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feat: jack_matmul no works with an arbitrary number of operands

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This commit is contained in:
Fabian Joswig 2021-11-18 10:46:30 +00:00
parent a673a8f656
commit c31034565a
1 changed files with 13 additions and 14 deletions
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27
pyerrors/linalg.py
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@ -174,20 +174,19 @@ def matmul(*operands):
return derived_array(multi_dot, operands)
def jack_matmul(a, b):
def jack_matmul(*operands):
"""Matrix multiply both operands making use of the jackknife approximation.
Parameters
----------
a : numpy.ndarray
First matrix, can be real or complex Obs valued
b : numpy.ndarray
Second matrix, can be real or complex Obs valued
operands : numpy.ndarray
Arbitrary number of 2d-numpy arrays which can be real or complex
Obs valued.
For large matrices this is considerably faster compared to matmul.
"""
if any(isinstance(o[0, 0], CObs) for o in [a, b]):
if any(isinstance(o[0, 0], CObs) for o in operands):
def _exp_to_jack(matrix):
base_matrix = np.empty_like(matrix)
for (n, m), entry in np.ndenumerate(matrix):
@ -201,10 +200,10 @@ def jack_matmul(a, b):
import_jackknife(entry.imag, name))
return base_matrix
j_a = _exp_to_jack(a)
j_b = _exp_to_jack(b)
r = j_a @ j_b
return _imp_from_jack(r, a.ravel()[0].real.names[0])
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])
else:
def _exp_to_jack(matrix):
base_matrix = np.empty_like(matrix)
@ -218,10 +217,10 @@ def jack_matmul(a, b):
base_matrix[n, m] = import_jackknife(entry, name)
return base_matrix
j_a = _exp_to_jack(a)
j_b = _exp_to_jack(b)
r = j_a @ j_b
return _imp_from_jack(r, a.ravel()[0].names[0])
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])
def inv(x):