mirror of
https://github.com/fjosw/pyerrors.git
synced 2025-03-15 14:50:25 +01:00
commit
63b2f4fd22
2 changed files with 20 additions and 6 deletions
|
@ -969,6 +969,8 @@ class Corr:
|
|||
content_string += "Description: " + self.tag + "\n"
|
||||
if self.N != 1:
|
||||
return content_string
|
||||
if isinstance(self[0], CObs):
|
||||
return content_string
|
||||
|
||||
if print_range[1]:
|
||||
print_range[1] += 1
|
||||
|
@ -1136,8 +1138,10 @@ class Corr:
|
|||
for t in range(self.T):
|
||||
if _check_for_none(self, newcontent[t]):
|
||||
continue
|
||||
if np.isnan(np.sum(newcontent[t]).value):
|
||||
newcontent[t] = None
|
||||
tmp_sum = np.sum(newcontent[t])
|
||||
if hasattr(tmp_sum, "value"):
|
||||
if np.isnan(tmp_sum.value):
|
||||
newcontent[t] = None
|
||||
if all([item is None for item in newcontent]):
|
||||
raise Exception('Operation returns undefined correlator')
|
||||
return Corr(newcontent)
|
||||
|
@ -1194,8 +1198,8 @@ class Corr:
|
|||
@property
|
||||
def real(self):
|
||||
def return_real(obs_OR_cobs):
|
||||
if isinstance(obs_OR_cobs, CObs):
|
||||
return obs_OR_cobs.real
|
||||
if isinstance(obs_OR_cobs.flatten()[0], CObs):
|
||||
return np.vectorize(lambda x: x.real)(obs_OR_cobs)
|
||||
else:
|
||||
return obs_OR_cobs
|
||||
|
||||
|
@ -1204,8 +1208,8 @@ class Corr:
|
|||
@property
|
||||
def imag(self):
|
||||
def return_imag(obs_OR_cobs):
|
||||
if isinstance(obs_OR_cobs, CObs):
|
||||
return obs_OR_cobs.imag
|
||||
if isinstance(obs_OR_cobs.flatten()[0], CObs):
|
||||
return np.vectorize(lambda x: x.imag)(obs_OR_cobs)
|
||||
else:
|
||||
return obs_OR_cobs * 0 # So it stays the right type
|
||||
|
||||
|
|
|
@ -532,3 +532,13 @@ def test_prune():
|
|||
with pytest.raises(Exception):
|
||||
corr_mat.prune(3)
|
||||
corr_mat.prune(4)
|
||||
|
||||
|
||||
def test_complex_Corr():
|
||||
o1 = pe.pseudo_Obs(1.0, 0.1, "test")
|
||||
cobs = pe.CObs(o1, -o1)
|
||||
ccorr = pe.Corr([cobs, cobs, cobs])
|
||||
assert np.all([ccorr.imag[i] == -ccorr.real[i] for i in range(ccorr.T)])
|
||||
print(ccorr)
|
||||
mcorr = pe.Corr(np.array([[ccorr, ccorr], [ccorr, ccorr]]))
|
||||
assert np.all([mcorr.imag[i] == -mcorr.real[i] for i in range(mcorr.T)])
|
||||
|
|
Loading…
Add table
Reference in a new issue