diff --git a/docs/pyerrors/obs.html b/docs/pyerrors/obs.html
index f40d96b6..86a504d0 100644
--- a/docs/pyerrors/obs.html
+++ b/docs/pyerrors/obs.html
@@ -660,6 +660,8 @@
ens_content : bool
print details about the ensembles and replica if true.
"""
+ if self.tag is not None:
+ print("Description:", self.tag)
if self.value == 0.0:
percentage = np.nan
else:
@@ -675,8 +677,6 @@
print(' t_int\t %3.8e +/- %3.8e tau_exp = %3.2f, N_sigma = %1.0i' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.tau_exp[e_name], self.N_sigma[e_name]))
else:
print(' t_int\t %3.8e +/- %3.8e S = %3.2f' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.S[e_name]))
- if self.tag is not None:
- print("Description:", self.tag)
if ens_content is True:
if len(self.e_names) == 1:
print(self.N, 'samples in', len(self.e_names), 'ensemble:')
@@ -2214,6 +2214,8 @@
ens_content : bool
print details about the ensembles and replica if true.
"""
+ if self.tag is not None:
+ print("Description:", self.tag)
if self.value == 0.0:
percentage = np.nan
else:
@@ -2229,8 +2231,6 @@
print(' t_int\t %3.8e +/- %3.8e tau_exp = %3.2f, N_sigma = %1.0i' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.tau_exp[e_name], self.N_sigma[e_name]))
else:
print(' t_int\t %3.8e +/- %3.8e S = %3.2f' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.S[e_name]))
- if self.tag is not None:
- print("Description:", self.tag)
if ens_content is True:
if len(self.e_names) == 1:
print(self.N, 'samples in', len(self.e_names), 'ensemble:')
@@ -3139,6 +3139,8 @@ of the autocorrelation function (default True)
ens_content : bool
print details about the ensembles and replica if true.
"""
+ if self.tag is not None:
+ print("Description:", self.tag)
if self.value == 0.0:
percentage = np.nan
else:
@@ -3154,8 +3156,6 @@ of the autocorrelation function (default True)
print(' t_int\t %3.8e +/- %3.8e tau_exp = %3.2f, N_sigma = %1.0i' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.tau_exp[e_name], self.N_sigma[e_name]))
else:
print(' t_int\t %3.8e +/- %3.8e S = %3.2f' % (self.e_tauint[e_name], self.e_dtauint[e_name], self.S[e_name]))
- if self.tag is not None:
- print("Description:", self.tag)
if ens_content is True:
if len(self.e_names) == 1:
print(self.N, 'samples in', len(self.e_names), 'ensemble:')