Source code for PyMca5.PyMcaPlugins.XASScanNormalizationPlugin

#/*##########################################################################
# 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.
#
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# furnished to do so, subject to the following conditions:
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# all copies or substantial portions of the Software.
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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__author__ = "V.A. Sole - ESRF Data Analysis"
__contact__ = "sole@esrf.fr"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
import numpy
try:
    from PyMca5 import Plugin1DBase
except ImportError:
    from . import Plugin1DBase

try:
    from PyMca5.PyMcaPhysics.xas import XASNormalization
    from PyMca5.PyMcaGui.physics.xas import XASNormalizationWindow
    from PyMca5.PyMcaMath.fitting import SpecfitFuns
except ImportError:
    print("XASScanNormalizationPlugin problem")

[docs]class XASScanNormalizationPlugin(Plugin1DBase.Plugin1DBase): def __init__(self, plotWindow, **kw): Plugin1DBase.Plugin1DBase.__init__(self, plotWindow, **kw) self.methodDict = {} text = "Configure normalization parameters." function = self.configure info = text icon = None self.methodDict["Configure"] =[function, info, icon] function = self.XASNormalize text = "Replace all curves by normalized ones." info = text icon = None self.methodDict["Normalize"] =[function, info, icon] self.widget = None self.parameters = None #Methods to be implemented by the plugin
[docs] 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, ... """ names = list(self.methodDict.keys()) names.sort() return names
[docs] def getMethodToolTip(self, name): """ Returns the help associated to the particular method name or None. """ return self.methodDict[name][1]
[docs] def getMethodPixmap(self, name): """ Returns the pixmap associated to the particular method name or None. """ return self.methodDict[name][2]
[docs] def applyMethod(self, name): """ The plugin is asked to apply the method associated to name. """ self.methodDict[name][0]() return
[docs] def configure(self): #get active curve activeCurve = self.getActiveCurve() if activeCurve is None: raise ValueError("Please select an active curve") return x, y, legend0, info = activeCurve if self.widget is None: self._createWidget(y, energy=x) else: oldParameters = self.widget.getParameters() oldEnergy = self.widget.parametersWidget.energy oldEMin = oldEnergy.min() oldEMax = oldEnergy.max() self.widget.setData(y, energy=x) if abs(oldEMin - x.min()) < 1: if abs(oldEMax - x.max()) < 1: self.widget.setParameters(oldParameters) ret = self.widget.exec_() if ret: self.parameters = self.widget.getParameters()
def _createWidget(self, spectrum, energy=None): parent = None self.widget = XASNormalizationWindow.XASNormalizationDialog(parent, spectrum, energy=energy) self.parameters = self.widget.getParameters()
[docs] def XASNormalize(self): #all curves curves = self.getAllCurves() nCurves = len(curves) if nCurves < 1: raise ValueError("At least one curve needed") return #get active curve activeCurve = self.getActiveCurve() if activeCurve is None: raise ValueError("Please select an active curve") return x, y, legend0, info = activeCurve #sort the values idx = numpy.argsort(x, kind='mergesort') x0 = numpy.take(x, idx) y0 = numpy.take(y, idx) xmin, xmax = self.getGraphXLimits() # get calculation parameters if self.widget is None: self._createWidget(y0, x0) parameters = self.parameters if parameters['auto_edge']: edge = None else: edge = parameters['edge_energy'] energy = x pre_edge_regions = parameters['pre_edge']['regions'] post_edge_regions = parameters['post_edge']['regions'] algorithm ='polynomial' algorithm_parameters = {} algorithm_parameters['pre_edge_order'] = parameters['pre_edge']\ ['polynomial'] algorithm_parameters['post_edge_order'] = parameters['post_edge']\ ['polynomial'] i = 0 lastCurve = None for curve in curves: x, y, legend, info = curve[0:4] #take the portion ox 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) idx = numpy.nonzero((x0>=x.min()) & (x0<=x.max()))[0] if not len(idx): #no overlap continue xi = numpy.take(x0, idx) yi = numpy.take(y0, idx) #perform interpolation xi.shape = -1, 1 yw = SpecfitFuns.interpol([x], y, xi, yi.min()) # try: ... except: here? yw.shape = -1 xi.shape = -1 x, y = XASNormalization.XASNormalization(yw, energy=xi, edge=edge, pre_edge_regions=pre_edge_regions, post_edge_regions=post_edge_regions, algorithm=algorithm, algorithm_parameters=algorithm_parameters)[0:2] # if i == 0: replace = True replot = True i = 1 else: replot = False replace = False newLegend = " ".join(legend.split(" ")[:-1]) if not newLegend.startswith('Norm.'): newLegend = "Norm. " + newLegend self.addCurve(x, y, legend=newLegend, info=info, replot=replot, replace=replace) lastCurve = [x, y, newLegend] self.addCurve(lastCurve[0], lastCurve[1], legend=lastCurve[2], info=info, replot=True, replace=False)
MENU_TEXT = "XAS Normalization"
[docs]def getPlugin1DInstance(plotWindow, **kw): ob = XASScanNormalizationPlugin(plotWindow) return ob
if __name__ == "__main__": 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())