/usr/lib/python2.7/dist-packages/PyMca/PyMcaPlugins/XASScanNormalizationPlugin.py is in pymca 4.7.1+dfsg-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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# Copyright (C) 2004-2013 European Synchrotron Radiation Facility
#
# This file is part of the PyMca X-ray Fluorescence Toolkit developed at
# the ESRF by the Software group.
#
# This toolkit is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the Free
# Software Foundation; either version 2 of the License, or (at your option)
# any later version.
#
# PyMca is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# PyMca; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#
# PyMca follows the dual licensing model of Riverbank's PyQt and cannot be
# used as a free plugin for a non-free program.
#
# Please contact the ESRF industrial unit (industry@esrf.fr) if this license
# is a problem for you.
#############################################################################*/
__author__ = "V.A. Sole - ESRF Software Group"
import numpy
try:
from PyMca import Plugin1DBase
except ImportError:
from . import Plugin1DBase
try:
from PyMca import XASNormalization
from PyMca import XASNormalizationWindow
from PyMca import SpecfitFuns
except ImportError:
print("XASScanNormalizationPlugin importing from somewhere else")
import XASNormalization
import XASNormalizationWindow
import SpecfitFuns
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
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
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 self.methodDict[name][2]
def applyMethod(self, name):
"""
The plugin is asked to apply the method associated to name.
"""
self.methodDict[name][0]()
return
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()
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"
def getPlugin1DInstance(plotWindow, **kw):
ob = XASScanNormalizationPlugin(plotWindow)
return ob
if __name__ == "__main__":
from PyMca import Plot1D
x = numpy.arange(100.)
y = x * x
plot = Plot1D.Plot1D()
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())
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