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+# 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__ = ["D. Naudet"]
+__license__ = "MIT"
+__date__ = "01/02/2016"
+
+"""
+Tests of the histogramnd function, error cases.
+"""
+import sys
+import platform
+import unittest
+
+import numpy as np
+
+from silx.math.chistogramnd import chistogramnd as histogramnd
+from silx.math import Histogramnd
+
+
+# ==============================================================
+# ==============================================================
+# ==============================================================
+
+
+class _Test_chistogramnd_errors(unittest.TestCase):
+ """
+ Unit tests of the chistogramnd error cases.
+ """
+ __test__ = False # ignore abstract class
+
+ def setUp(self):
+ self.skipTest("Abstract class")
+
+ def test_weights_shape(self):
+ """
+ """
+
+ for err_w_shape in self.err_weights_shapes:
+ test_msg = ('Testing invalid weights shape : {0}'
+ ''.format(err_w_shape))
+
+ err_weights = np.random.randint(0,
+ high=10,
+ size=err_w_shape)
+ err_weights = err_weights.astype(np.double)
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=err_weights)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str,
+ '<weights> must be an array whose length '
+ 'is equal to the number of samples.')
+
+ def test_histo_range_shape(self):
+ """
+ """
+ n_dims = 1 if len(self.s_shape) == 1 else self.s_shape[1]
+ expected_txt_tpl = ('<histo_range> error : expected {n_dims} sets '
+ 'of lower and upper bin edges, '
+ 'got the following instead : {histo_range}. '
+ '(provided <sample> contains '
+ '{n_dims}D values)')
+
+ for err_histo_range in self.err_histo_range_shapes:
+ test_msg = ('Testing invalid histo_range shape : {0}'
+ ''.format(err_histo_range))
+
+ expected_txt = expected_txt_tpl.format(histo_range=err_histo_range,
+ n_dims=n_dims)
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ err_histo_range,
+ self.n_bins,
+ weights=self.weights)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_nbins_shape(self):
+ """
+ """
+
+ expected_txt = ('n_bins must be either a scalar (same number '
+ 'of bins for all dimensions) or '
+ 'an array (number of bins for each '
+ 'dimension).')
+
+ for err_n_bins in self.err_n_bins_shapes:
+ test_msg = ('Testing invalid n_bins shape : {0}'
+ ''.format(err_n_bins))
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ err_n_bins,
+ weights=self.weights)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_nbins_values(self):
+ """
+ """
+ expected_txt = ('<n_bins> : only positive values allowed.')
+
+ for err_n_bins in self.err_n_bins_values:
+ test_msg = ('Testing invalid n_bins value : {0}'
+ ''.format(err_n_bins))
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ err_n_bins,
+ weights=self.weights)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_histo_shape(self):
+ """
+ """
+ for err_h_shape in self.err_histo_shapes:
+
+ # windows & python 2.7 : numpy shapes are long values
+ if platform.system() == 'Windows':
+ version = (sys.version_info.major, sys.version_info.minor)
+ if version <= (2, 7):
+ err_h_shape = tuple([long(val) for val in err_h_shape])
+
+ test_msg = ('Testing invalid histo shape : {0}'
+ ''.format(err_h_shape))
+
+ expected_txt = ('Provided <histo> array doesn\'t have '
+ 'a shape compatible with <n_bins> '
+ ': should be {0} instead of {1}.'
+ ''.format(self.h_shape, err_h_shape))
+
+ histo = np.zeros(shape=err_h_shape, dtype=np.uint32)
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ histo=histo)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_histo_dtype(self):
+ """
+ """
+ for err_h_dtype in self.err_histo_dtypes:
+ test_msg = ('Testing invalid histo dtype : {0}'
+ ''.format(err_h_dtype))
+
+ histo = np.zeros(shape=self.h_shape, dtype=err_h_dtype)
+
+ expected_txt = ('Provided <histo> array doesn\'t have '
+ 'the expected type '
+ ': should be {0} instead of {1}.'
