/usr/lib/python2.7/dist-packages/PyMca/PyMcaPlugins/NormalizationPlugins.py is in pymca 4.7.4+dfsg-1build1.
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) 2004-2012 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 Data Analysis"
try:
from PyMca import Plugin1DBase
except ImportError:
from . import Plugin1DBase
import numpy
try:
import PyMca.PyMca_Icons as PyMca_Icons
except ImportError:
#This happens in frozen versions
import PyMca_Icons
try:
from PyMca import SpecfitFuns
HAS_SPECFIT = True
except ImportError:
#This happens in frozen versions
try:
import SpecfitFuns
HAS_SPECFIT = True
except:
HAS_SPECFIT = False
class NormalizationPlugins(Plugin1DBase.Plugin1DBase):
def __init__(self, plotWindow, **kw):
Plugin1DBase.Plugin1DBase.__init__(self, plotWindow, **kw)
self.methodDict = {'y/max(y)':[self.toMaximum,
"Normalize to maximum",
None],
'(y-min(y))/(max(y)-min(y))':[self.offsetAndMaximum,
"Subtract offset and normalize to new maximum",
None],
'(y-min(y))/trapz(max(y)-min(y),x)':[self.offsetAndArea,
"Subtract offset and normalize to integrated are",
None],
'(y-min(y))/sum(max(y)-min(y))':[self.offsetAndCounts,
"Subtract offset and normalize to counts",
None]}
if HAS_SPECFIT:
self.methodDict['y/yactive'] = [self.divideByActiveCurve,
"Divide all curves by active curve",
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 toMaximum(self):
curves = self.getAllCurves()
nCurves = len(curves)
if not nCurves:
return
xmin, xmax = self.getGraphXLimits()
i = 0
for curve in curves:
x, y, legend, info = curve[0:4]
i1 = numpy.nonzero((x >= xmin) & (x <= xmax))[0]
yMax = numpy.take(y, i1).max()
try:
y = y/yMax
except:
continue
if i == 0:
replace = True
replot = True
i = 1
else:
replot = False
replace = False
self.addCurve(x, y,
legend=legend,
info=info,
replot=replot,
replace=replace)
self.addCurve(x, y,
legend=legend,
info=info,
replot=True,
replace=False)
def offsetAndMaximum(self):
curves = self.getAllCurves()
nCurves = len(curves)
if not nCurves:
return
xmin, xmax = self.getGraphXLimits()
i = 0
for curve in curves:
x, y, legend, info = curve[0:4]
i1 = numpy.nonzero((x >= xmin) & (x <= xmax))[0]
x = numpy.take(x, i1)
y = numpy.take(y, i1)
try:
y = y - y.min()
y = y/y.max()
except:
continue
if i == 0:
replace = True
replot = True
i = 1
else:
replot = False
replace = False
self.addCurve(x, y,
legend=legend,
info=info,
replot=replot,
replace=replace)
self.addCurve(x, y,
legend=legend,
info=info,
replot=True,
replace=False)
def offsetAndCounts(self):
curves = self.getAllCurves()
nCurves = len(curves)
if not nCurves:
return
xmin, xmax = self.getGraphXLimits()
i = 0
for curve in curves:
x, y, legend, info = curve[0:4]
i1 = numpy.nonzero((x >= xmin) & (x <= xmax))[0]
x = numpy.take(x, i1)
y = numpy.take(y, i1)
try:
y = y - y.min()
y = y/y.sum()
except:
continue
if i == 0:
replace = True
replot = True
i = 1
else:
replot = False
replace = False
self.addCurve(x, y,
legend=legend,
info=info,
replot=replot,
replace=replace)
self.addCurve(x, y,
legend=legend,
info=info,
replot=True,
replace=False)
def offsetAndArea(self):
curves = self.getAllCurves()
nCurves = len(curves)
if not nCurves:
return
xmin, xmax = self.getGraphXLimits()
i = 0
for curve in curves:
x, y, legend, info = curve[0:4]
i1 = numpy.nonzero((x >= xmin) & (x <= xmax))[0]
x = numpy.take(x, i1)
y = numpy.take(y, i1)
try:
y = y - y.min()
y = y/numpy.trapz(y, x)
except:
continue
if i == 0:
replace = True
replot = True
i = 1
else:
replot = False
replace = False
self.addCurve(x, y,
legend=legend,
info=info,
replot=replot,
replace=replace)
self.addCurve(x, y,
legend=legend,
info=info,
replot=True,
replace=False)
def divideByActiveCurve(self):
#all curves
curves = self.getAllCurves()
nCurves = len(curves)
if nCurves < 2:
raise ValueError("At least two curves 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
xmin, xmax = self.getGraphXLimits()
y = y.astype(numpy.float)
#get the nonzero values
idx = numpy.nonzero(abs(y) != 0.0)[0]
if not len(idx):
raise ValueError("All divisor values are zero!")
x0 = numpy.take(x, idx)
y0 = numpy.take(y, idx)
#sort the values
idx = numpy.argsort(x0, kind='mergesort')
x0 = numpy.take(x0, idx)
y0 = numpy.take(y0, idx)
i = 0
for curve in curves:
x, y, legend, info = curve[0:4]
if legend == legend0:
continue
#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())
y = yw / yi
if i == 0:
replace = True
replot = True
i = 1
else:
replot = False
replace = False
self.addCurve(x, y,
legend=legend,
info=info,
replot=replot,
replace=replace)
lastCurve = [x, y, legend]
self.addCurve(lastCurve[0],
lastCurve[1],
legend=lastCurve[2],
info=info,
replot=True,
replace=False)
MENU_TEXT = "Normalization"
def getPlugin1DInstance(plotWindow, **kw):
ob = NormalizationPlugins(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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