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Diffstat (limited to 'silx/gui/plot/Colormap.py')
| -rw-r--r-- | silx/gui/plot/Colormap.py | 410 |
1 files changed, 410 insertions, 0 deletions
diff --git a/silx/gui/plot/Colormap.py b/silx/gui/plot/Colormap.py new file mode 100644 index 0000000..abe8546 --- /dev/null +++ b/silx/gui/plot/Colormap.py @@ -0,0 +1,410 @@ +# coding: utf-8 +# /*########################################################################## +# +# Copyright (c) 2015-2017 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 the Colormap object +""" + +from __future__ import absolute_import + +__authors__ = ["T. Vincent", "H.Payno"] +__license__ = "MIT" +__date__ = "05/12/2016" + +from silx.gui import qt +import copy as copy_mdl +import numpy +from .matplotlib import Colormap as MPLColormap +import logging +from silx.math.combo import min_max + +_logger = logging.getLogger(__file__) + +DEFAULT_COLORMAPS = ( + 'gray', 'reversed gray', 'temperature', 'red', 'green', 'blue') +"""Tuple of supported colormap names.""" + +DEFAULT_MIN_LIN = 0 +"""Default min value if in linear normalization""" +DEFAULT_MAX_LIN = 1 +"""Default max value if in linear normalization""" +DEFAULT_MIN_LOG = 1 +"""Default min value if in log normalization""" +DEFAULT_MAX_LOG = 10 +"""Default max value if in log normalization""" + + +class Colormap(qt.QObject): + """Description of a colormap + + :param str name: Name of the colormap + :param tuple colors: optional, custom colormap. + Nx3 or Nx4 numpy array of RGB(A) colors, + either uint8 or float in [0, 1]. + If 'name' is None, then this array is used as the colormap. + :param str norm: Normalization: 'linear' (default) or 'log' + :param float vmin: + Lower bound of the colormap or None for autoscale (default) + :param float vmax: + Upper bounds of the colormap or None for autoscale (default) + """ + + LINEAR = 'linear' + """constant for linear normalization""" + + LOGARITHM = 'log' + """constant for logarithmic normalization""" + + NORMALIZATIONS = (LINEAR, LOGARITHM) + """Tuple of managed normalizations""" + + sigChanged = qt.Signal() + + def __init__(self, name='gray', colors=None, normalization=LINEAR, vmin=None, vmax=None): + qt.QObject.__init__(self) + assert normalization in Colormap.NORMALIZATIONS + assert not (name is None and colors is None) + if normalization is Colormap.LOGARITHM: + if (vmin is not None and vmin < 0) or (vmax is not None and vmax < 0): + m = "Unsuported vmin (%s) and/or vmax (%s) given for a log scale." + m += ' Autoscale will be performed.' + m = m % (vmin, vmax) + _logger.warning(m) + vmin = None + vmax = None + + self._name = str(name) if name is not None else None + self._setColors(colors) + self._normalization = str(normalization) + self._vmin = float(vmin) if vmin is not None else None + self._vmax = float(vmax) if vmax is not None else None + + def isAutoscale(self): + """Return True if both min and max are in autoscale mode""" + return self._vmin is None or self._vmax is None + + def getName(self): + """Return the name of the colormap + :rtype: str + """ + return self._name + + def _setColors(self, colors): + if colors is None: + self._colors = None + else: + self._colors = numpy.array(colors, copy=True) + + def setName(self, name): + """Set the name of the colormap and load the colors corresponding to + the name + + :param str name: the name of the colormap (should be in ['gray', + 'reversed gray', 'temperature', 'red', 'green', 'blue', 'jet', + 'viridis', 'magma', 'inferno', 'plasma'] + """ + assert name in self.getSupportedColormaps() + self._name = str(name) + self._colors = None + self.sigChanged.emit() + + def getColormapLUT(self): + """Return the list of colors for the colormap. None if not setted + + :return: the list of colors for the colormap. None