ }
+ }
+ return 1;
+}
+
+static int
+__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
+{
+ if (buf->shape[dim] <= 1)
+ return 1;
+ if (buf->strides) {
+ if (spec & __Pyx_MEMVIEW_CONTIG) {
+ if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
+ if (buf->strides[dim] != sizeof(void *)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly contiguous "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ } else if (buf->strides[dim] != buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_FOLLOW) {
+ Py_ssize_t stride = buf->strides[dim];
+ if (stride < 0)
+ stride = -stride;
+ if (stride < buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ } else {
+ if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not contiguous in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (spec & (__Pyx_MEMVIEW_PTR)) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not indirect in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (buf->suboffsets) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer exposes suboffsets but no strides");
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
+{
+ if (spec & __Pyx_MEMVIEW_DIRECT) {
+ if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer not compatible with direct access "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_PTR) {
+ if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly accessible "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
+{
+ int i;
+ if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = 0; i < ndim; i++) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1)
+ {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not fortran contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = ndim - 1; i >- 1; i--) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not C contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj)
+{
+ struct __pyx_memoryview_obj *memview, *new_memview;
+ __Pyx_RefNannyDeclarations
+ Py_buffer *buf;
+ int i, spec = 0, retval = -1;
+ __Pyx_BufFmt_Context ctx;
+ int from_memoryview = __pyx_memoryview_check(original_obj);
+ __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
+ if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
+ original_obj)->typeinfo)) {
+ memview = (struct __pyx_memoryview_obj *) original_obj;
+ new_memview = NULL;
+ } else {
+ memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ original_obj, buf_flags, 0, dtype);
+ new_memview = memview;
+ if (unlikely(!memview))
+ goto fail;
+ }
+ buf = &memview->view;
+ if (buf->ndim != ndim) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ ndim, buf->ndim);
+ goto fail;
+ }
+ if (new_memview) {
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned) buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
+ "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
+ buf->itemsize,
+ (buf->itemsize > 1) ? "s" : "",
+ dtype->name,
+ dtype->size,
+ (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ for (i = 0; i < ndim; i++) {
+ spec = axes_specs[i];
+ if (!__pyx_check_strides(buf, i, ndim, spec))
+ goto fail;
+ if (!__pyx_check_suboffsets(buf, i, ndim, spec))
+ goto fail;
+ }
+ if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
+ new_memview != NULL) == -1)) {
+ goto fail;
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ Py_XDECREF(new_memview);
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *obj) {
+ __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+ __Pyx_BufFmt_StackElem stack[1];
+ int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+ int retcode;
+ if (obj == Py_None) {
+ result.memview = (struct __pyx_memoryview_obj *) Py_None;
+ return result;
+ }
+ retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+ (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
+ &__Pyx_TypeInfo_double, stack,
+ &result, obj);
+ if (unlikely(retcode == -1))
+ goto __pyx_fail;
+ return result;
+__pyx_fail:
+ result.memview = NULL;
+ result.data = NULL;
+ return result;
+}
+
+static int __Pyx_check_binary_version(void) {
+ char ctversion[4], rtversion[4];
+ PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
+ PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
+ if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
+ char message[200];
+ PyOS_snprintf(message, sizeof(message),
+ "compiletime version %s of module '%.100s' "
+ "does not match runtime version %s",
+ ctversion, __Pyx_MODULE_NAME, rtversion);
+ return PyErr_WarnEx(NULL, message, 1);
+ }
+ return 0;
+}
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
+ while (t->p) {
+ #if PY_MAJOR_VERSION < 3
+ if (t->is_unicode) {
+ *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
+ } else if (t->intern) {
+ *t->p = PyString_InternFromString(t->s);
+ } else {
+ *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
+ }
+ #else
+ if (t->is_unicode | t->is_str) {
+ if (t->intern) {
+ *t->p = PyUnicode_InternFromString(t->s);
+ } else if (t->encoding) {
+ *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
+ } else {
+ *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
+ }
+ } else {
+ *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
+ }
+ #endif
+ if (!*t->p)
+ return -1;
+ ++t;
+ }
+ return 0;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
+ return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
+ Py_ssize_t ignore;
+ return __Pyx_PyObject_AsStringAndSize(o, &ignore);
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+ if (
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ __Pyx_sys_getdefaultencoding_not_ascii &&
+#endif
+ PyUnicode_Check(o)) {
+#if PY_VERSION_HEX < 0x03030000
+ char* defenc_c;
+ PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
+ if (!defenc) return NULL;
+ defenc_c = PyBytes_AS_STRING(defenc);
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ {
+ char* end = defenc_c + PyBytes_GET_SIZE(defenc);
+ char* c;
+ for (c = defenc_c; c < end; c++) {
+ if ((unsigned char) (*c) >= 128) {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+ }
+ }
+#endif
+ *length = PyBytes_GET_SIZE(defenc);
+ return defenc_c;
+#else
+ if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ if (PyUnicode_IS_ASCII(o)) {
+ *length = PyUnicode_GET_LENGTH(o);
+ return PyUnicode_AsUTF8(o);
+ } else {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+#else
+ return PyUnicode_AsUTF8AndSize(o, length);
+#endif
+#endif
+ } else
+#endif
+#if !CYTHON_COMPILING_IN_PYPY
+ if (PyByteArray_Check(o)) {
+ *length = PyByteArray_GET_SIZE(o);
+ return PyByteArray_AS_STRING(o);
+ } else
+#endif
+ {
+ char* result;
+ int r = PyBytes_AsStringAndSize(o, &result, length);
+ if (unlikely(r < 0)) {
+ return NULL;
+ } else {
+ return result;
+ }
+ }
+}
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
+ int is_true = x == Py_True;
+ if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
+ else return PyObject_IsTrue(x);
+}
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
+ PyNumberMethods *m;
+ const char *name = NULL;
+ PyObject *res = NULL;
+#if PY_MAJOR_VERSION < 3
+ if (PyInt_Check(x) || PyLong_Check(x))
+#else
+ if (PyLong_Check(x))
+#endif
+ return Py_INCREF(x), x;
+ m = Py_TYPE(x)->tp_as_number;
+#if PY_MAJOR_VERSION < 3
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Int(x);
+ }
+ else if (m && m->nb_long) {
+ name = "long";
+ res = PyNumber_Long(x);
+ }
+#else
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Long(x);
+ }
+#endif
+ if (res) {
+#if PY_MAJOR_VERSION < 3
+ if (!PyInt_Check(res) && !PyLong_Check(res)) {
+#else
+ if (!PyLong_Check(res)) {
+#endif
+ PyErr_Format(PyExc_TypeError,
+ "__%.4s__ returned non-%.4s (type %.200s)",
+ name, name, Py_TYPE(res)->tp_name);
+ Py_DECREF(res);
+ return NULL;
+ }
+ }
+ else if (!PyErr_Occurred()) {
+ PyErr_SetString(PyExc_TypeError,
+ "an integer is required");
+ }
+ return res;
+}
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
+ Py_ssize_t ival;
+ PyObject *x;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_CheckExact(b)))
+ return PyInt_AS_LONG(b);
+#endif
+ if (likely(PyLong_CheckExact(b))) {
+ #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(b)) {
+ case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0];
+ case 0: return 0;
+ case 1: return ((PyLongObject*)b)->ob_digit[0];
+ }
+ #endif
+ #endif
+ return PyLong_AsSsize_t(b);
+ }
+ x = PyNumber_Index(b);
+ if (!x) return -1;
+ ival = PyInt_AsSsize_t(x);
+ Py_DECREF(x);
+ return ival;
+}
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
+ return PyInt_FromSize_t(ival);
+}
+
+
+#endif /* Py_PYTHON_H */
diff --git a/silx/math/fit/functions/functions.pyx b/silx/math/fit/functions/functions.pyx
new file mode 100644
index 0000000..196b682
--- /dev/null
+++ b/silx/math/fit/functions/functions.pyx
@@ -0,0 +1,986 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+"""This module provides fit functions.
+
+List of fit functions:
+-----------------------
+
+ - :func:`sum_gauss`
+ - :func:`sum_agauss`
+ - :func:`sum_splitgauss`
+ - :func:`sum_fastagauss`
+
+ - :func:`sum_apvoigt`
+ - :func:`sum_pvoigt`
+ - :func:`sum_splitpvoigt`
+
+ - :func:`sum_lorentz`
+ - :func:`sum_alorentz`
+ - :func:`sum_splitlorentz`
+
+ - :func:`sum_stepdown`
+ - :func:`sum_stepup`
+ - :func:`sum_slit`
+
+ - :func:`sum_ahypermet`
+ - :func:`sum_fastahypermet`
+
+Full documentation:
+-------------------
+
+"""
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "17/06/2016"
+
+import logging
+import numpy
+
+logging.basicConfig()
+_logger = logging.getLogger(__name__)
+
+cimport cython
+cimport functions_wrapper
+
+
+def erf(x):
+ """Return the gaussian error function
+
+ :param x: Independant variable where the gaussian error function is
+ calculated
+ :type x: numpy.ndarray or scalar
+ :return: Gaussian error function ``y=erf(x)``
+ :raise: IndexError if ``x`` is an empty array
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] y_c
+
+
+ # force list into numpy array
+ if not hasattr(x, "shape"):
+ x = numpy.asarray(x)
+
+ for len_dim in x.shape:
+ if len_dim == 0:
+ raise IndexError("Cannot compute erf for an empty array")
+
+ x_c = numpy.array(x, copy=False, dtype=numpy.float64, order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x_c.size,), dtype=numpy.float64)
+
+ status = functions_wrapper.erf_array(&x_c[0], x_c.size, &y_c[0])
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def erfc(x):
+ """Return the gaussian complementary error function
+
+ :param x: Independant variable where the gaussian complementary error
+ function is calculated
+ :type x: numpy.ndarray or scalar
+ :return: Gaussian complementary error function ``y=erfc(x)``
+ :type rtype: numpy.ndarray
+ :raise: IndexError if ``x`` is an empty array
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] y_c
+
+ # force list into numpy array
+ if not hasattr(x, "shape"):
+ x = numpy.asarray(x)
+
+ for len_dim in x.shape:
+ if len_dim == 0:
+ raise IndexError("Cannot compute erfc for an empty array")
+
+ x_c = numpy.array(x, copy=False, dtype=numpy.float64, order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x_c.size,), dtype=numpy.float64)
+
+ status = functions_wrapper.erfc_array(&x_c[0], x_c.size, &y_c[0])
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_gauss(x, *params):
+ """Return a sum of gaussian functions defined by *(height, centroid, fwhm)*,
+ where:
+
+ - *height* is the peak amplitude
+ - *centroid* is the peak x-coordinate
+ - *fwhm* is the full-width at half maximum
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of gaussian parameters (length must be a multiple
+ of 3):
+ *(height1, centroid1, fwhm1, height2, centroid2, fwhm2,...)*
+ :return: Array of sum of gaussian functions at each ``x`` coordinate.
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No gaussian parameters specified. " +
+ "At least 3 parameters are required.")
+
+ # ensure float64 (double) type and 1D contiguous data layout in memory
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_gauss(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ # reshape y_c to match original, possibly unusual, data shape
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_agauss(x, *params):
+ """Return a sum of gaussian functions defined by *(area, centroid, fwhm)*,
+ where:
+
+ - *area* is the area underneath the peak
+ - *centroid* is the peak x-coordinate
+ - *fwhm* is the full-width at half maximum
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of gaussian parameters (length must be a multiple
+ of 3):
+ *(area1, centroid1, fwhm1, area2, centroid2, fwhm2,...)*
+ :return: Array of sum of gaussian functions at each ``x`` coordinate.
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No gaussian parameters specified. " +
+ "At least 3 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_agauss(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_fastagauss(x, *params):
+ """Return a sum of gaussian functions defined by *(area, centroid, fwhm)*,
+ where:
+
+ - *area* is the area underneath the peak
+ - *centroid* is the peak x-coordinate
+ - *fwhm* is the full-width at half maximum
+
+ This implementation differs from :func:`sum_agauss` by the usage of a
+ lookup table with precalculated exponential values. This might speed up
+ the computation for large numbers of individual gaussian functions.
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of gaussian parameters (length must be a multiple
+ of 3):
+ *(area1, centroid1, fwhm1, area2, centroid2, fwhm2,...)*
+ :return: Array of sum of gaussian functions at each ``x`` coordinate.
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No gaussian parameters specified. " +
+ "At least 3 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_fastagauss(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_splitgauss(x, *params):
+ """Return a sum of gaussian functions defined by *(area, centroid, fwhm1, fwhm2)*,
+ where:
+
+ - *height* is the peak amplitude
+ - *centroid* is the peak x-coordinate
+ - *fwhm1* is the full-width at half maximum for the distribution
+ when ``x < centroid``
+ - *fwhm2* is the full-width at half maximum for the distribution
+ when ``x > centroid``
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of gaussian parameters (length must be a multiple
+ of 4):
+ *(height1, centroid1, fwhm11, fwhm21, height2, centroid2, fwhm12, fwhm22,...)*
+ :return: Array of sum of split gaussian functions at each ``x`` coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No gaussian parameters specified. " +
+ "At least 4 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_splitgauss(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_apvoigt(x, *params):
+ """Return a sum of pseudo-Voigt functions, defined by *(area, centroid, fwhm,
+ eta)*.
+
+ The pseudo-Voigt profile ``PV(x)`` is an approximation of the Voigt
+ profile using a linear combination of a Gaussian curve ``G(x)`` and a
+ Lorentzian curve ``L(x)`` instead of their convolution.
+
+ - *area* is the area underneath both G(x) and L(x)
+ - *centroid* is the peak x-coordinate for both functions
+ - *fwhm* is the full-width at half maximum of both functions
+ - *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of pseudo-Voigt parameters (length must be a multiple
+ of 4):
+ *(area1, centroid1, fwhm1, eta1, area2, centroid2, fwhm2, eta2,...)*
+ :return: Array of sum of pseudo-Voigt functions at each ``x`` coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 4 parameters are required.")
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_apvoigt(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_pvoigt(x, *params):
+ """Return a sum of pseudo-Voigt functions, defined by *(height, centroid,
+ fwhm, eta)*.
+
+ The pseudo-Voigt profile ``PV(x)`` is an approximation of the Voigt
+ profile using a linear combination of a Gaussian curve ``G(x)`` and a
+ Lorentzian curve ``L(x)`` instead of their convolution.
+
+ - *height* is the peak amplitude of G(x) and L(x)
+ - *centroid* is the peak x-coordinate for both functions
+ - *fwhm* is the full-width at half maximum of both functions
+ - *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of pseudo-Voigt parameters (length must be a multiple
+ of 4):
+ *(height1, centroid1, fwhm1, eta1, height2, centroid2, fwhm2, eta2,...)*
+ :return: Array of sum of pseudo-Voigt functions at each ``x`` coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 4 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_pvoigt(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_splitpvoigt(x, *params):
+ """Return a sum of split pseudo-Voigt functions, defined by *(height,
+ centroid, fwhm1, fwhm2, eta)*.
+
+ The pseudo-Voigt profile ``PV(x)`` is an approximation of the Voigt
+ profile using a linear combination of a Gaussian curve ``G(x)`` and a
+ Lorentzian curve ``L(x)`` instead of their convolution.
+
+ - *height* is the peak amplitudefor G(x) and L(x)
+ - *centroid* is the peak x-coordinate for both functions
+ - *fwhm1* is the full-width at half maximum of both functions
+ when ``x < centroid``
+ - *fwhm2* is the full-width at half maximum of both functions
+ when ``x > centroid``
+ - *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of pseudo-Voigt parameters (length must be a multiple
+ of 5):
+ *(height1, centroid1, fwhm11, fwhm21, eta1,...)*
+ :return: Array of sum of split pseudo-Voigt functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 5 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_splitpvoigt(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_lorentz(x, *params):
+ """Return a sum of Lorentz distributions, also known as Cauchy distribution,
+ defined by *(height, centroid, fwhm)*.
+
+ - *height* is the peak amplitude
+ - *centroid* is the peak x-coordinate
+ - *fwhm* is the full-width at half maximum
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of Lorentz parameters (length must be a multiple
+ of 3):
+ *(height1, centroid1, fwhm1,...)*
+ :return: Array of sum Lorentz functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 3 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_lorentz(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_alorentz(x, *params):
+ """Return a sum of Lorentz distributions, also known as Cauchy distribution,
+ defined by *(area, centroid, fwhm)*.
+
+ - *area* is the area underneath the peak
+ - *centroid* is the peak x-coordinate for both functions
+ - *fwhm* is the full-width at half maximum
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of Lorentz parameters (length must be a multiple
+ of 3):
+ *(area1, centroid1, fwhm1,...)*
+ :return: Array of sum of Lorentz functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 3 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_alorentz(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_splitlorentz(x, *params):
+ """Return a sum of split Lorentz distributions,
+ defined by *(height, centroid, fwhm1, fwhm2)*.
+
+ - *height* is the peak amplitude
+ - *centroid* is the peak x-coordinate for both functions
+ - *fwhm1* is the full-width at half maximum for ``x < centroid``
+ - *fwhm2* is the full-width at half maximum for ``x > centroid``
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of Lorentz parameters (length must be a multiple
+ of 4):
+ *(height1, centroid1, fwhm11, fwhm21...)*
+ :return: Array of sum of Lorentz functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 4 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_splitlorentz(
+ &x_c[0], x.size,
+ &params_c[0], params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_stepdown(x, *params):
+ """Return a sum of stepdown functions.
+ defined by *(height, centroid, fwhm)*.
+
+ - *height* is the step's amplitude
+ - *centroid* is the step's x-coordinate
+ - *fwhm* is the full-width at half maximum for the derivative,
+ which is a measure of the *sharpness* of the step-down's edge
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of stepdown parameters (length must be a multiple
+ of 3):
+ *(height1, centroid1, fwhm1,...)*
+ :return: Array of sum of stepdown functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 3 parameters are required.")
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_stepdown(&x_c[0],
+ x.size,
+ &params_c[0],
+ params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_stepup(x, *params):
+ """Return a sum of stepup functions.
+ defined by *(height, centroid, fwhm)*.
+
+ - *height* is the step's amplitude
+ - *centroid* is the step's x-coordinate
+ - *fwhm* is the full-width at half maximum for the derivative,
+ which is a measure of the *sharpness* of the step-up's edge
+
+ :param x: Independant variable where the gaussians are calculated
+ :type x: numpy.ndarray
+ :param params: Array of stepup parameters (length must be a multiple
+ of 3):
+ *(height1, centroid1, fwhm1,...)*
+ :return: Array of sum of stepup functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 3 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_stepup(&x_c[0],
+ x.size,
+ &params_c[0],
+ params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_slit(x, *params):
+ """Return a sum of slit functions.
+ defined by *(height, position, fwhm, beamfwhm)*.
+
+ - *height* is the slit's amplitude
+ - *position* is the center of the slit's x-coordinate
+ - *fwhm* is the full-width at half maximum of the slit
+ - *beamfwhm* is the full-width at half maximum of the
+ derivative, which is a measure of the *sharpness*
+ of the edges of the slit
+
+ :param x: Independant variable where the slits are calculated
+ :type x: numpy.ndarray
+ :param params: Array of slit parameters (length must be a multiple
+ of 4):
+ *(height1, centroid1, fwhm1, beamfwhm1,...)*
+ :return: Array of sum of slit functions at each ``x``
+ coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 4 parameters are required.")
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_slit(&x_c[0],
+ x.size,
+ &params_c[0],
+ params_c.size,
+ &y_c[0])
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_ahypermet(x, *params,
+ gaussian_term=True, st_term=True, lt_term=True, step_term=True):
+ """Return a sum of ahypermet functions.
+ defined by *(area, position, fwhm, st_area_r, st_slope_r, lt_area_r,
+ lt_slope_r, step_height_r)*.
+
+ - *area* is the area underneath the gaussian peak
+ - *position* is the center of the various peaks and the position of
+ the step down
+ - *fwhm* is the full-width at half maximum of the terms
+ - *st_area_r* is factor between the gaussian area and the area of the
+ short tail term
+ - *st_slope_r* is a ratio related to the slope of the short tail
+ in the low ``x`` values (the lower, the steeper)
+ - *lt_area_r* is ratio between the gaussian area and the area of the
+ long tail term
+ - *lt_slope_r* is a ratio related to the slope of the long tail
+ in the low ``x`` values (the lower, the steeper)
+ - *step_height_r* is the ratio between the height of the step down
+ and the gaussian height
+
+ A hypermet function is a sum of four functions (terms):
+
+ - a gaussian term
+ - a long tail term
+ - a short tail term
+ - a step down term
+
+ :param x: Independant variable where the hypermets are calculated
+ :type x: numpy.ndarray
+ :param params: Array of hypermet parameters (length must be a multiple
+ of 8):
+ *(area1, position1, fwhm1, st_area_r1, st_slope_r1, lt_area_r1,
+ lt_slope_r1, step_height_r1...)*
+ :param gaussian_term: If ``True``, enable gaussian term. Default ``True``
+ :param st_term: If ``True``, enable gaussian term. Default ``True``
+ :param lt_term: If ``True``, enable gaussian term. Default ``True``
+ :param step_term: If ``True``, enable gaussian term. Default ``True``
+ :return: Array of sum of hypermet functions at each ``x`` coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 8 parameters are required.")
+
+ # Sum binary flags to activate various terms of the equation
+ tail_flags = 1 if gaussian_term else 0
+ if st_term:
+ tail_flags += 2
+ if lt_term:
+ tail_flags += 4
+ if step_term:
+ tail_flags += 8
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_ahypermet(&x_c[0],
+ x.size,
+ &params_c[0],
+ params_c.size,
+ &y_c[0],
+ tail_flags)
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def sum_fastahypermet(x, *params,
+ gaussian_term=True, st_term=True,
+ lt_term=True, step_term=True):
+ """Return a sum of hypermet functions defined by *(area, position, fwhm,
+ st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r)*.
+
+ - *area* is the area underneath the gaussian peak
+ - *position* is the center of the various peaks and the position of
+ the step down
+ - *fwhm* is the full-width at half maximum of the terms
+ - *st_area_r* is factor between the gaussian area and the area of the
+ short tail term
+ - *st_slope_r* is a parameter related to the slope of the short tail
+ in the low ``x`` values (the lower, the steeper)
+ - *lt_area_r* is factor between the gaussian area and the area of the
+ long tail term
+ - *lt_slope_r* is a parameter related to the slope of the long tail
+ in the low ``x`` values (the lower, the steeper)
+ - *step_height_r* is the factor between the height of the step down
+ and the gaussian height
+
+ A hypermet function is a sum of four functions (terms):
+
+ - a gaussian term
+ - a long tail term
+ - a short tail term
+ - a step down term
+
+ This function differs from :func:`sum_ahypermet` by the use of a lookup
+ table for calculating exponentials. This offers better performance when
+ calculating many functions for large ``x`` arrays.
+
+ :param x: Independant variable where the hypermets are calculated
+ :type x: numpy.ndarray
+ :param params: Array of hypermet parameters (length must be a multiple
+ of 8):
+ *(area1, position1, fwhm1, st_area_r1, st_slope_r1, lt_area_r1,
+ lt_slope_r1, step_height_r1...)*
+ :param gaussian_term: If ``True``, enable gaussian term. Default ``True``
+ :param st_term: If ``True``, enable gaussian term. Default ``True``
+ :param lt_term: If ``True``, enable gaussian term. Default ``True``
+ :param step_term: If ``True``, enable gaussian term. Default ``True``
+ :return: Array of sum of hypermet functions at each ``x`` coordinate
+ """
+ cdef:
+ double[::1] x_c
+ double[::1] params_c
+ double[::1] y_c
+
+ if not len(params):
+ raise IndexError("No parameters specified. " +
+ "At least 8 parameters are required.")
+
+ # Sum binary flags to activate various terms of the equation
+ tail_flags = 1 if gaussian_term else 0
+ if st_term:
+ tail_flags += 2
+ if lt_term:
+ tail_flags += 4
+ if step_term:
+ tail_flags += 8
+
+ # TODO (maybe):
+ # Set flags according to params, to move conditional
+ # branches out of the C code.
+ # E.g., set st_term = False if any of the st_slope_r params
+ # (params[8*i + 4]) is 0, to prevent division by 0. Same thing for
+ # lt_slope_r (params[8*i + 6]) and lt_term.
+
+ x_c = numpy.array(x,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ params_c = numpy.array(params,
+ copy=False,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ y_c = numpy.empty(shape=(x.size,),
+ dtype=numpy.float64)
+
+ status = functions_wrapper.sum_fastahypermet(&x_c[0],
+ x.size,
+ &params_c[0],
+ params_c.size,
+ &y_c[0],
+ tail_flags)
+
+ if status:
+ raise IndexError("Wrong number of parameters for function")
+
+ return numpy.asarray(y_c).reshape(x.shape)
+
+
+def atan_stepup(x, a, b, c):
+ """
+ Step up function using an inverse tangent.
+
+ :param x: Independant variable where the function is calculated
+ :type x: numpy array
+ :param a: Height of the step up
+ :param b: Center of the step up
+ :param c: Parameter related to the slope of the step. A lower ``c``
+ value yields a sharper step.
+ :return: ``a * (0.5 + (arctan((x - b) / c) / pi))``
+ :rtype: numpy array
+ """
+ if not hasattr(x, "shape"):
+ x = numpy.array(x)
+ return a * (0.5 + (numpy.arctan((1.0 * x - b) / c) / numpy.pi))
+
+
+def periodic_gauss(x, *pars):
+ """
+ Return a sum of gaussian functions defined by
+ *(npeaks, delta, height, centroid, fwhm)*,
+ where:
+
+ - *npeaks* is the number of gaussians peaks
+ - *delta* is the constant distance between 2 peaks
+ - *height* is the peak amplitude of all the gaussians
+ - *centroid* is the peak x-coordinate of the first gaussian
+ - *fwhm* is the full-width at half maximum for all the gaussians
+
+ :param x: Independant variable where the function is calculated
+ :param pars: *(npeaks, delta, height, centroid, fwhm)*
+ :return: Sum of ``npeaks`` gaussians
+ """
+
+ if not len(pars):
+ raise IndexError("No parameters specified. " +
+ "At least 5 parameters are required.")
+
+ newpars = numpy.zeros((pars[0], 3), numpy.float)
+ for i in range(int(pars[0])):
+ newpars[i, 0] = pars[2]
+ newpars[i, 1] = pars[3] + i * pars[1]
+ newpars[:, 2] = pars[4]
+ return sum_gauss(x, newpars)
diff --git a/silx/math/fit/functions/functions_wrapper.pxd b/silx/math/fit/functions/functions_wrapper.pxd
new file mode 100644
index 0000000..780116c
--- /dev/null
+++ b/silx/math/fit/functions/functions_wrapper.pxd
@@ -0,0 +1,170 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "14/06/2016"
+
+cimport cython
+
+cdef extern from "functions.h":
+ int erfc_array(double* x,
+ int len_x,
+ double* y)
+
+ int erf_array(double* x,
+ int len_x,
+ double* y);
+
+ void snip1d(double *data,
+ int size,
+ int width)
+
+ void snip2d(double *data,
+ int nrows,
+ int ncolumns,
+ int width)
+
+ void snip3d(double *data,
+ int nx,
+ int ny,
+ int nz,
+ int width)
+
+ int strip(double* input,
+ long len_input,
+ double c,
+ long niter,
+ int deltai,
+ long* anchors,
+ long len_anchors,
+ double* output)
+
+ int sum_gauss(double* x,
+ int len_x,
+ double* pgauss,
+ int len_pgauss,
+ double* y)
+
+ int sum_agauss(double* x,
+ int len_x,
+ double* pgauss,
+ int len_pgauss,
+ double* y)
+
+ int sum_fastagauss(double* x,
+ int len_x,
+ double* pgauss,
+ int len_pgauss,
+ double* y)
+
+ int sum_splitgauss(double* x,
+ int len_x,
+ double* pgauss,
+ int len_pgauss,
+ double* y)
+
+ int sum_apvoigt(double* x,
+ int len_x,
+ double* pvoigt,
+ int len_pvoigt,
+ double* y)
+
+ int sum_pvoigt(double* x,
+ int len_x,
+ double* pvoigt,
+ int len_pvoigt,
+ double* y)
+
+ int sum_splitpvoigt(double* x,
+ int len_x,
+ double* pvoigt,
+ int len_pvoigt,
+ double* y)
+
+ int sum_lorentz(double* x,
+ int len_x,
+ double* plorentz,
+ int len_plorentz,
+ double* y)
+
+ int sum_alorentz(double* x,
+ int len_x,
+ double* plorentz,
+ int len_plorentz,
+ double* y)
+
+ int sum_splitlorentz(double* x,
+ int len_x,
+ double* plorentz,
+ int len_plorentz,
+ double* y)
+
+ int sum_stepdown(double* x,
+ int len_x,
+ double* pdstep,
+ int len_pdstep,
+ double* y)
+
+ int sum_stepup(double* x,
+ int len_x,
+ double* pustep,
+ int len_pustep,
+ double* y)
+
+ int sum_slit(double* x,
+ int len_x,
+ double* pslit,
+ int len_pslit,
+ double* y)
+
+ int sum_ahypermet(double* x,
+ int len_x,
+ double* phypermet,
+ int len_phypermet,
+ double* y,
+ int tail_flags)
+
+ int sum_fastahypermet(double* x,
+ int len_x,
+ double* phypermet,
+ int len_phypermet,
+ double* y,
+ int tail_flags)
+
+ long seek(long begin_index,
+ long end_index,
+ long nsamples,
+ double fwhm,
+ double sensitivity,
+ double debug_info,
+ long max_npeaks,
+ double * data,
+ double * peaks,
+ double * relevances)
+
+ int SavitskyGolay(double* input,
+ long len_input,
+ int npoints,
+ double* output)
diff --git a/silx/math/fit/functions/include/functions.h b/silx/math/fit/functions/include/functions.h
new file mode 100644
index 0000000..de4209b
--- /dev/null
+++ b/silx/math/fit/functions/include/functions.h
@@ -0,0 +1,68 @@
+/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+#ifndef FITFUNCTIONS_H
+#define FITFUNCTIONS_H
+
+/* Helper functions */
+int test_params(int len_params, int len_params_one_function, char* fun_name, char* param_names);
+double myerfc(double x);
+double myerf(double x);
+int erfc_array(double* x, int len_x, double* y);
+int erf_array(double* x, int len_x, double* y);
+
+/* Background functions */
+void snip1d(double *data, int size, int width);
+//void snip1d_multiple(double *data, int n_channels, int snip_width, int n_spectra);
+void snip2d(double *data, int nrows, int ncolumns, int width);
+void snip3d(double *data, int nx, int ny, int nz, int width);
+
+int strip(double* input, long len_input, double c, long niter, int deltai,
+ long* anchors, long len_anchors, double* output);
+
+/* Smoothing functions */
+
+int SavitskyGolay(double* input, long len_input, int npoints, double* output);
+
+/* Fit functions */
+int sum_gauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y);
+int sum_agauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y);
+int sum_fastagauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y);
+int sum_splitgauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y);
+
+int sum_apvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y);
+int sum_pvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y);
+int sum_splitpvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y);
+
+int sum_lorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y);
+int sum_alorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y);
+int sum_splitlorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y);
+
+int sum_stepdown(double* x, int len_x, double* pdstep, int len_pdstep, double* y);
+int sum_stepup(double* x, int len_x, double* pustep, int len_pustep, double* y);
+int sum_slit(double* x, int len_x, double* pslit, int len_pslit, double* y);
+
+int sum_ahypermet(double* x, int len_x, double* phypermet, int len_phypermet, double* y, int tail_flags);
+int sum_fastahypermet(double* x, int len_x, double* phypermet, int len_phypermet, double* y, int tail_flags);
+
+#endif /* #define FITFUNCTIONS_H */
diff --git a/silx/math/fit/functions/src/funs.c b/silx/math/fit/functions/src/funs.c
new file mode 100644
index 0000000..aae173f
--- /dev/null
+++ b/silx/math/fit/functions/src/funs.c
@@ -0,0 +1,1265 @@
+#/*##########################################################################
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+/*
+ This file provides fit functions.
+
+ It is adapted from PyMca source file "SpecFitFuns.c". The main difference
+ with the original code is that this code does not handle the python
+ wrapping, which is done elsewhere using cython.
+
+ Authors: V.A. Sole, P. Knobel
+ License: MIT
+ Last modified: 17/06/2016
+*/
+#include <math.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include "functions.h"
+
+#ifndef M_PI
+#define M_PI 3.1415926535
+#endif
+
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+#if defined(_WIN32)
+#define erf myerf
+#define erfc myerfc
+#endif
+
+#define LOG2 0.69314718055994529
+
+
+int test_params(int len_params,
+ int len_params_one_function,
+ char* fun_name,
+ char* param_names)
+{
+ if (len_params % len_params_one_function) {
+ printf("[%s]Error: Number of parameters must be a multiple of %d.",
+ fun_name, len_params_one_function);
+ printf("\nParameters expected for %s: %s\n",
+ fun_name, param_names);
+ return(1);
+ }
+ if (len_params == 0) {
+ printf("[%s]Error: No parameters specified.", fun_name);
+ printf("\nParameters expected for %s: %s\n",
+ fun_name, param_names);
+ return(1);
+ }
+ return(0);
+}
+
+/* Complementary error function for a single value*/
+double myerfc(double x)
+{
+ double z;
+ double t;
+ double r;
+
+ z=fabs(x);
+ t=1.0/(1.0+0.5*z);
+ r=t * exp(-z * z - 1.26551223 + t * (1.00002368 + t * (0.3740916 +
+ t * (0.09678418 + t * (-0.18628806 + t * (0.27886807 + t * (-1.13520398 +
+ t * (1.48851587 + t * (-0.82215223+t*0.17087277)))))))));
+ if (x<0)
+ r=2.0-r;
+ return (r);
+}
+
+/* Gauss error function for a single value*/
+double myerf(double x)
+{
+ return (1.0 - myerfc(x));
+}
+
+/* Gauss error function for an array
+ y[i]=erf(x[i])
+ returns status code 0
+*/
+int erf_array(double* x, int len_x, double* y)
+{
+ int j;
+ for (j=0; j<len_x; j++) {
+ y[j] = erf(x[j]);
+ }
+ return(0);
+}
+
+/* Complementary error function for an array
+ y[i]=erfc(x[i])
+ returns status code 0*/
+int erfc_array(double* x, int len_x, double* y)
+{
+ int j;
+ for (j=0; j<len_x; j++) {
+ y[j] = erfc(x[j]);
+ }
+ return(0);
+}
+
+/* Use lookup table for fast exp computation */
+double fastexp(double x)
+{
+ int expindex;
+ static double EXP[5000] = {0.0};
+ int i;
+
+/*initialize */
+ if (EXP[0] < 1){
+ for (i=0;i<5000;i++){
+ EXP[i] = exp(-0.01 * i);
+ }
+ }
+/*calculate*/
+ if (x < 0){
+ x = -x;
+ if (x < 50){
+ expindex = (int) (x * 100);
+ return EXP[expindex]*(1.0 - (x - 0.01 * expindex)) ;
+ }else if (x < 100) {
+ expindex = (int) (x * 10);
+ return pow(EXP[expindex]*(1.0 - (x - 0.1 * expindex)),10) ;
+ }else if (x < 1000){
+ expindex = (int) x;
+ return pow(EXP[expindex]*(1.0 - (x - expindex)),20) ;
+ }else if (x < 10000){
+ expindex = (int) (x * 0.1);
+ return pow(EXP[expindex]*(1.0 - (x - 10.0 * expindex)),30) ;
+ }else{
+ return 0;
+ }
+ }else{
+ if (x < 50){
+ expindex = (int) (x * 100);
+ return 1.0/EXP[expindex]*(1.0 - (x - 0.01 * expindex)) ;
+ }else if (x < 100) {
+ expindex = (int) (x * 10);
+ return pow(EXP[expindex]*(1.0 - (x - 0.1 * expindex)),-10) ;
+ }else{
+ return exp(x);
+ }
+ }
+}
+
+
+/* sum_gauss
+ Sum of gaussian functions, defined by (height, centroid, fwhm)
+
+ *height* is the peak amplitude
+ *centroid* is the peak x-coordinate
+ *fwhm* is the full-width at half maximum
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pvoigt: Array of gaussian parameters:
+ (height1, centroid1, fwhm1, height2, centroid2, fwhm2,...)
+ - len_pgauss: Number of elements in the pgauss array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_gauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y)
+{
+ int i, j;
+ double dhelp, inv_two_sqrt_two_log2, sigma;
+ double fwhm, centroid, height;
+
+ if (test_params(len_pgauss, 3, "sum_gauss", "height, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pgauss/3; i++) {
+ height = pgauss[3*i];
+ centroid = pgauss[3*i+1];
+ fwhm = pgauss[3*i+2];
+
+ sigma = fwhm * inv_two_sqrt_two_log2;
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid) / sigma;
+ if (dhelp <= 20) {
+ y[j] += height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_agauss
+ Sum of gaussian functions defined by (area, centroid, fwhm)
+
+ *area* is the area underneath the peak
+ *centroid* is the peak x-coordinate
+ *fwhm* is the full-width at half maximum
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pgauss: Array of gaussian parameters:
+ (area1, centroid1, fwhm1, area2, centroid2, fwhm2,...)
