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Merge branch 'develop' into documentation

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fjosw 2022-02-22 15:11:04 +00:00
commit 0666eb3533
2 changed files with 38 additions and 7 deletions
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15
pyerrors/correlators.py
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@ -867,6 +867,11 @@ class Corr:
else:
newcontent.append(self.content[t] + y)
return Corr(newcontent, prange=self.prange)
elif isinstance(y, np.ndarray):
if y.shape == (self.T,):
return Corr(list((np.array(self.content).T + y).T))
else:
raise ValueError("operands could not be broadcast together")
else:
raise TypeError("Corr + wrong type")
@ -890,6 +895,11 @@ class Corr:
else:
newcontent.append(self.content[t] * y)
return Corr(newcontent, prange=self.prange)
elif isinstance(y, np.ndarray):
if y.shape == (self.T,):
return Corr(list((np.array(self.content).T * y).T))
else:
raise ValueError("operands could not be broadcast together")
else:
raise TypeError("Corr * wrong type")
@ -939,6 +949,11 @@ class Corr:
else:
newcontent.append(self.content[t] / y)
return Corr(newcontent, prange=self.prange)
elif isinstance(y, np.ndarray):
if y.shape == (self.T,):
return Corr(list((np.array(self.content).T / y).T))
else:
raise ValueError("operands could not be broadcast together")
else:
raise TypeError('Corr / wrong type')

30
tests/correlators_test.py
View file

@ -219,13 +219,6 @@ def test_prange():
def test_matrix_corr():
def _gen_corr(val):
corr_content = []
for t in range(16):
corr_content.append(pe.pseudo_Obs(val, 0.1, 't', 2000))
return pe.correlators.Corr(corr_content)
corr_aa = _gen_corr(1)
corr_ab = _gen_corr(0.5)
@ -311,3 +304,26 @@ def test_corr_matrix_none_entries():
corr = pe.Corr(oy)
corr = corr.deriv()
pe.Corr(np.array([[corr, corr], [corr, corr]]))
def test_corr_vector_operations():
my_corr = _gen_corr(1.0)
my_vec = np.arange(1, 17)
my_corr + my_vec
my_corr - my_vec
my_corr * my_vec
my_corr / my_vec
assert np.all([o == 0 for o in ((my_corr + my_vec) - my_vec) - my_corr])
assert np.all([o == 0 for o in ((my_corr - my_vec) + my_vec) - my_corr])
assert np.all([o == 0 for o in ((my_corr * my_vec) / my_vec) - my_corr])
assert np.all([o == 0 for o in ((my_corr / my_vec) * my_vec) - my_corr])
def _gen_corr(val):
corr_content = []
for t in range(16):
corr_content.append(pe.pseudo_Obs(val, 0.1, 't', 2000))
return pe.correlators.Corr(corr_content)