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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 Data Analysis"
import numpy
try:
from PyMca import Plugin1DBase
except ImportError:
print("WARNING:MedianFilterScanPlugin import from somewhere else")
from . import Plugin1DBase
from PyMca import SpecfitFuns
class AlignmentScanPlugin(Plugin1DBase.Plugin1DBase):
def __init__(self, plotWindow, **kw):
Plugin1DBase.Plugin1DBase.__init__(self, plotWindow, **kw)
self.__randomization = True
self.__methodKeys = []
self.methodDict = {}
text = "FFT based alignment\n"
info = text
icon = None
function = self.fftAlignment
method = "FFT Alignment"
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.
"""
return self.methodDict[name][0]()
def fftAlignment(self):
curves = self.getMonotonicCurves()
nCurves = len(curves)
if nCurves < 2:
raise ValueError("At least 2 curves needed")
return
# get legend of active curve
try:
activeCurveLegend = self.getActiveCurve()[2]
if activeCurveLegend is None:
activeCurveLegend = curves[0][2]
for curve in curves:
if curve[2] == activeCurveLegend:
activeCurve = curve
break
except:
activeCurve = curves[0]
# apply between graph limits
x0, y0 = activeCurve[0:2]
xmin, xmax =self.getGraphXLimits()
for curve in curves:
xmax = float(min(xmax, curve[0][-1]))
xmin = float(max(xmin, curve[0][0]))
idx = numpy.nonzero((x0 >= xmin) & (x0 <= xmax))[0]
x0 = numpy.take(x0, idx)
y0 = numpy.take(y0, idx)
#make sure values are regularly spaced
xi = numpy.linspace(x0[0], x0[-1], len(idx)).reshape(-1, 1)
yi = SpecfitFuns.interpol([x0], y0, xi, y0.min())
x0 = xi * 1
y0 = yi * 1
y0.shape = -1
fft0 = numpy.fft.fft(y0)
y0.shape = -1, 1
x0.shape = -1, 1
nChannels = x0.shape[0]
# built a couple of temporary array of spectra for handy access
shiftList = []
curveList = []
i = 0
for idx in range(nCurves):
x, y, legend, info = curves[idx][0:4]
if x.size != x0.size:
needInterpolation = True
elif numpy.allclose(x, x0):
# no need for interpolation
needInterpolation = False
else:
needInterpolation = True
if needInterpolation:
# we have to interpolate
x.shape = -1
y.shape = -1
xi = x0[:] * 1
y = SpecfitFuns.interpol([x], y, xi, y0.min())
x = xi
y.shape = -1
i += 1
# now calculate the shift
ffty = numpy.fft.fft(y)
if numpy.allclose(fft0, ffty):
shiftList.append(0.0)
else:
shift = numpy.fft.ifft(fft0 * ffty.conjugate()).real
shift2 = numpy.zeros(shift.shape, dtype=shift.dtype)
m = shift2.size//2
shift2[m:] = shift[:-m]
shift2[:m] = shift[-m:]
threshold = 0.80*shift2.max()
#threshold = shift2.mean()
idx = numpy.nonzero(shift2 > threshold)[0]
#print("max indices = %d" % (m - idx))
shift = (shift2[idx] * idx/shift2[idx].sum()).sum()
#print("shift = ", shift - m, "in x units = ", (shift - m) * (x[1]-x[0]))
# shift the curve
shift = (shift - m) * (x[1]-x[0])
x.shape = -1
y = numpy.fft.ifft(numpy.exp(-2.0*numpy.pi*numpy.sqrt(numpy.complex(-1))*\
numpy.fft.fftfreq(len(x), d=x[1]-x[0])*shift)*ffty)
y = y.real
y.shape = -1
curveList.append([x, y, legend + "SHIFT", False, False])
curveList[-1][-2] = True
curveList[-1][-1] = False
x, y, legend, replot, replace = curveList[0]
self.addCurve(x, y, legend=legend, replot=True, replace=True)
for i in range(1, len(curveList)):
x, y, legend, replot, replace = curveList[i]
self.addCurve(x,
y,
legend=legend,
info=None,
replot=replot,
replace=False)
return
MENU_TEXT = "Alignment Plugin"
def getPlugin1DInstance(plotWindow, **kw):
ob = AlignmentScanPlugin(plotWindow)
return ob
if __name__ == "__main__":
from PyMca import PyMcaQt as qt
app = qt.QApplication([])
from PyMca.Plot1DQwt import Plot1DQwt as Plot1D
i = numpy.arange(1000.)
y1 = 10.0 + 5000.0 * numpy.exp(-0.01*(i-50)**2)
y2 = 10.0 + 5000.0 * numpy.exp(-((i-55)/5.)**2)
plot = Plot1D()
plot.addCurve(i, y1, "y1")
plot.addCurve(i, y2, "y2")
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()
plot.show()
app.exec_()
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