+ - len_pgauss: Number of elements in the pgauss array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_agauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y)
+{
+ int i, j;
+ double dhelp, height, sqrt2PI, sigma, inv_two_sqrt_two_log2;
+ double fwhm, centroid, area;
+
+ if (test_params(len_pgauss, 3, "sum_agauss", "area, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+ sqrt2PI = sqrt(2.0*M_PI);
+
+ for (i=0; i<len_pgauss/3; i++) {
+ area = pgauss[3*i];
+ centroid = pgauss[3*i+1];
+ fwhm = pgauss[3*i+2];
+
+ sigma = fwhm * inv_two_sqrt_two_log2;
+ height = area / (sigma * sqrt2PI);
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid)/sigma;
+ if (dhelp <= 35) {
+ y[j] += height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ return(0);
+}
+
+
+/* sum_fastagauss
+ Sum of gaussian functions defined by (area, centroid, fwhm).
+ This implementation uses a lookup table of precalculated exp values
+ and a limited development (exp(-x) = 1 - x for small values of x)
+
+ *area* is the area underneath the peak
+ *centroid* is the peak x-coordinate
+ *fwhm* is the full-width at half maximum
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pgauss: Array of gaussian parameters:
+ (area1, centroid1, fwhm1, area2, centroid2, fwhm2,...)
+ - len_pgauss: Number of elements in the pgauss array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+
+int sum_fastagauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y)
+{
+ int i, j, expindex;
+ double dhelp, height, sqrt2PI, sigma, inv_two_sqrt_two_log2;
+ double fwhm, centroid, area;
+ static double EXP[5000];
+
+ if (test_params(len_pgauss, 3, "sum_fastagauss", "area, centroid, fwhm")) {
+ return(1);
+ }
+
+ if (EXP[0] < 1){
+ for (i=0; i<5000; i++){
+ EXP[i] = exp(-0.01 * i);
+ }
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+ sqrt2PI = sqrt(2.0*M_PI);
+
+ for (i=0; i<len_pgauss/3; i++) {
+ area = pgauss[3*i];
+ centroid = pgauss[3*i+1];
+ fwhm = pgauss[3*i+2];
+
+ sigma = fwhm * inv_two_sqrt_two_log2;
+ height = area / (sigma * sqrt2PI);
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid)/sigma;
+ if (dhelp <= 15){
+ dhelp = 0.5 * dhelp * dhelp;
+ if (dhelp < 50){
+ expindex = (int) (dhelp * 100);
+ y[j] += height * EXP[expindex] * (1.0 - (dhelp - 0.01 * expindex));
+ }
+ else if (dhelp < 100) {
+ expindex = (int) (dhelp * 10);
+ y[j] += height * pow(EXP[expindex] * (1.0 - (dhelp - 0.1 * expindex)), 10);
+ }
+ else if (dhelp < 1000){
+ expindex = (int) (dhelp);
+ y[j] += height * pow(EXP[expindex] * (1.0 - (dhelp - expindex)), 20);
+ }
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_splitgauss
+ Sum of split gaussian functions, defined by (height, centroid, fwhm1, fwhm2)
+
+ *height* is the peak amplitude
+ *centroid* is the peak x-coordinate
+ *fwhm1* is the full-width at half maximum of the left half of the curve (x < centroid)
+ *fwhm1* is the full-width at half maximum of the right half of the curve (x > centroid)
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pgauss: Array of gaussian parameters:
+ (height1, centroid1, fwhm11, fwhm21, height2, centroid2, fwhm12, fwhm22,...)
+ - len_pgauss: Number of elements in the pgauss array. Must be
+ a multiple of 4.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_splitgauss(double* x, int len_x, double* pgauss, int len_pgauss, double* y)
+{
+ int i, j;
+ double dhelp, inv_two_sqrt_two_log2, sigma1, sigma2;
+ double fwhm1, fwhm2, centroid, height;
+
+ if (test_params(len_pgauss, 4, "sum_splitgauss", "height, centroid, fwhm1, fwhm2")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pgauss/4; i++) {
+ height = pgauss[4*i];
+ centroid = pgauss[4*i+1];
+ fwhm1 = pgauss[4*i+2];
+ fwhm2 = pgauss[4*i+3];
+
+ sigma1 = fwhm1 * inv_two_sqrt_two_log2;
+ sigma2 = fwhm2 * inv_two_sqrt_two_log2;
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid);
+ if (dhelp > 0) {
+ /* Use fwhm2 when x > centroid */
+ dhelp = dhelp / sigma2;
+ }
+ else {
+ /* Use fwhm1 when x < centroid */
+ dhelp = dhelp / sigma1;
+ }
+
+ if (dhelp <= 20) {
+ y[j] += height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_apvoigt
+ Sum of pseudo-Voigt functions, defined by (area, centroid, fwhm, eta).
+
+ The pseudo-Voigt profile PV(x) is an approximation of the Voigt profile
+ using a linear combination of a Gaussian curve G(x) and a Lorentzian curve
+ L(x) instead of their convolution.
+
+ *area* is the area underneath both G(x) and L(x)
+ *centroid* is the peak x-coordinate for both functions
+ *fwhm* is the full-width at half maximum of both functions
+ *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pvoigt: Array of Voigt function parameters:
+ (area1, centroid1, fwhm1, eta1, area2, centroid2, fwhm2, eta2,...)
+ - len_voigt: Number of elements in the pvoigt array. Must be
+ a multiple of 4.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_apvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y)
+{
+ int i, j;
+ double dhelp, inv_two_sqrt_two_log2, sqrt2PI, sigma, height;
+ double area, centroid, fwhm, eta;
+
+ if (test_params(len_pvoigt, 4, "sum_apvoigt", "area, centroid, fwhm, eta")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+ sqrt2PI = sqrt(2.0*M_PI);
+
+
+ for (i=0; i<len_pvoigt/4; i++) {
+ area = pvoigt[4*i];
+ centroid = pvoigt[4*i+1];
+ fwhm = pvoigt[4*i+2];
+ eta = pvoigt[4*i+3];
+
+ sigma = fwhm * inv_two_sqrt_two_log2;
+ height = area / (sigma * sqrt2PI);
+
+ for (j=0; j<len_x; j++) {
+ /* Lorentzian term */
+ dhelp = (x[j] - centroid) / (0.5 * fwhm);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += eta * (area / (0.5 * M_PI * fwhm * dhelp));
+
+ /* Gaussian term */
+ dhelp = (x[j] - centroid) / sigma;
+ if (dhelp <= 35) {
+ y[j] += (1.0 - eta) * height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_pvoigt
+ Sum of pseudo-Voigt functions, defined by (height, centroid, fwhm, eta).
+
+ The pseudo-Voigt profile PV(x) is an approximation of the Voigt profile
+ using a linear combination of a Gaussian curve G(x) and a Lorentzian curve
+ L(x) instead of their convolution.
+
+ *height* is the peak amplitude of G(x) and L(x)
+ *centroid* is the peak x-coordinate for both functions
+ *fwhm* is the full-width at half maximum of both functions
+ *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pvoigt: Array of Voigt function parameters:
+ (height1, centroid1, fwhm1, eta1, height2, centroid2, fwhm2, eta2,...)
+ - len_voigt: Number of elements in the pvoigt array. Must be
+ a multiple of 4.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_pvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y)
+{
+ int i, j;
+ double dhelp, inv_two_sqrt_two_log2, sigma;
+ double height, centroid, fwhm, eta;
+
+ if (test_params(len_pvoigt, 4, "sum_pvoigt", "height, centroid, fwhm, eta")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pvoigt/4; i++) {
+ height = pvoigt[4*i];
+ centroid = pvoigt[4*i+1];
+ fwhm = pvoigt[4*i+2];
+ eta = pvoigt[4*i+3];
+
+ sigma = fwhm * inv_two_sqrt_two_log2;
+
+ for (j=0; j<len_x; j++) {
+ /* Lorentzian term */
+ dhelp = (x[j] - centroid) / (0.5 * fwhm);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += eta * height / dhelp;
+
+ /* Gaussian term */
+ dhelp = (x[j] - centroid) / sigma;
+ if (dhelp <= 35) {
+ y[j] += (1.0 - eta) * height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_splitpvoigt
+ Sum of split pseudo-Voigt functions, defined by
+ (height, centroid, fwhm1, fwhm2, eta).
+
+ The pseudo-Voigt profile PV(x) is an approximation of the Voigt profile
+ using a linear combination of a Gaussian curve G(x) and a Lorentzian curve
+ L(x) instead of their convolution.
+
+ *height* is the peak amplitude of G(x) and L(x)
+ *centroid* is the peak x-coordinate for both functions
+ *fwhm1* is the full-width at half maximum of both functions for x < centroid
+ *fwhm2* is the full-width at half maximum of both functions for x > centroid
+ *eta* is the Lorentz factor: PV(x) = eta * L(x) + (1 - eta) * G(x)
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the gaussians are calculated.
+ - len_x: Number of elements in the x array.
+ - pvoigt: Array of Voigt function parameters:
+ (height1, centroid1, fwhm11, fwhm21, eta1, ...)
+ - len_voigt: Number of elements in the pvoigt array. Must be
+ a multiple of 5.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_splitpvoigt(double* x, int len_x, double* pvoigt, int len_pvoigt, double* y)
+{
+ int i, j;
+ double dhelp, inv_two_sqrt_two_log2, x_minus_centroid, sigma1, sigma2;
+ double height, centroid, fwhm1, fwhm2, eta;
+
+ if (test_params(len_pvoigt, 5, "sum_splitpvoigt", "height, centroid, fwhm1, fwhm2, eta")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ inv_two_sqrt_two_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pvoigt/5; i++) {
+ height = pvoigt[5*i];
+ centroid = pvoigt[5*i+1];
+ fwhm1 = pvoigt[5*i+2];
+ fwhm2 = pvoigt[5*i+3];
+ eta = pvoigt[5*i+4];
+
+ sigma1 = fwhm1 * inv_two_sqrt_two_log2;
+ sigma2 = fwhm2 * inv_two_sqrt_two_log2;
+
+ for (j=0; j<len_x; j++) {
+ x_minus_centroid = (x[j] - centroid);
+
+ /* Use fwhm2 when x > centroid */
+ if (x_minus_centroid > 0) {
+ /* Lorentzian term */
+ dhelp = x_minus_centroid / (0.5 * fwhm2);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += eta * height / dhelp;
+
+ /* Gaussian term */
+ dhelp = x_minus_centroid / sigma2;
+ if (dhelp <= 35) {
+ y[j] += (1.0 - eta) * height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ /* Use fwhm1 when x < centroid */
+ else {
+ /* Lorentzian term */
+ dhelp = x_minus_centroid / (0.5 * fwhm1);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += eta * height / dhelp;
+
+ /* Gaussian term */
+ dhelp = x_minus_centroid / sigma1;
+ if (dhelp <= 35) {
+ y[j] += (1.0 - eta) * height * exp (-0.5 * dhelp * dhelp);
+ }
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_lorentz
+ Sum of Lorentz functions, defined by (height, centroid, fwhm).
+
+ *height* is the peak amplitude
+ *centroid* is the peak's x-coordinate
+ *fwhm* is the full-width at half maximum
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the Lorentzians are calculated.
+ - len_x: Number of elements in the x array.
+ - plorentz: Array of lorentz function parameters:
+ (height1, centroid1, fwhm1, ...)
+ - len_lorentz: Number of elements in the plorentz array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_lorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y)
+{
+ int i, j;
+ double dhelp;
+ double height, centroid, fwhm;
+
+ if (test_params(len_plorentz, 3, "sum_lorentz", "height, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ for (i=0; i<len_plorentz/3; i++) {
+ height = plorentz[3*i];
+ centroid = plorentz[3*i+1];
+ fwhm = plorentz[3*i+2];
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid) / (0.5 * fwhm);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += height / dhelp;
+ }
+ }
+ return(0);
+}
+
+
+/* sum_alorentz
+ Sum of Lorentz functions, defined by (area, centroid, fwhm).
+
+ *area* is the area underneath the peak
+ *centroid* is the peak's x-coordinate
+ *fwhm* is the full-width at half maximum
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the Lorentzians are calculated.
+ - len_x: Number of elements in the x array.
+ - plorentz: Array of lorentz function parameters:
+ (area1, centroid1, fwhm1, ...)
+ - len_lorentz: Number of elements in the plorentz array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_alorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y)
+{
+ int i, j;
+ double dhelp;
+ double area, centroid, fwhm;
+
+ if (test_params(len_plorentz, 3, "sum_alorentz", "area, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ for (i=0; i<len_plorentz/3; i++) {
+ area = plorentz[3*i];
+ centroid = plorentz[3*i+1];
+ fwhm = plorentz[3*i+2];
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid) / (0.5 * fwhm);
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += area / (0.5 * M_PI * fwhm * dhelp);
+ }
+ }
+ return(0);
+}
+
+
+/* sum_splitlorentz
+ Sum of Lorentz functions, defined by (height, centroid, fwhm1, fwhm2).
+
+ *height* is the peak amplitude
+ *centroid* is the peak's x-coordinate
+ *fwhm1* is the full-width at half maximum for x < centroid
+ *fwhm2* is the full-width at half maximum for x > centroid
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the Lorentzians are calculated.
+ - len_x: Number of elements in the x array.
+ - plorentz: Array of lorentz function parameters:
+ (height1, centroid1, fwhm11, fwhm21 ...)
+ - len_lorentz: Number of elements in the plorentz array. Must be
+ a multiple of 4.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_splitlorentz(double* x, int len_x, double* plorentz, int len_plorentz, double* y)
+{
+ int i, j;
+ double dhelp;
+ double height, centroid, fwhm1, fwhm2;
+
+ if (test_params(len_plorentz, 4, "sum_splitlorentz", "height, centroid, fwhm1, fwhm2")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ for (i=0; i<len_plorentz/4; i++) {
+ height = plorentz[4*i];
+ centroid = plorentz[4*i+1];
+ fwhm1 = plorentz[4*i+2];
+ fwhm2 = plorentz[4*i+3];
+
+ for (j=0; j<len_x; j++) {
+ dhelp = (x[j] - centroid);
+ if (dhelp>0) {
+ dhelp = dhelp / (0.5 * fwhm2);
+ }
+ else {
+ dhelp = dhelp / (0.5 * fwhm1);
+ }
+ dhelp = 1.0 + (dhelp * dhelp);
+ y[j] += height / dhelp;
+ }
+ }
+ return(0);
+}
+
+/* sum_stepdown
+ Sum of stepdown functions, defined by (height, centroid, fwhm).
+
+ *height* is the step amplitude
+ *centroid* is the step's x-coordinate
+ *fwhm* is the full-width at half maximum of the derivative
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the stepdown functions are calculated.
+ - len_x: Number of elements in the x array.
+ - pdstep: Array of downstpe function parameters:
+ (height1, centroid1, fwhm1, ...)
+ - len_pdstep: Number of elements in the pdstep array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_stepdown(double* x, int len_x, double* pdstep, int len_pdstep, double* y)
+{
+ int i, j;
+ double dhelp, sqrt2_inv_2_sqrt_two_log2 ;
+ double height, centroid, fwhm;
+
+ if (test_params(len_pdstep, 3, "sum_stepdown", "height, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ sqrt2_inv_2_sqrt_two_log2 = sqrt(2.0) / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pdstep/3; i++) {
+ height = pdstep[3*i];
+ centroid = pdstep[3*i+1];
+ fwhm = pdstep[3*i+2];
+
+ for (j=0; j<len_x; j++) {
+ dhelp = fwhm * sqrt2_inv_2_sqrt_two_log2;
+ dhelp = (x[j] - centroid) / dhelp;
+ y[j] += height * 0.5 * erfc(dhelp);
+ }
+ }
+ return(0);
+}
+
+/* sum_stepup
+ Sum of stepup functions, defined by (height, centroid, fwhm).
+
+ *height* is the step amplitude
+ *centroid* is the step's x-coordinate
+ *fwhm* is the full-width at half maximum of the derivative
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the stepup functions are calculated.
+ - len_x: Number of elements in the x array.
+ - pustep: Array of stepdown function parameters:
+ (height1, centroid1, fwhm1, ...)
+ - len_pustep: Number of elements in the pustep array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_stepup(double* x, int len_x, double* pustep, int len_pustep, double* y)
+{
+ int i, j;
+ double dhelp, sqrt2_inv_2_sqrt_two_log2 ;
+ double height, centroid, fwhm;
+
+ if (test_params(len_pustep, 3, "sum_stepup", "height, centroid, fwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ sqrt2_inv_2_sqrt_two_log2 = sqrt(2.0) / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pustep/3; i++) {
+ height = pustep[3*i];
+ centroid = pustep[3*i+1];
+ fwhm = pustep[3*i+2];
+
+ for (j=0; j<len_x; j++) {
+ dhelp = fwhm * sqrt2_inv_2_sqrt_two_log2;
+ dhelp = (x[j] - centroid) / dhelp;
+ y[j] += height * 0.5 * (1.0 + erf(dhelp));
+ }
+ }
+ return(0);
+}
+
+
+/* sum_slit
+ Sum of slit functions, defined by (height, position, fwhm, beamfwhm).
+
+ *height* is the slit height
+ *position* is the slit's center x-coordinate
+ *fwhm* is the full-width at half maximum of the slit
+ *beamfwhm* is the full-width at half maximum of derivative's peaks
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the slit functions are calculated.
+ - len_x: Number of elements in the x array.
+ - pslit: Array of slit function parameters:
+ (height1, centroid1, fwhm1, beamfwhm1 ...)
+ - len_pslit: Number of elements in the pslit array. Must be
+ a multiple of 3.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_slit(double* x, int len_x, double* pslit, int len_pslit, double* y)
+{
+ int i, j;
+ double dhelp, dhelp1, dhelp2, sqrt2_inv_2_sqrt_two_log2, centroid1, centroid2;
+ double height, position, fwhm, beamfwhm;
+
+ if (test_params(len_pslit, 4, "sum_slit", "height, centroid, fwhm, beamfwhm")) {
+ return(1);
+ }
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ sqrt2_inv_2_sqrt_two_log2 = sqrt(2.0) / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_pslit/4; i++) {
+ height = pslit[4*i];
+ position = pslit[4*i+1];
+ fwhm = pslit[4*i+2];
+ beamfwhm = pslit[4*i+3];
+
+ centroid1 = position - 0.5 * fwhm;
+ centroid2 = position + 0.5 * fwhm;
+
+ for (j=0; j<len_x; j++) {
+ dhelp = beamfwhm * sqrt2_inv_2_sqrt_two_log2;
+ dhelp1 = (x[j] - centroid1) / dhelp;
+ dhelp2 = (x[j] - centroid2) / dhelp;
+ y[j] += height * 0.25 * (1.0 + erf(dhelp1)) * erfc(dhelp2);
+ }
+ }
+ return(0);
+}
+
+
+/* sum_ahypermet
+ Sum of hypermet functions, defined by
+ (area, position, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r).
+
+ - *area* is the area underneath the gaussian peak
+ - *position* is the center of the various peaks and the position of
+ the step down
+ - *fwhm* is the full-width at half maximum of the terms
+ - *st_area_r* is factor between the gaussian area and the area of the
+ short tail term
+ - *st_slope_r* is a parameter related to the slope of the short tail
+ in the low ``x`` values (the lower, the steeper)
+ - *lt_area_r* is factor between the gaussian area and the area of the
+ long tail term
+ - *lt_slope_r* is a parameter related to the slope of the long tail
+ in the low ``x`` values (the lower, the steeper)
+ - *step_height_r* is the factor between the height of the step down
+ and the gaussian height
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the functions are calculated.
+ - len_x: Number of elements in the x array.
+ - phypermet: Array of hypermet function parameters:
+ *(area1, position1, fwhm1, st_area_r1, st_slope_r1, lt_area_r1,
+ lt_slope_r1, step_height_r1, ...)*
+ - len_phypermet: Number of elements in the phypermet array. Must be
+ a multiple of 8.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+ - tail_flags: sum of binary flags to activate the various terms of the
+ function:
+
+ - 1 (b0001): Gaussian term
+ - 2 (b0010): st term
+ - 4 (b0100): lt term
+ - 8 (b1000): step term
+
+ E.g., to activate all termsof the hypermet, use ``tail_flags = 1 + 2 + 4 + 8 = 15``
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_ahypermet(double* x, int len_x, double* phypermet, int len_phypermet, double* y, int tail_flags)
+{
+ int i, j;
+ int g_term_flag, st_term_flag, lt_term_flag, step_term_flag;
+ double c1, c2, sigma, height, sigma_sqrt2, sqrt2PI, inv_2_sqrt_2_log2, x_minus_position, epsilon;
+ double area, position, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r;
+
+ if (test_params(len_phypermet, 8, "sum_hypermet",
+ "height, centroid, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r")) {
+ return(1);
+ }
+
+ g_term_flag = tail_flags & 1;
+ st_term_flag = (tail_flags>>1) & 1;
+ lt_term_flag = (tail_flags>>2) & 1;
+ step_term_flag = (tail_flags>>3) & 1;
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ /* define epsilon to compare floating point values with 0. */
+ epsilon = 0.00000000001;
+
+ sqrt2PI= sqrt(2.0 * M_PI);
+ inv_2_sqrt_2_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_phypermet/8; i++) {
+ area = phypermet[8*i];
+ position = phypermet[8*i+1];
+ fwhm = phypermet[8*i+2];
+ st_area_r = phypermet[8*i+3];
+ st_slope_r = phypermet[8*i+4];
+ lt_area_r = phypermet[8*i+5];
+ lt_slope_r = phypermet[8*i+6];
+ step_height_r = phypermet[8*i+7];
+
+ sigma = fwhm * inv_2_sqrt_2_log2;
+ height = area / (sigma * sqrt2PI);
+
+ /* Prevent division by 0 */
+ if (sigma == 0) {
+ printf("fwhm must not be equal to 0");
+ return(1);
+ }
+ sigma_sqrt2 = sigma * 1.4142135623730950488;
+
+ for (j=0; j<len_x; j++) {
+ x_minus_position = x[j] - position;
+ c2 = (0.5 * x_minus_position * x_minus_position) / (sigma * sigma);
+ /* gaussian term */
+ if (g_term_flag) {
+ y[j] += exp(-c2) * height;
+ }
+
+ /* st term */
+ if (st_term_flag) {
+ if (fabs(st_slope_r) > epsilon) {
+ c1 = st_area_r * 0.5 * \
+ erfc((x_minus_position/sigma_sqrt2) + 0.5 * sigma_sqrt2 / st_slope_r);
+ y[j] += ((area * c1) / st_slope_r) * \
+ exp(0.5 * (sigma / st_slope_r) * (sigma / st_slope_r) + \
+ (x_minus_position / st_slope_r));
+ }
+ }
+
+ /* lt term */
+ if (lt_term_flag) {
+ if (fabs(lt_slope_r) > epsilon) {
+ c1 = lt_area_r * \
+ 0.5 * erfc((x_minus_position/sigma_sqrt2) + 0.5 * sigma_sqrt2 / lt_slope_r);
+ y[j] += ((area * c1) / lt_slope_r) * \
+ exp(0.5 * (sigma / lt_slope_r) * (sigma / lt_slope_r) + \
+ (x_minus_position / lt_slope_r));
+ }
+ }
+
+ /* step term flag */
+ if (step_term_flag) {
+ y[j] += step_height_r * (area / (sigma * sqrt2PI)) * \
+ 0.5 * erfc(x_minus_position / sigma_sqrt2);
+ }
+ }
+ }
+ return(0);
+}
+
+/* sum_fastahypermet
+
+ Sum of hypermet functions, defined by
+ (area, position, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r).
+
+ - *area* is the area underneath the gaussian peak
+ - *position* is the center of the various peaks and the position of
+ the step down
+ - *fwhm* is the full-width at half maximum of the terms
+ - *st_area_r* is factor between the gaussian area and the area of the
+ short tail term
+ - *st_slope_r* is a parameter related to the slope of the short tail
+ in the low ``x`` values (the lower, the steeper)
+ - *lt_area_r* is factor between the gaussian area and the area of the
+ long tail term
+ - *lt_slope_r* is a parameter related to the slope of the long tail
+ in the low ``x`` values (the lower, the steeper)
+ - *step_height_r* is the factor between the height of the step down
+ and the gaussian height
+
+ Parameters:
+ -----------
+
+ - x: Independant variable where the functions are calculated.
+ - len_x: Number of elements in the x array.
+ - phypermet: Array of hypermet function parameters:
+ *(area1, position1, fwhm1, st_area_r1, st_slope_r1, lt_area_r1,
+ lt_slope_r1, step_height_r1, ...)*
+ - len_phypermet: Number of elements in the phypermet array. Must be
+ a multiple of 8.
+ - y: Output array. Must have memory allocated for the same number
+ of elements as x (len_x).
+ - tail_flags: sum of binary flags to activate the various terms of the
+ function:
+
+ - 1 (b0001): Gaussian term
+ - 2 (b0010): st term
+ - 4 (b0100): lt term
+ - 8 (b1000): step term
+
+ E.g., to activate all termsof the hypermet, use ``tail_flags = 1 + 2 + 4 + 8 = 15``
+
+ Adapted from PyMca module SpecFitFuns
+*/
+int sum_fastahypermet(double* x, int len_x, double* phypermet, int len_phypermet, double* y, int tail_flags)
+{
+ int i, j;
+ int g_term_flag, st_term_flag, lt_term_flag, step_term_flag;
+ double c1, c2, sigma, height, sigma_sqrt2, sqrt2PI, inv_2_sqrt_2_log2, x_minus_position, epsilon;
+ double area, position, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r;
+
+ if (test_params(len_phypermet, 8, "sum_hypermet",
+ "height, centroid, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r")) {
+ return(1);
+ }
+
+ g_term_flag = tail_flags & 1;
+ st_term_flag = (tail_flags>>1) & 1;
+ lt_term_flag = (tail_flags>>2) & 1;
+ step_term_flag = (tail_flags>>3) & 1;
+
+ /* Initialize output array */
+ for (j=0; j<len_x; j++) {
+ y[j] = 0.;
+ }
+
+ /* define epsilon to compare floating point values with 0. */
+ epsilon = 0.00000000001;
+
+ sqrt2PI= sqrt(2.0 * M_PI);
+ inv_2_sqrt_2_log2 = 1.0 / (2.0 * sqrt(2.0 * LOG2));
+
+ for (i=0; i<len_phypermet/8; i++) {
+ area = phypermet[8*i];
+ position = phypermet[8*i+1];
+ fwhm = phypermet[8*i+2];
+ st_area_r = phypermet[8*i+3];
+ st_slope_r = phypermet[8*i+4];
+ lt_area_r = phypermet[8*i+5];
+ lt_slope_r = phypermet[8*i+6];
+ step_height_r = phypermet[8*i+7];
+
+ sigma = fwhm * inv_2_sqrt_2_log2;
+ height = area / (sigma * sqrt2PI);
+
+ /* Prevent division by 0 */
+ if (sigma == 0) {
+ printf("fwhm must not be equal to 0");
+ return(1);
+ }
+ sigma_sqrt2 = sigma * 1.4142135623730950488;
+
+ for (j=0; j<len_x; j++) {
+ x_minus_position = x[j] - position;
+ c2 = (0.5 * x_minus_position * x_minus_position) / (sigma * sigma);
+ /* gaussian term */
+ if (g_term_flag && c2 < 100) {
+ y[j] += fastexp(-c2) * height;
+ }
+
+ /* st term */
+ if (st_term_flag && (fabs(st_slope_r) > epsilon) && (x_minus_position / st_slope_r) <= 612) {
+ c1 = st_area_r * 0.5 * \
+ erfc((x_minus_position/sigma_sqrt2) + 0.5 * sigma_sqrt2 / st_slope_r);
+ y[j] += ((area * c1) / st_slope_r) * \
+ fastexp(0.5 * (sigma / st_slope_r) * (sigma / st_slope_r) +\
+ (x_minus_position / st_slope_r));
+ }
+
+ /* lt term */
+ if (lt_term_flag && (fabs(lt_slope_r) > epsilon) && (x_minus_position / lt_slope_r) <= 612) {
+ c1 = lt_area_r * \
+ 0.5 * erfc((x_minus_position/sigma_sqrt2) + 0.5 * sigma_sqrt2 / lt_slope_r);
+ y[j] += ((area * c1) / lt_slope_r) * \
+ fastexp(0.5 * (sigma / lt_slope_r) * (sigma / lt_slope_r) +\
+ (x_minus_position / lt_slope_r));
+
+ }
+
+ /* step term flag */
+ if (step_term_flag) {
+ y[j] += step_height_r * (area / (sigma * sqrt2PI)) *\
+ 0.5 * erfc(x_minus_position / sigma_sqrt2);
+ }
+ }
+ }
+ return(0);
+}
+
+void pileup(double* x, long len_x, double* ret, int input2, double zero, double gain)
+{
+ //int input2=0;
+ //double zero=0.0;
+ //double gain=1.0;
+
+ int i, j, k;
+ double *px, *pret, *pall;
+
+ /* the pointer to the starting position of par data */
+ px = x;
+ pret = ret;
+
+ *pret = 0;
+ k = (int )(zero/gain);
+ for (i=input2; i<len_x; i++){
+ pall = x;
+ if ((i+k) >= 0)
+ {
+ pret = (double *) ret+(i+k);
+ for (j=0; j<len_x-i-k ;j++){
+ *pret += *px * (*pall);
+ pall++;
+ pret++;
+ }
+ }
+ px++;
+ }
+}
diff --git a/silx/math/fit/leastsq.py b/silx/math/fit/leastsq.py
new file mode 100644
index 0000000..874c23a
--- /dev/null
+++ b/silx/math/fit/leastsq.py
@@ -0,0 +1,902 @@
+# coding: utf-8
+# /*##########################################################################
+#
+# Copyright (c) 2004-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+"""
+This module implements a Levenberg-Marquardt algorithm with constraints on the
+fitted parameters without introducing any other dependendency than numpy.
+
+If scipy dependency is not an issue, and no constraints are applied to the fitting
+parameters, there is no real gain compared to the use of scipy.optimize.curve_fit
+other than a more conservative calculation of uncertainties on fitted parameters.
+
+This module is a refactored version of PyMca Gefit.py module.
+"""
+__authors__ = ["V.A. Sole"]
+__license__ = "MIT"
+__date__ = "24/01/2017"
+__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
+
+import numpy
+from numpy.linalg import inv
+from numpy.linalg.linalg import LinAlgError
+import time
+import logging
+import copy
+
+logging.basicConfig()
+_logger = logging.getLogger(__name__)
+
+# codes understood by the routine
+CFREE = 0
+CPOSITIVE = 1
+CQUOTED = 2
+CFIXED = 3
+CFACTOR = 4
+CDELTA = 5
+CSUM = 6
+CIGNORED = 7
+
+def leastsq(model, xdata, ydata, p0, sigma=None,
+ constraints=None, model_deriv=None, epsfcn=None,
+ deltachi=None, full_output=None,
+ check_finite=True,
+ left_derivative=False,
+ max_iter=100):
+ """
+ Use non-linear least squares Levenberg-Marquardt algorithm to fit a function, f, to
+ data with optional constraints on the fitted parameters.
+
+ Assumes ``ydata = f(xdata, *params) + eps``
+
+ :param model: callable
+ The model function, f(x, ...). It must take the independent
+ variable as the first argument and the parameters to fit as
+ separate remaining arguments.
+ The returned value is a one dimensional array of floats.
+
+ :param xdata: An M-length sequence.
+ The independent variable where the data is measured.
+
+ :param ydata: An M-length sequence
+ The dependent data --- nominally f(xdata, ...)
+
+ :param p0: N-length sequence
+ Initial guess for the parameters.
+
+ :param sigma: None or M-length sequence, optional
+ If not None, the uncertainties in the ydata array. These are used as
+ weights in the least-squares problem
+ i.e. minimising ``np.sum( ((f(xdata, *popt) - ydata) / sigma)**2 )``
+ If None, the uncertainties are assumed to be 1
+
+ :param constraints:
+ If provided, it is a 2D sequence of dimension (n_parameters, 3) where,
+ for each parameter denoted by the index i, the meaning is
+
+ - constraints[i][0]
+
+ - 0 - Free (CFREE)
+ - 1 - Positive (CPOSITIVE)
+ - 2 - Quoted (CQUOTED)
+ - 3 - Fixed (CFIXED)
+ - 4 - Factor (CFACTOR)
+ - 5 - Delta (CDELTA)
+ - 6 - Sum (CSUM)
+
+
+ - constraints[i][1]
+
+ - Ignored if constraints[i][0] is 0, 1, 3
+ - Min value of the parameter if constraints[i][0] is CQUOTED
+ - Index of fitted parameter to which it is related
+
+ - constraints[i][2]
+
+ - Ignored if constraints[i][0] is 0, 1, 3
+ - Max value of the parameter if constraints[i][0] is CQUOTED
+ - Factor to apply to related parameter with index constraints[i][1]
+ - Difference with parameter with index constraints[i][1]
+ - Sum obtained when adding parameter with index constraints[i][1]
+ :type constraints: *optional*, None or 2D sequence
+
+ :param model_deriv:
+ None (default) or function providing the derivatives of the fitting function respect to the fitted parameters.
+ It will be called as model_deriv(xdata, parameters, index) where parameters is a sequence with the current
+ values of the fitting parameters, index is the fitting parameter index for which the the derivative has
+ to be provided in the supplied array of xdata points.
+ :type model_deriv: *optional*, None or callable
+
+
+ :param epsfcn: float
+ A variable used in determining a suitable parameter variation when
+ calculating the numerical derivatives (for model_deriv=None).
+ Normally the actual step length will be sqrt(epsfcn)*x
+ Original Gefit module was using epsfcn 1.0e-5 while default value
+ is now numpy.finfo(numpy.float).eps as in scipy
+ :type epsfcn: *optional*, float
+
+ :param deltachi: float
+ A variable used to control the minimum change in chisq to consider the
+ fitting process not worth to be continued. Default is 0.1 %.
+ :type deltachi: *optional*, float
+
+ :param full_output: bool, optional
+ non-zero to return all optional outputs. The default is None what will give a warning in case
+ of a constrained fit without having set this kweyword.
+
+ :param check_finite: bool, optional
+ If True, check that the input arrays do not contain nans of infs,
+ and raise a ValueError if they do. Setting this parameter to
+ False will ignore input arrays values containing nans.
+ Default is True.
+
+ :param left_derivative:
+ This parameter only has an influence if no derivative function
+ is provided. When True the left and right derivatives of the
+ model will be calculated for each fitted parameters thus leading to
+ the double number of function evaluations. Default is False.
+ Original Gefit module was always using left_derivative as True.
+ :type left_derivative: *optional*, bool
+
+ :param max_iter: Maximum number of iterations (default is 100)
+
+ :return: Returns a tuple of length 2 (or 3 if full_ouput is True) with the content:
+
+ ``popt``: array
+ Optimal values for the parameters so that the sum of the squared error
+ of ``f(xdata, *popt) - ydata`` is minimized
+ ``pcov``: 2d array
+ If no constraints are applied, this array contains the estimated covariance
+ of popt. The diagonal provides the variance of the parameter estimate.
+ To compute one standard deviation errors use ``perr = np.sqrt(np.diag(pcov))``.
+ If constraints are applied, this array does not contain the estimated covariance of
+ the parameters actually used during the fitting process but the uncertainties after
+ recalculating the covariance if all the parameters were free.
+ To get the actual uncertainties following error propagation of the actually fitted
+ parameters one should set full_output to True and access the uncertainties key.
+ ``infodict``: dict
+ a dictionary of optional outputs with the keys:
+
+ ``uncertainties``
+ The actual uncertainty on the optimized parameters.
+ ``nfev``
+ The number of function calls
+ ``fvec``
+ The function evaluated at the output
+ ``niter``
+ The number of iterations performed
+ ``chisq``
+ The chi square ``np.sum( ((f(xdata, *popt) - ydata) / sigma)**2 )``
+ ``reduced_chisq``
+ The chi square ``np.sum( ((f(xdata, *popt) - ydata) / sigma)**2 )`` divided
+ by the number of degrees of freedom ``(M - number_of_free_parameters)``
+ """
+ function_call_counter = 0
+ if numpy.isscalar(p0):
+ p0 = [p0]
+ parameters = numpy.array(p0, dtype=numpy.float64, copy=False)
+ if deltachi is None:
+ deltachi = 0.001
+
+ # NaNs can not be handled
+ if check_finite:
+ xdata = numpy.asarray_chkfinite(xdata)
+ ydata = numpy.asarray_chkfinite(ydata)
+ if sigma is not None:
+ sigma = numpy.asarray_chkfinite(sigma)
+ else:
+ sigma = numpy.ones((ydata.shape), dtype=numpy.float)
+ ydata.shape = -1
+ sigma.shape = -1
+ else:
+ ydata = numpy.asarray(ydata)
+ xdata = numpy.asarray(xdata)
+ ydata.shape = -1
+ if sigma is not None:
+ sigma = numpy.asarray(sigma)
+ else:
+ sigma = numpy.ones((ydata.shape), dtype=numpy.float)
+ sigma.shape = -1
+ # get rid of NaN in input data
+ idx = numpy.isfinite(ydata)
+ if False in idx:
+ # xdata must have a shape able to be understood by the user function
+ # in principle, one should not need to change it, however, if there are
+ # points to be excluded, one has to be able to exclude them.
+ # We can only hope that the sequence is properly arranged
+ if xdata.size == ydata.size:
+ if len(xdata.shape) != 1:
+ msg = "Need to reshape input xdata."
