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feat: linalg.jack_matmul now also works with irregular monte carlo

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This commit is contained in:
Fabian Joswig 2021-11-18 11:17:20 +00:00
parent 0954ebee6e
commit 28bf0f1701
2 changed files with 15 additions and 9 deletions
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20
pyerrors/linalg.py
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@ -187,40 +187,46 @@ def jack_matmul(*operands):
"""
if any(isinstance(o[0, 0], CObs) for o in operands):
name = operands[0][0, 0].real.names[0]
idl = operands[0][0, 0].real.idl[name]
def _exp_to_jack(matrix):
base_matrix = np.empty_like(matrix)
for (n, m), entry in np.ndenumerate(matrix):
base_matrix[n, m] = entry.real.export_jackknife() + 1j * entry.imag.export_jackknife()
return base_matrix
def _imp_from_jack(matrix, name):
def _imp_from_jack(matrix):
base_matrix = np.empty_like(matrix)
for (n, m), entry in np.ndenumerate(matrix):
base_matrix[n, m] = CObs(import_jackknife(entry.real, name),
import_jackknife(entry.imag, name))
base_matrix[n, m] = CObs(import_jackknife(entry.real, name, [idl]),
import_jackknife(entry.imag, name, [idl]))
return base_matrix
r = _exp_to_jack(operands[0])
for op in operands[1:]:
r = r @ _exp_to_jack(op)
return _imp_from_jack(r, op.ravel()[0].real.names[0])
return _imp_from_jack(r)
else:
name = operands[0][0, 0].names[0]
idl = operands[0][0, 0].idl[name]
def _exp_to_jack(matrix):
base_matrix = np.empty_like(matrix)
for (n, m), entry in np.ndenumerate(matrix):
base_matrix[n, m] = entry.export_jackknife()
return base_matrix
def _imp_from_jack(matrix, name):
def _imp_from_jack(matrix):
base_matrix = np.empty_like(matrix)
for (n, m), entry in np.ndenumerate(matrix):
base_matrix[n, m] = import_jackknife(entry, name)
base_matrix[n, m] = import_jackknife(entry, name, [idl])
return base_matrix
r = _exp_to_jack(operands[0])
for op in operands[1:]:
r = r @ _exp_to_jack(op)
return _imp_from_jack(r, op.ravel()[0].names[0])
return _imp_from_jack(r)
def inv(x):

4
pyerrors/obs.py
View file

@ -1559,7 +1559,7 @@ def load_object(path):
return pickle.load(file)
def import_jackknife(jacks, name):
def import_jackknife(jacks, name, idl=None):
"""Imports jackknife samples and returns an Obs
Parameters
@ -1573,7 +1573,7 @@ def import_jackknife(jacks, name):
length = len(jacks) - 1
prj = (np.ones((length, length)) - (length - 1) * np.identity(length))
samples = jacks[1:] @ prj
new_obs = Obs([samples], [name])
new_obs = Obs([samples], [name], idl=idl)
new_obs._value = jacks[0]
return new_obs