def medianThresholdFilter(self, activeOnly, threshold, length):
if activeOnly:
active = self.getActiveCurve()
if not active:
return
else:
x, y, legend, info = active
self.removeCurve(legend)
spectra = [active]
else:
spectra = self.getAllCurves()
for (idx, spec) in enumerate(spectra):
x, y, legend, info = spec
filtered = medfilt1d(y, length)
diff = filtered-y
mean = diff.mean()
sigma = (y-mean)**2
sigma = numpy.sqrt(sigma.sum()/float(len(sigma)))
ynew = numpy.where(abs(diff) > threshold * sigma, filtered, y)
legend = info.get('selectionlegend',legend) + ' SR'
if (idx==0) and (len(spectra)!=1):
self.addCurve(x,ynew,legend,info, replace=True, replot=False)
elif idx == (len(spectra)- 1):
self.addCurve(x,ynew,legend,info, replace=False, replot=True)
else:
self.addCurve(x,ynew,legend,info, replace=False, replot=False)
def medianThresholdFilter(self, activeOnly, threshold, length):
if activeOnly:
active = self.getActiveCurve()
if not active:
return
else:
x, y, legend, info = active
self.removeCurve(legend)
spectra = [active]
else:
spectra = self.getAllCurves()
for (idx, spec) in enumerate(spectra):
x, y, legend, info = spec
filtered = medfilt1d(y, length)
diff = filtered-y
mean = diff.mean()
sigma = (y-mean)**2
sigma = numpy.sqrt(sigma.sum()/float(len(sigma)))
ynew = numpy.where(abs(diff) > threshold * sigma, filtered, y)
legend = info.get('selectionlegend',legend) + ' SR'
if (idx==0) and (len(spectra)!=1):
self.addCurve(x,ynew,legend,info, replace=True, replot=False)
elif idx == (len(spectra)- 1):
self.addCurve(x,ynew,legend,info, replace=False, replot=True)
else:
self.addCurve(x,ynew,legend,info, replace=False, replot=False)