if not setted + :rtype: numpy.ndarray + """ + return self._colors + + def setColormapLUT(self, colors): + """ + Set the colors of the colormap. + + :param numpy.ndarray colors: the colors of the LUT + + .. warning: this will set the value of name to an empty string + """ + self._setColors(colors) + if len(colors) is 0: + self._colors = None + + self._name = None + self.sigChanged.emit() + + def getNormalization(self): + """Return the normalization of the colormap ('log' or 'linear') + + :return: the normalization of the colormap + :rtype: str + """ + return self._normalization + + def setNormalization(self, norm): + """Set the norm ('log', 'linear') + + :param str norm: the norm to set + """ + self._normalization = str(norm) + self.sigChanged.emit() + + def getVMin(self): + """Return the lower bound of the colormap + + :return: the lower bound of the colormap + :rtype: float or None + """ + return self._vmin + + def setVMin(self, vmin): + """Set the minimal value of the colormap + + :param float vmin: Lower bound of the colormap or None for autoscale + (default) + value) + """ + if vmin is not None: + if self._vmax is not None and vmin >= self._vmax: + err = "Can't set vmin because vmin >= vmax." + err += "vmin = %s, vmax = %s" %(vmin, self._vmax) + raise ValueError(err) + + self._vmin = vmin + self.sigChanged.emit() + + def getVMax(self): + """Return the upper bounds of the colormap or None + + :return: the upper bounds of the colormap or None + :rtype: float or None + """ + return self._vmax + + def setVMax(self, vmax): + """Set the maximal value of the colormap + + :param float vmax: Upper bounds of the colormap or None for autoscale + (default) + """ + if vmax is not None: + if self._vmin is not None and vmax <= self._vmin: + err = "Can't set vmax because vmax <= vmin." + err += "vmin = %s, vmax = %s" %(self._vmin, vmax) + raise ValueError(err) + + self._vmax = vmax + self.sigChanged.emit() + + def getColormapRange(self, data=None): + """Return (vmin, vmax) + + :return: the tuple vmin, vmax fitting vmin, vmax, normalization and + data if any given + :rtype: tuple + """ + vmin = self._vmin + vmax = self._vmax + assert vmin is None or vmax is None or vmin <= vmax # TODO handle this in setters + + if self.getNormalization() == self.LOGARITHM: + # Handle negative bounds as autoscale + if vmin is not None and (vmin is not None and vmin <= 0.): + mess = 'negative vmin, moving to autoscale for lower bound' + _logger.warning(mess) + vmin = None + if vmax is not None and (vmax is not None and vmax <= 0.): + mess = 'negative vmax, moving to autoscale for upper bound' + _logger.warning(mess) + vmax = None + + if vmin is None or vmax is None: # Handle autoscale + # Get min/max from data + if data is not None: + data = numpy.array(data, copy=False) + if data.size == 0: # Fallback an array but no data + min_, max_ = self._getDefaultMin(), self._getDefaultMax() + else: + if self.getNormalization() == self.LOGARITHM: + result = min_max(data, min_positive=True, finite=True) + min_ = result.min_positive # >0 or None + max_ = result.maximum # can be <= 0 + else: + min_, max_ = min_max(data, min_positive=False, finite=True) + + # Handle fallback + if min_ is None or not numpy.isfinite(min_): + min_ = self._getDefaultMin() + if max_ is None or not numpy.isfinite(max_): + max_ = self._getDefaultMax() + else: # Fallback if no data is provided + min_, max_ = self._getDefaultMin(), self._getDefaultMax() + + if vmin is None: # Set vmin respecting provided vmax + vmin = min_ if vmax is None else min(min_, vmax) + + if vmax is None: + vmax = max(max_, vmin) # Handle max_ <= 0 for log scale + + return vmin, vmax + + def setVRange(self, vmin, vmax): + """ + Set bounds to the colormap + + :param vmin: Lower bound of the colormap or None for autoscale + (default) + :param