#/*########################################################################## # Copyright (C) 2004-2014 V.A. Sole, 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. # #############################################################################*/ __author__ = "V.A. Sole - ESRF Data Analysis" __contact__ = "sole@esrf.fr" __license__ = "MIT" __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France" import numpy from PyMca5 import Plugin1DBase from PyMca5.PyMcaMath.fitting import SpecfitFuns from PyMca5.PyMcaMath.PyMcaSciPy.signal.median import medfilt1d class MedianFilterScanPlugin(Plugin1DBase.Plugin1DBase): def __init__(self, plotWindow, **kw): Plugin1DBase.Plugin1DBase.__init__(self, plotWindow, **kw) self.__randomization = True self.__methodKeys = [] self.methodDict = {} text = "Use a random order instead\n" text += "of the plotting order." info = text icon = None function = self.toggleRandomization method = "Toggle Randomization OFF" self.methodDict[method] = [function, info, icon] self.__methodKeys.append(method) method = "Toggle Randomization ON" text = "Use plotting order instead\n" text += "of a random order." self.methodDict[method] = [function, info, icon] self.__methodKeys.append(method) function = self.applyMedianFilter for i in [3, 5, 7, 9]: info = "Replace curves by their %d-point median filter average" % i method = "Replace by %d-point median filter" % i self.methodDict[method] = [function, info, icon] self.__methodKeys.append(method) #Methods to be implemented by the plugin def getMethods(self, plottype=None): """ A list with the NAMES associated to the callable methods that are applicable to the specified plot. Plot type can be "SCAN", "MCA", None, ... """ if self.__randomization: return self.__methodKeys[0:1] + self.__methodKeys[2:] else: return self.__methodKeys[1:] def getMethodToolTip(self, name): """ Returns the help associated to the particular method name or None. """ return self.methodDict[name][1] def getMethodPixmap(self, name): """ Returns the pixmap associated to the particular method name or None. """ return None def applyMethod(self, name): """ The plugin is asked to apply the method associated to name. """ if name.startswith('Toggle'): return self.methodDict[name][0]() n = int(name.split('-')[0].split()[-1]) return self.applyMedianFilter(width=n) def toggleRandomization(self): if self.__randomization: self.__randomization = False else: self.__randomization = True def applyMedianFilter(self, width=3): curves = self.getAllCurves() nCurves = len(curves) if nCurves < width: raise ValueError("At least %d curves needed" % width) return if self.__randomization: indices = numpy.random.permutation(nCurves) else: indices = range(nCurves) # get active curve activeCurve = self.getActiveCurve() if activeCurve is None: activeCurve = curves[0] # apply between graph limits x0 = activeCurve[0][:] y0 = activeCurve[1][:] xmin, xmax =self.getGraphXLimits() idx = numpy.nonzero((x0 >= xmin) & (x0 <= xmax))[0] x0 = numpy.take(x0, idx) y0 = numpy.take(y0, idx) #sort the values idx = numpy.argsort(x0, kind='mergesort') x0 = numpy.take(x0, idx) y0 = numpy.take(y0, idx) #remove duplicates x0 = x0.ravel() idx = numpy.nonzero((x0[1:] > x0[:-1]))[0] x0 = numpy.take(x0, idx) y0 = numpy.take(y0, idx) x0.shape = -1, 1 nChannels = x0.shape[0] # built a couple of temporary array of spectra for handy access tmpArray = numpy.zeros((nChannels, nCurves), numpy.float) medianSpectra = numpy.zeros((nChannels, nCurves), numpy.float) i = 0 for idx in indices: x, y, legend, info = curves[idx][0:4] #sort the values x = x[:] idx = numpy.argsort(x, kind='mergesort') x = numpy.take(x, idx) y = numpy.take(y, idx) #take the portion of x between limits idx = numpy.nonzero((x>=xmin) & (x<=xmax))[0] if not len(idx): # no overlap continue x = numpy.take(x, idx) y = numpy.take(y, idx) #remove duplicates x = x.ravel() idx = numpy.nonzero((x[1:] > x[:-1]))[0] x = numpy.take(x, idx) y = numpy.take(y, idx) x.shape = -1, 1 if numpy.allclose(x, x0): # no need for interpolation pass else: # we have to interpolate x.shape = -1 y.shape = -1 xi = x0[:] y = SpecfitFuns.interpol([x], y, xi, y0.min()) y.shape = -1 tmpArray[:, i] = y i += 1 # now perform the median filter for i in range(nChannels): medianSpectra[i, :] = medfilt1d(tmpArray[i,:], kernel_size=width) tmpArray = None # now get the final spectrum y = medianSpectra.sum(axis=1) / nCurves x0.shape = -1 y.shape = x0.shape legend = "%d Median from %s to %s" % (width, curves[0][2], curves[-1][2]) self.addCurve(x0, y, legend=legend, info=None, replot=True, replace=True) MENU_TEXT = "Median Filter Average" def getPlugin1DInstance(plotWindow, **kw): ob = MedianFilterScanPlugin(plotWindow) return ob if __name__ == "__main__": from PyMca5.PyMcaGui import PyMcaQt as qt app = qt.QApplication([]) from PyMca5.PyMcaGraph import Plot x = numpy.arange(100.) y = x * x plot = Plot.Plot() plot.addCurve(x, y, "dummy") plot.addCurve(x+100, -x*x) plugin = getPlugin1DInstance(plot) for method in plugin.getMethods(): print(method, ":", plugin.getMethodToolTip(method)) plugin.applyMethod(plugin.getMethods()[0]) curves = plugin.getAllCurves() for curve in curves: print(curve[2]) print("LIMITS = ", plugin.getGraphYLimits()) #app = qt.QApplication()