71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
from __future__ import print_function,division
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import mcutils as mc
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import joblib
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import numpy as np
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# /--------\
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# | |
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# | UTILS |
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# | |
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# \--------/
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def rebin1D(a,shape):
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n0 = a.shape[0]//shape
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sh = shape,n0
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return a[:n0*shape].reshape(sh).mean(1)
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def calcFOM(p1,p2,ratio,threshold=0.1):
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idx = ( p1>p1.max()*threshold )# & (p2>p2.max()/10)
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ratio = ratio[idx]
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return ratio.std()/np.abs(ratio.mean())
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def getCenterOfMass(img,x=None,axis=0,threshold=0.05):
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img = img.copy()
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if img.ndim == 1: img=img[np.newaxis,:]; axis=1
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img[img<img.max()*threshold] = 0
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if axis == 1: img=img.T
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p = img.mean(1)
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if x is None: x = np.arange(img.shape[0])
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return np.sum(x*p)/np.sum(p)
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def maskLowIntensity(p1,p2,threshold=0.03,squeeze=True):
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if p1.ndim == 1:
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p1 = p1[np.newaxis,:]
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p2 = p2[np.newaxis,:]
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p1 = np.ma.asarray( p1.copy() )
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p2 = np.ma.asarray( p2.copy() )
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if threshold is not None:
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m1 = np.nanmax(p1,axis=1); m2 = np.nanmax(p2,axis=1)
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# find where each spectrum is smaller than threshold*max_for_that_shot; they will be masked out
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idx1 = p1 < (m1[:,np.newaxis]*threshold)
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#idx2 = p2 < (m2[:,np.newaxis]*threshold)
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idx = idx1# & idx2
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p1.mask = idx
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p2.mask = idx
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if squeeze:
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p1 = np.squeeze(p1);
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p2 = np.squeeze(p2)
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return p1,p2
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def ratioOfAverage(p1,p2,threshold=0.03):
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"""
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p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
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calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
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p1,p2 = maskLowIntensity(p1,p2,threshold=threshold,squeeze=False)
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# using masked array because some pixel will have zero shots contributing
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av1 = np.ma.average(p1,axis=0,weights=p1)
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av2 = np.ma.average(p2,axis=0,weights=p2)
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return av2/av1
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def medianRatio(p1,p2,threshold=0.03):
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"""
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p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
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calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
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p1,p2 = maskLowIntensity(p1,p2,threshold=threshold,squeeze=False)
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ratio = p2/p1
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return np.ma.average(ratio,axis=0,weights=p1)
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