vmax: Upper bounds of the colormap or None for autoscale + (default) + """ + if vmin is not None and vmax is not None: + if vmin >= vmax: + err = "Can't set vmin and vmax because vmin >= vmax" + err += "vmin = %s, vmax = %s" %(vmin, self._vmax) + raise ValueError(err) + + self._vmin = vmin + self._vmax = vmax + self.sigChanged.emit() + + def __getitem__(self, item): + if item == 'autoscale': + return self.isAutoscale() + elif item == 'name': + return self.getName() + elif item == 'normalization': + return self.getNormalization() + elif item == 'vmin': + return self.getVMin() + elif item == 'vmax': + return self.getVMax() + elif item == 'colors': + return self.getColormapLUT() + else: + raise KeyError(item) + + def _toDict(self): + """Return the equivalent colormap as a dictionary + (old colormap representation) + + :return: the representation of the Colormap as a dictionary + :rtype: dict + """ + return { + 'name': self._name, + 'colors': copy_mdl.copy(self._colors), + 'vmin': self._vmin, + 'vmax': self._vmax, + 'autoscale': self.isAutoscale(), + 'normalization': self._normalization + } + + def _setFromDict(self, dic): + """Set values to the colormap from a dictionary + + :param dict dic: the colormap as a dictionary + """ + name = dic['name'] if 'name' in dic else None + colors = dic['colors'] if 'colors' in dic else None + vmin = dic['vmin'] if 'vmin' in dic else None + vmax = dic['vmax'] if 'vmax' in dic else None + if 'normalization' in dic: + normalization = dic['normalization'] + else: + warn = 'Normalization not given in the dictionary, ' + warn += 'set by default to ' + Colormap.LINEAR + _logger.warning(warn) + normalization = Colormap.LINEAR + + if name is None and colors is None: + err = 'The colormap should have a name defined or a tuple of colors' + raise ValueError(err) + if normalization not in Colormap.NORMALIZATIONS: + err = 'Given normalization is not recoginized (%s)' % normalization + raise ValueError(err) + + # If autoscale, then set boundaries to None + if dic.get('autoscale', False): + vmin, vmax = None, None + + self._name = name + self._colors = colors + self._vmin = vmin + self._vmax = vmax + self._autoscale = True if (vmin is None and vmax is None) else False + self._normalization = normalization + + self.sigChanged.emit() + + @staticmethod + def _fromDict(dic): + colormap = Colormap(name="") + colormap._setFromDict(dic) + return colormap + + def copy(self): + """ + + :return: a copy of the Colormap object + """ + return Colormap(name=self._name, + colors=copy_mdl.copy(self._colors), + vmin=self._vmin, + vmax=self._vmax, + normalization=self._normalization) + + def applyToData(self, data): + """Apply the colormap to the data + + :param numpy.ndarray data: The data to convert. + """ + rgbaImage = MPLColormap.applyColormapToData(colormap=self, data=data) + return rgbaImage + + @staticmethod + def getSupportedColormaps(): + """Get the supported colormap names as a tuple of str. + + The list should at least contain and start by: + ('gray', 'reversed gray', 'temperature', 'red', 'green', 'blue') + :rtype: tuple + """ + maps = MPLColormap.getSupportedColormaps() + return DEFAULT_COLORMAPS + maps + + def __str__(self): + return str(self._toDict()) + + def _getDefaultMin(self): + return DEFAULT_MIN_LIN if self._normalization == Colormap.LINEAR else DEFAULT_MIN_LOG + + def _getDefaultMax(self): + return DEFAULT_MAX_LIN if self._normalization == Colormap.LINEAR else DEFAULT_MAX_LOG + + def __eq__(self, other): + """Compare colormap values and not pointers""" + return (self.getName() == other.getName() and + self.getNormalization() == other.getNormalization() and + self.getVMin() == other.getVMin() and + self.getVMax() == other.getVMax() and + numpy.array_equal(self.getColormapLUT(), other.getColormapLUT()) + ) + |