+ _logger.warning(msg)
+ xdata.shape = -1
+ else:
+ raise ValueError("Cannot reshape xdata to deal with NaN in ydata")
+ ydata = ydata[idx]
+ xdata = xdata[idx]
+ sigma = sigma[idx]
+ idx = numpy.isfinite(sigma)
+ if False in idx:
+ # xdata must have a shape able to be understood by the user function
+ # in principle, one should not need to change it, however, if there are
+ # points to be excluded, one has to be able to exclude them.
+ # We can only hope that the sequence is properly arranged
+ ydata = ydata[idx]
+ xdata = xdata[idx]
+ sigma = sigma[idx]
+ idx = numpy.isfinite(xdata)
+ filter_xdata = False
+ if False in idx:
+ # What to do?
+ try:
+ # Let's see if the function is able to deal with non-finite data
+ msg = "Checking if function can deal with non-finite data"
+ _logger.debug(msg)
+ evaluation = model(xdata, *parameters)
+ function_call_counter += 1
+ if evaluation.shape != ydata.shape:
+ if evaluation.size == ydata.size:
+ msg = "Supplied function does not return a proper array of floats."
+ msg += "\nFunction should be rewritten to return a 1D array of floats."
+ msg += "\nTrying to reshape output."
+ _logger.warning(msg)
+ evaluation.shape = ydata.shape
+ if False in numpy.isfinite(evaluation):
+ msg = "Supplied function unable to handle non-finite x data"
+ msg += "\nAttempting to filter out those x data values."
+ _logger.warning(msg)
+ filter_xdata = True
+ else:
+ filter_xdata = False
+ evaluation = None
+ except:
+ # function cannot handle input data
+ filter_xdata = True
+ if filter_xdata:
+ if xdata.size != ydata.size:
+ raise ValueError("xdata contains non-finite data that cannot be filtered")
+ else:
+ # we leave the xdata as they where
+ old_shape = xdata.shape
+ xdata.shape = ydata.shape
+ idx0 = numpy.isfinite(xdata)
+ xdata.shape = old_shape
+ ydata = ydata[idx0]
+ xdata = xdata[idx]
+ sigma = sigma[idx0]
+ weight = 1.0 / (sigma + numpy.equal(sigma, 0))
+ weight0 = weight * weight
+
+ nparameters = len(parameters)
+
+ if epsfcn is None:
+ epsfcn = numpy.finfo(numpy.float).eps
+ else:
+ epsfcn = max(epsfcn, numpy.finfo(numpy.float).eps)
+
+ # check if constraints have been passed as text
+ constrained_fit = False
+ if constraints is not None:
+ # make sure we work with a list of lists
+ input_constraints = constraints
+ tmp_constraints = [None] * len(input_constraints)
+ for i in range(nparameters):
+ tmp_constraints[i] = list(input_constraints[i])
+ constraints = tmp_constraints
+ for i in range(nparameters):
+ if hasattr(constraints[i][0], "upper"):
+ txt = constraints[i][0].upper()
+ if txt == "FREE":
+ constraints[i][0] = CFREE
+ elif txt == "POSITIVE":
+ constraints[i][0] = CPOSITIVE
+ elif txt == "QUOTED":
+ constraints[i][0] = CQUOTED
+ elif txt == "FIXED":
+ constraints[i][0] = CFIXED
+ elif txt == "FACTOR":
+ constraints[i][0] = CFACTOR
+ constraints[i][1] = int(constraints[i][1])
+ elif txt == "DELTA":
+ constraints[i][0] = CDELTA
+ constraints[i][1] = int(constraints[i][1])
+ elif txt == "SUM":
+ constraints[i][0] = CSUM
+ constraints[i][1] = int(constraints[i][1])
+ elif txt in ["IGNORED", "IGNORE"]:
+ constraints[i][0] = CIGNORED
+ else:
+ #I should raise an exception
+ raise ValueError("Unknown constraint %s" % constraints[i][0])
+ if constraints[i][0] > 0:
+ constrained_fit = True
+ if constrained_fit:
+ if full_output is None:
+ _logger.info("Recommended to set full_output to True when using constraints")
+
+ # Levenberg-Marquardt algorithm
+ fittedpar = parameters.__copy__()
+ flambda = 0.001
+ iiter = max_iter
+ #niter = 0
+ last_evaluation=None
+ x = xdata
+ y = ydata
+ chisq0 = -1
+ iteration_counter = 0
+ while (iiter > 0):
+ weight = weight0
+ """
+ I cannot evaluate the initial chisq here because I do not know
+ if some parameters are to be ignored, otherways I could do it as follows:
+ if last_evaluation is None:
+ yfit = model(x, *fittedpar)
+ last_evaluation = yfit
+ chisq0 = (weight * pow(y-yfit, 2)).sum()
+ and chisq would not need to be recalculated.
+ Passing the last_evaluation assumes that there are no parameters being
+ ignored or not between calls.
+ """
+ iteration_counter += 1
+ chisq0, alpha0, beta, internal_output = chisq_alpha_beta(
+ model, fittedpar,
+ x, y, weight, constraints=constraints,
+ model_deriv=model_deriv,
+ epsfcn=epsfcn,
+ left_derivative=left_derivative,
+ last_evaluation=last_evaluation,
+ full_output=True)
+ n_free = internal_output["n_free"]
+ free_index = internal_output["free_index"]
+ noigno = internal_output["noigno"]
+ fitparam = internal_output["fitparam"]
+ function_calls = internal_output["function_calls"]
+ function_call_counter += function_calls
+ #print("chisq0 = ", chisq0, n_free, fittedpar)
+ #raise
+ nr, nc = alpha0.shape
+ flag = 0
+ #lastdeltachi = chisq0
+ while flag == 0:
+ alpha = alpha0 * (1.0 + flambda * numpy.identity(nr))
+ deltapar = numpy.dot(beta, inv(alpha))
+ if constraints is None:
+ newpar = fitparam + deltapar [0]
+ else:
+ newpar = parameters.__copy__()
+ pwork = numpy.zeros(deltapar.shape, numpy.float)
+ for i in range(n_free):
+ if constraints is None:
+ pwork [0] [i] = fitparam [i] + deltapar [0] [i]
+ elif constraints [free_index[i]][0] == CFREE:
+ pwork [0] [i] = fitparam [i] + deltapar [0] [i]
+ elif constraints [free_index[i]][0] == CPOSITIVE:
+ #abs method
+ pwork [0] [i] = fitparam [i] + deltapar [0] [i]
+ #square method
+ #pwork [0] [i] = (numpy.sqrt(fitparam [i]) + deltapar [0] [i]) * \
+ # (numpy.sqrt(fitparam [i]) + deltapar [0] [i])
+ elif constraints[free_index[i]][0] == CQUOTED:
+ pmax = max(constraints[free_index[i]][1],
+ constraints[free_index[i]][2])
+ pmin = min(constraints[free_index[i]][1],
+ constraints[free_index[i]][2])
+ A = 0.5 * (pmax + pmin)
+ B = 0.5 * (pmax - pmin)
+ if B != 0:
+ pwork [0] [i] = A + \
+ B * numpy.sin(numpy.arcsin((fitparam[i] - A)/B)+ \
+ deltapar [0] [i])
+ else:
+ txt = "Error processing constrained fit\n"
+ txt += "Parameter limits are %g and %g\n" % (pmin, pmax)
+ txt += "A = %g B = %g" % (A, B)
+ raise ValueError("Invalid parameter limits")
+ newpar[free_index[i]] = pwork [0] [i]
+ newpar = numpy.array(_get_parameters(newpar, constraints))
+ workpar = numpy.take(newpar, noigno)
+ yfit = model(x, *workpar)
+ if last_evaluation is None:
+ if len(yfit.shape) > 1:
+ msg = "Supplied function does not return a 1D array of floats."
+ msg += "\nFunction should be rewritten."
+ msg += "\nTrying to reshape output."
+ _logger.warning(msg)
+ yfit.shape = -1
+ function_call_counter += 1
+ chisq = (weight * pow(y-yfit, 2)).sum()
+ absdeltachi = chisq0 - chisq
+ if absdeltachi < 0:
+ flambda *= 10.0
+ if flambda > 1000:
+ flag = 1
+ iiter = 0
+ else:
+ flag = 1
+ fittedpar = newpar.__copy__()
+ lastdeltachi = 100 * (absdeltachi / (chisq + (chisq == 0)))
+ if iteration_counter < 2:
+ # ignore any limit, the fit *has* to be improved
+ pass
+ elif (lastdeltachi) < deltachi:
+ iiter = 0
+ elif absdeltachi < numpy.sqrt(epsfcn):
+ iiter = 0
+ _logger.info("Iteration finished due to too small absolute chi decrement")
+ chisq0 = chisq
+ flambda = flambda / 10.0
+ last_evaluation = yfit
+ iiter = iiter - 1
+ # this is the covariance matrix of the actually fitted parameters
+ cov0 = inv(alpha0)
+ if constraints is None:
+ cov = cov0
+ else:
+ # yet another call needed with all the parameters being free except those
+ # that are FIXED and that will be assigned a 100 % uncertainty.
+ new_constraints = copy.deepcopy(constraints)
+ flag_special = [0] * len(fittedpar)
+ for idx, constraint in enumerate(constraints):
+ if constraints[idx][0] in [CFIXED, CIGNORED]:
+ flag_special[idx] = constraints[idx][0]
+ else:
+ new_constraints[idx][0] = CFREE
+ new_constraints[idx][1] = 0
+ new_constraints[idx][2] = 0
+ chisq, alpha, beta, internal_output = chisq_alpha_beta(
+ model, fittedpar,
+ x, y, weight, constraints=new_constraints,
+ model_deriv=model_deriv,
+ epsfcn=epsfcn,
+ left_derivative=left_derivative,
+ last_evaluation=last_evaluation,
+ full_output=True)
+ # obtained chisq should be identical to chisq0
+ try:
+ cov = inv(alpha)
+ except LinAlgError:
+ _logger.critical("Error calculating covariance matrix after successful fit")
+ cov = None
+ if cov is not None:
+ for idx, value in enumerate(flag_special):
+ if value in [CFIXED, CIGNORED]:
+ cov = numpy.insert(numpy.insert(cov, idx, 0, axis=1), idx, 0, axis=0)
+ cov[idx, idx] = fittedpar[idx] * fittedpar[idx]
+
+ if not full_output:
+ return fittedpar, cov
+ else:
+ sigma0 = numpy.sqrt(abs(numpy.diag(cov0)))
+ sigmapar = _get_sigma_parameters(fittedpar, sigma0, constraints)
+ ddict = {}
+ ddict["chisq"] = chisq0
+ ddict["reduced_chisq"] = chisq0 / (len(yfit)-n_free)
+ ddict["covariance"] = cov0
+ ddict["uncertainties"] = sigmapar
+ ddict["fvec"] = last_evaluation
+ ddict["nfev"] = function_call_counter
+ ddict["niter"] = iteration_counter
+ return fittedpar, cov, ddict #, chisq/(len(yfit)-len(sigma0)), sigmapar,niter,lastdeltachi
+
+def chisq_alpha_beta(model, parameters, x, y, weight, constraints=None,
+ model_deriv=None, epsfcn=None, left_derivative=False,
+ last_evaluation=None, full_output=False):
+
+ """
+ Get chi square, the curvature matrix alpha and the matrix beta according to the input parameters.
+ If all the parameters are unconstrained, the covariance matrix is the inverse of the alpha matrix.
+
+ :param model: callable
+ The model function, f(x, ...). It must take the independent
+ variable as the first argument and the parameters to fit as
+ separate remaining arguments.
+ The returned value is a one dimensional array of floats.
+
+ :param parameters: N-length sequence
+ Values of parameters at which function and derivatives are to be calculated.
+
+ :param x: An M-length sequence.
+ The independent variable where the data is measured.
+
+ :param y: An M-length sequence
+ The dependent data --- nominally f(xdata, ...)
+
+ :param weight: M-length sequence
+ Weights to be applied in the calculation of chi square
+ As a reminder ``chisq = np.sum(weigth * (model(x, *parameters) - y)**2)``
+
+ :param constraints:
+ If provided, it is a 2D sequence of dimension (n_parameters, 3) where,
+ for each parameter denoted by the index i, the meaning is
+
+ - constraints[i][0]
+
+ - 0 - Free (CFREE)
+ - 1 - Positive (CPOSITIVE)
+ - 2 - Quoted (CQUOTED)
+ - 3 - Fixed (CFIXED)
+ - 4 - Factor (CFACTOR)
+ - 5 - Delta (CDELTA)
+ - 6 - Sum (CSUM)
+
+
+ - constraints[i][1]
+
+ - Ignored if constraints[i][0] is 0, 1, 3
+ - Min value of the parameter if constraints[i][0] is CQUOTED
+ - Index of fitted parameter to which it is related
+
+ - constraints[i][2]
+
+ - Ignored if constraints[i][0] is 0, 1, 3
+ - Max value of the parameter if constraints[i][0] is CQUOTED
+ - Factor to apply to related parameter with index constraints[i][1]
+ - Difference with parameter with index constraints[i][1]
+ - Sum obtained when adding parameter with index constraints[i][1]
+ :type constraints: *optional*, None or 2D sequence
+
+ :param model_deriv:
+ None (default) or function providing the derivatives of the fitting function respect to the fitted parameters.
+ It will be called as model_deriv(xdata, parameters, index) where parameters is a sequence with the current
+ values of the fitting parameters, index is the fitting parameter index for which the the derivative has
+ to be provided in the supplied array of xdata points.
+ :type model_deriv: *optional*, None or callable
+
+
+ :param epsfcn: float
+ A variable used in determining a suitable parameter variation when
+ calculating the numerical derivatives (for model_deriv=None).
+ Normally the actual step length will be sqrt(epsfcn)*x
+ Original Gefit module was using epsfcn 1.0e-10 while default value
+ is now numpy.finfo(numpy.float).eps as in scipy
+ :type epsfcn: *optional*, float
+
+ :param left_derivative:
+ This parameter only has an influence if no derivative function
+ is provided. When True the left and right derivatives of the
+ model will be calculated for each fitted parameters thus leading to
+ the double number of function evaluations. Default is False.
+ Original Gefit module was always using left_derivative as True.
+ :type left_derivative: *optional*, bool
+
+ :param last_evaluation: An M-length array
+ Used for optimization purposes. If supplied, this array will be taken as the result of
+ evaluating the function, that is as the result of ``model(x, *parameters)`` thus avoiding
+ the evaluation call.
+
+ :param full_output: bool, optional
+ Additional output used for internal purposes with the keys:
+ ``function_calls``
+ The number of model function calls performed.
+ ``fitparam``
+ A sequence with the actual free parameters
+ ``free_index``
+ Sequence with the indices of the free parameters in input parameters sequence.
+ ``noigno``
+ Sequence with the indices of the original parameters considered in the calculations.
+ """
+ if epsfcn is None:
+ epsfcn = numpy.finfo(numpy.float).eps
+ else:
+ epsfcn = max(epsfcn, numpy.finfo(numpy.float).eps)
+ #nr0, nc = data.shape
+ n_param = len(parameters)
+ if constraints is None:
+ derivfactor = numpy.ones((n_param, ))
+ n_free = n_param
+ noigno = numpy.arange(n_param)
+ free_index = noigno * 1
+ fitparam = parameters * 1
+ else:
+ n_free = 0
+ fitparam = []
+ free_index = []
+ noigno = []
+ derivfactor = []
+ for i in range(n_param):
+ if constraints[i][0] != CIGNORED:
+ noigno.append(i)
+ if constraints[i][0] == CFREE:
+ fitparam.append(parameters [i])
+ derivfactor.append(1.0)
+ free_index.append(i)
+ n_free += 1
+ elif constraints[i][0] == CPOSITIVE:
+ fitparam.append(abs(parameters[i]))
+ derivfactor.append(1.0)
+ #fitparam.append(numpy.sqrt(abs(parameters[i])))
+ #derivfactor.append(2.0*numpy.sqrt(abs(parameters[i])))
+ free_index.append(i)
+ n_free += 1
+ elif constraints[i][0] == CQUOTED:
+ pmax = max(constraints[i][1], constraints[i][2])
+ pmin =min(constraints[i][1], constraints[i][2])
+ if ((pmax-pmin) > 0) & \
+ (parameters[i] <= pmax) & \
+ (parameters[i] >= pmin):
+ A = 0.5 * (pmax + pmin)
+ B = 0.5 * (pmax - pmin)
+ fitparam.append(parameters[i])
+ derivfactor.append(B*numpy.cos(numpy.arcsin((parameters[i] - A)/B)))
+ free_index.append(i)
+ n_free += 1
+ elif (pmax-pmin) > 0:
+ print("WARNING: Quoted parameter outside boundaries")
+ print("Initial value = %f" % parameters[i])
+ print("Limits are %f and %f" % (pmin, pmax))
+ print("Parameter will be kept at its starting value")
+ fitparam = numpy.array(fitparam, numpy.float)
+ alpha = numpy.zeros((n_free, n_free), numpy.float)
+ beta = numpy.zeros((1, n_free), numpy.float)
+ #delta = (fitparam + numpy.equal(fitparam, 0.0)) * 0.00001
+ delta = (fitparam + numpy.equal(fitparam, 0.0)) * numpy.sqrt(epsfcn)
+ nr = y.size
+ ##############
+ # Prior to each call to the function one has to re-calculate the
+ # parameters
+ pwork = parameters.__copy__()
+ for i in range(n_free):
+ pwork [free_index[i]] = fitparam [i]
+ if n_free == 0:
+ raise ValueError("No free parameters to fit")
+ function_calls = 0
+ if not left_derivative:
+ if last_evaluation is not None:
+ f2 = last_evaluation
+ else:
+ f2 = model(x, *parameters)
+ f2.shape = -1
+ function_calls += 1
+ for i in range(n_free):
+ if model_deriv is None:
+ #pwork = parameters.__copy__()
+ pwork[free_index[i]] = fitparam [i] + delta [i]
+ newpar = _get_parameters(pwork.tolist(), constraints)
+ newpar = numpy.take(newpar, noigno)
+ f1 = model(x, *newpar)
+ f1.shape = -1
+ function_calls += 1
+ if left_derivative:
+ pwork[free_index[i]] = fitparam [i] - delta [i]
+ newpar = _get_parameters(pwork.tolist(), constraints)
+ newpar=numpy.take(newpar, noigno)
+ f2 = model(x, *newpar)
+ function_calls += 1
+ help0 = (f1 - f2) / (2.0 * delta[i])
+ else:
+ help0 = (f1 - f2) / (delta[i])
+ help0 = help0 * derivfactor[i]
+ pwork[free_index[i]] = fitparam [i]
+ #removed I resize outside the loop:
+ #help0 = numpy.resize(help0, (1, nr))
+ else:
+ help0 = model_deriv(x, pwork, free_index[i])
+ help0 = help0 * derivfactor[i]
+
+ if i == 0:
+ deriv = help0
+ else:
+ deriv = numpy.concatenate((deriv, help0), 0)
+
+ #line added to resize outside the loop
+ deriv = numpy.resize(deriv, (n_free, nr))
+ if last_evaluation is None:
+ if constraints is None:
+ yfit = model(x, *fitparam)
+ yfit.shape = -1
+ else:
+ newpar = _get_parameters(pwork.tolist(), constraints)
+ newpar = numpy.take(newpar, noigno)
+ yfit = model(x, *newpar)
+ yfit.shape = -1
+ function_calls += 1
+ else:
+ yfit = last_evaluation
+ deltay = y - yfit
+ help0 = weight * deltay
+ for i in range(n_free):
+ derivi = numpy.resize(deriv[i, :], (1, nr))
+ help1 = numpy.resize(numpy.sum((help0 * derivi), 1), (1, 1))
+ if i == 0:
+ beta = help1
+ else:
+ beta = numpy.concatenate((beta, help1), 1)
+ help1 = numpy.inner(deriv, weight*derivi)
+ if i == 0:
+ alpha = help1
+ else:
+ alpha = numpy.concatenate((alpha, help1), 1)
+ chisq = (help0 * deltay).sum()
+ if full_output:
+ ddict = {}
+ ddict["n_free"] = n_free
+ ddict["free_index"] = free_index
+ ddict["noigno"] = noigno
+ ddict["fitparam"] = fitparam
+ ddict["derivfactor"] = derivfactor
+ ddict["function_calls"] = function_calls
+ return chisq, alpha, beta, ddict
+ else:
+ return chisq, alpha, beta
+
+
+def _get_parameters(parameters, constraints):
+ """
+ Apply constraints to input parameters.
+
+ Parameters not depending on other parameters, they are returned as the input.
+
+ Parameters depending on other parameters, return the value after applying the
+ relation to the parameter wo which they are related.
+ """
+ # 0 = Free 1 = Positive 2 = Quoted
+ # 3 = Fixed 4 = Factor 5 = Delta
+ if constraints is None:
+ return parameters * 1
+ newparam = []
+ #first I make the free parameters
+ #because the quoted ones put troubles
+ for i in range(len(constraints)):
+ if constraints[i][0] == CFREE:
+ newparam.append(parameters[i])
+ elif constraints[i][0] == CPOSITIVE:
+ #newparam.append(parameters[i] * parameters[i])
+ newparam.append(abs(parameters[i]))
+ elif constraints[i][0] == CQUOTED:
+ newparam.append(parameters[i])
+ elif abs(constraints[i][0]) == CFIXED:
+ newparam.append(parameters[i])
+ else:
+ newparam.append(parameters[i])
+ for i in range(len(constraints)):
+ if constraints[i][0] == CFACTOR:
+ newparam[i] = constraints[i][2] * newparam[int(constraints[i][1])]
+ elif constraints[i][0] == CDELTA:
+ newparam[i] = constraints[i][2] + newparam[int(constraints[i][1])]
+ elif constraints[i][0] == CIGNORED:
+ # The whole ignored stuff should not be documented because setting
+ # a parameter to 0 is not the same as being ignored.
+ # Being ignored should imply the parameter is simply not accounted for
+ # and should be stripped out of the list of parameters by the program
+ # using this module
+ newparam[i] = 0
+ elif constraints[i][0] == CSUM:
+ newparam[i] = constraints[i][2]-newparam[int(constraints[i][1])]
+ return newparam
+
+
+def _get_sigma_parameters(parameters, sigma0, constraints):
+ """
+ Internal function propagating the uncertainty on the actually fitted parameters and related parameters to the
+ final parameters considering the applied constraints.
+
+ Parameters
+ ----------
+ parameters : 1D sequence of length equal to the number of free parameters N
+ The parameters actually used in the fitting process.
+ sigma0 : 1D sequence of length N
+ Uncertainties calculated as the square-root of the diagonal of
+ the covariance matrix
+ constraints : The set of constraints applied in the fitting process
+ """
+ # 0 = Free 1 = Positive 2 = Quoted
+ # 3 = Fixed 4 = Factor 5 = Delta
+ if constraints is None:
+ return sigma0
+ n_free = 0
+ sigma_par = numpy.zeros(parameters.shape, numpy.float)
+ for i in range(len(constraints)):
+ if constraints[i][0] == CFREE:
+ sigma_par [i] = sigma0[n_free]
+ n_free += 1
+ elif constraints[i][0] == CPOSITIVE:
+ #sigma_par [i] = 2.0 * sigma0[n_free]
+ sigma_par [i] = sigma0[n_free]
+ n_free += 1
+ elif constraints[i][0] == CQUOTED:
+ pmax = max(constraints [i][1], constraints [i][2])
+ pmin = min(constraints [i][1], constraints [i][2])
+ # A = 0.5 * (pmax + pmin)
+ B = 0.5 * (pmax - pmin)
+ if (B > 0) & (parameters [i] < pmax) & (parameters [i] > pmin):
+ sigma_par [i] = abs(B * numpy.cos(parameters[i]) * sigma0[n_free])
+ n_free += 1
+ else:
+ sigma_par [i] = parameters[i]
+ elif abs(constraints[i][0]) == CFIXED:
+ sigma_par[i] = parameters[i]
+ for i in range(len(constraints)):
+ if constraints[i][0] == CFACTOR:
+ sigma_par [i] = constraints[i][2]*sigma_par[int(constraints[i][1])]
+ elif constraints[i][0] == CDELTA:
+ sigma_par [i] = sigma_par[int(constraints[i][1])]
+ elif constraints[i][0] == CSUM:
+ sigma_par [i] = sigma_par[int(constraints[i][1])]
+ return sigma_par
+
+
+def main(argv=None):
+ if argv is None:
+ npoints = 10000
+ elif hasattr(argv, "__len__"):
+ if len(argv) > 1:
+ npoints = int(argv[1])
+ else:
+ print("Usage:")
+ print("fit [npoints]")
+ else:
+ # expected a number
+ npoints = argv
+
+ def gauss(t0, *param0):
+ param = numpy.array(param0)
+ t = numpy.array(t0)
+ dummy = 2.3548200450309493 * (t - param[3]) / param[4]
+ return param[0] + param[1] * t + param[2] * myexp(-0.5 * dummy * dummy)
+
+
+ def myexp(x):
+ # put a (bad) filter to avoid over/underflows
+ # with no python looping
+ return numpy.exp(x * numpy.less(abs(x), 250)) -\
+ 1.0 * numpy.greater_equal(abs(x), 250)
+
+ xx = numpy.arange(npoints, dtype=numpy.float)
+ yy = gauss(xx, *[10.5, 2, 1000.0, 20., 15])
+ sy = numpy.sqrt(abs(yy))
+ parameters = [0.0, 1.0, 900.0, 25., 10]
+ stime = time.time()
+
+ fittedpar, cov, ddict = leastsq(gauss, xx, yy, parameters,
+ sigma=sy,
+ left_derivative=False,
+ full_output=True,
+ check_finite=True)
+ etime = time.time()
+ sigmapars = numpy.sqrt(numpy.diag(cov))
+ print("Took ", etime - stime, "seconds")
+ print("Function calls = ", ddict["nfev"])
+ print("chi square = ", ddict["chisq"])
+ print("Fitted pars = ", fittedpar)
+ print("Sigma pars = ", sigmapars)
+ try:
+ from scipy.optimize import curve_fit as cfit
+ SCIPY = True
+ except ImportError:
+ SCIPY = False
+ if SCIPY:
+ counter = 0
+ stime = time.time()
+ scipy_fittedpar, scipy_cov = cfit(gauss,
+ xx,
+ yy,
+ parameters,
+ sigma=sy)
+ etime = time.time()
+ print("Scipy Took ", etime - stime, "seconds")
+ print("Counter = ", counter)
+ print("scipy = ", scipy_fittedpar)
+ print("Sigma = ", numpy.sqrt(numpy.diag(scipy_cov)))
+
+if __name__ == "__main__":
+ main()
diff --git a/silx/math/fit/peaks/include/peaks.h b/silx/math/fit/peaks/include/peaks.h
new file mode 100644
index 0000000..bd25d96
--- /dev/null
+++ b/silx/math/fit/peaks/include/peaks.h
@@ -0,0 +1,32 @@
+/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+#ifndef PEAKS_H
+#define PEAKS_H
+
+/* Smoothing functions */
+
+long seek(long begin_index, long end_index, long nsamples, double fwhm, double sensitivity,
+ double debug_info, double *data, double **peaks, double **relevances);
+
+#endif /* #define PEAKS_H */
diff --git a/silx/math/fit/peaks/peaks.c b/silx/math/fit/peaks/peaks.c
new file mode 100644
index 0000000..e7d9ddc
--- /dev/null
+++ b/silx/math/fit/peaks/peaks.c
@@ -0,0 +1,17746 @@
+/* Generated by Cython 0.21.1 */
+
+#define PY_SSIZE_T_CLEAN
+#ifndef CYTHON_USE_PYLONG_INTERNALS
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#else
+#include "pyconfig.h"
+#ifdef PYLONG_BITS_IN_DIGIT
+#define CYTHON_USE_PYLONG_INTERNALS 1
+#else
+#define CYTHON_USE_PYLONG_INTERNALS 0
+#endif
+#endif
+#endif
+#include "Python.h"
+#ifndef Py_PYTHON_H
+ #error Python headers needed to compile C extensions, please install development version of Python.
+#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000)
+ #error Cython requires Python 2.6+ or Python 3.2+.
+#else
+#define CYTHON_ABI "0_21_1"
+#include <stddef.h>
+#ifndef offsetof
+#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
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+#if !defined(WIN32) && !defined(MS_WINDOWS)
+ #ifndef __stdcall
+ #define __stdcall
+ #endif
+ #ifndef __cdecl
+ #define __cdecl
+ #endif
+ #ifndef __fastcall
+ #define __fastcall
+ #endif
+#endif
+#ifndef DL_IMPORT
+ #define DL_IMPORT(t) t
+#endif
+#ifndef DL_EXPORT
+ #define DL_EXPORT(t) t
+#endif
+#ifndef PY_LONG_LONG
+ #define PY_LONG_LONG LONG_LONG
+#endif
+#ifndef Py_HUGE_VAL
+ #define Py_HUGE_VAL HUGE_VAL
+#endif
+#ifdef PYPY_VERSION
+#define CYTHON_COMPILING_IN_PYPY 1
+#define CYTHON_COMPILING_IN_CPYTHON 0
+#else
+#define CYTHON_COMPILING_IN_PYPY 0
+#define CYTHON_COMPILING_IN_CPYTHON 1
+#endif
+#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600
+#define Py_OptimizeFlag 0
+#endif
+#define __PYX_BUILD_PY_SSIZE_T "n"
+#define CYTHON_FORMAT_SSIZE_T "z"
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyClass_Type
+#else
+ #define __Pyx_BUILTIN_MODULE_NAME "builtins"
+ #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
+ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+ #define __Pyx_DefaultClassType PyType_Type
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define Py_TPFLAGS_CHECKTYPES 0
+ #define Py_TPFLAGS_HAVE_INDEX 0
+ #define Py_TPFLAGS_HAVE_NEWBUFFER 0
+#endif
+#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE)
+ #define Py_TPFLAGS_HAVE_FINALIZE 0
+#endif
+#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
+ #define CYTHON_PEP393_ENABLED 1
+ #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \
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+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
+ #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u)
+ #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u)
+ #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
+#else
+ #define CYTHON_PEP393_ENABLED 0
+ #define __Pyx_PyUnicode_READY(op) (0)
+ #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
+ #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
+ #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
+ #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
+ #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
+#endif
+#if CYTHON_COMPILING_IN_PYPY
+ #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
+ #define __Pyx_PyFrozenSet_Size(s) PyObject_Size(s)
+#else
+ #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
+ #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \
+ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
+ #define __Pyx_PyFrozenSet_Size(s) PySet_Size(s)
+#endif
+#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
+#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
+#else
+ #define __Pyx_PyString_Format(a, b) PyString_Format(a, b)
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBaseString_Type PyUnicode_Type
+ #define PyStringObject PyUnicodeObject
+ #define PyString_Type PyUnicode_Type
+ #define PyString_Check PyUnicode_Check
+ #define PyString_CheckExact PyUnicode_CheckExact
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
+ #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
+#else
+ #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
+ #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
+#endif
+#ifndef PySet_CheckExact
+ #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
+#endif
+#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
+#if PY_MAJOR_VERSION >= 3
+ #define PyIntObject PyLongObject
+ #define PyInt_Type PyLong_Type
+ #define PyInt_Check(op) PyLong_Check(op)
+ #define PyInt_CheckExact(op) PyLong_CheckExact(op)
+ #define PyInt_FromString PyLong_FromString
+ #define PyInt_FromUnicode PyLong_FromUnicode
+ #define PyInt_FromLong PyLong_FromLong
+ #define PyInt_FromSize_t PyLong_FromSize_t
+ #define PyInt_FromSsize_t PyLong_FromSsize_t
+ #define PyInt_AsLong PyLong_AsLong
+ #define PyInt_AS_LONG PyLong_AS_LONG
+ #define PyInt_AsSsize_t PyLong_AsSsize_t
+ #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
+ #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
+ #define PyNumber_Int PyNumber_Long
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define PyBoolObject PyLongObject
+#endif
+#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
+ #ifndef PyUnicode_InternFromString
+ #define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
+ #endif
+#endif
+#if PY_VERSION_HEX < 0x030200A4
+ typedef long Py_hash_t;
+ #define __Pyx_PyInt_FromHash_t PyInt_FromLong
+ #define __Pyx_PyInt_AsHash_t PyInt_AsLong
+#else
+ #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
+ #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
+#endif
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
+#else
+ #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
+#endif
+#ifndef CYTHON_INLINE
+ #if defined(__GNUC__)
+ #define CYTHON_INLINE __inline__
+ #elif defined(_MSC_VER)
+ #define CYTHON_INLINE __inline
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_INLINE inline
+ #else
+ #define CYTHON_INLINE
+ #endif
+#endif
+#ifndef CYTHON_RESTRICT
+ #if defined(__GNUC__)
+ #define CYTHON_RESTRICT __restrict__
+ #elif defined(_MSC_VER) && _MSC_VER >= 1400
+ #define CYTHON_RESTRICT __restrict
+ #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+ #define CYTHON_RESTRICT restrict
+ #else
+ #define CYTHON_RESTRICT
+ #endif
+#endif
+#ifdef NAN
+#define __PYX_NAN() ((float) NAN)
+#else
+static CYTHON_INLINE float __PYX_NAN() {
+ /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and
+ a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is
+ a quiet NaN. */
+ float value;
+ memset(&value, 0xFF, sizeof(value));
+ return value;
+}
+#endif
+#ifdef __cplusplus
+template<typename T>
+void __Pyx_call_destructor(T* x) {
+ x->~T();
+}
+#endif
+
+
+#if PY_MAJOR_VERSION >= 3
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y)
+#else
+ #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y)
+ #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y)
+#endif
+
+#ifndef __PYX_EXTERN_C
+ #ifdef __cplusplus
+ #define __PYX_EXTERN_C extern "C"
+ #else
+ #define __PYX_EXTERN_C extern
+ #endif
+#endif
+
+#if defined(WIN32) || defined(MS_WINDOWS)
+#define _USE_MATH_DEFINES
+#endif
+#include <math.h>
+#define __PYX_HAVE__peaks
+#define __PYX_HAVE_API__peaks
+#include "string.h"
+#include "stdlib.h"
+#include "peaks.h"
+#include "pythread.h"
+#include "stdio.h"
+#include "pystate.h"
+#ifdef _OPENMP
+#include <omp.h>
+#endif /* _OPENMP */
+
+#ifdef PYREX_WITHOUT_ASSERTIONS
+#define CYTHON_WITHOUT_ASSERTIONS
+#endif
+
+#ifndef CYTHON_UNUSED
+# if defined(__GNUC__)
+# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
+# define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+# define CYTHON_UNUSED
+# endif
+#endif
+typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding;
+ const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
+
+#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
+#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
+#define __PYX_DEFAULT_STRING_ENCODING ""
+#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
+#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#define __Pyx_fits_Py_ssize_t(v, type, is_signed) ( \
+ (sizeof(type) < sizeof(Py_ssize_t)) || \
+ (sizeof(type) > sizeof(Py_ssize_t) && \
+ likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX) && \
+ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN || \
+ v == (type)PY_SSIZE_T_MIN))) || \
+ (sizeof(type) == sizeof(Py_ssize_t) && \
+ (is_signed || likely(v < (type)PY_SSIZE_T_MAX || \
+ v == (type)PY_SSIZE_T_MAX))) )
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
+#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
+#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
+#define __Pyx_PyBytes_FromString PyBytes_FromString
+#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
+#if PY_MAJOR_VERSION < 3
+ #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#else
+ #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
+ #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
+#endif
+#define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_FromUString(s) __Pyx_PyObject_FromString((const char*)s)
+#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((const char*)s)
+#define __Pyx_PyByteArray_FromUString(s) __Pyx_PyByteArray_FromString((const char*)s)
+#define __Pyx_PyStr_FromUString(s) __Pyx_PyStr_FromString((const char*)s)
+#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((const char*)s)
+#if PY_MAJOR_VERSION < 3
+static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
+{
+ const Py_UNICODE *u_end = u;
+ while (*u_end++) ;
+ return (size_t)(u_end - u - 1);
+}
+#else
+#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
+#endif
+#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
+#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
+#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
+#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
+#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
+#if CYTHON_COMPILING_IN_CPYTHON
+#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
+#else
+#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
+#endif
+#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+static int __Pyx_sys_getdefaultencoding_not_ascii;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ PyObject* ascii_chars_u = NULL;
+ PyObject* ascii_chars_b = NULL;
+ const char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ if (strcmp(default_encoding_c, "ascii") == 0) {
+ __Pyx_sys_getdefaultencoding_not_ascii = 0;
+ } else {
+ char ascii_chars[128];
+ int c;
+ for (c = 0; c < 128; c++) {
+ ascii_chars[c] = c;
+ }
+ __Pyx_sys_getdefaultencoding_not_ascii = 1;
+ ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
+ if (!ascii_chars_u) goto bad;
+ ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
+ if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
+ PyErr_Format(
+ PyExc_ValueError,
+ "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
+ default_encoding_c);
+ goto bad;
+ }
+ Py_DECREF(ascii_chars_u);
+ Py_DECREF(ascii_chars_b);
+ }
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ Py_XDECREF(ascii_chars_u);
+ Py_XDECREF(ascii_chars_b);
+ return -1;
+}
+#endif
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
+#else
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+static char* __PYX_DEFAULT_STRING_ENCODING;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+ PyObject* sys;
+ PyObject* default_encoding = NULL;
+ char* default_encoding_c;
+ sys = PyImport_ImportModule("sys");
+ if (!sys) goto bad;
+ default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+ Py_DECREF(sys);
+ if (!default_encoding) goto bad;
+ default_encoding_c = PyBytes_AsString(default_encoding);
+ if (!default_encoding_c) goto bad;
+ __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
+ if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
+ strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
+ Py_DECREF(default_encoding);
+ return 0;
+bad:
+ Py_XDECREF(default_encoding);
+ return -1;
+}
+#endif
+#endif
+
+
+/* Test for GCC > 2.95 */
+#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
+ #define likely(x) __builtin_expect(!!(x), 1)
+ #define unlikely(x) __builtin_expect(!!(x), 0)
+#else /* !__GNUC__ or GCC < 2.95 */
+ #define likely(x) (x)
+ #define unlikely(x) (x)
+#endif /* __GNUC__ */
+
+static PyObject *__pyx_m;
+static PyObject *__pyx_d;
+static PyObject *__pyx_b;
+static PyObject *__pyx_empty_tuple;
+static PyObject *__pyx_empty_bytes;
+static int __pyx_lineno;
+static int __pyx_clineno = 0;
+static const char * __pyx_cfilenm= __FILE__;
+static const char *__pyx_filename;
+
+
+static const char *__pyx_f[] = {
+ "peaks.pyx",
+ "stringsource",
+};
+struct __pyx_memoryview_obj;
+typedef struct {
+ struct __pyx_memoryview_obj *memview;
+ char *data;
+ Py_ssize_t shape[8];
+ Py_ssize_t strides[8];
+ Py_ssize_t suboffsets[8];
+} __Pyx_memviewslice;
+
+#define IS_UNSIGNED(type) (((type) -1) > 0)
+struct __Pyx_StructField_;
+#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
+typedef struct {
+ const char* name;
+ struct __Pyx_StructField_* fields;
+ size_t size;
+ size_t arraysize[8];
+ int ndim;
+ char typegroup;
+ char is_unsigned;
+ int flags;
+} __Pyx_TypeInfo;
+typedef struct __Pyx_StructField_ {
+ __Pyx_TypeInfo* type;
+ const char* name;
+ size_t offset;
+} __Pyx_StructField;
+typedef struct {
+ __Pyx_StructField* field;
+ size_t parent_offset;
+} __Pyx_BufFmt_StackElem;
+typedef struct {
+ __Pyx_StructField root;
+ __Pyx_BufFmt_StackElem* head;
+ size_t fmt_offset;
+ size_t new_count, enc_count;
+ size_t struct_alignment;
+ int is_complex;
+ char enc_type;
+ char new_packmode;
+ char enc_packmode;
+ char is_valid_array;
+} __Pyx_BufFmt_Context;
+
+#include <pythread.h>
+#ifndef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 1
+#endif
+#define __pyx_atomic_int_type int
+#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 || \
+ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \
+ !defined(__i386__)
+ #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
+ #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using GNU atomics"
+ #endif
+#elif CYTHON_ATOMICS && MSC_VER
+ #include <Windows.h>
+ #define __pyx_atomic_int_type LONG
+ #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using MSVC atomics"
+ #endif
+#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
+ #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
+ #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Using Intel atomics"
+ #endif
+#else
+ #undef CYTHON_ATOMICS
+ #define CYTHON_ATOMICS 0
+ #ifdef __PYX_DEBUG_ATOMICS
+ #warning "Not using atomics"
+ #endif
+#endif
+typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
+#if CYTHON_ATOMICS
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
+#else
+ #define __pyx_add_acquisition_count(memview) \
+ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+ #define __pyx_sub_acquisition_count(memview) \
+ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+#endif
+
+
+/*--- Type declarations ---*/
+struct __pyx_array_obj;
+struct __pyx_MemviewEnum_obj;
+struct __pyx_memoryview_obj;
+struct __pyx_memoryviewslice_obj;
+
+/* "View.MemoryView":99
+ *
+ * @cname("__pyx_array")
+ * cdef class array: # <<<<<<<<<<<<<<
+ *
+ * cdef:
+ */
+struct __pyx_array_obj {
+ PyObject_HEAD
+ char *data;
+ Py_ssize_t len;
+ char *format;
+ int ndim;
+ Py_ssize_t *_shape;
+ Py_ssize_t *_strides;
+ Py_ssize_t itemsize;
+ PyObject *mode;
+ PyObject *_format;
+ void (*callback_free_data)(void *);
+ int free_data;
+ int dtype_is_object;
+};
+
+
+/* "View.MemoryView":269
+ *
+ * @cname('__pyx_MemviewEnum')
+ * cdef class Enum(object): # <<<<<<<<<<<<<<
+ * cdef object name
+ * def __init__(self, name):
+ */
+struct __pyx_MemviewEnum_obj {
+ PyObject_HEAD
+ PyObject *name;
+};
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+struct __pyx_memoryview_obj {
+ PyObject_HEAD
+ struct __pyx_vtabstruct_memoryview *__pyx_vtab;
+ PyObject *obj;
+ PyObject *_size;
+ PyObject *_array_interface;
+ PyThread_type_lock lock;
+ __pyx_atomic_int acquisition_count[2];
+ __pyx_atomic_int *acquisition_count_aligned_p;
+ Py_buffer view;
+ int flags;
+ int dtype_is_object;
+ __Pyx_TypeInfo *typeinfo;
+};
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+struct __pyx_memoryviewslice_obj {
+ struct __pyx_memoryview_obj __pyx_base;
+ __Pyx_memviewslice from_slice;
+ PyObject *from_object;
+ PyObject *(*to_object_func)(char *);
+ int (*to_dtype_func)(char *, PyObject *);
+};
+
+
+
+/* "View.MemoryView":302
+ *
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object): # <<<<<<<<<<<<<<
+ *
+ * cdef object obj
+ */
+
+struct __pyx_vtabstruct_memoryview {
+ char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
+ PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+ PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
+ PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
+};
+static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
+
+
+/* "View.MemoryView":922
+ *
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
+ * "Internal class for passing memoryview slices to Python"
+ *
+ */
+
+struct __pyx_vtabstruct__memoryviewslice {
+ struct __pyx_vtabstruct_memoryview __pyx_base;
+};
+static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
+#ifndef CYTHON_REFNANNY
+ #define CYTHON_REFNANNY 0
+#endif
+#if CYTHON_REFNANNY
+ typedef struct {
+ void (*INCREF)(void*, PyObject*, int);
+ void (*DECREF)(void*, PyObject*, int);
+ void (*GOTREF)(void*, PyObject*, int);
+ void (*GIVEREF)(void*, PyObject*, int);
+ void* (*SetupContext)(const char*, int, const char*);
+ void (*FinishContext)(void**);
+ } __Pyx_RefNannyAPIStruct;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
+ static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname);
+ #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL;
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+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
+ if (acquire_gil) { \
+ PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \
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+ #define __Pyx_RefNannySetupContext(name, acquire_gil) \
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+ __Pyx_RefNanny->FinishContext(&__pyx_refnanny)
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+ #define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GOTREF(r) __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+ #define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
+ #define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
+ #define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
+ #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
+#else
+ #define __Pyx_RefNannyDeclarations
+ #define __Pyx_RefNannySetupContext(name, acquire_gil)
+ #define __Pyx_RefNannyFinishContext()
+ #define __Pyx_INCREF(r) Py_INCREF(r)
+ #define __Pyx_DECREF(r) Py_DECREF(r)
+ #define __Pyx_GOTREF(r)
+ #define __Pyx_GIVEREF(r)
+ #define __Pyx_XINCREF(r) Py_XINCREF(r)
+ #define __Pyx_XDECREF(r) Py_XDECREF(r)
+ #define __Pyx_XGOTREF(r)
+ #define __Pyx_XGIVEREF(r)
+#endif
+#define __Pyx_XDECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_XDECREF(tmp); \
+ } while (0)
+#define __Pyx_DECREF_SET(r, v) do { \
+ PyObject *tmp = (PyObject *) r; \
+ r = v; __Pyx_DECREF(tmp); \
+ } while (0)
+#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
+#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
+ PyTypeObject* tp = Py_TYPE(obj);
+ if (likely(tp->tp_getattro))
+ return tp->tp_getattro(obj, attr_name);
+#if PY_MAJOR_VERSION < 3
+ if (likely(tp->tp_getattr))
+ return tp->tp_getattr(obj, PyString_AS_STRING(attr_name));
+#endif
+ return PyObject_GetAttr(obj, attr_name);
+}
+#else
+#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
+#endif
+
+static PyObject *__Pyx_GetBuiltinName(PyObject *name);
+
+static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
+ Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
+
+static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
+
+static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \
+ PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \
+ const char* function_name);
+
+static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
+#else
+#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
+#endif
+
+static void __Pyx_RaiseBufferIndexError(int axis);
+
+static CYTHON_INLINE unsigned long __Pyx_abs_long(long x) {
+ if (unlikely(x == -LONG_MAX-1))
+ return ((unsigned long)LONG_MAX) + 1U;
+ return (unsigned long) labs(x);
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
+#endif
+
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
+
+static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
+
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
+
+#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) : \
+ (is_list ? (PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) : \
+ __Pyx_SetItemInt_Generic(o, to_py_func(i), v)))
+static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v);
+static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v,
+ int is_list, int wraparound, int boundscheck);
+
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
+ __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
+
+#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
+#define __Pyx_MEMVIEW_DIRECT 1
+#define __Pyx_MEMVIEW_PTR 2
+#define __Pyx_MEMVIEW_FULL 4
+#define __Pyx_MEMVIEW_CONTIG 8
+#define __Pyx_MEMVIEW_STRIDED 16
+#define __Pyx_MEMVIEW_FOLLOW 32
+#define __Pyx_IS_C_CONTIG 1
+#define __Pyx_IS_F_CONTIG 2
+static int __Pyx_init_memviewslice(
+ struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference);
+static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
+ __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
+#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
+#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
+#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
+static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
+
+#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \
+ (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \
+ __Pyx_GetItemInt_Generic(o, to_py_func(i))))
+#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
+ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
+ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
+ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck);
+
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact);
+
+#include <string.h>
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
+
+#if PY_MAJOR_VERSION >= 3
+#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
+#else
+#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
+#endif
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */
+
+#ifndef __PYX_FORCE_INIT_THREADS
+ #define __PYX_FORCE_INIT_THREADS 0
+#endif
+
+#define UNARY_NEG_WOULD_OVERFLOW(x) (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))
+
+static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb);
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb);
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
+
+static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len)) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
+#endif
+
+static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/
+static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/
+static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject* none = _PyList_Extend((PyListObject*)L, v);
+ if (unlikely(!none))
+ return -1;
+ Py_DECREF(none);
+ return 0;
+#else
+ return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
+#endif
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
+ PyListObject* L = (PyListObject*) list;
+ Py_ssize_t len = Py_SIZE(list);
+ if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
+ Py_INCREF(x);
+ PyList_SET_ITEM(list, len, x);
+ Py_SIZE(list) = len+1;
+ return 0;
+ }
+ return PyList_Append(list, x);
+}
+#else
+#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
+#endif
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
+
+static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */
+
+static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/
+static void __Pyx_WriteUnraisable(const char *name, int clineno,
+ int lineno, const char *filename,
+ int full_traceback);
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable);
+
+static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
+#else
+#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL)
+#endif
+
+typedef struct {
+ int code_line;
+ PyCodeObject* code_object;
+} __Pyx_CodeObjectCacheEntry;
+struct __Pyx_CodeObjectCache {
+ int count;
+ int max_count;
+ __Pyx_CodeObjectCacheEntry* entries;
+};
+static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
+static PyCodeObject *__pyx_find_code_object(int code_line);
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
+
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename);
+
+typedef struct {
+ Py_ssize_t shape, strides, suboffsets;
+} __Pyx_Buf_DimInfo;
+typedef struct {
+ size_t refcount;
+ Py_buffer pybuffer;
+} __Pyx_Buffer;
+typedef struct {
+ __Pyx_Buffer *rcbuffer;
+ char *data;
+ __Pyx_Buf_DimInfo diminfo[8];
+} __Pyx_LocalBuf_ND;
+
+#if PY_MAJOR_VERSION < 3
+ static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
+ static void __Pyx_ReleaseBuffer(Py_buffer *view);
+#else
+ #define __Pyx_GetBuffer PyObject_GetBuffer
+ #define __Pyx_ReleaseBuffer PyBuffer_Release
+#endif
+
+
+static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
+static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
+
+static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
+
+static PyObject *__pyx_memview_get_double(const char *itemp);
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj);
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_long(unsigned long value);
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
+
+static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim);
+
+static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize);
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object);
+
+static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
+
+static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
+
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj);
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *);
+
+static int __Pyx_check_binary_version(void);
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
+
+static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
+static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+
+/* Module declarations from 'cython.view' */
+
+/* Module declarations from 'cython' */
+
+/* Module declarations from 'libc.string' */
+
+/* Module declarations from 'libc.stdlib' */
+
+/* Module declarations from 'peaks_wrapper' */
+
+/* Module declarations from 'peaks' */
+static PyTypeObject *__pyx_array_type = 0;
+static PyTypeObject *__pyx_MemviewEnum_type = 0;
+static PyTypeObject *__pyx_memoryview_type = 0;
+static PyTypeObject *__pyx_memoryviewslice_type = 0;
+static PyObject *generic = 0;
+static PyObject *strided = 0;
+static PyObject *indirect = 0;
+static PyObject *contiguous = 0;
+static PyObject *indirect_contiguous = 0;
+static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
+static void *__pyx_align_pointer(void *, size_t); /*proto*/
+static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
+static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
+static PyObject *_unellipsify(PyObject *, int); /*proto*/
+static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
+static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
+static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
+static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
+static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
+static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
+static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
+static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
+static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
+static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
+static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
+static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
+static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
+static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
+#define __Pyx_MODULE_NAME "peaks"
+int __pyx_module_is_main_peaks = 0;
+
+/* Implementation of 'peaks' */
+static PyObject *__pyx_builtin_range;
+static PyObject *__pyx_builtin_MemoryError;
+static PyObject *__pyx_builtin_zip;
+static PyObject *__pyx_builtin_max;
+static PyObject *__pyx_builtin_ValueError;
+static PyObject *__pyx_builtin_enumerate;
+static PyObject *__pyx_builtin_Ellipsis;
+static PyObject *__pyx_builtin_TypeError;
+static PyObject *__pyx_builtin_xrange;
+static PyObject *__pyx_builtin_id;
+static PyObject *__pyx_builtin_IndexError;
+static PyObject *__pyx_pf_5peaks_peak_search(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_y, PyObject *__pyx_v_fwhm, PyObject *__pyx_v_sensitivity, PyObject *__pyx_v_begin_index, PyObject *__pyx_v_end_index, PyObject *__pyx_v_debug, PyObject *__pyx_v_relevance_info); /* proto */
+static PyObject *__pyx_pf_5peaks_2guess_fwhm(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_y); /* proto */
+static int __pyx_array_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
+static int __pyx_array_getbuffer_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static void __pyx_array_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *get_memview_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
+static PyObject *__pyx_array_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
+static int __pyx_array_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
+static int __pyx_MemviewEnum_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
+static PyObject *__pyx_MemviewEnum_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
+static void __pyx_memoryview_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
+static int __pyx_memoryview_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
+static int __pyx_memoryview_getbuffer_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static PyObject *__pyx_memoryview_transpose_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview__get__base_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_shape_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_strides_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_suboffsets_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_ndim_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_itemsize_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_nbytes_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_get_size_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static Py_ssize_t __pyx_memoryview_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static void __pyx_memoryviewslice_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryviewslice__get__base_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static char __pyx_k_C[] = "C";
+static char __pyx_k_O[] = "O";
+static char __pyx_k_c[] = "c";
+static char __pyx_k_i[] = "i";
+static char __pyx_k_w[] = "w";
+static char __pyx_k_y[] = "y";
+static char __pyx_k__2[] = "";
+static char __pyx_k_id[] = "id";
+static char __pyx_k_MIT[] = "MIT";
+static char __pyx_k_idx[] = "idx";
+static char __pyx_k_max[] = "max";
+static char __pyx_k_msg[] = "msg";
+static char __pyx_k_obj[] = "obj";
+static char __pyx_k_y_c[] = "y_c";
+static char __pyx_k_zip[] = "zip";
+static char __pyx_k_base[] = "base";
+static char __pyx_k_copy[] = "copy";
+static char __pyx_k_date[] = "__date__";
+static char __pyx_k_fwhm[] = "fwhm";
+static char __pyx_k_imax[] = "imax";
+static char __pyx_k_imin[] = "imin";
+static char __pyx_k_main[] = "__main__";
+static char __pyx_k_mode[] = "mode";
+static char __pyx_k_name[] = "name";
+static char __pyx_k_ndim[] = "ndim";
+static char __pyx_k_pack[] = "pack";
+static char __pyx_k_size[] = "size";
+static char __pyx_k_step[] = "step";
+static char __pyx_k_stop[] = "stop";
+static char __pyx_k_test[] = "__test__";
+static char __pyx_k_yfit[] = "yfit";
+static char __pyx_k_array[] = "array";
+static char __pyx_k_class[] = "__class__";
+static char __pyx_k_debug[] = "debug";
+static char __pyx_k_dtype[] = "dtype";
+static char __pyx_k_empty[] = "empty";
+static char __pyx_k_error[] = "error";
+static char __pyx_k_flags[] = "flags";
+static char __pyx_k_numpy[] = "numpy";
+static char __pyx_k_order[] = "order";
+static char __pyx_k_peaks[] = "peaks";
+static char __pyx_k_range[] = "range";
+static char __pyx_k_shape[] = "shape";
+static char __pyx_k_start[] = "start";
+static char __pyx_k_strip[] = "strip";
+static char __pyx_k_format[] = "format";
+static char __pyx_k_height[] = "height";
+static char __pyx_k_import[] = "__import__";
+static char __pyx_k_logger[] = "_logger";
+static char __pyx_k_name_2[] = "__name__";
+static char __pyx_k_struct[] = "struct";
+static char __pyx_k_unpack[] = "unpack";
+static char __pyx_k_xrange[] = "xrange";
+static char __pyx_k_authors[] = "__authors__";
+static char __pyx_k_filters[] = "filters";
+static char __pyx_k_float64[] = "float64";
+static char __pyx_k_fortran[] = "fortran";
+static char __pyx_k_license[] = "__license__";
+static char __pyx_k_logging[] = "logging";
+static char __pyx_k_maximum[] = "maximum";
+static char __pyx_k_memview[] = "memview";
+static char __pyx_k_n_peaks[] = "n_peaks";
+static char __pyx_k_nonzero[] = "nonzero";
+static char __pyx_k_peaks_c[] = "peaks_c";
+static char __pyx_k_reshape[] = "reshape";
+static char __pyx_k_Ellipsis[] = "Ellipsis";
+static char __pyx_k_P_Knobel[] = "P. Knobel";
+static char __pyx_k_fwhm_min[] = "fwhm_min";
+static char __pyx_k_itemsize[] = "itemsize";
+static char __pyx_k_posindex[] = "posindex";
+static char __pyx_k_TypeError[] = "TypeError";
+static char __pyx_k_end_index[] = "end_index";
+static char __pyx_k_enumerate[] = "enumerate";
+static char __pyx_k_getLogger[] = "getLogger";
+static char __pyx_k_17_06_2016[] = "17/06/2016";
+static char __pyx_k_IndexError[] = "IndexError";
+static char __pyx_k_ValueError[] = "ValueError";
+static char __pyx_k_background[] = "background";
+static char __pyx_k_guess_fwhm[] = "guess_fwhm";
+static char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
+static char __pyx_k_relevances[] = "relevances";
+static char __pyx_k_MemoryError[] = "MemoryError";
+static char __pyx_k_basicConfig[] = "basicConfig";
+static char __pyx_k_begin_index[] = "begin_index";
+static char __pyx_k_niterations[] = "niterations";
+static char __pyx_k_peak_search[] = "peak_search";
+static char __pyx_k_relevance_f[] = "relevance %f\n";
+static char __pyx_k_sensitivity[] = "sensitivity";
+static char __pyx_k_peak_index_f[] = "peak index %f, ";
+static char __pyx_k_relevances_c[] = "relevances_c";
+static char __pyx_k_output_arrays[] = "output arrays";
+static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
+static char __pyx_k_relevance_info[] = "relevance_info";
+static char __pyx_k_allocate_buffer[] = "allocate_buffer";
+static char __pyx_k_dtype_is_object[] = "dtype_is_object";
+static char __pyx_k_we_found_d_peaks[] = "we found %d peaks.\n";
+static char __pyx_k_strided_and_direct[] = "<strided and direct>";
+static char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
+static char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
+static char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
+static char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
+static char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
+static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
+static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)";
+static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct";
+static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
+static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)";
+static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)";
+static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
+static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
+static char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
+static char __pyx_k_Failed_to_reallocate_memory_for[] = "Failed to reallocate memory for output arrays";
+static char __pyx_k_mntdirect__scisoft_users_tvince[] = "/mntdirect/_scisoft/users/tvincent/src/silx/silx/math/fit/peaks/peaks.pyx";
+static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced";
+static char __pyx_k_Before_memory_allocation_error_h[] = "Before memory allocation error happened, ";
+static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
+static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
+static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions";
+static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
+static char __pyx_k_Failed_to_allocate_initial_memor[] = "Failed to allocate initial memory for ";
+static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
+static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
+static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
+static char __pyx_k_This_module_provides_a_peak_sear[] = "This module provides a peak search function and tools related to peak\nanalysis.\n";
+static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
+static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
+static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
+static PyObject *__pyx_kp_s_17_06_2016;
+static PyObject *__pyx_kp_s_Before_memory_allocation_error_h;
+static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
+static PyObject *__pyx_n_s_C;
+static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
+static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
+static PyObject *__pyx_n_s_Ellipsis;
+static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
+static PyObject *__pyx_kp_s_Failed_to_allocate_initial_memor;
+static PyObject *__pyx_kp_s_Failed_to_reallocate_memory_for;
+static PyObject *__pyx_n_s_IndexError;
+static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
+static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
+static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
+static PyObject *__pyx_n_s_MIT;
+static PyObject *__pyx_n_s_MemoryError;
+static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
+static PyObject *__pyx_kp_s_MemoryView_of_r_object;
+static PyObject *__pyx_n_b_O;
+static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
+static PyObject *__pyx_kp_s_P_Knobel;
+static PyObject *__pyx_n_s_TypeError;
+static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
+static PyObject *__pyx_n_s_ValueError;
+static PyObject *__pyx_kp_s__2;
+static PyObject *__pyx_n_s_allocate_buffer;
+static PyObject *__pyx_n_s_array;
+static PyObject *__pyx_n_s_authors;
+static PyObject *__pyx_n_s_background;
+static PyObject *__pyx_n_s_base;
+static PyObject *__pyx_n_s_basicConfig;
+static PyObject *__pyx_n_s_begin_index;
+static PyObject *__pyx_n_s_c;
+static PyObject *__pyx_n_u_c;
+static PyObject *__pyx_n_s_class;
+static PyObject *__pyx_kp_s_contiguous_and_direct;
+static PyObject *__pyx_kp_s_contiguous_and_indirect;
+static PyObject *__pyx_n_s_copy;
+static PyObject *__pyx_n_s_date;
+static PyObject *__pyx_n_s_debug;
+static PyObject *__pyx_n_s_dtype;
+static PyObject *__pyx_n_s_dtype_is_object;
+static PyObject *__pyx_n_s_empty;
+static PyObject *__pyx_n_s_end_index;
+static PyObject *__pyx_n_s_enumerate;
+static PyObject *__pyx_n_s_error;
+static PyObject *__pyx_n_s_filters;
+static PyObject *__pyx_n_s_flags;
+static PyObject *__pyx_n_s_float64;
+static PyObject *__pyx_n_s_format;
+static PyObject *__pyx_n_s_fortran;
+static PyObject *__pyx_n_u_fortran;
+static PyObject *__pyx_n_s_fwhm;
+static PyObject *__pyx_n_s_fwhm_min;
+static PyObject *__pyx_n_s_getLogger;
+static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
+static PyObject *__pyx_n_s_guess_fwhm;
+static PyObject *__pyx_n_s_height;
+static PyObject *__pyx_n_s_i;
+static PyObject *__pyx_n_s_id;
+static PyObject *__pyx_n_s_idx;
+static PyObject *__pyx_n_s_imax;
+static PyObject *__pyx_n_s_imin;
+static PyObject *__pyx_n_s_import;
+static PyObject *__pyx_n_s_itemsize;
+static PyObject *__pyx_kp_s_itemsize_0_for_cython_array;
+static PyObject *__pyx_n_s_license;
+static PyObject *__pyx_n_s_logger;
+static PyObject *__pyx_n_s_logging;
+static PyObject *__pyx_n_s_main;
+static PyObject *__pyx_n_s_max;
+static PyObject *__pyx_n_s_maximum;
+static PyObject *__pyx_n_s_memview;
+static PyObject *__pyx_kp_s_mntdirect__scisoft_users_tvince;
+static PyObject *__pyx_n_s_mode;
+static PyObject *__pyx_n_s_msg;
+static PyObject *__pyx_n_s_n_peaks;
+static PyObject *__pyx_n_s_name;
+static PyObject *__pyx_n_s_name_2;
+static PyObject *__pyx_n_s_ndim;
+static PyObject *__pyx_n_s_niterations;
+static PyObject *__pyx_n_s_nonzero;
+static PyObject *__pyx_n_s_numpy;
+static PyObject *__pyx_n_s_obj;
+static PyObject *__pyx_n_s_order;
+static PyObject *__pyx_kp_s_output_arrays;
+static PyObject *__pyx_n_s_pack;
+static PyObject *__pyx_kp_s_peak_index_f;
+static PyObject *__pyx_n_s_peak_search;
+static PyObject *__pyx_n_s_peaks;
+static PyObject *__pyx_n_s_peaks_c;
+static PyObject *__pyx_n_s_posindex;
+static PyObject *__pyx_n_s_pyx_getbuffer;
+static PyObject *__pyx_n_s_pyx_vtable;
+static PyObject *__pyx_n_s_range;
+static PyObject *__pyx_kp_s_relevance_f;
+static PyObject *__pyx_n_s_relevance_info;
+static PyObject *__pyx_n_s_relevances;
+static PyObject *__pyx_n_s_relevances_c;
+static PyObject *__pyx_n_s_reshape;
+static PyObject *__pyx_n_s_sensitivity;
+static PyObject *__pyx_n_s_shape;
+static PyObject *__pyx_n_s_size;
+static PyObject *__pyx_n_s_start;
+static PyObject *__pyx_n_s_step;
+static PyObject *__pyx_n_s_stop;
+static PyObject *__pyx_kp_s_strided_and_direct;
+static PyObject *__pyx_kp_s_strided_and_direct_or_indirect;
+static PyObject *__pyx_kp_s_strided_and_indirect;
+static PyObject *__pyx_n_s_strip;
+static PyObject *__pyx_n_s_struct;
+static PyObject *__pyx_n_s_test;
+static PyObject *__pyx_kp_s_unable_to_allocate_array_data;
+static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str;
+static PyObject *__pyx_n_s_unpack;
+static PyObject *__pyx_n_s_w;
+static PyObject *__pyx_kp_s_we_found_d_peaks;
+static PyObject *__pyx_n_s_xrange;
+static PyObject *__pyx_n_s_y;
+static PyObject *__pyx_n_s_y_c;
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+ * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil:
+ * if arg < 0: # <<<<<<<<<<<<<<
+ * return -arg
+ * else:
+ */
+ __pyx_t_1 = ((__pyx_v_arg < 0) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1064
+ * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil:
+ * if arg < 0:
+ * return -arg # <<<<<<<<<<<<<<
+ * else:
+ * return arg
+ */
+ __pyx_r = (-__pyx_v_arg);
+ goto __pyx_L0;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1066
+ * return -arg
+ * else:
+ * return arg # <<<<<<<<<<<<<<
+ *
+ * @cname('__pyx_get_best_slice_order')
+ */
+ __pyx_r = __pyx_v_arg;
+ goto __pyx_L0;
+ }
+
+ /* "View.MemoryView":1062
+ *
+ *
+ * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<<
+ * if arg < 0:
+ * return -arg
+ */
+
+ /* function exit code */
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":1069
+ *
+ * @cname('__pyx_get_best_slice_order')
+ * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<<
+ * """
+ * Figure out the best memory access order for a given slice.
+ */
+
+static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) {
+ int __pyx_v_i;
+ Py_ssize_t __pyx_v_c_stride;
+ Py_ssize_t __pyx_v_f_stride;
+ char __pyx_r;
+ int __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+
+ /* "View.MemoryView":1074
+ * """
+ * cdef int i
+ * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t f_stride = 0
+ *
+ */
+ __pyx_v_c_stride = 0;
+
+ /* "View.MemoryView":1075
+ * cdef int i
+ * cdef Py_ssize_t c_stride = 0
+ * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<<
+ *
+ * for i in range(ndim - 1, -1, -1):
+ */
+ __pyx_v_f_stride = 0;
+
+ /* "View.MemoryView":1077
+ * cdef Py_ssize_t f_stride = 0
+ *
+ * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
+ * if mslice.shape[i] > 1:
+ * c_stride = mslice.strides[i]
+ */
+ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) {
+ __pyx_v_i = __pyx_t_1;
+
+ /* "View.MemoryView":1078
+ *
+ * for i in range(ndim - 1, -1, -1):
+ * if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
+ * c_stride = mslice.strides[i]
+ * break
+ */
+ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1079
+ * for i in range(ndim - 1, -1, -1):
+ * if mslice.shape[i] > 1:
+ * c_stride = mslice.strides[i] # <<<<<<<<<<<<<<
+ * break
+ *
+ */
+ __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]);
+
+ /* "View.MemoryView":1080
+ * if mslice.shape[i] > 1:
+ * c_stride = mslice.strides[i]
+ * break # <<<<<<<<<<<<<<
+ *
+ * for i in range(ndim):
+ */
+ goto __pyx_L4_break;
+ }
+ }
+ __pyx_L4_break:;
+
+ /* "View.MemoryView":1082
+ * break
+ *
+ * for i in range(ndim): # <<<<<<<<<<<<<<
+ * if mslice.shape[i] > 1:
+ * f_stride = mslice.strides[i]
+ */
+ __pyx_t_1 = __pyx_v_ndim;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1083
+ *
+ * for i in range(ndim):
+ * if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
+ * f_stride = mslice.strides[i]
+ * break
+ */
+ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1084
+ * for i in range(ndim):
+ * if mslice.shape[i] > 1:
+ * f_stride = mslice.strides[i] # <<<<<<<<<<<<<<
+ * break
+ *
+ */
+ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]);
+
+ /* "View.MemoryView":1085
+ * if mslice.shape[i] > 1:
+ * f_stride = mslice.strides[i]
+ * break # <<<<<<<<<<<<<<
+ *
+ * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
+ */
+ goto __pyx_L7_break;
+ }
+ }
+ __pyx_L7_break:;
+
+ /* "View.MemoryView":1087
+ * break
+ *
+ * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<<
+ * return 'C'
+ * else:
+ */
+ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0);
+ if (__pyx_t_2) {
+
+ /* "View.MemoryView":1088
+ *
+ * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
+ * return 'C' # <<<<<<<<<<<<<<
+ * else:
+ * return 'F'
+ */
+ __pyx_r = 'C';
+ goto __pyx_L0;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1090
+ * return 'C'
+ * else:
+ * return 'F' # <<<<<<<<<<<<<<
+ *
+ * @cython.cdivision(True)
+ */
+ __pyx_r = 'F';
+ goto __pyx_L0;
+ }
+
+ /* "View.MemoryView":1069
+ *
+ * @cname('__pyx_get_best_slice_order')
+ * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<<
+ * """
+ * Figure out the best memory access order for a given slice.
