| 1 | import matplotlib.pyplot as plt
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| 2 | import numpy as np
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| 3 | import numpy.ma as ma
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| 4 |
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| 5 | class camplotter( object ):
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| 6 | def __init__( self ):
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| 7 | chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
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| 8 | self.fig = plt.figure()
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| 9 | self.xe = xe
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| 10 | self.ye = ye
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| 11 | self.H = (6,0,30./180.*3.1415926)
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| 12 |
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| 13 | def plotcam():
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| 14 | data = np.random.rand(1440)
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| 15 | chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
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| 16 | fig = plt.figure()
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| 17 | ax = fig.add_subplot(121, aspect='equal')
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| 18 | bx = fig.add_subplot(122, aspect='equal')
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| 19 |
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| 20 | H = (6,0,30./180.*3.1415926)
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| 21 |
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| 22 | ax.scatter( xe, ye , s=40 , alpha=0.75 , marker=H , linewidths=0.)
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| 23 | bx.scatter( xe, ye , s=40 , alpha=0.75 , marker=H , linewidths=0., c=data)
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| 24 | plt.show()
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| 25 |
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| 26 | def plotincam( data ):
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| 27 | ax = fig.add_subplot(aspect='equal')
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| 28 | ax.scatter(xe,ye,s=40,alpha=0.75,marker=H, c=data)
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| 29 | plt.show()
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| 30 |
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| 31 | def plotmaskedcam( thr):
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| 32 | chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
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| 33 | data = np.random.rand(1440)
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| 34 | mdata = ma.masked_greater(data, thr)
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| 35 | fig = plt.figure()
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| 36 | ax = fig.add_subplot(111, aspect='equal')
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| 37 | H = (6,0,30./180.*3.1415926)
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| 38 |
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| 39 | a = ma.masked_where(mdata.mask == True, xe)
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| 40 | b = ma.masked_where(mdata.mask == True, ye)
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| 41 |
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| 42 | xm = a.compressed()
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| 43 | ym = b.compressed()
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| 44 | dm = mdata.compressed()
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| 45 |
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| 46 | print xm
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| 47 | print ym
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| 48 | print dm
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| 49 | ax.scatter(xe,ye,s=80,alpha=0.75,marker=H, c=data, edgecolors='none')
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| 50 | ax.scatter( xm, ym ,s=80,alpha=1,marker=H,facecolors='none',linewidths=3)
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| 51 | plt.show()
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| 52 |
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| 53 |
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| 54 | def randomcam():
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| 55 | data = np.random.rand(1440)
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| 56 | plotincam( data )
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 | if __name__ == '__main__':
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| 63 | """
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| 64 | create an instance
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| 65 | """
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| 66 | cplt = camplotter()
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| 67 | # np.savez ( filename, amplitude=maxAmp, time=maxPos, integral=integ)
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| 68 | npz = np.load('test.npz')
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| 69 | print npz.files
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| 70 |
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| 71 | data = npz['integral']
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| 72 | print 'data.shape', data.shape()
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| 73 |
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| 74 | for event in data:
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| 75 | print 'event.shape', event.shape()
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| 76 |
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