def test_equivalence_diff_3(self):
norm = 3
bg, var = stats(self.test_data1)
data = multitau.acorr_multi(self.test_data1,
level_size=16,
norm=1,
method="corr",
binning=0)
data = multitau.normalize_multi(data, bg, var, norm=1)
x_, out0 = multitau.log_merge(*data)
data = multitau.ccorr_multi(self.test_data1,
self.test_data1,
level_size=16,
norm=norm,
method="diff",
binning=0)
data = multitau.normalize_multi(data, bg, var, norm=norm)
x_, out = multitau.log_merge(*data)
self.assertTrue(np.allclose(out0, out))
data, bg, var = multitau.iacorr_multi(fromarrays((self.test_data1, )),
count=64,
level_size=16,
norm=1,
method="diff",
binning=0)
data = multitau.normalize_multi(data, bg, var, norm=1)
x_, out = multitau.log_merge(*data)
self.assertTrue(np.allclose(out0, out))
def test_equivalence_norm_2(self):
norm = 2
bg, var = stats(self.test_data1)
data= multitau.acorr_multi(self.test_data1, level_size = 16, norm = norm)
data = multitau.normalize_multi(data,bg,var, norm = norm)
x_, out0 = multitau.log_merge(*data)
data = multitau.ccorr_multi(self.test_data1,self.test_data1, level_size = 16, norm = norm)
data = multitau.normalize_multi(data,bg,var, norm = norm)
x_, out = multitau.log_merge(*data)
self.assertTrue(np.allclose(out0,out))
data,bg,var = multitau.iacorr_multi(fromarrays((self.test_data1,)),count = 64, level_size = 16, norm = norm)
data = multitau.normalize_multi(data,bg,var, norm = norm)
x_, out = multitau.log_merge(*data)
self.assertTrue(np.allclose(out0,out))