+ */
+
+ /* function exit code */
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":1093
+ *
+ * @cython.cdivision(True)
+ * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<<
+ * char *dst_data, Py_ssize_t *dst_strides,
+ * Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
+ CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+ CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
+ Py_ssize_t __pyx_v_dst_extent;
+ Py_ssize_t __pyx_v_src_stride;
+ Py_ssize_t __pyx_v_dst_stride;
+ int __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+ Py_ssize_t __pyx_t_4;
+ Py_ssize_t __pyx_t_5;
+
+ /* "View.MemoryView":1100
+ *
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t dst_extent = dst_shape[0]
+ * cdef Py_ssize_t src_stride = src_strides[0]
+ */
+ __pyx_v_src_extent = (__pyx_v_src_shape[0]);
+
+ /* "View.MemoryView":1101
+ * cdef Py_ssize_t i
+ * cdef Py_ssize_t src_extent = src_shape[0]
+ * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t src_stride = src_strides[0]
+ * cdef Py_ssize_t dst_stride = dst_strides[0]
+ */
+ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]);
+
+ /* "View.MemoryView":1102
+ * cdef Py_ssize_t src_extent = src_shape[0]
+ * cdef Py_ssize_t dst_extent = dst_shape[0]
+ * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<<
+ * cdef Py_ssize_t dst_stride = dst_strides[0]
+ *
+ */
+ __pyx_v_src_stride = (__pyx_v_src_strides[0]);
+
+ /* "View.MemoryView":1103
+ * cdef Py_ssize_t dst_extent = dst_shape[0]
+ * cdef Py_ssize_t src_stride = src_strides[0]
+ * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<<
+ *
+ * if ndim == 1:
+ */
+ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]);
+
+ /* "View.MemoryView":1105
+ * cdef Py_ssize_t dst_stride = dst_strides[0]
+ *
+ * if ndim == 1: # <<<<<<<<<<<<<<
+ * if (src_stride > 0 and dst_stride > 0 and
+ * <size_t> src_stride == itemsize == <size_t> dst_stride):
+ */
+ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1106
+ *
+ * if ndim == 1:
+ * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<<
+ * <size_t> src_stride == itemsize == <size_t> dst_stride):
+ * memcpy(dst_data, src_data, itemsize * dst_extent)
+ */
+ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
+ if (__pyx_t_2) {
+ } else {
+ __pyx_t_1 = __pyx_t_2;
+ goto __pyx_L5_bool_binop_done;
+ }
+ __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
+ if (__pyx_t_2) {
+ } else {
+ __pyx_t_1 = __pyx_t_2;
+ goto __pyx_L5_bool_binop_done;
+ }
+
+ /* "View.MemoryView":1107
+ * if ndim == 1:
+ * if (src_stride > 0 and dst_stride > 0 and
+ * <size_t> src_stride == itemsize == <size_t> dst_stride): # <<<<<<<<<<<<<<
+ * memcpy(dst_data, src_data, itemsize * dst_extent)
+ * else:
+ */
+ __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize);
+ if (__pyx_t_2) {
+ __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride));
+ }
+ __pyx_t_3 = (__pyx_t_2 != 0);
+ __pyx_t_1 = __pyx_t_3;
+ __pyx_L5_bool_binop_done:;
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1108
+ * if (src_stride > 0 and dst_stride > 0 and
+ * <size_t> src_stride == itemsize == <size_t> dst_stride):
+ * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(dst_extent):
+ */
+ memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));
+ goto __pyx_L4;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1110
+ * memcpy(dst_data, src_data, itemsize * dst_extent)
+ * else:
+ * for i in range(dst_extent): # <<<<<<<<<<<<<<
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride
+ */
+ __pyx_t_4 = __pyx_v_dst_extent;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1111
+ * else:
+ * for i in range(dst_extent):
+ * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<<
+ * src_data += src_stride
+ * dst_data += dst_stride
+ */
+ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1112
+ * for i in range(dst_extent):
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride # <<<<<<<<<<<<<<
+ * dst_data += dst_stride
+ * else:
+ */
+ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+ /* "View.MemoryView":1113
+ * memcpy(dst_data, src_data, itemsize)
+ * src_data += src_stride
+ * dst_data += dst_stride # <<<<<<<<<<<<<<
+ * else:
+ * for i in range(dst_extent):
+ */
+ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+ }
+ }
+ __pyx_L4:;
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1115
+ * dst_data += dst_stride
+ * else:
+ * for i in range(dst_extent): # <<<<<<<<<<<<<<
+ * _copy_strided_to_strided(src_data, src_strides + 1,
+ * dst_data, dst_strides + 1,
+ */
+ __pyx_t_4 = __pyx_v_dst_extent;
+ for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
+ __pyx_v_i = __pyx_t_5;
+
+ /* "View.MemoryView":1116
+ * else:
+ * for i in range(dst_extent):
+ * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<<
+ * dst_data, dst_strides + 1,
+ * src_shape + 1, dst_shape + 1,
+ */
+ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);
+
+ /* "View.MemoryView":1120
+ * src_shape + 1, dst_shape + 1,
+ * ndim - 1, itemsize)
+ * src_data += src_stride # <<<<<<<<<<<<<<
+ * dst_data += dst_stride
+ *
+ */
+ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+ /* "View.MemoryView":1121
+ * ndim - 1, itemsize)
+ * src_data += src_stride
+ * dst_data += dst_stride # <<<<<<<<<<<<<<
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
+ */
+ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+ }
+ }
+ __pyx_L3:;
+
+ /* "View.MemoryView":1093
+ *
+ * @cython.cdivision(True)
+ * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<<
+ * char *dst_data, Py_ssize_t *dst_strides,
+ * Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1123
+ * dst_data += dst_stride
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ */
+
+static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
+
+ /* "View.MemoryView":1126
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<<
+ * src.shape, dst.shape, ndim, itemsize)
+ *
+ */
+ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);
+
+ /* "View.MemoryView":1123
+ * dst_data += dst_stride
+ *
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
+ * __Pyx_memviewslice *dst,
+ * int ndim, size_t itemsize) nogil:
+ */
+
+ /* function exit code */
+}
+
+/* "View.MemoryView":1130
+ *
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ */
+
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
+ int __pyx_v_i;
+ Py_ssize_t __pyx_v_size;
+ Py_ssize_t __pyx_r;
+ Py_ssize_t __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+
+ /* "View.MemoryView":1133
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<<
+ *
+ * for i in range(ndim):
+ */
+ __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
+ __pyx_v_size = __pyx_t_1;
+
+ /* "View.MemoryView":1135
+ * cdef Py_ssize_t size = src.memview.view.itemsize
+ *
+ * for i in range(ndim): # <<<<<<<<<<<<<<
+ * size *= src.shape[i]
+ *
+ */
+ __pyx_t_2 = __pyx_v_ndim;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_i = __pyx_t_3;
+
+ /* "View.MemoryView":1136
+ *
+ * for i in range(ndim):
+ * size *= src.shape[i] # <<<<<<<<<<<<<<
+ *
+ * return size
+ */
+ __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i]));
+ }
+
+ /* "View.MemoryView":1138
+ * size *= src.shape[i]
+ *
+ * return size # <<<<<<<<<<<<<<
+ *
+ * @cname('__pyx_fill_contig_strides_array')
+ */
+ __pyx_r = __pyx_v_size;
+ goto __pyx_L0;
+
+ /* "View.MemoryView":1130
+ *
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
+ * "Return the size of the memory occupied by the slice in number of bytes"
+ * cdef int i
+ */
+
+ /* function exit code */
+ __pyx_L0:;
+ return __pyx_r;
+}
+
+/* "View.MemoryView":1141
+ *
+ * @cname('__pyx_fill_contig_strides_array')
+ * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<<
+ * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
+ * int ndim, char order) nogil:
+ */
+
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
+ int __pyx_v_idx;
+ Py_ssize_t __pyx_r;
+ int __pyx_t_1;
+ int __pyx_t_2;
+ int __pyx_t_3;
+
+ /* "View.MemoryView":1150
+ * cdef int idx
+ *
+ * if order == 'F': # <<<<<<<<<<<<<<
+ * for idx in range(ndim):
+ * strides[idx] = stride
+ */
+ __pyx_t_1 = ((__pyx_v_order == 'F') != 0);
+ if (__pyx_t_1) {
+
+ /* "View.MemoryView":1151
+ *
+ * if order == 'F':
+ * for idx in range(ndim): # <<<<<<<<<<<<<<
+ * strides[idx] = stride
+ * stride = stride * shape[idx]
+ */
+ __pyx_t_2 = __pyx_v_ndim;
+ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+ __pyx_v_idx = __pyx_t_3;
+
+ /* "View.MemoryView":1152
+ * if order == 'F':
+ * for idx in range(ndim):
+ * strides[idx] = stride # <<<<<<<<<<<<<<
+ * stride = stride * shape[idx]
+ * else:
+ */
+ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
+
+ /* "View.MemoryView":1153
+ * for idx in range(ndim):
+ * strides[idx] = stride
+ * stride = stride * shape[idx] # <<<<<<<<<<<<<<
+ * else:
+ * for idx in range(ndim - 1, -1, -1):
+ */
+ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
+ }
+ goto __pyx_L3;
+ }
+ /*else*/ {
+
+ /* "View.MemoryView":1155
+ * stride = stride * shape[idx]
+ * else:
+ * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
+ * strides[idx] = stride
+ * stride = stride * shape[idx]
+ */
+ for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) {
+ __pyx_v_idx = __pyx_t_2;
+
+ /* "View.MemoryView":1156
+ * else:
+ * for idx in range(ndim - 1, -1, -1):
+ * strides[idx] = stride # <<<<<<<<<<<<<<
+ * stride = stride * shape[idx]
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+ * int src_ndim, int dst_ndim,
+ */
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+ void *__pyx_v_tmpdata;
+ size_t __pyx_v_itemsize;
+ int __pyx_v_i;
+ char __pyx_v_order;
+ int __pyx_v_broadcasting;
+ int __pyx_v_direct_copy;
+ __Pyx_memviewslice __pyx_v_tmp;
+ int __pyx_v_ndim;
+ int __pyx_r;
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+ int __pyx_t_2;
+ int __pyx_t_3;
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+ int __pyx_t_5;
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+ int __pyx_t_7;
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+ const char *__pyx_filename = NULL;
+ int __pyx_clineno = 0;
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+ /* "View.MemoryView":1277
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+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_array___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
+ PyObject *v = PyObject_GenericGetAttr(o, n);
+ if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+ PyErr_Clear();
+ v = __pyx_array___getattr__(o, n);
+ }
+ return v;
+}
+
+static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
+ return get_memview(o);
+}
+
+static PyMethodDef __pyx_methods_array[] = {
+ {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_array[] = {
+ {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_array = {
+ 0, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_array, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_array = {
+ 0, /*mp_length*/
+ __pyx_array___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_array = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_array_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_array = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "peaks.array", /*tp_name*/
+ sizeof(struct __pyx_array_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_array, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ 0, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_array, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_array, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ __pyx_tp_getattro_array, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_array, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
+ 0, /*tp_doc*/
+ 0, /*tp_traverse*/
+ 0, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_array, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_array, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_array, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
+ struct __pyx_MemviewEnum_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_MemviewEnum_obj *)o);
+ p->name = Py_None; Py_INCREF(Py_None);
+ return o;
+}
+
+static void __pyx_tp_dealloc_Enum(PyObject *o) {
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ Py_CLEAR(p->name);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ if (p->name) {
+ e = (*v)(p->name, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_Enum(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+ tmp = ((PyObject*)p->name);
+ p->name = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ return 0;
+}
+
+static PyMethodDef __pyx_methods_Enum[] = {
+ {0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_MemviewEnum = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "peaks.Enum", /*tp_name*/
+ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_Enum, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_MemviewEnum___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ 0, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_Enum, /*tp_traverse*/
+ __pyx_tp_clear_Enum, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_Enum, /*tp_methods*/
+ 0, /*tp_members*/
+ 0, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ __pyx_MemviewEnum___init__, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_Enum, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
+
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryview_obj *p;
+ PyObject *o;
+ if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+ o = (*t->tp_alloc)(t, 0);
+ } else {
+ o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+ }
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryview_obj *)o);
+ p->__pyx_vtab = __pyx_vtabptr_memoryview;
+ p->obj = Py_None; Py_INCREF(Py_None);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ p->view.obj = NULL;
+ if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) {
+ Py_DECREF(o); o = 0;
+ }
+ return o;
+}
+
+static void __pyx_tp_dealloc_memoryview(PyObject *o) {
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryview___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->obj);
+ Py_CLEAR(p->_size);
+ Py_CLEAR(p->_array_interface);
+ (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ if (p->obj) {
+ e = (*v)(p->obj, a); if (e) return e;
+ }
+ if (p->_size) {
+ e = (*v)(p->_size, a); if (e) return e;
+ }
+ if (p->_array_interface) {
+ e = (*v)(p->_array_interface, a); if (e) return e;
+ }
+ if (p->view.obj) {
+ e = (*v)(p->view.obj, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear_memoryview(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+ tmp = ((PyObject*)p->obj);
+ p->obj = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_size);
+ p->_size = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ tmp = ((PyObject*)p->_array_interface);
+ p->_array_interface = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ Py_CLEAR(p->view.obj);
+ return 0;
+}
+static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
+ PyObject *r;
+ PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+ r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+ Py_DECREF(x);
+ return r;
+}
+
+static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
+ if (v) {
+ return __pyx_memoryview___setitem__(o, i, v);
+ }
+ else {
+ PyErr_Format(PyExc_NotImplementedError,
+ "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+ return -1;
+ }
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_transpose(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview__get__base(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_shape(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_strides(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_suboffsets(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_ndim(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_itemsize(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_nbytes(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryview_get_size(o);
+}
+
+static PyMethodDef __pyx_methods_memoryview[] = {
+ {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
+ {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
+ {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
+ {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_memoryview[] = {
+ {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0},
+ {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0},
+ {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0},
+ {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0},
+ {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0},
+ {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0},
+ {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0},
+ {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0},
+ {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
+ __pyx_memoryview___len__, /*sq_length*/
+ 0, /*sq_concat*/
+ 0, /*sq_repeat*/
+ __pyx_sq_item_memoryview, /*sq_item*/
+ 0, /*sq_slice*/
+ 0, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
+ 0, /*sq_contains*/
+ 0, /*sq_inplace_concat*/
+ 0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
+ __pyx_memoryview___len__, /*mp_length*/
+ __pyx_memoryview___getitem__, /*mp_subscript*/
+ __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getreadbuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getwritebuffer*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getsegcount*/
+ #endif
+ #if PY_MAJOR_VERSION < 3
+ 0, /*bf_getcharbuffer*/
+ #endif
+ __pyx_memoryview_getbuffer, /*bf_getbuffer*/
+ 0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_memoryview = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "peaks.memoryview", /*tp_name*/
+ sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ __pyx_memoryview___repr__, /*tp_repr*/
+ 0, /*tp_as_number*/
+ &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
+ &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ __pyx_memoryview___str__, /*tp_str*/
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ 0, /*tp_doc*/
+ __pyx_tp_traverse_memoryview, /*tp_traverse*/
+ __pyx_tp_clear_memoryview, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods_memoryview, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets_memoryview, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new_memoryview, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;
+
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
+ struct __pyx_memoryviewslice_obj *p;
+ PyObject *o = __pyx_tp_new_memoryview(t, a, k);
+ if (unlikely(!o)) return 0;
+ p = ((struct __pyx_memoryviewslice_obj *)o);
+ p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ p->from_slice.memview = NULL;
+ return o;
+}
+
+static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ #if PY_VERSION_HEX >= 0x030400a1
+ if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+ if (PyObject_CallFinalizerFromDealloc(o)) return;
+ }
+ #endif
+ PyObject_GC_UnTrack(o);
+ {
+ PyObject *etype, *eval, *etb;
+ PyErr_Fetch(&etype, &eval, &etb);
+ ++Py_REFCNT(o);
+ __pyx_memoryviewslice___dealloc__(o);
+ --Py_REFCNT(o);
+ PyErr_Restore(etype, eval, etb);
+ }
+ Py_CLEAR(p->from_object);
+ PyObject_GC_Track(o);
+ __pyx_tp_dealloc_memoryview(o);
+}
+
+static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
+ int e;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
+ if (p->from_object) {
+ e = (*v)(p->from_object, a); if (e) return e;
+ }
+ return 0;
+}
+
+static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
+ PyObject* tmp;
+ struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+ __pyx_tp_clear_memoryview(o);
+ tmp = ((PyObject*)p->from_object);
+ p->from_object = Py_None; Py_INCREF(Py_None);
+ Py_XDECREF(tmp);
+ __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
+ return 0;
+}
+
+static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
+ return __pyx_memoryviewslice__get__base(o);
+}
+
+static PyMethodDef __pyx_methods__memoryviewslice[] = {
+ {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
+ {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, 0, 0},
+ {0, 0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_memoryviewslice = {
+ PyVarObject_HEAD_INIT(0, 0)
+ "peaks._memoryviewslice", /*tp_name*/
+ sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
+ 0, /*tp_itemsize*/
+ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
+ 0, /*tp_print*/
+ 0, /*tp_getattr*/
+ 0, /*tp_setattr*/
+ #if PY_MAJOR_VERSION < 3
+ 0, /*tp_compare*/
+ #else
+ 0, /*reserved*/
+ #endif
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___repr__, /*tp_repr*/
+ #else
+ 0, /*tp_repr*/
+ #endif
+ 0, /*tp_as_number*/
+ 0, /*tp_as_sequence*/
+ 0, /*tp_as_mapping*/
+ 0, /*tp_hash*/
+ 0, /*tp_call*/
+ #if CYTHON_COMPILING_IN_PYPY
+ __pyx_memoryview___str__, /*tp_str*/
+ #else
+ 0, /*tp_str*/
+ #endif
+ 0, /*tp_getattro*/
+ 0, /*tp_setattro*/
+ 0, /*tp_as_buffer*/
+ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+ "Internal class for passing memoryview slices to Python", /*tp_doc*/
+ __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
+ __pyx_tp_clear__memoryviewslice, /*tp_clear*/
+ 0, /*tp_richcompare*/
+ 0, /*tp_weaklistoffset*/
+ 0, /*tp_iter*/
+ 0, /*tp_iternext*/
+ __pyx_methods__memoryviewslice, /*tp_methods*/
+ 0, /*tp_members*/
+ __pyx_getsets__memoryviewslice, /*tp_getset*/
+ 0, /*tp_base*/
+ 0, /*tp_dict*/
+ 0, /*tp_descr_get*/
+ 0, /*tp_descr_set*/
+ 0, /*tp_dictoffset*/
+ 0, /*tp_init*/
+ 0, /*tp_alloc*/
+ __pyx_tp_new__memoryviewslice, /*tp_new*/
+ 0, /*tp_free*/
+ 0, /*tp_is_gc*/
+ 0, /*tp_bases*/
+ 0, /*tp_mro*/
+ 0, /*tp_cache*/
+ 0, /*tp_subclasses*/
+ 0, /*tp_weaklist*/
+ 0, /*tp_del*/
+ 0, /*tp_version_tag*/
+ #if PY_VERSION_HEX >= 0x030400a1
+ 0, /*tp_finalize*/
+ #endif
+};
+
+static PyMethodDef __pyx_methods[] = {
+ {0, 0, 0, 0}
+};
+
+#if PY_MAJOR_VERSION >= 3
+static struct PyModuleDef __pyx_moduledef = {
+ #if PY_VERSION_HEX < 0x03020000
+ { PyObject_HEAD_INIT(NULL) NULL, 0, NULL },
+ #else
+ PyModuleDef_HEAD_INIT,
+ #endif
+ "peaks",
+ __pyx_k_This_module_provides_a_peak_sear, /* m_doc */
+ -1, /* m_size */
+ __pyx_methods /* m_methods */,
+ NULL, /* m_reload */
+ NULL, /* m_traverse */
+ NULL, /* m_clear */
+ NULL /* m_free */
+};
+#endif
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+ __pyx_builtin_max = __Pyx_GetBuiltinName(__pyx_n_s_max); if (!__pyx_builtin_max) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 157; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ */
+
+ /*--- Wrapped vars code ---*/
+
+ goto __pyx_L0;
+ __pyx_L1_error:;
+ __Pyx_XDECREF(__pyx_t_1);
+ __Pyx_XDECREF(__pyx_t_2);
+ __Pyx_XDECREF(__pyx_t_3);
+ __Pyx_XDECREF(__pyx_t_4);
+ __Pyx_XDECREF(__pyx_t_5);
+ if (__pyx_m) {
+ if (__pyx_d) {
+ __Pyx_AddTraceback("init peaks", __pyx_clineno, __pyx_lineno, __pyx_filename);
+ }
+ Py_DECREF(__pyx_m); __pyx_m = 0;
+ } else if (!PyErr_Occurred()) {
+ PyErr_SetString(PyExc_ImportError, "init peaks");
+ }
+ __pyx_L0:;
+ __Pyx_RefNannyFinishContext();
+ #if PY_MAJOR_VERSION < 3
+ return;
+ #else
+ return __pyx_m;
+ #endif
+}
+
+/* Runtime support code */
+#if CYTHON_REFNANNY
+static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
+ PyObject *m = NULL, *p = NULL;
+ void *r = NULL;
+ m = PyImport_ImportModule((char *)modname);
+ if (!m) goto end;
+ p = PyObject_GetAttrString(m, (char *)"RefNannyAPI");
+ if (!p) goto end;
+ r = PyLong_AsVoidPtr(p);
+end:
+ Py_XDECREF(p);
+ Py_XDECREF(m);
+ return (__Pyx_RefNannyAPIStruct *)r;
+}
+#endif
+
+static PyObject *__Pyx_GetBuiltinName(PyObject *name) {
+ PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name);
+ if (unlikely(!result)) {
+ PyErr_Format(PyExc_NameError,
+#if PY_MAJOR_VERSION >= 3
+ "name '%U' is not defined", name);
+#else
+ "name '%.200s' is not defined", PyString_AS_STRING(name));
+#endif
+ }
+ return result;
+}
+
+static void __Pyx_RaiseArgtupleInvalid(
+ const char* func_name,
+ int exact,
+ Py_ssize_t num_min,
+ Py_ssize_t num_max,
+ Py_ssize_t num_found)
+{
+ Py_ssize_t num_expected;
+ const char *more_or_less;
+ if (num_found < num_min) {
+ num_expected = num_min;
+ more_or_less = "at least";
+ } else {
+ num_expected = num_max;
+ more_or_less = "at most";
+ }
+ if (exact) {
+ more_or_less = "exactly";
+ }
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
+ func_name, more_or_less, num_expected,
+ (num_expected == 1) ? "" : "s", num_found);
+}
+
+static void __Pyx_RaiseDoubleKeywordsError(
+ const char* func_name,
+ PyObject* kw_name)
+{
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION >= 3
+ "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
+ #else
+ "%s() got multiple values for keyword argument '%s'", func_name,
+ PyString_AsString(kw_name));
+ #endif
+}
+
+static int __Pyx_ParseOptionalKeywords(
+ PyObject *kwds,
+ PyObject **argnames[],
+ PyObject *kwds2,
+ PyObject *values[],
+ Py_ssize_t num_pos_args,
+ const char* function_name)
+{
+ PyObject *key = 0, *value = 0;
+ Py_ssize_t pos = 0;
+ PyObject*** name;
+ PyObject*** first_kw_arg = argnames + num_pos_args;
+ while (PyDict_Next(kwds, &pos, &key, &value)) {
+ name = first_kw_arg;
+ while (*name && (**name != key)) name++;
+ if (*name) {
+ values[name-argnames] = value;
+ continue;
+ }
+ name = first_kw_arg;
+ #if PY_MAJOR_VERSION < 3
+ if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
+ while (*name) {
+ if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
+ && _PyString_Eq(**name, key)) {
+ values[name-argnames] = value;
+ break;
+ }
+ name++;
+ }
+ if (*name) continue;
+ else {
+ PyObject*** argname = argnames;
+ while (argname != first_kw_arg) {
+ if ((**argname == key) || (
+ (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
+ && _PyString_Eq(**argname, key))) {
+ goto arg_passed_twice;
+ }
+ argname++;
+ }
+ }
+ } else
+ #endif
+ if (likely(PyUnicode_Check(key))) {
+ while (*name) {
+ int cmp = (**name == key) ? 0 :
+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
+ #endif
+ PyUnicode_Compare(**name, key);
+ if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+ if (cmp == 0) {
+ values[name-argnames] = value;
+ break;
+ }
+ name++;
+ }
+ if (*name) continue;
+ else {
+ PyObject*** argname = argnames;
+ while (argname != first_kw_arg) {
+ int cmp = (**argname == key) ? 0 :
+ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+ (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
+ #endif
+ PyUnicode_Compare(**argname, key);
+ if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+ if (cmp == 0) goto arg_passed_twice;
+ argname++;
+ }
+ }
+ } else
+ goto invalid_keyword_type;
+ if (kwds2) {
+ if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
+ } else {
+ goto invalid_keyword;
+ }
+ }
+ return 0;
+arg_passed_twice:
+ __Pyx_RaiseDoubleKeywordsError(function_name, key);
+ goto bad;
+invalid_keyword_type:
+ PyErr_Format(PyExc_TypeError,
+ "%.200s() keywords must be strings", function_name);
+ goto bad;
+invalid_keyword:
+ PyErr_Format(PyExc_TypeError,
+ #if PY_MAJOR_VERSION < 3
+ "%.200s() got an unexpected keyword argument '%.200s'",
+ function_name, PyString_AsString(key));
+ #else
+ "%s() got an unexpected keyword argument '%U'",
+ function_name, key);
+ #endif
+bad:
+ return -1;
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
+ PyObject *result;
+#if CYTHON_COMPILING_IN_CPYTHON
+ result = PyDict_GetItem(__pyx_d, name);
+ if (likely(result)) {
+ Py_INCREF(result);
+ } else {
+#else
+ result = PyObject_GetItem(__pyx_d, name);
+ if (!result) {
+ PyErr_Clear();
+#endif
+ result = __Pyx_GetBuiltinName(name);
+ }
+ return result;
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) {
+ PyObject *result;
+ ternaryfunc call = func->ob_type->tp_call;
+ if (unlikely(!call))
+ return PyObject_Call(func, arg, kw);
+ if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+ return NULL;
+ result = (*call)(func, arg, kw);
+ Py_LeaveRecursiveCall();
+ if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+ PyErr_SetString(
+ PyExc_SystemError,
+ "NULL result without error in PyObject_Call");
+ }
+ return result;
+}
+#endif
+
+static void __Pyx_RaiseBufferIndexError(int axis) {
+ PyErr_Format(PyExc_IndexError,
+ "Out of bounds on buffer access (axis %d)", axis);
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
+ PyObject *self, *result;
+ PyCFunction cfunc;
+ cfunc = PyCFunction_GET_FUNCTION(func);
+ self = PyCFunction_GET_SELF(func);
+ if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+ return NULL;
+ result = cfunc(self, arg);
+ Py_LeaveRecursiveCall();
+ if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+ PyErr_SetString(
+ PyExc_SystemError,
+ "NULL result without error in PyObject_Call");
+ }
+ return result;
+}
+#endif
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+ PyObject *result;
+ PyObject *args = PyTuple_New(1);
+ if (unlikely(!args)) return NULL;
+ Py_INCREF(arg);
+ PyTuple_SET_ITEM(args, 0, arg);
+ result = __Pyx_PyObject_Call(func, args, NULL);
+ Py_DECREF(args);
+ return result;
+}
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+#ifdef __Pyx_CyFunction_USED
+ if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
+#else
+ if (likely(PyCFunction_Check(func))) {
+#endif
+ if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
+ return __Pyx_PyObject_CallMethO(func, arg);
+ }
+ }
+ return __Pyx__PyObject_CallOneArg(func, arg);
+}
+#else
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+ PyObject* args = PyTuple_Pack(1, arg);
+ return (likely(args)) ? __Pyx_PyObject_Call(func, args, NULL) : NULL;
+}
+#endif
+
+static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->curexc_type;
+ tmp_value = tstate->curexc_value;
+ tmp_tb = tstate->curexc_traceback;
+ tstate->curexc_type = type;
+ tstate->curexc_value = value;
+ tstate->curexc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_Restore(type, value, tb);
+#endif
+}
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->curexc_type;
+ *value = tstate->curexc_value;
+ *tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(type, value, tb);
+#endif
+}
+
+#if PY_MAJOR_VERSION < 3
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
+ CYTHON_UNUSED PyObject *cause) {
+ Py_XINCREF(type);
+ if (!value || value == Py_None)
+ value = NULL;
+ else
+ Py_INCREF(value);
+ if (!tb || tb == Py_None)
+ tb = NULL;
+ else {
+ Py_INCREF(tb);
+ if (!PyTraceBack_Check(tb)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: arg 3 must be a traceback or None");
+ goto raise_error;
+ }
+ }
+ if (PyType_Check(type)) {
+#if CYTHON_COMPILING_IN_PYPY
+ if (!value) {
+ Py_INCREF(Py_None);
+ value = Py_None;
+ }
+#endif
+ PyErr_NormalizeException(&type, &value, &tb);
+ } else {
+ if (value) {
+ PyErr_SetString(PyExc_TypeError,
+ "instance exception may not have a separate value");
+ goto raise_error;
+ }
+ value = type;
+ type = (PyObject*) Py_TYPE(type);
+ Py_INCREF(type);
+ if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: exception class must be a subclass of BaseException");
+ goto raise_error;
+ }
+ }
+ __Pyx_ErrRestore(type, value, tb);
+ return;
+raise_error:
+ Py_XDECREF(value);
+ Py_XDECREF(type);
+ Py_XDECREF(tb);
+ return;
+}
+#else
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
+ PyObject* owned_instance = NULL;
+ if (tb == Py_None) {
+ tb = 0;
+ } else if (tb && !PyTraceBack_Check(tb)) {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: arg 3 must be a traceback or None");
+ goto bad;
+ }
+ if (value == Py_None)
+ value = 0;
+ if (PyExceptionInstance_Check(type)) {
+ if (value) {
+ PyErr_SetString(PyExc_TypeError,
+ "instance exception may not have a separate value");
+ goto bad;
+ }
+ value = type;
+ type = (PyObject*) Py_TYPE(value);
+ } else if (PyExceptionClass_Check(type)) {
+ PyObject *instance_class = NULL;
+ if (value && PyExceptionInstance_Check(value)) {
+ instance_class = (PyObject*) Py_TYPE(value);
+ if (instance_class != type) {
+ if (PyObject_IsSubclass(instance_class, type)) {
+ type = instance_class;
+ } else {
+ instance_class = NULL;
+ }
+ }
+ }
+ if (!instance_class) {
+ PyObject *args;
+ if (!value)
+ args = PyTuple_New(0);
+ else if (PyTuple_Check(value)) {
+ Py_INCREF(value);
+ args = value;
+ } else
+ args = PyTuple_Pack(1, value);
+ if (!args)
+ goto bad;
+ owned_instance = PyObject_Call(type, args, NULL);
+ Py_DECREF(args);
+ if (!owned_instance)
+ goto bad;
+ value = owned_instance;
+ if (!PyExceptionInstance_Check(value)) {
+ PyErr_Format(PyExc_TypeError,
+ "calling %R should have returned an instance of "
+ "BaseException, not %R",
+ type, Py_TYPE(value));
+ goto bad;
+ }
+ }
+ } else {
+ PyErr_SetString(PyExc_TypeError,
+ "raise: exception class must be a subclass of BaseException");
+ goto bad;
+ }
+#if PY_VERSION_HEX >= 0x03030000
+ if (cause) {
+#else
+ if (cause && cause != Py_None) {
+#endif
+ PyObject *fixed_cause;
+ if (cause == Py_None) {
+ fixed_cause = NULL;
+ } else if (PyExceptionClass_Check(cause)) {
+ fixed_cause = PyObject_CallObject(cause, NULL);
+ if (fixed_cause == NULL)
+ goto bad;
+ } else if (PyExceptionInstance_Check(cause)) {
+ fixed_cause = cause;
+ Py_INCREF(fixed_cause);
+ } else {
+ PyErr_SetString(PyExc_TypeError,
+ "exception causes must derive from "
+ "BaseException");
+ goto bad;
+ }
+ PyException_SetCause(value, fixed_cause);
+ }
+ PyErr_SetObject(type, value);
+ if (tb) {
+#if CYTHON_COMPILING_IN_PYPY
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyErr_Fetch(tmp_type, tmp_value, tmp_tb);
+ Py_INCREF(tb);
+ PyErr_Restore(tmp_type, tmp_value, tb);
+ Py_XDECREF(tmp_tb);
+#else
+ PyThreadState *tstate = PyThreadState_GET();
+ PyObject* tmp_tb = tstate->curexc_traceback;
+ if (tb != tmp_tb) {
+ Py_INCREF(tb);
+ tstate->curexc_traceback = tb;
+ Py_XDECREF(tmp_tb);
+ }
+#endif
+ }
+bad:
+ Py_XDECREF(owned_instance);
+ return;
+}
+#endif
+
+static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) {
+ int r;
+ if (!j) return -1;
+ r = PyObject_SetItem(o, j, v);
+ Py_DECREF(j);
+ return r;
+}
+static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v,
+ int is_list, int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (is_list || PyList_CheckExact(o)) {
+ Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o));
+ if ((!boundscheck) || likely((n >= 0) & (n < PyList_GET_SIZE(o)))) {
+ PyObject* old = PyList_GET_ITEM(o, n);
+ Py_INCREF(v);
+ PyList_SET_ITEM(o, n, v);
+ Py_DECREF(old);
+ return 1;
+ }
+ } else {
+ PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
+ if (likely(m && m->sq_ass_item)) {
+ if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
+ Py_ssize_t l = m->sq_length(o);
+ if (likely(l >= 0)) {
+ i += l;
+ } else {
+ if (PyErr_ExceptionMatches(PyExc_OverflowError))
+ PyErr_Clear();
+ else
+ return -1;
+ }
+ }
+ return m->sq_ass_item(o, i, v);
+ }
+ }
+#else
+#if CYTHON_COMPILING_IN_PYPY
+ if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) {
+#else
+ if (is_list || PySequence_Check(o)) {
+#endif
+ return PySequence_SetItem(o, i, v);
+ }
+#endif
+ return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v);
+}
+
+static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
+ unsigned int n = 1;
+ return *(unsigned char*)(&n) != 0;
+}
+static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
+ __Pyx_BufFmt_StackElem* stack,
+ __Pyx_TypeInfo* type) {
+ stack[0].field = &ctx->root;
+ stack[0].parent_offset = 0;
+ ctx->root.type = type;
+ ctx->root.name = "buffer dtype";
+ ctx->root.offset = 0;
+ ctx->head = stack;
+ ctx->head->field = &ctx->root;
+ ctx->fmt_offset = 0;
+ ctx->head->parent_offset = 0;
+ ctx->new_packmode = '@';
+ ctx->enc_packmode = '@';
+ ctx->new_count = 1;
+ ctx->enc_count = 0;
+ ctx->enc_type = 0;
+ ctx->is_complex = 0;
+ ctx->is_valid_array = 0;
+ ctx->struct_alignment = 0;
+ while (type->typegroup == 'S') {
+ ++ctx->head;
+ ctx->head->field = type->fields;
+ ctx->head->parent_offset = 0;
+ type = type->fields->type;
+ }
+}
+static int __Pyx_BufFmt_ParseNumber(const char** ts) {
+ int count;
+ const char* t = *ts;
+ if (*t < '0' || *t > '9') {
+ return -1;
+ } else {
+ count = *t++ - '0';
+ while (*t >= '0' && *t < '9') {
+ count *= 10;
+ count += *t++ - '0';
+ }
+ }
+ *ts = t;
+ return count;
+}
+static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
+ int number = __Pyx_BufFmt_ParseNumber(ts);
+ if (number == -1)
+ PyErr_Format(PyExc_ValueError,\
+ "Does not understand character buffer dtype format string ('%c')", **ts);
+ return number;
+}
+static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
+ PyErr_Format(PyExc_ValueError,
+ "Unexpected format string character: '%c'", ch);
+}
+static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
+ switch (ch) {
+ case 'c': return "'char'";
+ case 'b': return "'signed char'";
+ case 'B': return "'unsigned char'";
+ case 'h': return "'short'";
+ case 'H': return "'unsigned short'";
+ case 'i': return "'int'";
+ case 'I': return "'unsigned int'";
+ case 'l': return "'long'";
+ case 'L': return "'unsigned long'";
+ case 'q': return "'long long'";
+ case 'Q': return "'unsigned long long'";
+ case 'f': return (is_complex ? "'complex float'" : "'float'");
+ case 'd': return (is_complex ? "'complex double'" : "'double'");
+ case 'g': return (is_complex ? "'complex long double'" : "'long double'");
+ case 'T': return "a struct";
+ case 'O': return "Python object";
+ case 'P': return "a pointer";
+ case 's': case 'p': return "a string";
+ case 0: return "end";
+ default: return "unparseable format string";
+ }
+}
+static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return 2;
+ case 'i': case 'I': case 'l': case 'L': return 4;
+ case 'q': case 'Q': return 8;
+ case 'f': return (is_complex ? 8 : 4);
+ case 'd': return (is_complex ? 16 : 8);
+ case 'g': {
+ PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
+ return 0;
+ }
+ case 'O': case 'P': return sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
+ switch (ch) {
+ case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(short);
+ case 'i': case 'I': return sizeof(int);
+ case 'l': case 'L': return sizeof(long);
+ #ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(PY_LONG_LONG);
+ #endif
+ case 'f': return sizeof(float) * (is_complex ? 2 : 1);
+ case 'd': return sizeof(double) * (is_complex ? 2 : 1);
+ case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
+ case 'O': case 'P': return sizeof(void*);
+ default: {
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+ }
+}
+typedef struct { char c; short x; } __Pyx_st_short;
+typedef struct { char c; int x; } __Pyx_st_int;
+typedef struct { char c; long x; } __Pyx_st_long;
+typedef struct { char c; float x; } __Pyx_st_float;
+typedef struct { char c; double x; } __Pyx_st_double;
+typedef struct { char c; long double x; } __Pyx_st_longdouble;
+typedef struct { char c; void *x; } __Pyx_st_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
+ case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
+ case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
+#endif
+ case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
+ case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
+ case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
+ case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+/* These are for computing the padding at the end of the struct to align
+ on the first member of the struct. This will probably the same as above,
+ but we don't have any guarantees.
