Esempio n. 1
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 def testGlobalShotNoise(self):
     for sn, sng in ((5, self.constant5Burstgen), (50, self.constant50Burstgen), (500, self.constant500Burstgen), (5000, self.constant5000Burstgen)):
         tm = GlobalAVGKappaTransferMatrix(20, 11, 1000, sng, 5.475, (5, 6))
         tmx = tm.getMatrix()
         print "Burstsizes %d" % sn
         for _ in range(7):
             mbin = random.choice(range(20))
             binmid = generateBinMid(1, mbin, 20, 5)
             eff = rToEff(binmid, R0 = 5.475)
             print "Testing mbin %d at pos %f with efficiency %f" % (mbin, binmid, eff)
             shotnoise = getShotNoise(eff, 11, 1000, sn)
             tmxvec = tmx[mbin, :]
             tmxvec.shape = (11, 1)
             self.assertAlmostEqual((tmxvec - shotnoise).sum(), 0.0, delta = 0.005)
Esempio n. 2
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 def testDistanceAVGShotNoise(self):
     R = numpy.linspace(5, 6, 1100)
     kappa = [ 2. / 3 ] * 1100
     weights = [ 1. ] * 1100
     for sn, sng in ((5, self.constant5Burstgen), (50, self.constant50Burstgen), (500, self.constant500Burstgen), (5000, self.constant5000Burstgen)):
         tm = DistanceAVGKappaTransferMatrix(20, 11, 1000, sng, 5.475, R, kappa, weights, RRange = (5, 6))
         tmx = tm.getMatrix()
         print "Burstsizes %d" % sn
         for _ in range(7):
             mbin = random.choice(range(20))
             binmid = generateBinMid(1, mbin, 20, 5)
             eff = rToEff(binmid, R0 = 5.475)
             print "Testing mbin %d at pos %f with efficiency %f" % (mbin, binmid, eff)
             shotnoise = getShotNoise(eff, 11, 1000, sn)
             tmxvec = tmx[mbin, :]
             tmxvec.shape = (11, 1)
             self.assertAlmostEqual((tmxvec - shotnoise).sum(), 0.0, delta = 0.005)