From 6cdb15fa76129ac2f860ea95980f36be06797a4b Mon Sep 17 00:00:00 2001 From: fjosw Date: Sat, 4 Dec 2021 11:23:57 +0000 Subject: [PATCH] Documentation updated --- docs/pyerrors/obs.html | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/pyerrors/obs.html b/docs/pyerrors/obs.html index 9013aace..92601937 100644 --- a/docs/pyerrors/obs.html +++ b/docs/pyerrors/obs.html @@ -1564,22 +1564,22 @@ for i in range(len(obs)): if len(obs[i].cov_names): raise Exception('Error: Not possible to reweight an Obs that contains covobs!') - if sorted(weight.names) != sorted(obs[i].names): + if not set(obs[i].names).issubset(weight.names): raise Exception('Error: Ensembles do not fit') - for name in weight.names: + for name in obs[i].names: if not set(obs[i].idl[name]).issubset(weight.idl[name]): raise Exception('obs[%d] has to be defined on a subset of the configs in weight.idl[%s]!' % (i, name)) new_samples = [] w_deltas = {} - for name in sorted(weight.names): + for name in sorted(obs[i].names): w_deltas[name] = _reduce_deltas(weight.deltas[name], weight.idl[name], obs[i].idl[name]) new_samples.append((w_deltas[name] + weight.r_values[name]) * (obs[i].deltas[name] + obs[i].r_values[name])) - tmp_obs = Obs(new_samples, sorted(weight.names), idl=[obs[i].idl[name] for name in sorted(weight.names)]) + tmp_obs = Obs(new_samples, sorted(obs[i].names), idl=[obs[i].idl[name] for name in sorted(obs[i].names)]) if kwargs.get('all_configs'): new_weight = weight else: - new_weight = Obs([w_deltas[name] + weight.r_values[name] for name in sorted(weight.names)], sorted(weight.names), idl=[obs[i].idl[name] for name in sorted(weight.names)]) + new_weight = Obs([w_deltas[name] + weight.r_values[name] for name in sorted(obs[i].names)], sorted(obs[i].names), idl=[obs[i].idl[name] for name in sorted(obs[i].names)]) result.append(derived_observable(lambda x, **kwargs: x[0] / x[1], [tmp_obs, new_weight], **kwargs)) result[-1].reweighted = True @@ -4809,22 +4809,22 @@ functions. For the ratio of two observables one can e.g. use

for i in range(len(obs)): if len(obs[i].cov_names): raise Exception('Error: Not possible to reweight an Obs that contains covobs!') - if sorted(weight.names) != sorted(obs[i].names): + if not set(obs[i].names).issubset(weight.names): raise Exception('Error: Ensembles do not fit') - for name in weight.names: + for name in obs[i].names: if not set(obs[i].idl[name]).issubset(weight.idl[name]): raise Exception('obs[%d] has to be defined on a subset of the configs in weight.idl[%s]!' % (i, name)) new_samples = [] w_deltas = {} - for name in sorted(weight.names): + for name in sorted(obs[i].names): w_deltas[name] = _reduce_deltas(weight.deltas[name], weight.idl[name], obs[i].idl[name]) new_samples.append((w_deltas[name] + weight.r_values[name]) * (obs[i].deltas[name] + obs[i].r_values[name])) - tmp_obs = Obs(new_samples, sorted(weight.names), idl=[obs[i].idl[name] for name in sorted(weight.names)]) + tmp_obs = Obs(new_samples, sorted(obs[i].names), idl=[obs[i].idl[name] for name in sorted(obs[i].names)]) if kwargs.get('all_configs'): new_weight = weight else: - new_weight = Obs([w_deltas[name] + weight.r_values[name] for name in sorted(weight.names)], sorted(weight.names), idl=[obs[i].idl[name] for name in sorted(weight.names)]) + new_weight = Obs([w_deltas[name] + weight.r_values[name] for name in sorted(obs[i].names)], sorted(obs[i].names), idl=[obs[i].idl[name] for name in sorted(obs[i].names)]) result.append(derived_observable(lambda x, **kwargs: x[0] / x[1], [tmp_obs, new_weight], **kwargs)) result[-1].reweighted = True