+ */
+typedef struct { short x; char c; } __Pyx_pad_short;
+typedef struct { int x; char c; } __Pyx_pad_int;
+typedef struct { long x; char c; } __Pyx_pad_long;
+typedef struct { float x; char c; } __Pyx_pad_float;
+typedef struct { double x; char c; } __Pyx_pad_double;
+typedef struct { long double x; char c; } __Pyx_pad_longdouble;
+typedef struct { void *x; char c; } __Pyx_pad_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
+ switch (ch) {
+ case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+ case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
+ case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
+ case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+ case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
+#endif
+ case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
+ case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
+ case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
+ case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
+ default:
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+}
+static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
+ switch (ch) {
+ case 'c':
+ return 'H';
+ case 'b': case 'h': case 'i':
+ case 'l': case 'q': case 's': case 'p':
+ return 'I';
+ case 'B': case 'H': case 'I': case 'L': case 'Q':
+ return 'U';
+ case 'f': case 'd': case 'g':
+ return (is_complex ? 'C' : 'R');
+ case 'O':
+ return 'O';
+ case 'P':
+ return 'P';
+ default: {
+ __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+ return 0;
+ }
+ }
+}
+static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
+ if (ctx->head == NULL || ctx->head->field == &ctx->root) {
+ const char* expected;
+ const char* quote;
+ if (ctx->head == NULL) {
+ expected = "end";
+ quote = "";
+ } else {
+ expected = ctx->head->field->type->name;
+ quote = "'";
+ }
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected %s%s%s but got %s",
+ quote, expected, quote,
+ __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
+ } else {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_StructField* parent = (ctx->head - 1)->field;
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
+ field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
+ parent->type->name, field->name);
+ }
+}
+static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
+ char group;
+ size_t size, offset, arraysize = 1;
+ if (ctx->enc_type == 0) return 0;
+ if (ctx->head->field->type->arraysize[0]) {
+ int i, ndim = 0;
+ if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
+ ctx->is_valid_array = ctx->head->field->type->ndim == 1;
+ ndim = 1;
+ if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
+ PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %zu",
+ ctx->head->field->type->arraysize[0], ctx->enc_count);
+ return -1;
+ }
+ }
+ if (!ctx->is_valid_array) {
+ PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
+ ctx->head->field->type->ndim, ndim);
+ return -1;
+ }
+ for (i = 0; i < ctx->head->field->type->ndim; i++) {
+ arraysize *= ctx->head->field->type->arraysize[i];
+ }
+ ctx->is_valid_array = 0;
+ ctx->enc_count = 1;
+ }
+ group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
+ do {
+ __Pyx_StructField* field = ctx->head->field;
+ __Pyx_TypeInfo* type = field->type;
+ if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
+ size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
+ } else {
+ size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
+ }
+ if (ctx->enc_packmode == '@') {
+ size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
+ size_t align_mod_offset;
+ if (align_at == 0) return -1;
+ align_mod_offset = ctx->fmt_offset % align_at;
+ if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
+ if (ctx->struct_alignment == 0)
+ ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
+ ctx->is_complex);
+ }
+ if (type->size != size || type->typegroup != group) {
+ if (type->typegroup == 'C' && type->fields != NULL) {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ ++ctx->head;
+ ctx->head->field = type->fields;
+ ctx->head->parent_offset = parent_offset;
+ continue;
+ }
+ if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
+ } else {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ }
+ offset = ctx->head->parent_offset + field->offset;
+ if (ctx->fmt_offset != offset) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
+ (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
+ return -1;
+ }
+ ctx->fmt_offset += size;
+ if (arraysize)
+ ctx->fmt_offset += (arraysize - 1) * size;
+ --ctx->enc_count;
+ while (1) {
+ if (field == &ctx->root) {
+ ctx->head = NULL;
+ if (ctx->enc_count != 0) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return -1;
+ }
+ break;
+ }
+ ctx->head->field = ++field;
+ if (field->type == NULL) {
+ --ctx->head;
+ field = ctx->head->field;
+ continue;
+ } else if (field->type->typegroup == 'S') {
+ size_t parent_offset = ctx->head->parent_offset + field->offset;
+ if (field->type->fields->type == NULL) continue;
+ field = field->type->fields;
+ ++ctx->head;
+ ctx->head->field = field;
+ ctx->head->parent_offset = parent_offset;
+ break;
+ } else {
+ break;
+ }
+ }
+ } while (ctx->enc_count);
+ ctx->enc_type = 0;
+ ctx->is_complex = 0;
+ return 0;
+}
+static CYTHON_INLINE PyObject *
+__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
+{
+ const char *ts = *tsp;
+ int i = 0, number;
+ int ndim = ctx->head->field->type->ndim;
+;
+ ++ts;
+ if (ctx->new_count != 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Cannot handle repeated arrays in format string");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ while (*ts && *ts != ')') {
+ switch (*ts) {
+ case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
+ default: break;
+ }
+ number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a dimension of size %zu, got %d",
+ ctx->head->field->type->arraysize[i], number);
+ if (*ts != ',' && *ts != ')')
+ return PyErr_Format(PyExc_ValueError,
+ "Expected a comma in format string, got '%c'", *ts);
+ if (*ts == ',') ts++;
+ i++;
+ }
+ if (i != ndim)
+ return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
+ ctx->head->field->type->ndim, i);
+ if (!*ts) {
+ PyErr_SetString(PyExc_ValueError,
+ "Unexpected end of format string, expected ')'");
+ return NULL;
+ }
+ ctx->is_valid_array = 1;
+ ctx->new_count = 1;
+ *tsp = ++ts;
+ return Py_None;
+}
+static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
+ int got_Z = 0;
+ while (1) {
+ switch(*ts) {
+ case 0:
+ if (ctx->enc_type != 0 && ctx->head == NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ if (ctx->head != NULL) {
+ __Pyx_BufFmt_RaiseExpected(ctx);
+ return NULL;
+ }
+ return ts;
+ case ' ':
+ case '\r':
+ case '\n':
+ ++ts;
+ break;
+ case '<':
+ if (!__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '>':
+ case '!':
+ if (__Pyx_IsLittleEndian()) {
+ PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
+ return NULL;
+ }
+ ctx->new_packmode = '=';
+ ++ts;
+ break;
+ case '=':
+ case '@':
+ case '^':
+ ctx->new_packmode = *ts++;
+ break;
+ case 'T':
+ {
+ const char* ts_after_sub;
+ size_t i, struct_count = ctx->new_count;
+ size_t struct_alignment = ctx->struct_alignment;
+ ctx->new_count = 1;
+ ++ts;
+ if (*ts != '{') {
+ PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
+ return NULL;
+ }
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ ctx->enc_count = 0;
+ ctx->struct_alignment = 0;
+ ++ts;
+ ts_after_sub = ts;
+ for (i = 0; i != struct_count; ++i) {
+ ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
+ if (!ts_after_sub) return NULL;
+ }
+ ts = ts_after_sub;
+ if (struct_alignment) ctx->struct_alignment = struct_alignment;
+ }
+ break;
+ case '}':
+ {
+ size_t alignment = ctx->struct_alignment;
+ ++ts;
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_type = 0;
+ if (alignment && ctx->fmt_offset % alignment) {
+ ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
+ }
+ }
+ return ts;
+ case 'x':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->fmt_offset += ctx->new_count;
+ ctx->new_count = 1;
+ ctx->enc_count = 0;
+ ctx->enc_type = 0;
+ ctx->enc_packmode = ctx->new_packmode;
+ ++ts;
+ break;
+ case 'Z':
+ got_Z = 1;
+ ++ts;
+ if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
+ __Pyx_BufFmt_RaiseUnexpectedChar('Z');
+ return NULL;
+ }
+ case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
+ case 'l': case 'L': case 'q': case 'Q':
+ case 'f': case 'd': case 'g':
+ case 'O': case 'p':
+ if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
+ ctx->enc_packmode == ctx->new_packmode) {
+ ctx->enc_count += ctx->new_count;
+ ctx->new_count = 1;
+ got_Z = 0;
+ ++ts;
+ break;
+ }
+ case 's':
+ if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+ ctx->enc_count = ctx->new_count;
+ ctx->enc_packmode = ctx->new_packmode;
+ ctx->enc_type = *ts;
+ ctx->is_complex = got_Z;
+ ++ts;
+ ctx->new_count = 1;
+ got_Z = 0;
+ break;
+ case ':':
+ ++ts;
+ while(*ts != ':') ++ts;
+ ++ts;
+ break;
+ case '(':
+ if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
+ break;
+ default:
+ {
+ int number = __Pyx_BufFmt_ExpectNumber(&ts);
+ if (number == -1) return NULL;
+ ctx->new_count = (size_t)number;
+ }
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
+ buf->buf = NULL;
+ buf->obj = NULL;
+ buf->strides = __Pyx_zeros;
+ buf->shape = __Pyx_zeros;
+ buf->suboffsets = __Pyx_minusones;
+}
+static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
+ Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
+ int nd, int cast, __Pyx_BufFmt_StackElem* stack)
+{
+ if (obj == Py_None || obj == NULL) {
+ __Pyx_ZeroBuffer(buf);
+ return 0;
+ }
+ buf->buf = NULL;
+ if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
+ if (buf->ndim != nd) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ nd, buf->ndim);
+ goto fail;
+ }
+ if (!cast) {
+ __Pyx_BufFmt_Context ctx;
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned)buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
+ buf->itemsize, (buf->itemsize > 1) ? "s" : "",
+ dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
+ return 0;
+fail:;
+ __Pyx_ZeroBuffer(buf);
+ return -1;
+}
+static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
+ if (info->buf == NULL) return;
+ if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
+ __Pyx_ReleaseBuffer(info);
+}
+
+static int
+__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
+ int ndim,
+ __Pyx_memviewslice *memviewslice,
+ int memview_is_new_reference)
+{
+ __Pyx_RefNannyDeclarations
+ int i, retval=-1;
+ Py_buffer *buf = &memview->view;
+ __Pyx_RefNannySetupContext("init_memviewslice", 0);
+ if (!buf) {
+ PyErr_SetString(PyExc_ValueError,
+ "buf is NULL.");
+ goto fail;
+ } else if (memviewslice->memview || memviewslice->data) {
+ PyErr_SetString(PyExc_ValueError,
+ "memviewslice is already initialized!");
+ goto fail;
+ }
+ if (buf->strides) {
+ for (i = 0; i < ndim; i++) {
+ memviewslice->strides[i] = buf->strides[i];
+ }
+ } else {
+ Py_ssize_t stride = buf->itemsize;
+ for (i = ndim - 1; i >= 0; i--) {
+ memviewslice->strides[i] = stride;
+ stride *= buf->shape[i];
+ }
+ }
+ for (i = 0; i < ndim; i++) {
+ memviewslice->shape[i] = buf->shape[i];
+ if (buf->suboffsets) {
+ memviewslice->suboffsets[i] = buf->suboffsets[i];
+ } else {
+ memviewslice->suboffsets[i] = -1;
+ }
+ }
+ memviewslice->memview = memview;
+ memviewslice->data = (char *)buf->buf;
+ if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
+ Py_INCREF(memview);
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ memviewslice->memview = 0;
+ memviewslice->data = 0;
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
+ va_list vargs;
+ char msg[200];
+ va_start(vargs, fmt);
+#ifdef HAVE_STDARG_PROTOTYPES
+ va_start(vargs, fmt);
+#else
+ va_start(vargs);
+#endif
+ vsnprintf(msg, 200, fmt, vargs);
+ Py_FatalError(msg);
+ va_end(vargs);
+}
+static CYTHON_INLINE int
+__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)++;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE int
+__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+ PyThread_type_lock lock)
+{
+ int result;
+ PyThread_acquire_lock(lock, 1);
+ result = (*acquisition_count)--;
+ PyThread_release_lock(lock);
+ return result;
+}
+static CYTHON_INLINE void
+__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
+{
+ int first_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview || (PyObject *) memview == Py_None)
+ return;
+ if (__pyx_get_slice_count(memview) < 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ first_time = __pyx_add_acquisition_count(memview) == 0;
+ if (first_time) {
+ if (have_gil) {
+ Py_INCREF((PyObject *) memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_INCREF((PyObject *) memview);
+ PyGILState_Release(_gilstate);
+ }
+ }
+}
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
+ int have_gil, int lineno) {
+ int last_time;
+ struct __pyx_memoryview_obj *memview = memslice->memview;
+ if (!memview ) {
+ return;
+ } else if ((PyObject *) memview == Py_None) {
+ memslice->memview = NULL;
+ return;
+ }
+ if (__pyx_get_slice_count(memview) <= 0)
+ __pyx_fatalerror("Acquisition count is %d (line %d)",
+ __pyx_get_slice_count(memview), lineno);
+ last_time = __pyx_sub_acquisition_count(memview) == 1;
+ memslice->data = NULL;
+ if (last_time) {
+ if (have_gil) {
+ Py_CLEAR(memslice->memview);
+ } else {
+ PyGILState_STATE _gilstate = PyGILState_Ensure();
+ Py_CLEAR(memslice->memview);
+ PyGILState_Release(_gilstate);
+ }
+ } else {
+ memslice->memview = NULL;
+ }
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
+ PyObject *r;
+ if (!j) return NULL;
+ r = PyObject_GetItem(o, j);
+ Py_DECREF(j);
+ return r;
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
+ PyObject *r = PyList_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+ int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, i);
+ Py_INCREF(r);
+ return r;
+ }
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+ return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+ int is_list, int wraparound, int boundscheck) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (is_list || PyList_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
+ if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
+ PyObject *r = PyList_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ }
+ else if (PyTuple_CheckExact(o)) {
+ Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
+ if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
+ PyObject *r = PyTuple_GET_ITEM(o, n);
+ Py_INCREF(r);
+ return r;
+ }
+ } else {
+ PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
+ if (likely(m && m->sq_item)) {
+ if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
+ Py_ssize_t l = m->sq_length(o);
+ if (likely(l >= 0)) {
+ i += l;
+ } else {
+ if (PyErr_ExceptionMatches(PyExc_OverflowError))
+ PyErr_Clear();
+ else
+ return NULL;
+ }
+ }
+ return m->sq_item(o, i);
+ }
+ }
+#else
+ if (is_list || PySequence_Check(o)) {
+ return PySequence_GetItem(o, i);
+ }
+#endif
+ return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+}
+
+static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
+ PyErr_Format(PyExc_TypeError,
+ "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
+ name, type->tp_name, Py_TYPE(obj)->tp_name);
+}
+static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
+ const char *name, int exact)
+{
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (none_allowed && obj == Py_None) return 1;
+ else if (exact) {
+ if (likely(Py_TYPE(obj) == type)) return 1;
+ #if PY_MAJOR_VERSION == 2
+ else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
+ #endif
+ }
+ else {
+ if (likely(PyObject_TypeCheck(obj, type))) return 1;
+ }
+ __Pyx_RaiseArgumentTypeInvalid(name, obj, type);
+ return 0;
+}
+
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+ if (s1 == s2) {
+ return (equals == Py_EQ);
+ } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
+ const char *ps1, *ps2;
+ Py_ssize_t length = PyBytes_GET_SIZE(s1);
+ if (length != PyBytes_GET_SIZE(s2))
+ return (equals == Py_NE);
+ ps1 = PyBytes_AS_STRING(s1);
+ ps2 = PyBytes_AS_STRING(s2);
+ if (ps1[0] != ps2[0]) {
+ return (equals == Py_NE);
+ } else if (length == 1) {
+ return (equals == Py_EQ);
+ } else {
+ int result = memcmp(ps1, ps2, (size_t)length);
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
+ return (equals == Py_NE);
+ } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
+ return (equals == Py_NE);
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+#endif
+}
+
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+ return PyObject_RichCompareBool(s1, s2, equals);
+#else
+#if PY_MAJOR_VERSION < 3
+ PyObject* owned_ref = NULL;
+#endif
+ int s1_is_unicode, s2_is_unicode;
+ if (s1 == s2) {
+ goto return_eq;
+ }
+ s1_is_unicode = PyUnicode_CheckExact(s1);
+ s2_is_unicode = PyUnicode_CheckExact(s2);
+#if PY_MAJOR_VERSION < 3
+ if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
+ owned_ref = PyUnicode_FromObject(s2);
+ if (unlikely(!owned_ref))
+ return -1;
+ s2 = owned_ref;
+ s2_is_unicode = 1;
+ } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
+ owned_ref = PyUnicode_FromObject(s1);
+ if (unlikely(!owned_ref))
+ return -1;
+ s1 = owned_ref;
+ s1_is_unicode = 1;
+ } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
+ return __Pyx_PyBytes_Equals(s1, s2, equals);
+ }
+#endif
+ if (s1_is_unicode & s2_is_unicode) {
+ Py_ssize_t length;
+ int kind;
+ void *data1, *data2;
+ if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
+ return -1;
+ length = __Pyx_PyUnicode_GET_LENGTH(s1);
+ if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
+ goto return_ne;
+ }
+ kind = __Pyx_PyUnicode_KIND(s1);
+ if (kind != __Pyx_PyUnicode_KIND(s2)) {
+ goto return_ne;
+ }
+ data1 = __Pyx_PyUnicode_DATA(s1);
+ data2 = __Pyx_PyUnicode_DATA(s2);
+ if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
+ goto return_ne;
+ } else if (length == 1) {
+ goto return_eq;
+ } else {
+ int result = memcmp(data1, data2, (size_t)(length * kind));
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ) ? (result == 0) : (result != 0);
+ }
+ } else if ((s1 == Py_None) & s2_is_unicode) {
+ goto return_ne;
+ } else if ((s2 == Py_None) & s1_is_unicode) {
+ goto return_ne;
+ } else {
+ int result;
+ PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+ if (!py_result)
+ return -1;
+ result = __Pyx_PyObject_IsTrue(py_result);
+ Py_DECREF(py_result);
+ return result;
+ }
+return_eq:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_EQ);
+return_ne:
+ #if PY_MAJOR_VERSION < 3
+ Py_XDECREF(owned_ref);
+ #endif
+ return (equals == Py_NE);
+#endif
+}
+
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
+ Py_ssize_t q = a / b;
+ Py_ssize_t r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
+#if CYTHON_COMPILING_IN_CPYTHON
+#if PY_MAJOR_VERSION >= 3
+ if (likely(PyUnicode_Check(n)))
+#else
+ if (likely(PyString_Check(n)))
+#endif
+ return __Pyx_PyObject_GetAttrStr(o, n);
+#endif
+ return PyObject_GetAttr(o, n);
+}
+
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+ const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+ const char* encoding, const char* errors,
+ PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
+ Py_ssize_t length;
+ if (unlikely((start < 0) | (stop < 0))) {
+ length = strlen(cstring);
+ if (start < 0) {
+ start += length;
+ if (start < 0)
+ start = 0;
+ }
+ if (stop < 0)
+ stop += length;
+ }
+ length = stop - start;
+ if (unlikely(length <= 0))
+ return PyUnicode_FromUnicode(NULL, 0);
+ cstring += start;
+ if (decode_func) {
+ return decode_func(cstring, length, errors);
+ } else {
+ return PyUnicode_Decode(cstring, length, encoding, errors);
+ }
+}
+
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
+ PyErr_Format(PyExc_ValueError,
+ "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
+ PyErr_Format(PyExc_ValueError,
+ "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
+ index, (index == 1) ? "" : "s");
+}
+
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
+ PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
+}
+
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
+ if (unlikely(!type)) {
+ PyErr_SetString(PyExc_SystemError, "Missing type object");
+ return 0;
+ }
+ if (likely(PyObject_TypeCheck(obj, type)))
+ return 1;
+ PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
+ Py_TYPE(obj)->tp_name, type->tp_name);
+ return 0;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->exc_type;
+ *value = tstate->exc_value;
+ *tb = tstate->exc_traceback;
+ Py_XINCREF(*type);
+ Py_XINCREF(*value);
+ Py_XINCREF(*tb);
+#else
+ PyErr_GetExcInfo(type, value, tb);
+#endif
+}
+static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = type;
+ tstate->exc_value = value;
+ tstate->exc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(type, value, tb);
+#endif
+}
+
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *local_type, *local_value, *local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+ PyThreadState *tstate = PyThreadState_GET();
+ local_type = tstate->curexc_type;
+ local_value = tstate->curexc_value;
+ local_tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(&local_type, &local_value, &local_tb);
+#endif
+ PyErr_NormalizeException(&local_type, &local_value, &local_tb);
+#if CYTHON_COMPILING_IN_CPYTHON
+ if (unlikely(tstate->curexc_type))
+#else
+ if (unlikely(PyErr_Occurred()))
+#endif
+ goto bad;
+ #if PY_MAJOR_VERSION >= 3
+ if (local_tb) {
+ if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
+ goto bad;
+ }
+ #endif
+ Py_XINCREF(local_tb);
+ Py_XINCREF(local_type);
+ Py_XINCREF(local_value);
+ *type = local_type;
+ *value = local_value;
+ *tb = local_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = local_type;
+ tstate->exc_value = local_value;
+ tstate->exc_traceback = local_tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_SetExcInfo(local_type, local_value, local_tb);
+#endif
+ return 0;
+bad:
+ *type = 0;
+ *value = 0;
+ *tb = 0;
+ Py_XDECREF(local_type);
+ Py_XDECREF(local_value);
+ Py_XDECREF(local_tb);
+ return -1;
+}
+
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
+ PyObject *tmp_type, *tmp_value, *tmp_tb;
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->exc_type;
+ tmp_value = tstate->exc_value;
+ tmp_tb = tstate->exc_traceback;
+ tstate->exc_type = *type;
+ tstate->exc_value = *value;
+ tstate->exc_traceback = *tb;
+#else
+ PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
+ PyErr_SetExcInfo(*type, *value, *tb);
+#endif
+ *type = tmp_type;
+ *value = tmp_value;
+ *tb = tmp_tb;
+}
+
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
+ PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
+}
+
+static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
+ long q = a / b;
+ long r = a - q*b;
+ q -= ((r != 0) & ((r ^ b) < 0));
+ return q;
+}
+
+static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
+ CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
+ int full_traceback) {
+ PyObject *old_exc, *old_val, *old_tb;
+ PyObject *ctx;
+ __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
+ if (full_traceback) {
+ Py_XINCREF(old_exc);
+ Py_XINCREF(old_val);
+ Py_XINCREF(old_tb);
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ PyErr_PrintEx(1);
+ }
+ #if PY_MAJOR_VERSION < 3
+ ctx = PyString_FromString(name);
+ #else
+ ctx = PyUnicode_FromString(name);
+ #endif
+ __Pyx_ErrRestore(old_exc, old_val, old_tb);
+ if (!ctx) {
+ PyErr_WriteUnraisable(Py_None);
+ } else {
+ PyErr_WriteUnraisable(ctx);
+ Py_DECREF(ctx);
+ }
+}
+
+static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
+#if PY_VERSION_HEX >= 0x02070000
+ PyObject *ob = PyCapsule_New(vtable, 0, 0);
+#else
+ PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
+#endif
+ if (!ob)
+ goto bad;
+ if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
+ goto bad;
+ Py_DECREF(ob);
+ return 0;
+bad:
+ Py_XDECREF(ob);
+ return -1;
+}
+
+static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
+ PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
+ if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+ PyErr_Format(PyExc_ImportError,
+ #if PY_MAJOR_VERSION < 3
+ "cannot import name %.230s", PyString_AS_STRING(name));
+ #else
+ "cannot import name %S", name);
+ #endif
+ }
+ return value;
+}
+
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
+#ifdef __Pyx_CyFunction_USED
+ if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
+#else
+ if (likely(PyCFunction_Check(func))) {
+#endif
+ if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
+ return __Pyx_PyObject_CallMethO(func, NULL);
+ }
+ }
+ return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
+}
+#endif
+
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
+ int start = 0, mid = 0, end = count - 1;
+ if (end >= 0 && code_line > entries[end].code_line) {
+ return count;
+ }
+ while (start < end) {
+ mid = (start + end) / 2;
+ if (code_line < entries[mid].code_line) {
+ end = mid;
+ } else if (code_line > entries[mid].code_line) {
+ start = mid + 1;
+ } else {
+ return mid;
+ }
+ }
+ if (code_line <= entries[mid].code_line) {
+ return mid;
+ } else {
+ return mid + 1;
+ }
+}
+static PyCodeObject *__pyx_find_code_object(int code_line) {
+ PyCodeObject* code_object;
+ int pos;
+ if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
+ return NULL;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
+ return NULL;
+ }
+ code_object = __pyx_code_cache.entries[pos].code_object;
+ Py_INCREF(code_object);
+ return code_object;
+}
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
+ int pos, i;
+ __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
+ if (unlikely(!code_line)) {
+ return;
+ }
+ if (unlikely(!entries)) {
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (likely(entries)) {
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = 64;
+ __pyx_code_cache.count = 1;
+ entries[0].code_line = code_line;
+ entries[0].code_object = code_object;
+ Py_INCREF(code_object);
+ }
+ return;
+ }
+ pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+ if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
+ PyCodeObject* tmp = entries[pos].code_object;
+ entries[pos].code_object = code_object;
+ Py_DECREF(tmp);
+ return;
+ }
+ if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
+ int new_max = __pyx_code_cache.max_count + 64;
+ entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
+ __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
+ if (unlikely(!entries)) {
+ return;
+ }
+ __pyx_code_cache.entries = entries;
+ __pyx_code_cache.max_count = new_max;
+ }
+ for (i=__pyx_code_cache.count; i>pos; i--) {
+ entries[i] = entries[i-1];
+ }
+ entries[pos].code_line = code_line;
+ entries[pos].code_object = code_object;
+ __pyx_code_cache.count++;
+ Py_INCREF(code_object);
+}
+
+#include "compile.h"
+#include "frameobject.h"
+#include "traceback.h"
+static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
+ const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyObject *py_srcfile = 0;
+ PyObject *py_funcname = 0;
+ #if PY_MAJOR_VERSION < 3
+ py_srcfile = PyString_FromString(filename);
+ #else
+ py_srcfile = PyUnicode_FromString(filename);
+ #endif
+ if (!py_srcfile) goto bad;
+ if (c_line) {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #else
+ py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+ #endif
+ }
+ else {
+ #if PY_MAJOR_VERSION < 3
+ py_funcname = PyString_FromString(funcname);
+ #else
+ py_funcname = PyUnicode_FromString(funcname);
+ #endif
+ }
+ if (!py_funcname) goto bad;
+ py_code = __Pyx_PyCode_New(
+ 0,
+ 0,
+ 0,
+ 0,
+ 0,
+ __pyx_empty_bytes, /*PyObject *code,*/
+ __pyx_empty_tuple, /*PyObject *consts,*/
+ __pyx_empty_tuple, /*PyObject *names,*/
+ __pyx_empty_tuple, /*PyObject *varnames,*/
+ __pyx_empty_tuple, /*PyObject *freevars,*/
+ __pyx_empty_tuple, /*PyObject *cellvars,*/
+ py_srcfile, /*PyObject *filename,*/
+ py_funcname, /*PyObject *name,*/
+ py_line,
+ __pyx_empty_bytes /*PyObject *lnotab*/
+ );
+ Py_DECREF(py_srcfile);
+ Py_DECREF(py_funcname);
+ return py_code;
+bad:
+ Py_XDECREF(py_srcfile);
+ Py_XDECREF(py_funcname);
+ return NULL;
+}
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+ int py_line, const char *filename) {
+ PyCodeObject *py_code = 0;
+ PyFrameObject *py_frame = 0;
+ py_code = __pyx_find_code_object(c_line ? c_line : py_line);
+ if (!py_code) {
+ py_code = __Pyx_CreateCodeObjectForTraceback(
+ funcname, c_line, py_line, filename);
+ if (!py_code) goto bad;
+ __pyx_insert_code_object(c_line ? c_line : py_line, py_code);
+ }
+ py_frame = PyFrame_New(
+ PyThreadState_GET(), /*PyThreadState *tstate,*/
+ py_code, /*PyCodeObject *code,*/
+ __pyx_d, /*PyObject *globals,*/
+ 0 /*PyObject *locals*/
+ );
+ if (!py_frame) goto bad;
+ py_frame->f_lineno = py_line;
+ PyTraceBack_Here(py_frame);
+bad:
+ Py_XDECREF(py_code);
+ Py_XDECREF(py_frame);
+}
+
+#if PY_MAJOR_VERSION < 3
+static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
+ if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
+ if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
+ PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
+ return -1;
+}
+static void __Pyx_ReleaseBuffer(Py_buffer *view) {
+ PyObject *obj = view->obj;
+ if (!obj) return;
+ if (PyObject_CheckBuffer(obj)) {
+ PyBuffer_Release(view);
+ return;
+ }
+ Py_DECREF(obj);
+ view->obj = NULL;
+}
+#endif
+
+
+ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
+ PyObject *empty_list = 0;
+ PyObject *module = 0;
+ PyObject *global_dict = 0;
+ PyObject *empty_dict = 0;
+ PyObject *list;
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_import;
+ py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
+ if (!py_import)
+ goto bad;
+ #endif
+ if (from_list)
+ list = from_list;
+ else {
+ empty_list = PyList_New(0);
+ if (!empty_list)
+ goto bad;
+ list = empty_list;
+ }
+ global_dict = PyModule_GetDict(__pyx_m);
+ if (!global_dict)
+ goto bad;
+ empty_dict = PyDict_New();
+ if (!empty_dict)
+ goto bad;
+ {
+ #if PY_MAJOR_VERSION >= 3
+ if (level == -1) {
+ if (strchr(__Pyx_MODULE_NAME, '.')) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(1);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, 1);
+ #endif
+ if (!module) {
+ if (!PyErr_ExceptionMatches(PyExc_ImportError))
+ goto bad;
+ PyErr_Clear();
+ }
+ }
+ level = 0;
+ }
+ #endif
+ if (!module) {
+ #if PY_VERSION_HEX < 0x03030000
+ PyObject *py_level = PyInt_FromLong(level);
+ if (!py_level)
+ goto bad;
+ module = PyObject_CallFunctionObjArgs(py_import,
+ name, global_dict, empty_dict, list, py_level, NULL);
+ Py_DECREF(py_level);
+ #else
+ module = PyImport_ImportModuleLevelObject(
+ name, global_dict, empty_dict, list, level);
+ #endif
+ }
+ }
+bad:
+ #if PY_VERSION_HEX < 0x03030000
+ Py_XDECREF(py_import);
+ #endif
+ Py_XDECREF(empty_list);
+ Py_XDECREF(empty_dict);
+ return module;
+}
+
+static PyObject *__pyx_memview_get_double(const char *itemp) {
+ return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
+}
+static int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
+ double value = __pyx_PyFloat_AsDouble(obj);
+ if ((value == (double)-1) && PyErr_Occurred())
+ return 0;
+ *(double *) itemp = value;
+ return 1;
+}
+
+#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value) \
+ { \
+ func_type value = func_value; \
+ if (sizeof(target_type) < sizeof(func_type)) { \
+ if (unlikely(value != (func_type) (target_type) value)) { \
+ func_type zero = 0; \
+ if (is_unsigned && unlikely(value < zero)) \
+ goto raise_neg_overflow; \
+ else \
+ goto raise_overflow; \
+ } \
+ } \
+ return (target_type) value; \
+ }
+
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ #include "longintrepr.h"
+ #endif
+#endif
+
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(long) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (long) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(long) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(long, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(long) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x))
+ } else if (sizeof(long) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ long val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (long) -1;
+ }
+ } else {
+ long val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (long) -1;
+ val = __Pyx_PyInt_As_long(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to long");
+ return (long) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to long");
+ return (long) -1;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_long(unsigned long value) {
+ const unsigned long neg_one = (unsigned long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(unsigned long) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(unsigned long) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(unsigned long) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(unsigned long) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(unsigned long) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(unsigned long),
+ little, !is_unsigned);
+ }
+}
+
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(int) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (int) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(int) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(int, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(int) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x))
+ } else if (sizeof(int) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ int val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (int) -1;
+ }
+ } else {
+ int val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (int) -1;
+ val = __Pyx_PyInt_As_int(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to int");
+ return (int) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to int");
+ return (int) -1;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
+ const long neg_one = (long) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(long) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(long) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(long) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(long) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(long),
+ little, !is_unsigned);
+ }
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
+ const int neg_one = (int) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+ if (is_unsigned) {
+ if (sizeof(int) < sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long)) {
+ return PyLong_FromUnsignedLong((unsigned long) value);
+ } else if (sizeof(int) <= sizeof(unsigned long long)) {
+ return PyLong_FromUnsignedLongLong((unsigned long long) value);
+ }
+ } else {
+ if (sizeof(int) <= sizeof(long)) {
+ return PyInt_FromLong((long) value);
+ } else if (sizeof(int) <= sizeof(long long)) {
+ return PyLong_FromLongLong((long long) value);
+ }
+ }
+ {
+ int one = 1; int little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&value;
+ return _PyLong_FromByteArray(bytes, sizeof(int),
+ little, !is_unsigned);
+ }
+}
+
+static int
+__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
+ char order, int ndim)
+{
+ int i, index, step, start;
+ Py_ssize_t itemsize = mvs->memview->view.itemsize;
+ if (order == 'F') {
+ step = 1;
+ start = 0;
+ } else {
+ step = -1;
+ start = ndim - 1;
+ }
+ for (i = 0; i < ndim; i++) {
+ index = start + step * i;
+ if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize)
+ return 0;
+ itemsize *= mvs->shape[index];
+ }
+ return 1;
+}
+
+static void
+__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
+ void **out_start, void **out_end,
+ int ndim, size_t itemsize)
+{
+ char *start, *end;
+ int i;
+ start = end = slice->data;
+ for (i = 0; i < ndim; i++) {
+ Py_ssize_t stride = slice->strides[i];
+ Py_ssize_t extent = slice->shape[i];
+ if (extent == 0) {
+ *out_start = *out_end = start;
+ return;
+ } else {
+ if (stride > 0)
+ end += stride * (extent - 1);
+ else
+ start += stride * (extent - 1);
+ }
+ }
+ *out_start = start;
+ *out_end = end + itemsize;
+}
+static int
+__pyx_slices_overlap(__Pyx_memviewslice *slice1,
+ __Pyx_memviewslice *slice2,
+ int ndim, size_t itemsize)
+{
+ void *start1, *end1, *start2, *end2;
+ __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
+ __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
+ return (start1 < end2) && (start2 < end1);
+}
+
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+ const char *mode, int ndim,
+ size_t sizeof_dtype, int contig_flag,
+ int dtype_is_object)
+{
+ __Pyx_RefNannyDeclarations
+ int i;
+ __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
+ struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
+ Py_buffer *buf = &from_memview->view;
+ PyObject *shape_tuple = NULL;
+ PyObject *temp_int = NULL;
+ struct __pyx_array_obj *array_obj = NULL;
+ struct __pyx_memoryview_obj *memview_obj = NULL;
+ __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
+ for (i = 0; i < ndim; i++) {
+ if (from_mvs->suboffsets[i] >= 0) {
+ PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
+ "indirect dimensions (axis %d)", i);
+ goto fail;
+ }
+ }
+ shape_tuple = PyTuple_New(ndim);
+ if (unlikely(!shape_tuple)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(shape_tuple);
+ for(i = 0; i < ndim; i++) {
+ temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
+ if(unlikely(!temp_int)) {
+ goto fail;
+ } else {
+ PyTuple_SET_ITEM(shape_tuple, i, temp_int);
+ temp_int = NULL;
+ }
+ }
+ array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
+ if (unlikely(!array_obj)) {
+ goto fail;
+ }
+ __Pyx_GOTREF(array_obj);
+ memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ (PyObject *) array_obj, contig_flag,
+ dtype_is_object,
+ from_mvs->memview->typeinfo);
+ if (unlikely(!memview_obj))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
+ goto fail;
+ if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
+ dtype_is_object) < 0))
+ goto fail;
+ goto no_fail;
+fail:
+ __Pyx_XDECREF(new_mvs.memview);
+ new_mvs.memview = NULL;
+ new_mvs.data = NULL;
+no_fail:
+ __Pyx_XDECREF(shape_tuple);
+ __Pyx_XDECREF(temp_int);
+ __Pyx_XDECREF(array_obj);
+ __Pyx_RefNannyFinishContext();
+ return new_mvs;
+}
+
+static CYTHON_INLINE PyObject *
+__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
+{
+ PyObject *cobj;
+#if PY_VERSION_HEX >= 0x02070000
+ cobj = PyCapsule_New(p, sig, NULL);
+#else
+ cobj = PyCObject_FromVoidPtr(p, NULL);
+#endif
+ return cobj;
+}
+
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
+ const char neg_one = (char) -1, const_zero = 0;
+ const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_Check(x))) {
+ if (sizeof(char) < sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
+ } else {
+ long val = PyInt_AS_LONG(x);
+ if (is_unsigned && unlikely(val < 0)) {
+ goto raise_neg_overflow;
+ }
+ return (char) val;
+ }
+ } else
+#endif
+ if (likely(PyLong_Check(x))) {
+ if (is_unsigned) {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (unlikely(Py_SIZE(x) < 0)) {
+ goto raise_neg_overflow;
+ }
+ if (sizeof(char) <= sizeof(unsigned long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x))
+ } else if (sizeof(char) <= sizeof(unsigned long long)) {
+ __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x))
+ }
+ } else {
+#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(x)) {
+ case 0: return 0;
+ case 1: __PYX_VERIFY_RETURN_INT(char, digit, +(((PyLongObject*)x)->ob_digit[0]));
+ case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
+ }
+ #endif
+#endif
+ if (sizeof(char) <= sizeof(long)) {
+ __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x))
+ } else if (sizeof(char) <= sizeof(long long)) {
+ __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x))
+ }
+ }
+ {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+ PyErr_SetString(PyExc_RuntimeError,
+ "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+ char val;
+ PyObject *v = __Pyx_PyNumber_Int(x);
+ #if PY_MAJOR_VERSION < 3
+ if (likely(v) && !PyLong_Check(v)) {
+ PyObject *tmp = v;
+ v = PyNumber_Long(tmp);
+ Py_DECREF(tmp);
+ }
+ #endif
+ if (likely(v)) {
+ int one = 1; int is_little = (int)*(unsigned char *)&one;
+ unsigned char *bytes = (unsigned char *)&val;
+ int ret = _PyLong_AsByteArray((PyLongObject *)v,
+ bytes, sizeof(val),
+ is_little, !is_unsigned);
+ Py_DECREF(v);
+ if (likely(!ret))
+ return val;
+ }
+#endif
+ return (char) -1;
+ }
+ } else {
+ char val;
+ PyObject *tmp = __Pyx_PyNumber_Int(x);
+ if (!tmp) return (char) -1;
+ val = __Pyx_PyInt_As_char(tmp);
+ Py_DECREF(tmp);
+ return val;
+ }
+raise_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "value too large to convert to char");
+ return (char) -1;
+raise_neg_overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "can't convert negative value to char");
+ return (char) -1;
+}
+
+static int
+__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
+{
+ int i;
+ if (!a || !b)
+ return 0;
+ if (a == b)
+ return 1;
+ if (a->size != b->size || a->typegroup != b->typegroup ||
+ a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
+ if (a->typegroup == 'H' || b->typegroup == 'H') {
+ return a->size == b->size;
+ } else {
+ return 0;
+ }
+ }
+ if (a->ndim) {
+ for (i = 0; i < a->ndim; i++)
+ if (a->arraysize[i] != b->arraysize[i])
+ return 0;
+ }
+ if (a->typegroup == 'S') {
+ if (a->flags != b->flags)
+ return 0;
+ if (a->fields || b->fields) {
+ if (!(a->fields && b->fields))
+ return 0;
+ for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
+ __Pyx_StructField *field_a = a->fields + i;
+ __Pyx_StructField *field_b = b->fields + i;
+ if (field_a->offset != field_b->offset ||
+ !__pyx_typeinfo_cmp(field_a->type, field_b->type))
+ return 0;
+ }
+ return !a->fields[i].type && !b->fields[i].type;
+ }
+ }
+ return 1;
+}
+
+static int
+__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
+{
+ if (buf->shape[dim] <= 1)
+ return 1;
+ if (buf->strides) {
+ if (spec & __Pyx_MEMVIEW_CONTIG) {
+ if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
+ if (buf->strides[dim] != sizeof(void *)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly contiguous "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ } else if (buf->strides[dim] != buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_FOLLOW) {
+ Py_ssize_t stride = buf->strides[dim];
+ if (stride < 0)
+ stride = -stride;
+ if (stride < buf->itemsize) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer and memoryview are not contiguous "
+ "in the same dimension.");
+ goto fail;
+ }
+ }
+ } else {
+ if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not contiguous in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (spec & (__Pyx_MEMVIEW_PTR)) {
+ PyErr_Format(PyExc_ValueError,
+ "C-contiguous buffer is not indirect in "
+ "dimension %d", dim);
+ goto fail;
+ } else if (buf->suboffsets) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer exposes suboffsets but no strides");
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
+{
+ if (spec & __Pyx_MEMVIEW_DIRECT) {
+ if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer not compatible with direct access "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ if (spec & __Pyx_MEMVIEW_PTR) {
+ if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer is not indirectly accessible "
+ "in dimension %d.", dim);
+ goto fail;
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int
+__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
+{
+ int i;
+ if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = 0; i < ndim; i++) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1)
+ {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not fortran contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
+ Py_ssize_t stride = 1;
+ for (i = ndim - 1; i >- 1; i--) {
+ if (stride * buf->itemsize != buf->strides[i] &&
+ buf->shape[i] > 1) {
+ PyErr_SetString(PyExc_ValueError,
+ "Buffer not C contiguous.");
+ goto fail;
+ }
+ stride = stride * buf->shape[i];
+ }
+ }
+ return 1;
+fail:
+ return 0;
+}
+static int __Pyx_ValidateAndInit_memviewslice(
+ int *axes_specs,
+ int c_or_f_flag,
+ int buf_flags,
+ int ndim,
+ __Pyx_TypeInfo *dtype,
+ __Pyx_BufFmt_StackElem stack[],
+ __Pyx_memviewslice *memviewslice,
+ PyObject *original_obj)
+{
+ struct __pyx_memoryview_obj *memview, *new_memview;
+ __Pyx_RefNannyDeclarations
+ Py_buffer *buf;
+ int i, spec = 0, retval = -1;
+ __Pyx_BufFmt_Context ctx;
+ int from_memoryview = __pyx_memoryview_check(original_obj);
+ __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
+ if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
+ original_obj)->typeinfo)) {
+ memview = (struct __pyx_memoryview_obj *) original_obj;
+ new_memview = NULL;
+ } else {
+ memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+ original_obj, buf_flags, 0, dtype);
+ new_memview = memview;
+ if (unlikely(!memview))
+ goto fail;
+ }
+ buf = &memview->view;
+ if (buf->ndim != ndim) {
+ PyErr_Format(PyExc_ValueError,
+ "Buffer has wrong number of dimensions (expected %d, got %d)",
+ ndim, buf->ndim);
+ goto fail;
+ }
+ if (new_memview) {
+ __Pyx_BufFmt_Init(&ctx, stack, dtype);
+ if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
+ }
+ if ((unsigned) buf->itemsize != dtype->size) {
+ PyErr_Format(PyExc_ValueError,
+ "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
+ "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
+ buf->itemsize,
+ (buf->itemsize > 1) ? "s" : "",
+ dtype->name,
+ dtype->size,
+ (dtype->size > 1) ? "s" : "");
+ goto fail;
+ }
+ for (i = 0; i < ndim; i++) {
+ spec = axes_specs[i];
+ if (!__pyx_check_strides(buf, i, ndim, spec))
+ goto fail;
+ if (!__pyx_check_suboffsets(buf, i, ndim, spec))
+ goto fail;
+ }
+ if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
+ goto fail;
+ if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
+ new_memview != NULL) == -1)) {
+ goto fail;
+ }
+ retval = 0;
+ goto no_fail;
+fail:
+ Py_XDECREF(new_memview);
+ retval = -1;
+no_fail:
+ __Pyx_RefNannyFinishContext();
+ return retval;
+}
+
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *obj) {
+ __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+ __Pyx_BufFmt_StackElem stack[1];
+ int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+ int retcode;
+ if (obj == Py_None) {
+ result.memview = (struct __pyx_memoryview_obj *) Py_None;
+ return result;
+ }
+ retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+ (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
+ &__Pyx_TypeInfo_double, stack,
+ &result, obj);
+ if (unlikely(retcode == -1))
+ goto __pyx_fail;
+ return result;
+__pyx_fail:
+ result.memview = NULL;
+ result.data = NULL;
+ return result;
+}
+
+static int __Pyx_check_binary_version(void) {
+ char ctversion[4], rtversion[4];
+ PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
+ PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
+ if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
+ char message[200];
+ PyOS_snprintf(message, sizeof(message),
+ "compiletime version %s of module '%.100s' "
+ "does not match runtime version %s",
+ ctversion, __Pyx_MODULE_NAME, rtversion);
+ return PyErr_WarnEx(NULL, message, 1);
+ }
+ return 0;
+}
+
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
+ while (t->p) {
+ #if PY_MAJOR_VERSION < 3
+ if (t->is_unicode) {
+ *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
+ } else if (t->intern) {
+ *t->p = PyString_InternFromString(t->s);
+ } else {
+ *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
+ }
+ #else
+ if (t->is_unicode | t->is_str) {
+ if (t->intern) {
+ *t->p = PyUnicode_InternFromString(t->s);
+ } else if (t->encoding) {
+ *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
+ } else {
+ *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
+ }
+ } else {
+ *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
+ }
+ #endif
+ if (!*t->p)
+ return -1;
+ ++t;
+ }
+ return 0;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
+ return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
+ Py_ssize_t ignore;
+ return __Pyx_PyObject_AsStringAndSize(o, &ignore);
+}
+static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+ if (
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ __Pyx_sys_getdefaultencoding_not_ascii &&
+#endif
+ PyUnicode_Check(o)) {
+#if PY_VERSION_HEX < 0x03030000
+ char* defenc_c;
+ PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
+ if (!defenc) return NULL;
+ defenc_c = PyBytes_AS_STRING(defenc);
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ {
+ char* end = defenc_c + PyBytes_GET_SIZE(defenc);
+ char* c;
+ for (c = defenc_c; c < end; c++) {
+ if ((unsigned char) (*c) >= 128) {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+ }
+ }
+#endif
+ *length = PyBytes_GET_SIZE(defenc);
+ return defenc_c;
+#else
+ if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+ if (PyUnicode_IS_ASCII(o)) {
+ *length = PyUnicode_GET_LENGTH(o);
+ return PyUnicode_AsUTF8(o);
+ } else {
+ PyUnicode_AsASCIIString(o);
+ return NULL;
+ }
+#else
+ return PyUnicode_AsUTF8AndSize(o, length);
+#endif
+#endif
+ } else
+#endif
+#if !CYTHON_COMPILING_IN_PYPY
+ if (PyByteArray_Check(o)) {
+ *length = PyByteArray_GET_SIZE(o);
+ return PyByteArray_AS_STRING(o);
+ } else
+#endif
+ {
+ char* result;
+ int r = PyBytes_AsStringAndSize(o, &result, length);
+ if (unlikely(r < 0)) {
+ return NULL;
+ } else {
+ return result;
+ }
+ }
+}
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
+ int is_true = x == Py_True;
+ if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
+ else return PyObject_IsTrue(x);
+}
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
+ PyNumberMethods *m;
+ const char *name = NULL;
+ PyObject *res = NULL;
+#if PY_MAJOR_VERSION < 3
+ if (PyInt_Check(x) || PyLong_Check(x))
+#else
+ if (PyLong_Check(x))
+#endif
+ return Py_INCREF(x), x;
+ m = Py_TYPE(x)->tp_as_number;
+#if PY_MAJOR_VERSION < 3
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Int(x);
+ }
+ else if (m && m->nb_long) {
+ name = "long";
+ res = PyNumber_Long(x);
+ }
+#else
+ if (m && m->nb_int) {
+ name = "int";
+ res = PyNumber_Long(x);
+ }
+#endif
+ if (res) {
+#if PY_MAJOR_VERSION < 3
+ if (!PyInt_Check(res) && !PyLong_Check(res)) {
+#else
+ if (!PyLong_Check(res)) {
+#endif
+ PyErr_Format(PyExc_TypeError,
+ "__%.4s__ returned non-%.4s (type %.200s)",
+ name, name, Py_TYPE(res)->tp_name);
+ Py_DECREF(res);
+ return NULL;
+ }
+ }
+ else if (!PyErr_Occurred()) {
+ PyErr_SetString(PyExc_TypeError,
+ "an integer is required");
+ }
+ return res;
+}
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
+ Py_ssize_t ival;
+ PyObject *x;
+#if PY_MAJOR_VERSION < 3
+ if (likely(PyInt_CheckExact(b)))
+ return PyInt_AS_LONG(b);
+#endif
+ if (likely(PyLong_CheckExact(b))) {
+ #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
+ #if CYTHON_USE_PYLONG_INTERNALS
+ switch (Py_SIZE(b)) {
+ case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0];
+ case 0: return 0;
+ case 1: return ((PyLongObject*)b)->ob_digit[0];
+ }
+ #endif
+ #endif
+ return PyLong_AsSsize_t(b);
+ }
+ x = PyNumber_Index(b);
+ if (!x) return -1;
+ ival = PyInt_AsSsize_t(x);
+ Py_DECREF(x);
+ return ival;
+}
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
+ return PyInt_FromSize_t(ival);
+}
+
+
+#endif /* Py_PYTHON_H */
diff --git a/silx/math/fit/peaks/peaks.pyx b/silx/math/fit/peaks/peaks.pyx
new file mode 100644
index 0000000..02753b0
--- /dev/null
+++ b/silx/math/fit/peaks/peaks.pyx
@@ -0,0 +1,176 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+"""This module provides a peak search function and tools related to peak
+analysis.
