Esempio n. 1
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def SingleIteration(icm,data,filt,targ):
	
	icm.IterateLS(data)
	edge = image_processing.EnhanceEdge(icm.Y)
	corr = abs(PCECorrelate.PCECorrelation(edge,filt))
	pce = PCECorrelate.PEAK_CORRELATION_ENERGY(corr)
	pks = Peaks.Peaks(pce,targ)
	data, mask = Peaks.Enhance_peak(data,pks,targ)
	all_one = np.ones(data.shape)
	icm.T = mask*0.9*icm.T + (all_one-mask)*icm.T
	return data
Esempio n. 2
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 def testPeaks(self):
     peaks = [10, 56]
     n = np.random.normal(100.0, 1.0, 100)
     for peak in peaks:
         n[peak] = 500
     p = Peaks.peaks(n, 2)
     print "p=", p
Esempio n. 3
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 def findPeaks(self, m=2, useDifference=True):
     if useDifference:
         diff = self.baseline - self.mag
     else:
         diff = -self.mag
     self.peaksDict = Peaks.peaks(diff, m, returnDict=True)
     self.peaks = self.peaksDict['big']
     self.pk = self.peaksDict['pk']
Esempio n. 4
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 def findPeaks(self, m=2, useDifference=True):
     if useDifference:
         diff = self.baseline - self.mag
     else:
         diff = -self.mag            
     self.peaksDict = Peaks.peaks(diff,m,returnDict=True)
     self.peaks = self.peaksDict['big']
     self.pk = self.peaksDict['pk']