+ ''.format(np.uint32, histo.dtype))
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ histo=histo)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_weighted_histo_shape(self):
+ """
+ """
+ # using the same values as histo
+ for err_h_shape in self.err_histo_shapes:
+
+ # windows & python 2.7 : numpy shapes are long values
+ if platform.system() == 'Windows':
+ version = (sys.version_info.major, sys.version_info.minor)
+ if version <= (2, 7):
+ err_h_shape = tuple([long(val) for val in err_h_shape])
+
+ test_msg = ('Testing invalid weighted_histo shape : {0}'
+ ''.format(err_h_shape))
+
+ expected_txt = ('Provided <weighted_histo> array doesn\'t have '
+ 'a shape compatible with <n_bins> '
+ ': should be {0} instead of {1}.'
+ ''.format(self.h_shape, err_h_shape))
+
+ cumul = np.zeros(shape=err_h_shape, dtype=np.double)
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ weighted_histo=cumul)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_cumul_dtype(self):
+ """
+ """
+ # using the same values as histo
+ for err_h_dtype in self.err_histo_dtypes:
+ test_msg = ('Testing invalid weighted_histo dtype : {0}'
+ ''.format(err_h_dtype))
+
+ cumul = np.zeros(shape=self.h_shape, dtype=err_h_dtype)
+
+ expected_txt = ('Provided <weighted_histo> array doesn\'t have '
+ 'the expected type '
+ ': should be {0} or {1} instead of {2}.'
+ ''.format(np.float64, np.float32, cumul.dtype))
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ weighted_histo=cumul)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_wh_histo_dtype(self):
+ """
+ """
+ # using the same values as histo
+ for err_h_dtype in self.err_histo_dtypes:
+ test_msg = ('Testing invalid wh_dtype dtype : {0}'
+ ''.format(err_h_dtype))
+
+ expected_txt = ('<wh_dtype> type not supported : {0}.'
+ ''.format(err_h_dtype))
+
+ ex_str = None
+ try:
+ histo, cumul = histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ wh_dtype=err_h_dtype)[0:2]
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_unmanaged_dtypes(self):
+ """
+ """
+ for err_unmanaged_dtype in self.err_unmanaged_dtypes:
+ test_msg = ('Testing unmanaged dtypes : {0}'
+ ''.format(err_unmanaged_dtype))
+
+ sample = self.sample.astype(err_unmanaged_dtype[0])
+ weights = self.weights.astype(err_unmanaged_dtype[1])
+
+ expected_txt = ('Case not supported - sample:{0} '
+ 'and weights:{1}.'
+ ''.format(sample.dtype,
+ weights.dtype))
+
+ ex_str = None
+ try:
+ histogramnd(sample,
+ self.histo_range,
+ self.n_bins,
+ weights=weights)
+ except TypeError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str, msg=test_msg)
+ self.assertEqual(ex_str, expected_txt, msg=test_msg)
+
+ def test_uncontiguous_histo(self):
+ """
+ """
+ # non contiguous array
+ shape = np.array(self.n_bins, ndmin=1)
+ shape[0] *= 2
+ histo_tmp = np.zeros(shape)
+ histo = histo_tmp[::2, ...]
+
+ expected_txt = ('<histo> must be a C_CONTIGUOUS numpy array.')
+
+ ex_str = None
+ try:
+ histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ histo=histo)
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str)
+ self.assertEqual(ex_str, expected_txt)
+
+ def test_uncontiguous_weighted_histo(self):
+ """
+ """
+ # non contiguous array
+ shape = np.array(self.n_bins, ndmin=1)
+ shape[0] *= 2
+ cumul_tmp = np.zeros(shape)
+ cumul = cumul_tmp[::2, ...]
+
+ expected_txt = ('<weighted_histo> must be a C_CONTIGUOUS numpy array.')
+
+ ex_str = None
+ try:
+ histogramnd(self.sample,
+ self.histo_range,
+ self.n_bins,
+ weights=self.weights,
+ weighted_histo=cumul)
+ except ValueError as ex:
+ ex_str = str(ex)
+
+ self.assertIsNotNone(ex_str)
+ self.assertEqual(ex_str, expected_txt)
+
+
+class Test_chistogramnd_1D_errors(_Test_chistogramnd_errors):
+ """
+ Unit tests of the 1D histogramnd error cases.
+ """
+ __test__ = True # because _Test_chistogramnd_errors is ignored
+
+ def setUp(self):
+ # nominal values
+ self.n_elements = 1000
+ self.s_shape = (self.n_elements,)
+ self.w_shape = (self.n_elements,)
+
+ self.histo_range = [0., 100.]