+"""
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "17/06/2016"
+
+import logging
+import numpy
+
+from . import filters
+
+logging.basicConfig()
+_logger = logging.getLogger(__name__)
+
+cimport cython
+from libc.stdlib cimport free
+
+cimport peaks_wrapper
+
+
+def peak_search(y, fwhm, sensitivity=3.5,
+ begin_index=None, end_index=None,
+ debug=False, relevance_info=False):
+ """Find peaks in a curve.
+
+ :param y: Data array
+ :type y: numpy.ndarray
+ :param fwhm: Estimated full width at half maximum of the typical peaks we
+ are interested in (expressed in number of samples)
+ :param sensitivity: Threshold factor used for peak detection. Only peaks
+ with amplitudes higher than ``σ * sensitivity`` - where ``σ`` is the
+ standard deviation of the noise - qualify as peaks.
+ :param begin_index: Index of the first sample of the region of interest
+ in the ``y`` array. If ``None``, start from the first sample.
+ :param end_index: Index of the last sample of the region of interest in
+ the ``y`` array. If ``None``, process until the last sample.
+ :param debug: If ``True``, print debug messages. Default: ``False``
+ :param relevance_info: If ``True``, add a second dimension with relevance
+ information to the output array. Default: ``False``
+ :return: 1D sequence with indices of peaks in the data
+ if ``relevance_info`` is ``False``.
+ Else, sequence of ``(peak_index, peak_relevance)`` tuples (one tuple
+ per peak).
+ :raise: ``IndexError`` if the number of peaks is too large to fit in the
+ output array.
+ """
+ cdef:
+ int i
+ double[::1] y_c
+ double* peaks_c
+ double* relevances_c
+
+ y_c = numpy.array(y,
+ copy=True,
+ dtype=numpy.float64,
+ order='C').reshape(-1)
+ if debug:
+ debug = 1
+ else:
+ debug = 0
+
+ if begin_index is None:
+ begin_index = 0
+ if end_index is None:
+ end_index = y_c.size - 1
+
+ n_peaks = peaks_wrapper.seek(begin_index, end_index, y_c.size,
+ fwhm, sensitivity, debug,
+ &y_c[0], &peaks_c, &relevances_c)
+
+
+ # A negative return value means that peaks were found but not enough
+ # memory could be allocated for all
+ if n_peaks < 0 and n_peaks != -123456:
+ msg = "Before memory allocation error happened, "
+ msg += "we found %d peaks.\n" % abs(n_peaks)
+ _logger.debug(msg)
+ msg = ""
+ for i in range(abs(n_peaks)):
+ msg += "peak index %f, " % peaks_c[i]
+ msg += "relevance %f\n" % relevances_c[i]
+ _logger.debug(msg)
+ free(peaks_c)
+ free(relevances_c)
+ raise MemoryError("Failed to reallocate memory for output arrays")
+ # Special value -123456 is returned if the initial memory allocation
+ # fails, before any search could be performed
+ elif n_peaks == -123456:
+ raise MemoryError("Failed to allocate initial memory for " +
+ "output arrays")
+
+ peaks = numpy.empty(shape=(n_peaks,),
+ dtype=numpy.float64)
+ relevances = numpy.empty(shape=(n_peaks,),
+ dtype=numpy.float64)
+
+ for i in range(n_peaks):
+ peaks[i] = peaks_c[i]
+ relevances[i] = relevances_c[i]
+
+ free(peaks_c)
+ free(relevances_c)
+
+ if not relevance_info:
+ return peaks
+ else:
+ return list(zip(peaks, relevances))
+
+
+def guess_fwhm(y):
+ """Return the full-width at half maximum for the largest peak in
+ the data array.
+
+ The algorithm removes the background, then finds a global maximum
+ and its corresponding FWHM.
+
+ This value can be used as an initial fit parameter, used as input for
+ an iterative fit function.
+
+ :param y: Data to be used for guessing the fwhm.
+ :return: Estimation of full-width at half maximum, based on fwhm of
+ the global maximum.
+ """
+ # set at a minimum value for the fwhm
+ fwhm_min = 4
+
+ # remove data background (computed with a strip filter)
+ background = filters.strip(y, w=1, niterations=1000)
+ yfit = y - background
+
+ # basic peak search: find the global maximum
+ maximum = max(yfit)
+ # find indices of all values == maximum
+ idx = numpy.nonzero(yfit == maximum)[0]
+ # take the last one (if any)
+ if not len(idx):
+ return 0
+ posindex = idx[-1]
+ height = yfit[posindex]
+
+ # now find the width of the peak at half maximum
+ imin = posindex
+ while yfit[imin] > 0.5 * height and imin > 0:
+ imin -= 1
+ imax = posindex
+ while yfit[imax] > 0.5 * height and imax < len(yfit) - 1:
+ imax += 1
+
+ fwhm = max(imax - imin - 1, fwhm_min)
+
+ return fwhm
diff --git a/silx/math/fit/peaks/peaks_wrapper.pxd b/silx/math/fit/peaks/peaks_wrapper.pxd
new file mode 100644
index 0000000..4c77dc6
--- /dev/null
+++ b/silx/math/fit/peaks/peaks_wrapper.pxd
@@ -0,0 +1,41 @@
+# coding: utf-8
+#/*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+cimport cython
+
+cdef extern from "peaks.h":
+ long seek(long begin_index,
+ long end_index,
+ long nsamples,
+ double fwhm,
+ double sensitivity,
+ double debug_info,
+ double * data,
+ double ** peaks,
+ double ** relevances)
+
diff --git a/silx/math/fit/peaks/src/peaks.c b/silx/math/fit/peaks/src/peaks.c
new file mode 100644
index 0000000..65cb4f6
--- /dev/null
+++ b/silx/math/fit/peaks/src/peaks.c
@@ -0,0 +1,255 @@
+#/*##########################################################################
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+#include <math.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include "peaks.h"
+
+
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+/* Peak search function, adapted from PyMca SpecFitFuns
+
+ This uses a convolution with the second-derivative of a gaussian curve, to
+ smooth the data.
+
+ Arguments:
+
+ - begin_index: First index of the region of interest in the input data
+ array
+ - end_index: Last index of the region of interest in the input data
+ array
+ - nsamples: Number of samples in the input array
+ - fwhm: Full width at half maximum for the gaussian used for smoothing.
+ - sensitivity:
+ - debug_info: If different from 0, print debugging messages
+ - data: input array of 1D data
+ - peaks: pointer to output array of peak indices
+ - relevances: pointer to output array of peak relevances
+*/
+long seek(long begin_index,
+ long end_index,
+ long nsamples,
+ double fwhm,
+ double sensitivity,
+ double debug_info,
+ double *data,
+ double **peaks,
+ double **relevances)
+{
+ /* local variables */
+ double *peaks0, *relevances0;
+ double *realloc_peaks, *realloc_relevances;
+ double sigma, sigma2, sigma4;
+ long max_gfactor = 100;
+ double gfactor[100];
+ long nr_factor;
+ double lowthreshold;
+ double data2[2];
+ double nom;
+ double den2;
+ long channel1;
+ long lld;
+ long cch;
+ long cfac, cfac2, max_cfac;
+ long ihelp1, ihelp2;
+ long i;
+ long max_npeaks = 100;
+ long n_peaks = 0;
+ double peakstarted = 0;
+
+ peaks0 = malloc(100 * sizeof(double));
+ relevances0 = malloc(100 * sizeof(double));
+ if (peaks0 == NULL || relevances0 == NULL) {
+ printf("Error: failed to allocate memory for peaks array.");
+ return(-123456);
+ }
+ /* Make sure the peaks matrix is filled with zeros */
+ for (i=0;i<100;i++){
+ peaks0[i] = 0.0;
+ relevances0[i] = 0.0;
+ }
+ /* Output pointers */
+ *peaks = peaks0;
+ *relevances = relevances0;
+
+ /* prepare the calculation of the Gaussian scaling factors */
+
+ sigma = fwhm / 2.35482;
+ sigma2 = sigma * sigma;
+ sigma4 = sigma2 * sigma2;
+ lowthreshold = 0.01 / sigma2;
+
+ /* calculate the factors until lower threshold reached */
+ nr_factor = 0;
+ max_cfac = MIN(max_gfactor, ((end_index - begin_index - 2) / 2) - 1);
+ for (cfac=0; cfac < max_cfac; cfac++) {
+ nr_factor++;
+ cfac2 = (cfac+1) * (cfac+1);
+ gfactor[cfac] = (sigma2 - cfac2) * exp(-cfac2/(sigma2*2.0)) / sigma4;
+
+ if ((gfactor[cfac] < lowthreshold)
+ && (gfactor[cfac] > (-lowthreshold))){
+ break;
+ }
+ }
+
+ /* What comes now is specific to MCA spectra ... */
+ lld = 0;
+ while (data[lld] == 0) {
+ lld++;
+ }
+ lld = lld + (int) (0.5 * fwhm);
+
+ channel1 = begin_index - nr_factor - 1;
+ channel1 = MAX (channel1, lld);
+ if(debug_info){
+ printf("nrfactor = %ld\n", nr_factor);
+ }
+ /* calculates smoothed value and variance at begincalc */
+ cch = MAX(begin_index, 0);
+ nom = data[cch] / sigma2;
+ den2 = data[cch] / sigma4;
+ for (cfac = 0; cfac < nr_factor; cfac++){
+ ihelp1 = cch-cfac;
+ if (ihelp1 < 0){
+ ihelp1 = 0;
+ }
+ ihelp2 = cch+cfac;
+ if (ihelp2 >= nsamples){
+ ihelp2 = nsamples-1;
+ }
+ nom += gfactor[cfac] * (data[ihelp2] + data[ihelp1]);
+ den2 += gfactor[cfac] * gfactor[cfac] *
+ (data[ihelp2] + data[ihelp1]);
+ }
+
+ /* now normalize the smoothed value to the standard deviation */
+ if (den2 <= 0.0) {
+ data2[1] = 0.0;
+ }else{
+ data2[1] = nom / sqrt(den2);
+ }
+ data[0] = data[1];
+
+ while (cch <= MIN(end_index,nsamples-2)){
+ /* calculate gaussian smoothed values */
+ data2[0] = data2[1];
+ cch++;
+ nom = data[cch]/sigma2;
+ den2 = data[cch] / sigma4;
+ for (cfac = 1; cfac < nr_factor; cfac++){
+ ihelp1 = cch-cfac;
+ if (ihelp1 < 0){
+ ihelp1 = 0;
+ }
+ ihelp2 = cch+cfac;
+ if (ihelp2 >= nsamples){
+ ihelp2 = nsamples-1;
+ }
+ nom += gfactor[cfac-1] * (data[ihelp2] + data[ihelp1]);
+ den2 += gfactor[cfac-1] * gfactor[cfac-1] *
+ (data[ihelp2] + data[ihelp1]);
+ }
+ /* now normalize the smoothed value to the standard deviation */
+ if (den2 <= 0) {
+ data2[1] = 0;
+ }else{
+ data2[1] = nom / sqrt(den2);
+ }
+ /* look if the current point falls in a peak */
+ if (data2[1] > sensitivity) {
+ if(peakstarted == 0){
+ if (data2[1] > data2[0]){
+ /* this second test is to prevent a peak from outside
+ the region from being detected at the beginning of the search */
+ peakstarted=1;
+ }
+ }
+ /* there is a peak */
+ if (debug_info){
+ printf("At cch = %ld y[cch] = %g\n", cch, data[cch]);
+ printf("data2[0] = %g\n", data2[0]);
+ printf("data2[1] = %g\n", data2[1]);
+ printf("sensitivity = %g\n", sensitivity);
+ }
+ if(peakstarted == 1){
+ /* look for the top of the peak */
+ if (data2[1] < data2[0]) {
+ /* we are close to the top of the peak */
+ if (debug_info){
+ printf("we are close to the top of the peak\n");
+ }
+ if (n_peaks == max_npeaks) {
+ max_npeaks = max_npeaks + 100;
+ realloc_peaks = realloc(peaks0, max_npeaks * sizeof(double));
+ realloc_relevances = realloc(relevances0, max_npeaks * sizeof(double));
+ if (realloc_peaks == NULL || realloc_relevances == NULL) {
+ printf("Error: failed to extend memory for peaks array.");
+ *peaks = peaks0;
+ *relevances = relevances0;
+ return(-n_peaks);
+ }
+ else {
+ peaks0 = realloc_peaks;
+ relevances0 = realloc_relevances;
+ }
+ }
+ peaks0[n_peaks] = cch-1;
+ relevances0[n_peaks] = data2[0];
+ n_peaks++;
+ peakstarted=2;
+ }
+ }
+ /* Doublet case */
+ if(peakstarted == 2){
+ if ((cch-peaks0[n_peaks-1]) > 0.6 * fwhm) {
+ if (data2[1] > data2[0]){
+ if(debug_info){
+ printf("We may have a doublet\n");
+ }
+ peakstarted=1;
+ }
+ }
+ }
+ }else{
+ if (peakstarted==1){
+ /* We were on a peak but we did not find the top */
+ if(debug_info){
+ printf("We were on a peak but we did not find the top\n");
+ }
+ }
+ peakstarted=0;
+ }
+ }
+ if(debug_info){
+ for (i=0;i< n_peaks;i++){
+ printf("Peak %ld found at ",i+1);
+ printf("index %g with y = %g\n", peaks0[i],data[(long ) peaks0[i]]);
+ }
+ }
+ *peaks = peaks0;
+ *relevances = relevances0;
+ return (n_peaks);
+}
diff --git a/silx/math/fit/setup.py b/silx/math/fit/setup.py
new file mode 100644
index 0000000..f4e1f42
--- /dev/null
+++ b/silx/math/fit/setup.py
@@ -0,0 +1,89 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+import os.path
+
+import numpy
+
+from numpy.distutils.misc_util import Configuration
+
+def configuration(parent_package='', top_path=None):
+ config = Configuration('fit', parent_package, top_path)
+ config.add_subpackage('test')
+
+ # =====================================
+ # fit functions
+ # =====================================
+ fit_dir = 'functions'
+ fit_src = [os.path.join(fit_dir, "src", srcf)
+ for srcf in ["funs.c"]]
+ fit_src.append(os.path.join(fit_dir, "functions.pyx"))
+ fit_inc = [os.path.join(fit_dir, 'include'), numpy.get_include()]
+
+ config.add_extension('functions',
+ sources=fit_src,
+ include_dirs=fit_inc,
+ language='c')
+
+ # =====================================
+ # fit filters
+ # =====================================
+ fit_dir = 'filters'
+ fit_src = [os.path.join(fit_dir, "src", srcf)
+ for srcf in ["smoothnd.c", "snip1d.c",
+ "snip2d.c", "snip3d.c", "strip.c"]]
+ fit_src.append(os.path.join(fit_dir, "filters.pyx"))
+ fit_inc = [os.path.join(fit_dir, 'include'), numpy.get_include()]
+
+ config.add_extension('filters',
+ sources=fit_src,
+ include_dirs=fit_inc,
+ language='c')
+
+ # =====================================
+ # peaks
+ # =====================================
+ fit_dir = 'peaks'
+ fit_src = [os.path.join(fit_dir, "src", srcf)
+ for srcf in ["peaks.c"]]
+ fit_src.append(os.path.join(fit_dir, "peaks.pyx"))
+ fit_inc = [os.path.join(fit_dir, 'include'), numpy.get_include()]
+
+ config.add_extension('peaks',
+ sources=fit_src,
+ include_dirs=fit_inc,
+ language='c')
+ # =====================================
+ # =====================================
+ return config
+
+
+if __name__ == "__main__":
+ from numpy.distutils.core import setup
+
+ setup(configuration=configuration)
diff --git a/silx/math/fit/test/__init__.py b/silx/math/fit/test/__init__.py
new file mode 100644
index 0000000..d3d8ce8
--- /dev/null
+++ b/silx/math/fit/test/__init__.py
@@ -0,0 +1,46 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "22/06/2016"
+
+import unittest
+
+from .test_fit import suite as test_curve_fit
+from .test_functions import suite as test_fitfuns
+from .test_filters import suite as test_fitfilters
+from .test_peaks import suite as test_peaks
+from .test_fitmanager import suite as test_fitmanager
+from .test_bgtheories import suite as test_bgtheories
+
+
+def suite():
+ test_suite = unittest.TestSuite()
+ test_suite.addTest(test_curve_fit())
+ test_suite.addTest(test_fitfuns())
+ test_suite.addTest(test_fitfilters())
+ test_suite.addTest(test_peaks())
+ test_suite.addTest(test_fitmanager())
+ test_suite.addTest(test_bgtheories())
+ return test_suite
diff --git a/silx/math/fit/test/test_bgtheories.py b/silx/math/fit/test/test_bgtheories.py
new file mode 100644
index 0000000..e9fea37
--- /dev/null
+++ b/silx/math/fit/test/test_bgtheories.py
@@ -0,0 +1,169 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+import copy
+import unittest
+import numpy
+import random
+
+from silx.math.fit import bgtheories
+from silx.math.fit.functions import sum_gauss
+
+
+class TestBgTheories(unittest.TestCase):
+ """
+ """
+ def setUp(self):
+ self.x = numpy.arange(100)
+ self.y = 10 + 0.05 * self.x + sum_gauss(self.x, 10., 45., 15.)
+ # add a very narrow high amplitude peak to test strip and snip
+ self.y += sum_gauss(self.x, 100., 75., 2.)
+ self.narrow_peak_index = list(self.x).index(75)
+ random.seed()
+
+ def tearDown(self):
+ pass
+
+ def testTheoriesAttrs(self):
+ for theory_name in bgtheories.THEORY:
+ self.assertIsInstance(theory_name, str)
+ self.assertTrue(hasattr(bgtheories.THEORY[theory_name],
+ "function"))
+ self.assertTrue(hasattr(bgtheories.THEORY[theory_name].function,
+ "__call__"))
+ # Ensure legacy functions are not renamed accidentally
+ self.assertTrue(
+ {"No Background", "Constant", "Linear", "Strip", "Snip"}.issubset(
+ set(bgtheories.THEORY)))
+
+ def testNoBg(self):
+ nobgfun = bgtheories.THEORY["No Background"].function
+ self.assertTrue(numpy.array_equal(nobgfun(self.x, self.y),
+ numpy.zeros_like(self.x)))
+ # default estimate
+ self.assertEqual(bgtheories.THEORY["No Background"].estimate(self.x, self.y),
+ ([], []))
+
+ def testConstant(self):
+ consfun = bgtheories.THEORY["Constant"].function
+ c = random.random() * 100
+ self.assertTrue(numpy.array_equal(consfun(self.x, self.y, c),
+ c * numpy.ones_like(self.x)))
+ # default estimate
+ esti_par, cons = bgtheories.THEORY["Constant"].estimate(self.x, self.y)
+ self.assertEqual(cons,
+ [[0, 0, 0]])
+ self.assertAlmostEqual(esti_par,
+ min(self.y))
+
+ def testLinear(self):
+ linfun = bgtheories.THEORY["Linear"].function
+ a = random.random() * 100
+ b = random.random() * 100
+ self.assertTrue(numpy.array_equal(linfun(self.x, self.y, a, b),
+ a + b * self.x))
+ # default estimate
+ esti_par, cons = bgtheories.THEORY["Linear"].estimate(self.x, self.y)
+
+ self.assertEqual(cons,
+ [[0, 0, 0], [0, 0, 0]])
+ self.assertAlmostEqual(esti_par[0], 10, places=3)
+ self.assertAlmostEqual(esti_par[1], 0.05, places=3)
+
+ def testStrip(self):
+ stripfun = bgtheories.THEORY["Strip"].function
+ anchors = sorted(random.sample(list(self.x), 4))
+ anchors_indices = [list(self.x).index(a) for a in anchors]
+
+ # we really want to strip away the narrow peak
+ anchors_indices_copy = copy.deepcopy(anchors_indices)
+ for idx in anchors_indices_copy:
+ if abs(idx - self.narrow_peak_index) < 5:
+ anchors_indices.remove(idx)
+ anchors.remove(self.x[idx])
+
+ width = 2
+ niter = 1000
+ bgtheories.THEORY["Strip"].configure(AnchorsList=anchors, AnchorsFlag=True)
+
+ bg = stripfun(self.x, self.y, width, niter)
+
+ # assert peak amplitude has been decreased
+ self.assertLess(bg[self.narrow_peak_index],
+ self.y[self.narrow_peak_index])
+
+ # default estimate
+ for i in anchors_indices:
+ self.assertEqual(bg[i], self.y[i])
+
+ # estimated parameters are equal to the default ones in the config dict
+ bgtheories.THEORY["Strip"].configure(StripWidth=7, StripIterations=8)
+ esti_par, cons = bgtheories.THEORY["Strip"].estimate(self.x, self.y)
+ self.assertTrue(numpy.array_equal(cons, [[3, 0, 0], [3, 0, 0]]))
+ self.assertEqual(esti_par, [7, 8])
+
+ def testSnip(self):
+ snipfun = bgtheories.THEORY["Snip"].function
+ anchors = sorted(random.sample(list(self.x), 4))
+ anchors_indices = [list(self.x).index(a) for a in anchors]
+
+ # we want to strip away the narrow peak, so remove nearby anchors
+ anchors_indices_copy = copy.deepcopy(anchors_indices)
+ for idx in anchors_indices_copy:
+ if abs(idx - self.narrow_peak_index) < 5:
+ anchors_indices.remove(idx)
+ anchors.remove(self.x[idx])
+
+ width = 16
+ bgtheories.THEORY["Snip"].configure(AnchorsList=anchors, AnchorsFlag=True)
+ bg = snipfun(self.x, self.y, width)
+
+ # assert peak amplitude has been decreased
+ self.assertLess(bg[self.narrow_peak_index],
+ self.y[self.narrow_peak_index],
+ "Snip didn't decrease the peak amplitude.")
+
+ # anchored data must remain fixed
+ for i in anchors_indices:
+ self.assertEqual(bg[i], self.y[i])
+
+ # estimated parameters are equal to the default ones in the config dict
+ bgtheories.THEORY["Snip"].configure(SnipWidth=7)
+ esti_par, cons = bgtheories.THEORY["Snip"].estimate(self.x, self.y)
+ self.assertTrue(numpy.array_equal(cons, [[3, 0, 0]]))
+ self.assertEqual(esti_par, [7])
+
+
+test_cases = (TestBgTheories,)
+
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")
diff --git a/silx/math/fit/test/test_filters.py b/silx/math/fit/test/test_filters.py
new file mode 100644
index 0000000..078b998
--- /dev/null
+++ b/silx/math/fit/test/test_filters.py
@@ -0,0 +1,137 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+import numpy
+import unittest
+from silx.math.fit import filters
+from silx.math.fit import functions
+from silx.test.utils import add_relative_noise
+
+
+class TestSmooth(unittest.TestCase):
+ """
+ Unit tests of smoothing functions.
+
+ Test that the difference between a synthetic curve with 5% added random
+ noise and the result of smoothing that signal is less than 5%. We compare
+ the sum of all samples in each curve.
+ """
+ def setUp(self):
+ x = numpy.arange(5000)
+ # (height1, center1, fwhm1, beamfwhm...)
+ slit_params = (50, 500, 200, 100,
+ 50, 600, 80, 30,
+ 20, 2000, 150, 150,
+ 50, 2250, 110, 100,
+ 40, 3000, 50, 10,
+ 23, 4980, 250, 20)
+
+ self.y1 = functions.sum_slit(x, *slit_params)
+ # 5% noise
+ self.y1 = add_relative_noise(self.y1, 5.)
+
+ # (height1, center1, fwhm1...)
+ step_params = (50, 500, 200,
+ 50, 600, 80,
+ 20, 2000, 150,
+ 50, 2250, 110,
+ 40, 3000, 50,
+ 23, 4980, 250,)
+
+ self.y2 = functions.sum_stepup(x, *step_params)
+ # 5% noise
+ self.y2 = add_relative_noise(self.y2, 5.)
+
+ self.y3 = functions.sum_stepdown(x, *step_params)
+ # 5% noise
+ self.y3 = add_relative_noise(self.y3, 5.)
+
+ def tearDown(self):
+ pass
+
+ def testSavitskyGolay(self):
+ npts = 25
+ for y in [self.y1, self.y2, self.y3]:
+ smoothed_y = filters.savitsky_golay(y, npoints=npts)
+
+ # we added +-5% of random noise. The difference must be much lower
+ # than 5%.
+ diff = abs(sum(smoothed_y) - sum(y)) / sum(y)
+ self.assertLess(diff, 0.05,
+ "Difference between data with 5%% noise and " +
+ "smoothed data is > 5%% (%f %%)" % (diff * 100))
+
+ # Try various smoothing levels
+ npts += 25
+
+ def testSmooth1d(self):
+ """Test the 1D smoothing against the formula
+ ys[i] = (y[i-1] + 2 * y[i] + y[i+1]) / 4 (for 1 < i < n-1)"""
+ smoothed_y = filters.smooth1d(self.y1)
+
+ for i in range(1, len(self.y1) - 1):
+ self.assertAlmostEqual(4 * smoothed_y[i],
+ self.y1[i-1] + 2 * self.y1[i] + self.y1[i+1])
+
+ def testSmooth2d(self):
+ """Test that a 2D smoothing is the same as two successive and
+ orthogonal 1D smoothings"""
+ x = numpy.arange(10000)
+
+ noise = 2 * numpy.random.random(10000) - 1
+ noise *= 0.05
+ y = x * (1 + noise)
+
+ y.shape = (100, 100)
+
+ smoothed_y = filters.smooth2d(y)
+
+ intermediate_smooth = numpy.zeros_like(y)
+ expected_smooth = numpy.zeros_like(y)
+ # smooth along first dimension
+ for i in range(0, y.shape[0]):
+ intermediate_smooth[i, :] = filters.smooth1d(y[i, :])
+
+ # smooth along second dimension
+ for j in range(0, y.shape[1]):
+ expected_smooth[:, j] = filters.smooth1d(intermediate_smooth[:, j])
+
+ for i in range(0, y.shape[0]):
+ for j in range(0, y.shape[1]):
+ self.assertAlmostEqual(smoothed_y[i, j],
+ expected_smooth[i, j])
+
+
+test_cases = (TestSmooth,)
+
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")
diff --git a/silx/math/fit/test/test_fit.py b/silx/math/fit/test/test_fit.py
new file mode 100644
index 0000000..4d159c0
--- /dev/null
+++ b/silx/math/fit/test/test_fit.py
@@ -0,0 +1,382 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+"""
+Nominal tests of the leastsq function.
+"""
+
+import unittest
+
+import numpy
+import sys
+
+
+class Test_leastsq(unittest.TestCase):
+ """
+ Unit tests of the leastsq function.
