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feat: determination of idx in input.hadrons module optimized

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Fabian Joswig 2021-11-18 15:14:30 +00:00
parent 8c95ca8318
commit 4df0e7bc82
1 changed files with 15 additions and 10 deletions
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25
pyerrors/input/hadrons.py
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@ -29,10 +29,15 @@ def _get_files(path, filestem):
for line in files: for line in files:
cnfg_numbers.append(get_cnfg_number(line)) cnfg_numbers.append(get_cnfg_number(line))
if not all(np.diff(cnfg_numbers) == np.diff(cnfg_numbers)[0]): dc = np.unique(np.diff(cnfg_numbers))
if np.any(dc < 0):
raise Exception("Unsorted files")
if len(dc) == 1:
idx = range(cnfg_numbers[0], cnfg_numbers[-1] + dc[0], dc[0])
else:
raise Exception('Configurations are not evenly spaced.') raise Exception('Configurations are not evenly spaced.')
return files, cnfg_numbers return files, idx
def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'): def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'):
@ -55,7 +60,7 @@ def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'):
from other modules with similar structures. from other modules with similar structures.
""" """
files, cnfg_numbers = _get_files(path, filestem) files, idx = _get_files(path, filestem)
corr_data = [] corr_data = []
infos = [] infos = []
@ -72,7 +77,7 @@ def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'):
l_obs = [] l_obs = []
for c in corr_data.T: for c in corr_data.T:
l_obs.append(Obs([c], [ens_id], idl=[cnfg_numbers])) l_obs.append(Obs([c], [ens_id], idl=[idx]))
corr = Corr(l_obs) corr = Corr(l_obs)
corr.tag = r", ".join(infos) corr.tag = r", ".join(infos)
@ -92,7 +97,7 @@ def read_ExternalLeg_hd5(path, filestem, ens_id, order='F'):
'C' for the last index changing fastest (16 3x3 matrices), 'C' for the last index changing fastest (16 3x3 matrices),
""" """
files, cnfg_numbers = _get_files(path, filestem) files, idx = _get_files(path, filestem)
mom = None mom = None
@ -110,8 +115,8 @@ def read_ExternalLeg_hd5(path, filestem, ens_id, order='F'):
matrix = np.empty((rolled_array.shape[:-1]), dtype=object) matrix = np.empty((rolled_array.shape[:-1]), dtype=object)
for si, sj, ci, cj in np.ndindex(rolled_array.shape[:-1]): for si, sj, ci, cj in np.ndindex(rolled_array.shape[:-1]):
real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers]) real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[idx])
imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers]) imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[idx])
matrix[si, sj, ci, cj] = CObs(real, imag) matrix[si, sj, ci, cj] = CObs(real, imag)
return Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom) return Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom)
@ -130,7 +135,7 @@ def read_Bilinear_hd5(path, filestem, ens_id, order='F'):
'C' for the last index changing fastest (16 3x3 matrices), 'C' for the last index changing fastest (16 3x3 matrices),
""" """
files, cnfg_numbers = _get_files(path, filestem) files, idx = _get_files(path, filestem)
mom_in = None mom_in = None
mom_out = None mom_out = None
@ -160,8 +165,8 @@ def read_Bilinear_hd5(path, filestem, ens_id, order='F'):
matrix = np.empty((rolled_array.shape[:-1]), dtype=object) matrix = np.empty((rolled_array.shape[:-1]), dtype=object)
for si, sj, ci, cj in np.ndindex(rolled_array.shape[:-1]): for si, sj, ci, cj in np.ndindex(rolled_array.shape[:-1]):
real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers]) real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[idx])
imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers]) imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[idx])
matrix[si, sj, ci, cj] = CObs(real, imag) matrix[si, sj, ci, cj] = CObs(real, imag)
result_dict[key] = Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom_in, mom_out=mom_out) result_dict[key] = Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom_in, mom_out=mom_out)