+ self.n_bins = 10
+
+ self.h_shape = (self.n_bins,)
+
+ self.sample = np.random.randint(0,
+ high=10,
+ size=self.s_shape)
+ self.sample = self.sample.astype(np.double)
+
+ self.weights = np.random.randint(0,
+ high=10,
+ size=self.w_shape)
+ self.weights = self.weights.astype(np.double)
+
+ self.err_weights_shapes = ((self.n_elements+1,),
+ (self.n_elements-1,),
+ (self.n_elements-1, 3))
+ self.err_histo_range_shapes = ([0.],
+ [0., 1., 2.],
+ [[0.], [1.]])
+ self.err_n_bins_shapes = ([10, 2],
+ [[10], [2]])
+ self.err_n_bins_values = (0,
+ [-10],
+ None)
+ self.err_histo_shapes = ((self.n_bins+1,),
+ (self.n_bins-1,),
+ (self.n_bins, self.n_bins))
+ # these are used for testing the histo parameter as well
+ # as the weighted_histo parameter.
+ self.err_histo_dtypes = (np.uint16,
+ np.float16)
+
+ self.err_unmanaged_dtypes = ((np.double, np.uint16),
+ (np.uint16, np.double),
+ (np.uint16, np.uint16))
+
+class Test_chistogramnd_ND_range(unittest.TestCase):
+ """
+
+ """
+
+ def test_invalid_histo_range(self):
+ data = np.random.random((60, 60))
+ nbins = 10
+
+ with self.assertRaises(ValueError):
+ histo_range = data.min(), np.inf
+
+ Histogramnd(sample=data.ravel(),
+ histo_range=histo_range,
+ n_bins=nbins)
+
+ histo_range = data.min(), np.nan
+
+ Histogramnd(sample=data.ravel(),
+ histo_range=histo_range,
+ n_bins=nbins)
+
+
+class Test_chistogramnd_ND_errors(_Test_chistogramnd_errors):
+ """
+ Unit tests of the 3D histogramnd error cases.
+ """
+ __test__ = True # because _Test_chistogramnd_errors is ignored
+
+ def setUp(self):
+ # nominal values
+ self.n_elements = 1000
+ self.s_shape = (self.n_elements, 3)
+ self.w_shape = (self.n_elements,)
+
+ self.histo_range = [[0., 100.], [0., 100.], [0., 100.]]
+ self.n_bins = (10, 20, 30)
+
+ self.h_shape = self.n_bins
+
+ self.sample = np.random.randint(0,
+ high=10,
+ size=self.s_shape)
+ self.sample = self.sample.astype(np.double)
+
+ self.weights = np.random.randint(0,
+ high=10,
+ size=self.w_shape)
+ self.weights = self.weights.astype(np.double)
+
+ self.err_weights_shapes = ((self.n_elements+1,),
+ (self.n_elements-1,),
+ (self.n_elements-1, 3))
+ self.err_histo_range_shapes = ([0.],
+ [0., 1.],
+ [[0., 10.], [0., 10.]],
+ [0., 10., 0, 10., 0, 10.])
+ self.err_n_bins_shapes = ([10, 2],
+ [[10], [20], [30]])
+ self.err_n_bins_values = (0,
+ [-10],
+ [10, 20, -4],
+ None,
+ [10, None, 30])
+ self.err_histo_shapes = ((self.n_bins[0]+1,
+ self.n_bins[1],
+ self.n_bins[2]),
+ (self.n_bins[0],
+ self.n_bins[1],
+ self.n_bins[2]-1),
+ (self.n_bins[0],
+ self.n_bins[1]),
+ (self.n_bins[1],
+ self.n_bins[0],
+ self.n_bins[2]),
+ (self.n_bins[0],
+ self.n_bins[1],
+ self.n_bins[2],
+ 10)
+ )
+ # these are used for testing the histo parameter as well
+ # as the weighted_histo parameter.
+ self.err_histo_dtypes = (np.uint16,
+ np.float16)
+
+ self.err_unmanaged_dtypes = ((np.double, np.uint16),
+ (np.uint16, np.double),
+ (np.uint16, np.uint16))
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