+ """
+
+ ndims = None
+
+ def setUp(self):
+ try:
+ from silx.math.fit import leastsq
+ self.instance = leastsq
+ except ImportError:
+ self.instance = None
+
+ def myexp(x):
+ # put a (bad) filter to avoid over/underflows
+ # with no python looping
+ return numpy.exp(x*numpy.less(abs(x), 250)) - \
+ 1.0 * numpy.greater_equal(abs(x), 250)
+
+ self.my_exp = myexp
+
+ def gauss(x, *params):
+ params = numpy.array(params, copy=False, dtype=numpy.float)
+ result = params[0] + params[1] * x
+ for i in range(2, len(params), 3):
+ p = params[i:(i+3)]
+ dummy = 2.3548200450309493*(x - p[1])/p[2]
+ result += p[0] * self.my_exp(-0.5 * dummy * dummy)
+ return result
+
+ self.gauss = gauss
+
+ def gauss_derivative(x, params, idx):
+ if idx == 0:
+ return numpy.ones(len(x), numpy.float)
+ if idx == 1:
+ return x
+ gaussian_peak = (idx - 2) // 3
+ gaussian_parameter = (idx - 2) % 3
+ actual_idx = 2 + 3 * gaussian_peak
+ p = params[actual_idx:(actual_idx+3)]
+ if gaussian_parameter == 0:
+ return self.gauss(x, *[0, 0, 1.0, p[1], p[2]])
+ if gaussian_parameter == 1:
+ tmp = self.gauss(x, *[0, 0, p[0], p[1], p[2]])
+ tmp *= 2.3548200450309493*(x - p[1])/p[2]
+ return tmp * 2.3548200450309493/p[2]
+ if gaussian_parameter == 2:
+ tmp = self.gauss(x, *[0, 0, p[0], p[1], p[2]])
+ tmp *= 2.3548200450309493*(x - p[1])/p[2]
+ return tmp * 2.3548200450309493*(x - p[1])/(p[2]*p[2])
+
+ self.gauss_derivative = gauss_derivative
+
+ def tearDown(self):
+ self.instance = None
+ self.gauss = None
+ self.gauss_derivative = None
+ self.my_exp = None
+ self.model_function = None
+ self.model_derivative = None
+
+ def testImport(self):
+ self.assertTrue(self.instance is not None,
+ "Cannot import leastsq from silx.math.fit")
+
+ def testUnconstrainedFitNoWeight(self):
+ parameters_actual = [10.5, 2, 1000.0, 20., 15]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10]
+ model_function = self.gauss
+
+ fittedpar, cov = self.instance(model_function, x, y, parameters_estimate)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testUnconstrainedFitWeight(self):
+ parameters_actual = [10.5,2,1000.0,20.,15]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ sigma = numpy.sqrt(y)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10]
+ model_function = self.gauss
+
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testDerivativeFunction(self):
+ parameters_actual = [10.5, 2, 10000.0, 20., 150, 5000, 900., 300]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ delta = numpy.sqrt(numpy.finfo(numpy.float).eps)
+ for i in range(len(parameters_actual)):
+ p = parameters_actual * 1
+ if p[i] == 0:
+ delta_par = delta
+ else:
+ delta_par = p[i] * delta
+ if i > 2:
+ p[0] = 0.0
+ p[1] = 0.0
+ p[i] += delta_par
+ yPlus = self.gauss(x, *p)
+ p[i] = parameters_actual[i] - delta_par
+ yMinus = self.gauss(x, *p)
+ numerical_derivative = (yPlus - yMinus) / (2 * delta_par)
+ #numerical_derivative = (self.gauss(x, *p) - y) / delta_par
+ p[i] = parameters_actual[i]
+ derivative = self.gauss_derivative(x, p, i)
+ diff = numerical_derivative - derivative
+ test_condition = numpy.allclose(numerical_derivative,
+ derivative, atol=5.0e-6)
+ if not test_condition:
+ msg = "Error calculating derivative of parameter %d." % i
+ msg += "\n diff min = %g diff max = %g" % (diff.min(), diff.max())
+ self.assertTrue(test_condition, msg)
+
+ def testConstrainedFit(self):
+ CFREE = 0
+ CPOSITIVE = 1
+ CQUOTED = 2
+ CFIXED = 3
+ CFACTOR = 4
+ CDELTA = 5
+ CSUM = 6
+ parameters_actual = [10.5, 2, 10000.0, 20., 150, 5000, 900., 300]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10, 400, 850, 200]
+ model_function = self.gauss
+ model_deriv = self.gauss_derivative
+ constraints_all_free = [[0, 0, 0]] * len(parameters_actual)
+ constraints_all_positive = [[1, 0, 0]] * len(parameters_actual)
+ constraints_delta_position = [[0, 0, 0]] * len(parameters_actual)
+ constraints_delta_position[6] = [CDELTA, 3, 880]
+ constraints_sum_position = constraints_all_positive * 1
+ constraints_sum_position[6] = [CSUM, 3, 920]
+ constraints_factor = constraints_delta_position * 1
+ constraints_factor[2] = [CFACTOR, 5, 2]
+ constraints_list = [None,
+ constraints_all_free,
+ constraints_all_positive,
+ constraints_delta_position,
+ constraints_sum_position]
+
+ # for better code coverage, the warning recommending to set full_output
+ # to True when using constraints should be shown at least once
+ full_output = True
+ for index, constraints in enumerate(constraints_list):
+ if index == 2:
+ full_output = None
+ elif index == 3:
+ full_output = 0
+ for model_deriv in [None, self.gauss_derivative]:
+ for sigma in [None, numpy.sqrt(y)]:
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ constraints=constraints,
+ model_deriv=model_deriv,
+ full_output=full_output)[:2]
+ full_output = True
+
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testUnconstrainedFitAnalyticalDerivative(self):
+ parameters_actual = [10.5, 2, 1000.0, 20., 15]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ sigma = numpy.sqrt(y)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10]
+ model_function = self.gauss
+ model_deriv = self.gauss_derivative
+
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ model_deriv=model_deriv)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testBadlyShapedData(self):
+ parameters_actual = [10.5, 2, 1000.0, 20., 15]
+ x = numpy.arange(10000.).reshape(1000, 10)
+ y = self.gauss(x, *parameters_actual)
+ sigma = numpy.sqrt(y)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10]
+ model_function = self.gauss
+
+ for check_finite in [True, False]:
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ check_finite=check_finite)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testDataWithNaN(self):
+ parameters_actual = [10.5, 2, 1000.0, 20., 15]
+ x = numpy.arange(10000.).reshape(1000, 10)
+ y = self.gauss(x, *parameters_actual)
+ sigma = numpy.sqrt(y)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10]
+ model_function = self.gauss
+ x[500] = numpy.inf
+ # check default behavior
+ try:
+ self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma)
+ except ValueError:
+ info = "%s" % sys.exc_info()[1]
+ self.assertTrue("array must not contain inf" in info)
+
+ # check requested behavior
+ try:
+ self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ check_finite=True)
+ except ValueError:
+ info = "%s" % sys.exc_info()[1]
+ self.assertTrue("array must not contain inf" in info)
+
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ check_finite=False)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ # testing now with ydata containing NaN
+ x = numpy.arange(10000.).reshape(1000, 10)
+ y[500] = numpy.nan
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ check_finite=False)
+
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ # testing now with sigma containing NaN
+ sigma[300] = numpy.nan
+ fittedpar, cov = self.instance(model_function, x, y,
+ parameters_estimate,
+ sigma=sigma,
+ check_finite=False)
+ test_condition = numpy.allclose(parameters_actual, fittedpar)
+ if not test_condition:
+ msg = "Unsuccessfull fit\n"
+ for i in range(len(fittedpar)):
+ msg += "Expected %g obtained %g\n" % (parameters_actual[i],
+ fittedpar[i])
+ self.assertTrue(test_condition, msg)
+
+ def testUncertainties(self):
+ """Test for validity of uncertainties in returned full-output
+ dictionary. This is a non-regression test for pull request #197"""
+ parameters_actual = [10.5, 2, 1000.0, 20., 15, 2001.0, 30.1, 16]
+ x = numpy.arange(10000.)
+ y = self.gauss(x, *parameters_actual)
+ parameters_estimate = [0.0, 1.0, 900.0, 25., 10., 1500., 20., 2.0]
+
+ # test that uncertainties are not 0.
+ fittedpar, cov, infodict = self.instance(self.gauss, x, y, parameters_estimate,
+ full_output=True)
+ uncertainties = infodict["uncertainties"]
+ self.assertEqual(len(uncertainties), len(parameters_actual))
+ self.assertEqual(len(uncertainties), len(fittedpar))
+ for uncertainty in uncertainties:
+ self.assertNotAlmostEqual(uncertainty, 0.)
+
+ # set constraint FIXED for half the parameters.
+ # This should cause leastsq to return 100% uncertainty.
+ parameters_estimate = [10.6, 2.1, 1000.1, 20.1, 15.1, 2001.1, 30.2, 16.1]
+ CFIXED = 3
+ CFREE = 0
+ constraints = []
+ for i in range(len(parameters_estimate)):
+ if i % 2:
+ constraints.append([CFIXED, 0, 0])
+ else:
+ constraints.append([CFREE, 0, 0])
+ fittedpar, cov, infodict = self.instance(self.gauss, x, y, parameters_estimate,
+ constraints=constraints,
+ full_output=True)
+ uncertainties = infodict["uncertainties"]
+ for i in range(len(parameters_estimate)):
+ if i % 2:
+ # test that all FIXED parameters have 100% uncertainty
+ self.assertAlmostEqual(uncertainties[i],
+ parameters_estimate[i])
+
+
+test_cases = (Test_leastsq,)
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")
diff --git a/silx/math/fit/test/test_fitmanager.py b/silx/math/fit/test/test_fitmanager.py
new file mode 100644
index 0000000..38c4802
--- /dev/null
+++ b/silx/math/fit/test/test_fitmanager.py
@@ -0,0 +1,498 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016-2017 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+"""
+Tests for fitmanager module
+"""
+
+import unittest
+import numpy
+import os.path
+
+from silx.math.fit import fitmanager
+from silx.math.fit import fittheories
+from silx.math.fit import bgtheories
+from silx.math.fit.fittheory import FitTheory
+from silx.math.fit.functions import sum_gauss, sum_stepdown, sum_stepup
+
+from silx.test.utils import temp_dir
+
+custom_function_definition = """
+import copy
+from silx.math.fit.fittheory import FitTheory
+
+CONFIG = {'d': 1.}
+
+def myfun(x, a, b, c):
+ "Model function"
+ return (a * x**2 + b * x + c) / CONFIG['d']
+
+def myesti(x, y):
+ "Initial parameters for iterative fit (a, b, c) = (1, 1, 1)"
+ return (1., 1., 1.), ((0, 0, 0), (0, 0, 0), (0, 0, 0))
+
+def myconfig(d=1., **kw):
+ "This function can modify CONFIG"
+ CONFIG["d"] = d
+ return CONFIG
+
+def myderiv(x, parameters, index):
+ "Custom derivative (does not work, causes singular matrix)"
+ pars_plus = copy.copy(parameters)
+ pars_plus[index] *= 1.0001
+
+ pars_minus = parameters
+ pars_minus[index] *= copy.copy(0.9999)
+
+ delta_fun = myfun(x, *pars_plus) - myfun(x, *pars_minus)
+ delta_par = parameters[index] * 0.0001 * 2
+
+ return delta_fun / delta_par
+
+THEORY = {
+ 'my fit theory':
+ FitTheory(function=myfun,
+ parameters=('A', 'B', 'C'),
+ estimate=myesti,
+ configure=myconfig,
+ derivative=myderiv)
+}
+
+"""
+
+old_custom_function_definition = """
+CONFIG = {'d': 1.0}
+
+def myfun(x, a, b, c):
+ "Model function"
+ return (a * x**2 + b * x + c) / CONFIG['d']
+
+def myesti(x, y, bg, xscalinq, yscaling):
+ "Initial parameters for iterative fit (a, b, c) = (1, 1, 1)"
+ return (1., 1., 1.), ((0, 0, 0), (0, 0, 0), (0, 0, 0))
+
+def myconfig(**kw):
+ "Update or complete CONFIG dictionary"
+ for key in kw:
+ CONFIG[key] = kw[key]
+ return CONFIG
+
+THEORY = ['my fit theory']
+PARAMETERS = [('A', 'B', 'C')]
+FUNCTION = [myfun]
+ESTIMATE = [myesti]
+CONFIGURE = [myconfig]
+
+"""
+
+
+def _order_of_magnitude(x):
+ return numpy.log10(x).round()
+
+
+class TestFitmanager(unittest.TestCase):
+ """
+ Unit tests of multi-peak functions.
+ """
+ def setUp(self):
+ pass
+
+ def tearDown(self):
+ pass
+
+ def testFitManager(self):
+ """Test fit manager on synthetic data using a gaussian function
+ and a linear background"""
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(1000).astype(numpy.float)
+
+ p = [1000, 100., 250,
+ 255, 650., 45,
+ 1500, 800.5, 95]
+ linear_bg = 2.65 * x + 13
+ y = linear_bg + sum_gauss(x, *p)
+
+ # Fitting
+ fit = fitmanager.FitManager()
+ fit.setdata(x=x, y=y)
+ fit.loadtheories(fittheories)
+ # Use one of the default fit functions
+ fit.settheory('Gaussians')
+ fit.setbackground('Linear')
+ fit.estimate()
+ fit.runfit()
+
+ # fit.fit_results[]
+
+ # first 2 parameters are related to the linear background
+ self.assertEqual(fit.fit_results[0]["name"], "Constant")
+ self.assertAlmostEqual(fit.fit_results[0]["fitresult"], 13)
+ self.assertEqual(fit.fit_results[1]["name"], "Slope")
+ self.assertAlmostEqual(fit.fit_results[1]["fitresult"], 2.65)
+
+ for i, param in enumerate(fit.fit_results[2:]):
+ param_number = i // 3 + 1
+ if i % 3 == 0:
+ self.assertEqual(param["name"],
+ "Height%d" % param_number)
+ elif i % 3 == 1:
+ self.assertEqual(param["name"],
+ "Position%d" % param_number)
+ elif i % 3 == 2:
+ self.assertEqual(param["name"],
+ "FWHM%d" % param_number)
+
+ self.assertAlmostEqual(param["fitresult"],
+ p[i])
+ self.assertAlmostEqual(_order_of_magnitude(param["estimation"]),
+ _order_of_magnitude(p[i]))
+
+ def testLoadCustomFitFunction(self):
+ """Test FitManager using a custom fit function defined in an external
+ file and imported with FitManager.loadtheories"""
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(100).astype(numpy.float)
+
+ # a, b, c are the fit parameters
+ # d is a known scaling parameter that is set using configure()
+ a, b, c, d = 1.5, 2.5, 3.5, 4.5
+ y = (a * x**2 + b * x + c) / d
+
+ # Fitting
+ fit = fitmanager.FitManager()
+ fit.setdata(x=x, y=y)
+
+ # Create a temporary function definition file, and import it
+ with temp_dir() as tmpDir:
+ tmpfile = os.path.join(tmpDir, 'customfun.py')
+ # custom_function_definition
+ fd = open(tmpfile, "w")
+ fd.write(custom_function_definition)
+ fd.close()
+ fit.loadtheories(tmpfile)
+ tmpfile_pyc = os.path.join(tmpDir, 'customfun.pyc')
+ if os.path.exists(tmpfile_pyc):
+ os.unlink(tmpfile_pyc)
+ os.unlink(tmpfile)
+
+ fit.settheory('my fit theory')
+ # Test configure
+ fit.configure(d=4.5)
+ fit.estimate()
+ fit.runfit()
+
+ self.assertEqual(fit.fit_results[0]["name"],
+ "A1")
+ self.assertAlmostEqual(fit.fit_results[0]["fitresult"],
+ 1.5)
+ self.assertEqual(fit.fit_results[1]["name"],
+ "B1")
+ self.assertAlmostEqual(fit.fit_results[1]["fitresult"],
+ 2.5)
+ self.assertEqual(fit.fit_results[2]["name"],
+ "C1")
+ self.assertAlmostEqual(fit.fit_results[2]["fitresult"],
+ 3.5)
+
+ def testLoadOldCustomFitFunction(self):
+ """Test FitManager using a custom fit function defined in an external
+ file and imported with FitManager.loadtheories (legacy PyMca format)"""
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(100).astype(numpy.float)
+
+ # a, b, c are the fit parameters
+ # d is a known scaling parameter that is set using configure()
+ a, b, c, d = 1.5, 2.5, 3.5, 4.5
+ y = (a * x**2 + b * x + c) / d
+
+ # Fitting
+ fit = fitmanager.FitManager()
+ fit.setdata(x=x, y=y)
+
+ # Create a temporary function definition file, and import it
+ with temp_dir() as tmpDir:
+ tmpfile = os.path.join(tmpDir, 'oldcustomfun.py')
+ # custom_function_definition
+ fd = open(tmpfile, "w")
+ fd.write(old_custom_function_definition)
+ fd.close()
+ fit.loadtheories(tmpfile)
+ tmpfile_pyc = os.path.join(tmpDir, 'oldcustomfun.pyc')
+ if os.path.exists(tmpfile_pyc):
+ os.unlink(tmpfile_pyc)
+ os.unlink(tmpfile)
+
+ fit.settheory('my fit theory')
+ fit.configure(d=4.5)
+ fit.estimate()
+ fit.runfit()
+
+ self.assertEqual(fit.fit_results[0]["name"],
+ "A1")
+ self.assertAlmostEqual(fit.fit_results[0]["fitresult"],
+ 1.5)
+ self.assertEqual(fit.fit_results[1]["name"],
+ "B1")
+ self.assertAlmostEqual(fit.fit_results[1]["fitresult"],
+ 2.5)
+ self.assertEqual(fit.fit_results[2]["name"],
+ "C1")
+ self.assertAlmostEqual(fit.fit_results[2]["fitresult"],
+ 3.5)
+
+ def testAddTheory(self, estimate=True):
+ """Test FitManager using a custom fit function imported with
+ FitManager.addtheory"""
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(100).astype(numpy.float)
+
+ # a, b, c are the fit parameters
+ # d is a known scaling parameter that is set using configure()
+ a, b, c, d = -3.14, 1234.5, 10000, 4.5
+ y = (a * x**2 + b * x + c) / d
+
+ # Fitting
+ fit = fitmanager.FitManager()
+ fit.setdata(x=x, y=y)
+
+ # Define and add the fit theory
+ CONFIG = {'d': 1.}
+
+ def myfun(x_, a_, b_, c_):
+ """"Model function"""
+ return (a_ * x_**2 + b_ * x_ + c_) / CONFIG['d']
+
+ def myesti(x_, y_):
+ """"Initial parameters for iterative fit:
+ (a, b, c) = (1, 1, 1)
+ Constraints all set to 0 (FREE)"""
+ return (1., 1., 1.), ((0, 0, 0), (0, 0, 0), (0, 0, 0))
+
+ def myconfig(d_=1., **kw):
+ """This function can modify CONFIG"""
+ CONFIG["d"] = d_
+ return CONFIG
+
+ def myderiv(x_, parameters, index):
+ """Custom derivative"""
+ pars_plus = numpy.array(parameters, copy=True)
+ pars_plus[index] *= 1.001
+
+ pars_minus = numpy.array(parameters, copy=True)
+ pars_minus[index] *= 0.999
+
+ delta_fun = myfun(x_, *pars_plus) - myfun(x_, *pars_minus)
+ delta_par = parameters[index] * 0.001 * 2
+
+ return delta_fun / delta_par
+
+ fit.addtheory("polynomial",
+ FitTheory(function=myfun,
+ parameters=["A", "B", "C"],
+ estimate=myesti if estimate else None,
+ configure=myconfig,
+ derivative=myderiv))
+
+ fit.settheory('polynomial')
+ fit.configure(d_=4.5)
+ fit.estimate()
+ params1, sigmas, infodict = fit.runfit()
+
+ self.assertEqual(fit.fit_results[0]["name"],
+ "A1")
+ self.assertAlmostEqual(fit.fit_results[0]["fitresult"],
+ -3.14)
+ self.assertEqual(fit.fit_results[1]["name"],
+ "B1")
+ # params1[1] is the same as fit.fit_results[1]["fitresult"]
+ self.assertAlmostEqual(params1[1],
+ 1234.5)
+ self.assertEqual(fit.fit_results[2]["name"],
+ "C1")
+ self.assertAlmostEqual(params1[2],
+ 10000)
+
+ # change configuration scaling factor and check that the fit returns
+ # different values
+ fit.configure(d_=5.)
+ fit.estimate()
+ params2, sigmas, infodict = fit.runfit()
+ for p1, p2 in zip(params1, params2):
+ self.assertFalse(numpy.array_equal(p1, p2),
+ "Fit parameters are equal even though the " +
+ "configuration has been changed")
+
+ def testNoEstimate(self):
+ """Ensure that the in the absence of the estimation function,
+ the default estimation function :meth:`FitTheory.default_estimate`
+ is used."""
+ self.testAddTheory(estimate=False)
+
+ def testStep(self):
+ """Test fit manager on a step function with a more complex estimate
+ function than the gaussian (convolution filter)"""
+ for theory_name, theory_fun in (('Step Down', sum_stepdown),
+ ('Step Up', sum_stepup)):
+ # Create synthetic data with a sum of gaussian functions
+ x = numpy.arange(1000).astype(numpy.float)
+
+ # ('Height', 'Position', 'FWHM')
+ p = [1000, 439, 250]
+
+ constantbg = 13
+ y = theory_fun(x, *p) + constantbg
+
+ # Fitting
+ fit = fitmanager.FitManager()
+ fit.setdata(x=x, y=y)
+ fit.loadtheories(fittheories)
+ fit.settheory(theory_name)
+ fit.setbackground('Constant')
+
+ fit.estimate()
+
+ params, sigmas, infodict = fit.runfit()
+
+ # first parameter is the constant background
+ self.assertAlmostEqual(params[0], 13, places=5)
+ for i, param in enumerate(params[1:]):
+ self.assertAlmostEqual(param, p[i], places=5)
+ self.assertAlmostEqual(_order_of_magnitude(fit.fit_results[i+1]["estimation"]),
+ _order_of_magnitude(p[i]))
+
+
+def quadratic(x, a, b, c):
+ return a * x**2 + b * x + c
+
+
+def cubic(x, a, b, c, d):
+ return a * x**3 + b * x**2 + c * x + d
+
+
+class TestPolynomials(unittest.TestCase):
+ """Test polynomial fit theories and fit background"""
+ def setUp(self):
+ self.x = numpy.arange(100).astype(numpy.float)
+
+ def testQuadraticBg(self):
+ gaussian_params = [100, 45, 8]
+ poly_params = [0.05, -2, 3]
+ p = numpy.poly1d(poly_params)
+
+ y = p(self.x) + sum_gauss(self.x, *gaussian_params)
+
+ fm = fitmanager.FitManager(self.x, y)
+ fm.loadbgtheories(bgtheories)
+ fm.loadtheories(fittheories)
+ fm.settheory("Gaussians")
+ fm.setbackground("Degree 2 Polynomial")
+ esti_params = fm.estimate()
+ fit_params = fm.runfit()[0]
+
+ for p, pfit in zip(poly_params + gaussian_params, fit_params):
+ self.assertAlmostEqual(p,
+ pfit)
+
+ def testCubicBg(self):
+ gaussian_params = [1000, 45, 8]
+ poly_params = [0.0005, -0.05, 3, -4]
+ p = numpy.poly1d(poly_params)
+
+ y = p(self.x) + sum_gauss(self.x, *gaussian_params)
+
+ fm = fitmanager.FitManager(self.x, y)
+ fm.loadtheories(fittheories)
+ fm.settheory("Gaussians")
+ fm.setbackground("Degree 3 Polynomial")
+ esti_params = fm.estimate()
+ fit_params = fm.runfit()[0]
+
+ for p, pfit in zip(poly_params + gaussian_params, fit_params):
+ self.assertAlmostEqual(p,
+ pfit)
+
+ def testQuarticcBg(self):
+ gaussian_params = [10000, 69, 25]
+ poly_params = [5e-10, 0.0005, 0.005, 2, 4]
+ p = numpy.poly1d(poly_params)
+
+ y = p(self.x) + sum_gauss(self.x, *gaussian_params)
+
+ fm = fitmanager.FitManager(self.x, y)
+ fm.loadtheories(fittheories)
+ fm.settheory("Gaussians")
+ fm.setbackground("Degree 4 Polynomial")
+ esti_params = fm.estimate()
+ fit_params = fm.runfit()[0]
+
+ for p, pfit in zip(poly_params + gaussian_params, fit_params):
+ self.assertAlmostEqual(p,
+ pfit,
+ places=5)
+
+ def _testPoly(self, poly_params, theory, places=5):
+ p = numpy.poly1d(poly_params)
+
+ y = p(self.x)
+
+ fm = fitmanager.FitManager(self.x, y)
+ fm.loadbgtheories(bgtheories)
+ fm.loadtheories(fittheories)
+ fm.settheory(theory)
+ esti_params = fm.estimate()
+ fit_params = fm.runfit()[0]
+
+ for p, pfit in zip(poly_params, fit_params):
+ self.assertAlmostEqual(p, pfit, places=places)
+
+ def testQuadratic(self):
+ self._testPoly([0.05, -2, 3],
+ "Degree 2 Polynomial")
+
+ def testCubic(self):
+ self._testPoly([0.0005, -0.05, 3, -4],
+ "Degree 3 Polynomial")
+
+ def testQuartic(self):
+ self._testPoly([1, -2, 3, -4, -5],
+ "Degree 4 Polynomial")
+
+ def testQuintic(self):
+ self._testPoly([1, -2, 3, -4, -5, 6],
+ "Degree 5 Polynomial",
+ places=4)
+
+
+test_cases = (TestFitmanager, TestPolynomials)
+
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")
diff --git a/silx/math/fit/test/test_functions.py b/silx/math/fit/test/test_functions.py
new file mode 100644
index 0000000..ce7dbd6
--- /dev/null
+++ b/silx/math/fit/test/test_functions.py
@@ -0,0 +1,272 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+"""
+Tests for functions module
+"""
+
+import unittest
+import numpy
+import math
+
+from silx.math.fit import functions
+
+__authors__ = ["P. Knobel"]
+__license__ = "MIT"
+__date__ = "21/07/2016"
+
+class Test_functions(unittest.TestCase):
+ """
+ Unit tests of multi-peak functions.
+ """
+ def setUp(self):
+ self.x = numpy.arange(11)
+
+ # height, center, sigma1, sigma2
+ (h, c, s1, s2) = (7., 5., 3., 2.1)
+ self.g_params = {
+ "height": h,
+ "center": c,
+ #"sigma": s,
+ "fwhm1": 2 * math.sqrt(2 * math.log(2)) * s1,
+ "fwhm2": 2 * math.sqrt(2 * math.log(2)) * s2,
+ "area1": h * s1 * math.sqrt(2 * math.pi)
+ }
+ # result of `7 * scipy.signal.gaussian(11, 3)`
+ self.scipy_gaussian = numpy.array(
+ [1.74546546, 2.87778603, 4.24571462, 5.60516182, 6.62171628,
+ 7., 6.62171628, 5.60516182, 4.24571462, 2.87778603,
+ 1.74546546]
+ )
+
+ # result of:
+ # numpy.concatenate((7 * scipy.signal.gaussian(11, 3)[0:5],
+ # 7 * scipy.signal.gaussian(11, 2.1)[5:11]))
+ self.scipy_asym_gaussian = numpy.array(
+ [1.74546546, 2.87778603, 4.24571462, 5.60516182, 6.62171628,
+ 7., 6.24968751, 4.44773692, 2.52313452, 1.14093853, 0.41124877]
+ )
+
+ def tearDown(self):
+ pass
+
+ def testGauss(self):
+ """Compare sum_gauss with scipy.signals.gaussian"""
+ y = functions.sum_gauss(self.x,
+ self.g_params["height"],
+ self.g_params["center"],
+ self.g_params["fwhm1"])
+
+ for i in range(11):
+ self.assertAlmostEqual(y[i], self.scipy_gaussian[i])
+
+ def testAGauss(self):
+ """Compare sum_agauss with scipy.signals.gaussian"""
+ y = functions.sum_agauss(self.x,
+ self.g_params["area1"],
+ self.g_params["center"],
+ self.g_params["fwhm1"])
+ for i in range(11):
+ self.assertAlmostEqual(y[i], self.scipy_gaussian[i])
+
+ def testFastAGauss(self):
+ """Compare sum_fastagauss with scipy.signals.gaussian
+ Limit precision to 3 decimal places."""
+ y = functions.sum_fastagauss(self.x,
+ self.g_params["area1"],
+ self.g_params["center"],
+ self.g_params["fwhm1"])
+ for i in range(11):
+ self.assertAlmostEqual(y[i], self.scipy_gaussian[i], 3)
+
+
+ def testSplitGauss(self):
+ """Compare sum_splitgauss with scipy.signals.gaussian"""
+ y = functions.sum_splitgauss(self.x,
+ self.g_params["height"],
+ self.g_params["center"],
+ self.g_params["fwhm1"],
+ self.g_params["fwhm2"])
+ for i in range(11):
+ self.assertAlmostEqual(y[i], self.scipy_asym_gaussian[i])
+
+ def testErf(self):
+ """Compare erf with math.erf"""
+ # scalars
+ self.assertAlmostEqual(functions.erf(0.14), math.erf(0.14), places=5)
+ self.assertAlmostEqual(functions.erf(0), math.erf(0), places=5)
+ self.assertAlmostEqual(functions.erf(-0.74), math.erf(-0.74), places=5)
+
+ # lists
+ x = [-5, -2, -1.5, -0.6, 0, 0.1, 2, 3]
+ erfx = functions.erf(x)
+ for i in range(len(x)):
+ self.assertAlmostEqual(erfx[i],
+ math.erf(x[i]),
+ places=5)
+
+ # ndarray
+ x = numpy.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
+ erfx = functions.erf(x)
+ for i in range(x.shape[0]):
+ for j in range(x.shape[1]):
+ self.assertAlmostEqual(erfx[i, j],
+ math.erf(x[i, j]),
+ places=5)
+
+ def testErfc(self):
+ """Compare erf with math.erf"""
+ # scalars
+ self.assertAlmostEqual(functions.erfc(0.14), math.erfc(0.14), places=5)
+ self.assertAlmostEqual(functions.erfc(0), math.erfc(0), places=5)
+ self.assertAlmostEqual(functions.erfc(-0.74), math.erfc(-0.74), places=5)
+
+ # lists
+ x = [-5, -2, -1.5, -0.6, 0, 0.1, 2, 3]
+ erfcx = functions.erfc(x)
+ for i in range(len(x)):
+ self.assertAlmostEqual(erfcx[i], math.erfc(x[i]), places=5)
+
+ # ndarray
+ x = numpy.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
+ erfcx = functions.erfc(x)
+ for i in range(x.shape[0]):
+ for j in range(x.shape[1]):
+ self.assertAlmostEqual(erfcx[i, j], math.erfc(x[i, j]), places=5)
+
+ def testAtanStepUp(self):
+ """Compare atan_stepup with math.atan
+
+ atan_stepup(x, a, b, c) = a * (0.5 + (arctan((x - b) / c) / pi))"""
+ x0 = numpy.arange(100) / 6.33
+ y0 = functions.atan_stepup(x0, 11.1, 22.2, 3.33)
+
+ for x, y in zip(x0, y0):
+ self.assertAlmostEqual(
+ 11.1 * (0.5 + math.atan((x - 22.2) / 3.33) / math.pi),
+ y
+ )
+
+ def testStepUp(self):
+ """sanity check for step up:
+
+ - derivative must be largest around the step center
+ - max value must be close to height parameter
+
+ """
+ x0 = numpy.arange(1000)
+ center = 444
+ height = 1234
+ fwhm = 210
+ y0 = functions.sum_stepup(x0, height, center, fwhm)
+
+ self.assertLess(max(y0), height)
+ self.assertAlmostEqual(max(y0), height, places=1)
+ self.assertAlmostEqual(min(y0), 0, places=1)
+
+ deriv0 = _numerical_derivative(functions.sum_stepup, x0, [height, center, fwhm])
+
+ # Test center position within +- 1 sample of max derivative
+ index_max_deriv = numpy.argmax(deriv0)
+ self.assertLess(abs(index_max_deriv - center),
+ 1)
+
+ def testStepDown(self):
+ """sanity check for step down:
+
+ - absolute value of derivative must be largest around the step center
+ - max value must be close to height parameter
+
+ """
+ x0 = numpy.arange(1000)
+ center = 444
+ height = 1234
+ fwhm = 210
+ y0 = functions.sum_stepdown(x0, height, center, fwhm)
+
+ self.assertLess(max(y0), height)
+ self.assertAlmostEqual(max(y0), height, places=1)
+ self.assertAlmostEqual(min(y0), 0, places=1)
+
+ deriv0 = _numerical_derivative(functions.sum_stepdown, x0, [height, center, fwhm])
+
+ # Test center position within +- 1 sample of max derivative
+ index_min_deriv = numpy.argmax(-deriv0)
+ self.assertLess(abs(index_min_deriv - center),
+ 1)
+
+ def testSlit(self):
+ """sanity check for slit:
+
+ - absolute value of derivative must be largest around the step center
+ - max value must be close to height parameter
+
+ """
+ x0 = numpy.arange(1000)
+ center = 444
+ height = 1234
+ fwhm = 210
+ beamfwhm = 30
+ y0 = functions.sum_slit(x0, height, center, fwhm, beamfwhm)
+
+ self.assertAlmostEqual(max(y0), height, places=1)
+ self.assertAlmostEqual(min(y0), 0, places=1)
+
+ deriv0 = _numerical_derivative(functions.sum_slit, x0, [height, center, fwhm, beamfwhm])
+
+ # Test step up center position (center - fwhm/2) within +- 1 sample of max derivative
+ index_max_deriv = numpy.argmax(deriv0)
+ self.assertLess(abs(index_max_deriv - (center - fwhm/2)),
+ 1)
+ # Test step down center position (center + fwhm/2) within +- 1 sample of min derivative
+ index_min_deriv = numpy.argmin(deriv0)
+ self.assertLess(abs(index_min_deriv - (center + fwhm/2)),
+ 1)
+
+
+def _numerical_derivative(f, x, params=[], delta_factor=0.0001):
+ """Compute the numerical derivative of ``f`` for all values of ``x``.
+
+ :param f: function
+ :param x: Array of evenly spaced abscissa values
+ :param params: list of additional parameters
+ :return: Array of derivative values
+ """
+ deltax = (x[1] - x[0]) * delta_factor
+ y_plus = f(x + deltax, *params)
+ y_minus = f(x - deltax, *params)
+
+ return (y_plus - y_minus) / (2 * deltax)
+
+test_cases = (Test_functions,)
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")
diff --git a/silx/math/fit/test/test_peaks.py b/silx/math/fit/test/test_peaks.py
new file mode 100644
index 0000000..17eb75d
--- /dev/null
+++ b/silx/math/fit/test/test_peaks.py
@@ -0,0 +1,146 @@
+# coding: utf-8
+# /*##########################################################################
+# Copyright (C) 2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+"""
+Tests for peaks module
+"""
+
+import unittest
+import numpy
+import math
+
+from silx.math.fit import functions
+from silx.math.fit import peaks
+
+class Test_peak_search(unittest.TestCase):
+ """
+ Unit tests of peak_search on various types of multi-peak functions.
+ """
+ def setUp(self):
+ self.x = numpy.arange(5000)
+ # (height1, center1, fwhm1, ...)
+ self.h_c_fwhm = (50, 500, 100,
+ 50, 600, 80,
+ 20, 2000, 100,
+ 50, 2250, 110,
+ 40, 3000, 99,
+ 23, 4980, 80)
+ # (height1, center1, fwhm1, eta1 ...)
+ self.h_c_fwhm_eta = (50, 500, 100, 0.4,
+ 50, 600, 80, 0.5,
+ 20, 2000, 100, 0.6,
+ 50, 2250, 110, 0.7,
+ 40, 3000, 99, 0.8,
+ 23, 4980, 80, 0.3,)
+ # (height1, center1, fwhm11, fwhm21, ...)
+ self.h_c_fwhm_fwhm = (50, 500, 100, 85,
+ 50, 600, 80, 110,
+ 20, 2000, 100, 100,
+ 50, 2250, 110, 99,
+ 40, 3000, 99, 110,
+ 23, 4980, 80, 80,)
+ # (height1, center1, fwhm11, fwhm21, eta1 ...)
+ self.h_c_fwhm_fwhm_eta = (50, 500, 100, 85, 0.4,
+ 50, 600, 80, 110, 0.5,
+ 20, 2000, 100, 100, 0.6,
+ 50, 2250, 110, 99, 0.7,
+ 40, 3000, 99, 110, 0.8,
+ 23, 4980, 80, 80, 0.3,)
+ # (area1, center1, fwhm1, ...)
+ self.a_c_fwhm = (2550, 500, 100,
+ 2000, 600, 80,
+ 500, 2000, 100,
+ 4000, 2250, 110,
+ 2300, 3000, 99,
+ 3333, 4980, 80)
+ # (area1, center1, fwhm1, eta1 ...)
+ self.a_c_fwhm_eta = (500, 500, 100, 0.4,
+ 500, 600, 80, 0.5,
+ 200, 2000, 100, 0.6,
+ 500, 2250, 110, 0.7,
+ 400, 3000, 99, 0.8,
+ 230, 4980, 80, 0.3,)
+ # (area, position, fwhm, st_area_r, st_slope_r, lt_area_r, lt_slope_r, step_height_r)
+ self.hypermet_params = (1000, 500, 200, 0.2, 100, 0.3, 100, 0.05,
+ 1000, 1000, 200, 0.2, 100, 0.3, 100, 0.05,
+ 1000, 2000, 200, 0.2, 100, 0.3, 100, 0.05,
+ 1000, 2350, 200, 0.2, 100, 0.3, 100, 0.05,
+ 1000, 3000, 200, 0.2, 100, 0.3, 100, 0.05,
+ 1000, 4900, 200, 0.2, 100, 0.3, 100, 0.05,)
+
+
+ def tearDown(self):
+ pass
+
+ def get_peaks(self, function, params):
+ """
+
+ :param function: Multi-peak function
+ :param params: Parameter for this function
+ :return: list of (peak, relevance) tuples
+ """
+ y = function(self.x, *params)
+ return peaks.peak_search(y=y, fwhm=100, relevance_info=True)
+
+ def testPeakSearch_various_functions(self):
+ """Run peak search on a variety of synthetic functions, and
+ check that result falls within +-25 samples of the actual peak
+ (reasonable delta considering a fwhm of ~100 samples) and effects
+ of overlapping peaks)."""
+ f_p = ((functions.sum_gauss, self.h_c_fwhm ),
+ (functions.sum_lorentz, self.h_c_fwhm),
+ (functions.sum_pvoigt, self.h_c_fwhm_eta),
+ (functions.sum_splitgauss, self.h_c_fwhm_fwhm),
+ (functions.sum_splitlorentz, self.h_c_fwhm_fwhm),
+ (functions.sum_splitpvoigt, self.h_c_fwhm_fwhm_eta),
+ (functions.sum_agauss, self.a_c_fwhm),
+ (functions.sum_fastagauss, self.a_c_fwhm),
+ (functions.sum_alorentz, self.a_c_fwhm),
+ (functions.sum_apvoigt, self.a_c_fwhm_eta),
+ (functions.sum_ahypermet, self.hypermet_params),
+ (functions.sum_fastahypermet, self.hypermet_params),)
+
+ for function, params in f_p:
+ peaks = self.get_peaks(function, params)
+
+ self.assertEqual(len(peaks), 6,
+ "Wrong number of peaks detected")
+
+ for i in range(6):
+ theoretical_peak_index = params[i*(len(params)//6) + 1]
+ found_peak_index = peaks[i][0]
+ self.assertLess(abs(found_peak_index - theoretical_peak_index), 25)
+
+
+test_cases = (Test_peak_search,)
+
+def suite():
+ loader = unittest.defaultTestLoader
+ test_suite = unittest.TestSuite()
+ for test_class in test_cases:
+ tests = loader.loadTestsFromTestCase(test_class)
+ test_suite.addTests(tests)
+ return test_suite
+
+if __name__ == '__main__':
+ unittest.main(defaultTest="suite")