diff --git a/docs/pyerrors/input/hadrons.html b/docs/pyerrors/input/hadrons.html
index 3ed3dd36..12ef819e 100644
--- a/docs/pyerrors/input/hadrons.html
+++ b/docs/pyerrors/input/hadrons.html
@@ -115,7 +115,7 @@
if not all(np.diff(cnfg_numbers) == np.diff(cnfg_numbers)[0]):
raise Exception('Configurations are not evenly spaced.')
- return files
+ return files, cnfg_numbers
def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'):
@@ -138,7 +138,7 @@
from other modules with similar structures.
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
corr_data = []
infos = []
@@ -155,7 +155,7 @@
l_obs = []
for c in corr_data.T:
- l_obs.append(Obs([c], [ens_id]))
+ l_obs.append(Obs([c], [ens_id], idl=[cnfg_numbers]))
corr = Corr(l_obs)
corr.tag = r", ".join(infos)
@@ -175,7 +175,7 @@
'C' for the last index changing fastest (16 3x3 matrices),
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
mom = None
@@ -195,8 +195,8 @@
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])
+ real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers])
+ imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers])
matrix[si, sj, ci, cj] = CObs(real, imag)
matrix[si, sj, ci, cj].gamma_method()
@@ -216,7 +216,7 @@
'C' for the last index changing fastest (16 3x3 matrices),
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
mom_in = None
mom_out = None
@@ -250,8 +250,8 @@
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])
+ real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers])
+ imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers])
matrix[si, sj, ci, cj] = CObs(real, imag)
matrix[si, sj, ci, cj].gamma_method()
@@ -293,7 +293,7 @@
from other modules with similar structures.
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
corr_data = []
infos = []
@@ -310,7 +310,7 @@
l_obs = []
for c in corr_data.T:
- l_obs.append(Obs([c], [ens_id]))
+ l_obs.append(Obs([c], [ens_id], idl=[cnfg_numbers]))
corr = Corr(l_obs)
corr.tag = r", ".join(infos)
@@ -365,7 +365,7 @@ from other modules with similar structures.
'C' for the last index changing fastest (16 3x3 matrices),
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
mom = None
@@ -385,8 +385,8 @@ from other modules with similar structures.
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])
+ real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers])
+ imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers])
matrix[si, sj, ci, cj] = CObs(real, imag)
matrix[si, sj, ci, cj].gamma_method()
@@ -433,7 +433,7 @@ from other modules with similar structures.
'C' for the last index changing fastest (16 3x3 matrices),
"""
- files = _get_files(path, filestem)
+ files, cnfg_numbers = _get_files(path, filestem)
mom_in = None
mom_out = None
@@ -467,8 +467,8 @@ from other modules with similar structures.
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])
+ real = Obs([rolled_array[si, sj, ci, cj].real], [ens_id], idl=[cnfg_numbers])
+ imag = Obs([rolled_array[si, sj, ci, cj].imag], [ens_id], idl=[cnfg_numbers])
matrix[si, sj, ci, cj] = CObs(real, imag)
matrix[si, sj, ci, cj].gamma_method()