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[chore] Stricter ruff rules

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Fabian Joswig 2026-04-20 19:33:15 +02:00
commit c896843664
22 changed files with 400 additions and 311 deletions
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15
pyerrors/linalg.py
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@ -1,6 +1,7 @@
import numpy as np
import autograd.numpy as anp # Thinly-wrapped numpy
from .obs import derived_observable, CObs, Obs, import_jackknife
import numpy as np
from .obs import CObs, Obs, derived_observable, import_jackknife
def matmul(*operands):
@ -24,7 +25,7 @@ def matmul(*operands):
def multi_dot(operands, part):
stack_r = operands[0]
stack_i = operands[1]
for op_r, op_i in zip(operands[2::2], operands[3::2]):
for op_r, op_i in zip(operands[2::2], operands[3::2], strict=True):
tmp_r = stack_r @ op_r - stack_i @ op_i
tmp_i = stack_r @ op_i + stack_i @ op_r
@ -46,7 +47,7 @@ def matmul(*operands):
Ni = derived_observable(multi_dot_i, extended_operands, array_mode=True)
res = np.empty_like(Nr)
for (n, m), entry in np.ndenumerate(Nr):
for (n, m), _entry in np.ndenumerate(Nr):
res[n, m] = CObs(Nr[n, m], Ni[n, m])
return res
@ -134,13 +135,13 @@ def einsum(subscripts, *operands):
def _exp_to_jack(matrix):
base_matrix = []
for index, entry in np.ndenumerate(matrix):
for _index, entry in np.ndenumerate(matrix):
base_matrix.append(entry.export_jackknife())
return np.asarray(base_matrix).reshape(matrix.shape + base_matrix[0].shape)
def _exp_to_jack_c(matrix):
base_matrix = []
for index, entry in np.ndenumerate(matrix):
for _index, entry in np.ndenumerate(matrix):
base_matrix.append(entry.real.export_jackknife() + 1j * entry.imag.export_jackknife())
return np.asarray(base_matrix).reshape(matrix.shape + base_matrix[0].shape)
@ -251,7 +252,7 @@ def _mat_mat_op(op, obs, **kwargs):
op_A = op_big_matrix[0: dim // 2, 0: dim // 2]
op_B = op_big_matrix[dim // 2:, 0: dim // 2]
res = np.empty_like(op_A)
for (n, m), entry in np.ndenumerate(op_A):
for (n, m), _entry in np.ndenumerate(op_A):
res[n, m] = CObs(op_A[n, m], op_B[n, m])
return res
else: