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read bilinear added to input/hadrons

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Fabian Joswig 2021-10-22 18:29:28 +01:00
parent 1223676b08
commit 94e3ebe7f0
1 changed files with 57 additions and 0 deletions
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57
pyerrors/input/hadrons.py
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@ -109,3 +109,60 @@ def read_ExternalLeg_hd5(path, filestem, ens_id, order='F'):
matrix[si, sj, ci, cj].gamma_method()
return Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom)
def read_Bilinear_hd5(path, filestem, ens_id, order='F'):
"""Read hadrons Bilinear hdf5 file and output an array of CObs
Parameters
-----------------
path -- path to the files to read
filestem -- namestem of the files to read
ens_id -- name of the ensemble, required for internal bookkeeping
order -- order in which the array is to be reshaped,
'F' for the first index changing fastest (9 4x4 matrices) default.
'C' for the last index changing fastest (16 3x3 matrices),
"""
files = _get_files(path, filestem)
mom_in = None
mom_out = None
corr_data = {}
for hd5_file in files:
file = h5py.File(path + '/' + hd5_file, "r")
for i in range(16):
name = file['Bilinear/Bilinear_' + str(i) + '/info'].attrs['gamma'][0].decode('UTF-8')
if name not in corr_data:
corr_data[name] = []
raw_data = file['Bilinear/Bilinear_' + str(i) + '/corr'][0][0].view('complex')
corr_data[name].append(raw_data)
if mom_in is not None:
assert np.allclose(mom_in, np.array(str(file['Bilinear/Bilinear_' + str(i) + '/info'].attrs['pIn'])[3:-2].strip().split(' '), dtype=int))
else:
mom_in = np.array(str(file['Bilinear/Bilinear_' + str(i) + '/info'].attrs['pIn'])[3:-2].strip().split(' '), dtype=int)
if mom_out is not None:
assert np.allclose(mom_out, np.array(str(file['Bilinear/Bilinear_' + str(i) + '/info'].attrs['pIn'])[3:-2].strip().split(' '), dtype=int))
else:
mom_out = np.array(str(file['Bilinear/Bilinear_' + str(i) + '/info'].attrs['pIn'])[3:-2].strip().split(' '), dtype=int)
file.close()
result_dict = {}
for key, data in corr_data.items():
local_data = np.array(data)
rolled_array = np.rollaxis(local_data, 0, 5)
matrix = np.empty((rolled_array.shape[:-1]), dtype=object)
for si, sj, ci, cj in np.ndindex(rolled_array.shape[:-1]):
real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id])
imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id])
matrix[si, sj, ci, cj] = CObs(real, imag)
matrix[si, sj, ci, cj].gamma_method()
result_dict[key] = Npr_matrix(matrix.swapaxes(1, 2).reshape((12, 12), order=order), mom_in=mom_in, mom_out=mom_out)
return result_dict