def test_from_msm(): assignments, _ = _metastable_system() msm = MarkovStateModel() msm.fit(assignments) pcca = PCCA.from_msm(msm, 2) msm = MarkovStateModel() msm.fit(assignments) pccaplus = PCCAPlus.from_msm(msm, 2)
for this_assign in geo_assign: this_list = [] for this_item in this_assign: try: this_list.append(partial_raw_to_micro_mapping[this_item]) except KeyError: pass partial_micro_assign.append(this_list) unique_assign = [] for this_assign in partial_micro_assign: unique_assign.extend(np.unique(this_assign)) unique_assign = np.unique(np.array(unique_assign)) N_MACRO = 10 pcca = PCCA.from_msm(micro_msm,N_MACRO) micro_to_macro_mapping = {} for ii in range(len(pcca.microstate_mapping_)): micro_to_macro_mapping[ii] = pcca.microstate_mapping_[ii] # for n macrostates, any frame that does not belong to any microstate and thus macrostate is labeled to be in the nth macrostate for ii in range(len(raw_clusters)): if ii in micro_to_macro_mapping.keys(): pass else: micro_to_macro_mapping[ii] = N_MACRO # assignments to macro states macro_assign = [] for this_assign in geo_assign:
for this_assign in geo_assign: this_list = [] for this_item in this_assign: try: this_list.append(partial_raw_to_micro_mapping[this_item]) except KeyError: pass partial_micro_assign.append(this_list) unique_assign = [] for this_assign in partial_micro_assign: unique_assign.extend(np.unique(this_assign)) unique_assign = np.unique(np.array(unique_assign)) N_MACRO = 5 pcca = PCCA.from_msm(micro_msm, N_MACRO) micro_to_macro_mapping = {} for ii in range(len(pcca.microstate_mapping_)): micro_to_macro_mapping[ii] = pcca.microstate_mapping_[ii] # for n macrostates, any frame that does not belong to any microstate and thus macrostate is labeled to be in the nth macrostate for ii in range(len(raw_clusters)): if ii in micro_to_macro_mapping.keys(): pass else: micro_to_macro_mapping[ii] = N_MACRO # assignments to macro states macro_assign = [] for this_assign in geo_assign: