sphinx.addnodesdocument)}( rawsourcechildren]docutils.nodessection)}(hhh](h title)}(h core packageh]h Text core package}(parenth _documenthsourceNlineNuba attributes}(ids]classes]names]dupnames]backrefs]utagnamehhh hhhLC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\docs\core\core.rsthKubh )}(hhh]h)}(h Submodulesh]h Submodules}(hh0hhhNhNubah}(h!]h#]h%]h']h)]uh+hhh-hhhh,hKubah}(h!] submodulesah#]h%] submodulesah']h)]uh+h hh hhhh,hKubh )}(hhh](h)}(hcore.AutoML moduleh]hcore.AutoML module}(hhIhhhNhNubah}(h!]h#]h%]h']h)]uh+hhhFhhhh,hKubhindex)}(hhh]h}(h!]h#]h%]h']h)]entries](pairmodule; core.AutoMLmodule-core.AutoMLhNtauh+hWhhFhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](single autogluon (class in core.AutoML)core.AutoML.autogluonhNtauh+hWhhFhhhNhNubhdesc)}(hhh](hdesc_signature)}(hautogluon(endogenous_variable, save_path='twinstat_autogluon', num_trials=10, search_strategy='auto', eval_metric='rmse', problem_type='regression', validation_frac=0.1, preload=True)h](hdesc_annotation)}(h2[<#text: 'class'>, >]h](hclass}(hhhhhNhNubhdesc_sig_space)}(h h]h }(hhhhhNhNubah}(h!]h#]wah%]h']h)]uh+hhhubeh}(h!]h#]h%]h']h)] xml:spacepreserveuh+hhh~hhhtC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluonhKubh desc_addname)}(h core.AutoML.h]h core.AutoML.}(hhhhhNhNubah}(h!]h#]( sig-prename descclassnameeh%]h']h)]hhuh+hhh~hhhhhKubh desc_name)}(h autogluonh]h autogluon}(hhhhhNhNubah}(h!]h#](sig-namedescnameeh%]h']h)]hhuh+hhh~hhhhhKubhdesc_parameterlist)}(hendogenous_variable, save_path='twinstat_autogluon', num_trials=10, search_strategy='auto', eval_metric='rmse', problem_type='regression', validation_frac=0.1, preload=Trueh](hdesc_parameter)}(hendogenous_variableh]h desc_sig_name)}(hendogenous_variableh]hendogenous_variable}(hhhhhNhNubah}(h!]h#]nah%]h']h)]uh+hhhubah}(h!]h#]h%]h']h)]hhuh+hhhubh)}(hsave_path='twinstat_autogluon'h](h)}(h save_pathh]h save_path}(hhhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhhubhdesc_sig_operator)}(h=h]h=}(hjhhhNhNubah}(h!]h#]oah%]h']h)]uh+hhhubh inline)}(h'twinstat_autogluon'h]h'twinstat_autogluon'}(hjhhhNhNubah}(h!]h#] default_valueah%]h']h)]support_smartquotesuh+jhhubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(h num_trials=10h](h)}(h num_trialsh]h num_trials}(hj,hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj(ubj)}(h=h]h=}(hj:hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj(ubj)}(h10h]h10}(hjHhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj(ubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(hsearch_strategy='auto'h](h)}(hsearch_strategyh]hsearch_strategy}(hjahhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj]ubj)}(h=h]h=}(hjohhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj]ubj)}(h'auto'h]h'auto'}(hj}hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj]ubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(heval_metric='rmse'h](h)}(h eval_metrich]h eval_metric}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubj)}(h=h]h=}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubj)}(h'rmse'h]h'rmse'}(hjhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(hproblem_type='regression'h](h)}(h problem_typeh]h problem_type}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubj)}(h=h]h=}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubj)}(h 'regression'h]h 'regression'}(hjhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(hvalidation_frac=0.1h](h)}(hvalidation_frach]hvalidation_frac}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubj)}(h=h]h=}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubj)}(h0.1h]h0.1}(hjhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjubeh}(h!]h#]h%]h']h)]hhuh+hhhubh)}(h preload=Trueh](h)}(hpreloadh]hpreload}(hj5hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj1ubj)}(h=h]h=}(hjChhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj1ubj)}(hTrueh]hTrue}(hjQhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj1ubeh}(h!]h#]h%]h']h)]hhuh+hhhubeh}(h!]h#]h%]h']h)]hhuh+hhh~hhhhhKubeh}(h!]huah#](sig sig-objecteh%]h']h)]module core.AutoMLclasshfullnameh _toc_partsjuh _toc_namehuh+h|hhhKhhyhhubh desc_content)}(hhh](h paragraph)}(hBases: :py:class:`object`h](hBases: }(hjhhhNhNubh pending_xref)}(h:py:class:`object`h]h literal)}(hjh]hobject}(hjhhhNhNubah}(h!]h#](xrefpypy-classeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdoc core/core refdomainjreftypeclass refexplicitrefwarn py:modulejupy:classh reftargetobjectuh+jhtC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluonhKhjubeh}(h!]h#]h%]h']h)]uh+jhjhKhj}hhubj)}(hEnables low effort utilization of autogluon for echelon model development and hyperparameter tuning. Specifically setup for only tabular data.h]hEnables low effort utilization of autogluon for echelon model development and hyperparameter tuning. Specifically setup for only tabular data.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhtC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluonhKhj}hhubj)}(hLSee https://auto.gluon.ai/dev/index.html for more options and customization.h](hSee }(hjhhhNhNubh reference)}(h$https://auto.gluon.ai/dev/index.htmlh]h$https://auto.gluon.ai/dev/index.html}(hjhhhNhNubah}(h!]h#]h%]h']h)]refurijuh+jhjubh$ for more options and customization.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjhKhj}hhubh field_list)}(hhh](h field)}(hhh](h field_name)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhhhKubh field_body)}(hhh]h bullet_list)}(hhh](h list_item)}(hhh]j)}(hBendogenous_variable (str) -- Variable name of the output variable.h](hliteral_strong)}(hendogenous_variableh]hendogenous_variable}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]hliteral_emphasis)}(hstrh]hstr}(hj2hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj-ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj4 refspecificjjujhuh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubh%Variable name of the output variable.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(h~save_path (str, optional) -- File directory path where the Autogluon files will be saved. The default is 'twinstat_autogluon'.h](j)}(h save_pathh]h save_path}(hjkhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjgubh (}(hjghhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj}ubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjjKjjujhuh+jhjgubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjgubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjjKjjujhuh+jhjgubh)}(hjghhhNhNubh – }(hjghhhNhNubheFile directory path where the Autogluon files will be saved. The default is ‘twinstat_autogluon’.}(hjghhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjdubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(h\num_trials (int, optional) -- Number of hyperparameter tuning iterations. The default is 10.h](j)}(h num_trialsh]h num_trials}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjjKjjujhuh+jhjubj1)}(h, h]h, }(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetj jKjjujhuh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubh>Number of hyperparameter tuning iterations. The default is 10.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(hWsearch_strategy (str, optional) -- Hyperparameter tuning method. The default is 'auto'.h](j)}(hsearch_strategyh]hsearch_strategy}(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjQubh (}(hjQhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjgubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjljKjjujhuh+jhjQubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjQubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjjKjjujhuh+jhjQubh)}(hjQhhhNhNubh – }(hjQhhhNhNubh8Hyperparameter tuning method. The default is ‘auto’.}(hjQhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjNubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(hCeval_metric (str, optional) -- Metric used . The default is 'rmse'.h](j)}(h eval_metrich]h eval_metric}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjjKjjujhuh+jhjubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetj jKjjujhuh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubh(Metric used . The default is ‘rmse’.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(hhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj;ubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetj@jKjjujhuh+jhj%ubj1)}(h, h]h, }(hjVhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj%ubj)}(hhh]j1)}(hoptionalh]hoptional}(hjghhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjdubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetjijKjjujhuh+jhj%ubh)}(hj%hhhNhNubh – }(hj%hhhNhNubhAt inference time, autogluon can be quite slow when making predictions. This option will preload all of the models into RAM enabling significantly faster predictions, albeit at the cost of more RAM usage. The default is True.}(hj%hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj"ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+j hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhhhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftargetNone.jKjjujhuh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj}hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs&train() (core.AutoML.autogluon method)core.AutoML.autogluon.trainhNtauh+hWhj}hhhNhNubhx)}(hhh](h})}(h!autogluon.train(data, num_gpus=0)h](h)}(htrainh]htrain}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhzC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.trainhKubh)}(hdata, num_gpus=0h](h)}(hdatah]h)}(hdatah]hdata}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubah}(h!]h#]h%]h']h)]hhuh+hhjubh)}(h num_gpus=0h](h)}(hnum_gpush]hnum_gpus}(hj/hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj+ubj)}(h=h]h=}(hj=hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj+ubj)}(h0h]h0}(hjKhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj+ubeh}(h!]h#]h%]h']h)]hhuh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhjhKubeh}(h!]jah#](jojpeh%]h']h)]jt core.AutoMLjvhjwautogluon.trainjxjl autogluontrainjzautogluon.train()uh+h|hjhKhjhhubj|)}(hhh](j)}(hSTraining include Monte Carlo hyperparameter search for each model used in training.h]hSTraining include Monte Carlo hyperparameter search for each model used in training.}(hjuhhhNhNubah}(h!]h#]h%]h']h)]uh+jhzC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.trainhKhjrhhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hjh]hNone}(hjhhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainjreftypeobj refexplicitrefwarnjjljhjNoneuh+jhjhKhjhhubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hJdata (pandas.DataFrame) -- Data includes both the model inputs and outputsh](j)}(hdatah]hdata}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hpandas.DataFrameh]hpandas.DataFrame}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjjKjjljhuh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubh/Data includes both the model inputs and outputs}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh]j)}(h-num_gpus (int, optional) -- The default is 0.h](j)}(hnum_gpush]hnum_gpus}(hj<hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj8ubh (}(hj8hhhNhNubj)}(hhh]j1)}(hinth]hint}(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetjSjKjjljhuh+jhj8ubj1)}(h, h]h, }(hjihhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj8ubj)}(hhh]j1)}(hoptionalh]hoptional}(hjzhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjwubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetj|jKjjljhuh+jhj8ubh)}(hj8hhhNhNubh – }(hj8hhhNhNubhThe default is 0.}(hj8hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj5ubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+j hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hNoneh]j)}(hhh]hNone}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetNonejKjjljhuh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjrhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjhhhjhKubeh}(h!]h#](jmethodeh%]h']h)]domainjobjtypej desctypej noindex noindexentrynocontentsentryuh+hwhhhj}hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs(predict() (core.AutoML.autogluon method)core.AutoML.autogluon.predicthNtauh+hWhj}hhhNhNubhx)}(hhh](h})}(hautogluon.predict(data)h](h)}(hpredicth]hpredict}(hj& hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj" hhh|C:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.predicthKubh)}(hdatah]h)}(hdatah]h)}(hdatah]hdata}(hj= hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj9 ubah}(h!]h#]h%]h']h)]hhuh+hhj5 ubah}(h!]h#]h%]h']h)]hhuh+hhj" hhhj4 hKubeh}(h!]j ah#](jojpeh%]h']h)]jt core.AutoMLjvhjwautogluon.predictjxj] autogluonpredictjzautogluon.predict()uh+h|hj4 hKhj hhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(h Return typeh]h Return type}(hjl hhhNhNubah}(h!]h#]h%]h']h)]uh+jhji hj4 hKubj)}(hhh]j)}(hSeriesh]j)}(h&:py:class:`~pandas.core.series.Series`h]j)}(hj h]hSeries}(hj hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]refdocj refdomainj reftypeclass refexplicitrefwarnjj] jhjpandas.core.series.Seriesuh+jh|C:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.predicthKhj} hhubah}(h!]h#]h%]h']h)]uh+jhjz ubah}(h!]h#]h%]h']h)]uh+jhji ubeh}(h!]h#]h%]h']h)]uh+jhjf ubah}(h!]h#]h%]h']h)]uh+jhjc hhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj hhhj4 hKubeh}(h!]h#](pymethodeh%]h']h)]j j j j j j j j j uh+hwhhhj}hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs,load_models() (core.AutoML.autogluon method)!core.AutoML.autogluon.load_modelshNtauh+hWhj}hhhNhNubhx)}(hhh](h})}(hautogluon.load_models()h](h)}(h load_modelsh]h load_models}(hj hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.load_modelshKubh)}(h()h]h}(h!]h#]h%]h']h)]hhuh+hhj hhhj hKubeh}(h!]j ah#](jojpeh%]h']h)]jt core.AutoMLjvhjwautogluon.load_modelsjxj autogluon load_modelsjzautogluon.load_models()uh+h|hj hKhj hhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hj hKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hj" h]hNone}(hj$ hhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]refdocj refdomainj. reftypeobj refexplicitrefwarnjj jhjNoneuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.load_modelshKhj hhubah}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj hhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj hhhj hKubeh}(h!]h#](pymethodeh%]h']h)]j jb j jc j jc j j j uh+hwhhhj}hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs?determine_variable_sensitivity() (core.AutoML.autogluon method)4core.AutoML.autogluon.determine_variable_sensitivityhNtauh+hWhj}hhhNhNubhx)}(hhh](h})}(h*autogluon.determine_variable_sensitivity()h](h)}(hdetermine_variable_sensitivityh]hdetermine_variable_sensitivity}(hj| hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjx hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.determine_variable_sensitivityhKubh)}(h()h]h}(h!]h#]h%]h']h)]hhuh+hhjx hhhj hKubeh}(h!]js ah#](jojpeh%]h']h)]jt core.AutoMLjvhjw(autogluon.determine_variable_sensitivityjxj autogluondetermine_variable_sensitivityjz*autogluon.determine_variable_sensitivity()uh+h|hj hKhju hhubj|)}(hhh](j)}(hRPerforms permutation importance sampling to determine model sensitivity to inputs.h]hRPerforms permutation importance sampling to determine model sensitivity to inputs.}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\AutoML.py:docstring of core.AutoML.autogluon.determine_variable_sensitivityhKhj hhubj)}(h2A matplotlib figure is generated with the results.h]h2A matplotlib figure is generated with the results.}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hKhj hhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hj hKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hj h]hNone}(hj hhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]refdocj refdomainj reftypeobj refexplicitrefwarnjj jhjNoneuh+jhj hKhj hhubah}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hj hKubj)}(hhh]j)}(hNoneh]j)}(hhh]hNone}(hj& hhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetNonejKjj jhuh+jhj" ubah}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhj hhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hju hhhj hKubeh}(h!]h#](j4 methodeh%]h']h)]j j4 j jZ j jZ j j j uh+hwhhhj}hNhNubeh}(h!]h#]h%]h']h)]uh+j{hhyhhhhhKubeh}(h!]h#](jGclasseh%]h']h)]j jGj jg j jg j j j uh+hwhhhhFhNhNubeh}(h!](hfcore-automl-moduleeh#]h%]core.automl moduleah']h)]uh+h hh hhhh,hKubh )}(hhh](h)}(hcore.LinearRegression moduleh]hcore.LinearRegression module}(hjv hhhNhNubah}(h!]h#]h%]h']h)]uh+hhjs hhhh,hKubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hdmodule; core.LinearRegressionmodule-core.LinearRegressionhNtauh+hWhjs hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs,LinearModel (class in core.LinearRegression)!core.LinearRegression.LinearModelhNtauh+hWhjs hhhNhNubhx)}(hhh](h})}(hLinearModel(backend='torch')h](h)}(h2[<#text: 'class'>, >]h](hclass}(hj hhhNhNubh)}(h h]h }(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj ubeh}(h!]h#]h%]h']h)]hhuh+hhj hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModelhKubh)}(hcore.LinearRegression.h]hcore.LinearRegression.}(hj hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj hhhj hKubh)}(h LinearModelh]h LinearModel}(hj hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj hhhj hKubh)}(hbackend='torch'h]h)}(hbackend='torch'h](h)}(hbackendh]hbackend}(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj ubj)}(h=h]h=}(hj hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj ubj)}(h'torch'h]h'torch'}(hj hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubah}(h!]h#]h%]h']h)]hhuh+hhj hhhj hKubeh}(h!]j ah#](jojpeh%]h']h)]jtcore.LinearRegressionjvhjwj jxj% j jzj uh+h|hj hKhj hhubj|)}(hhh](j)}(hBases: :py:class:`object`h](hBases: }(hj* hhhNhNubj)}(h:py:class:`object`h]j)}(hj4 h]hobject}(hj6 hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj2 ubah}(h!]h#]h%]h']h)]refdocj refdomainj@ reftypeclass refexplicitrefwarnjj% jj jobjectuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModelhKhj* ubeh}(h!]h#]h%]h']h)]uh+jhjR hKhj' hhubj)}(hBase linear regression object.h]hBase linear regression object.}(hjY hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModelhKhj' hhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hjn hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjk hj hKubj)}(hhh]j)}(hbackend (str, optional) -- The backend solver can be "numpy" or "torch". Pytorch provides GPU functionality if needed for large problems. The default is 'torch'.h](j)}(hbackendh]hbackend}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj ubh (}(hj hhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj jKjj% jj uh+jhj ubj1)}(h, h]h, }(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj ubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetj jKjj% jj uh+jhj ubh)}(hj hhhNhNubh – }(hj hhhNhNubhThe backend solver can be “numpy” or “torch”. Pytorch provides GPU functionality if needed for large problems. The default is ‘torch’.}(hj hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj| ubah}(h!]h#]h%]h']h)]uh+jhjk ubeh}(h!]h#]h%]h']h)]uh+jhjh ubj)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hj hKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hj hhhNhNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetNone.jKjj% jj uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhjh ubeh}(h!]h#]h%]h']h)]uh+jhj' hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs0fit() (core.LinearRegression.LinearModel method)%core.LinearRegression.LinearModel.fithNtauh+hWhj' hhhNhNubhx)}(hhh](h})}(h*LinearModel.fit(X, y, beta_relevance=None)h](h)}(hfith]hfit}(hjO hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjK hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModel.fithKubh)}(hX, y, beta_relevance=Noneh](h)}(hXh]h)}(hXh]hX}(hjf hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjb ubah}(h!]h#]h%]h']h)]hhuh+hhj^ ubh)}(hyh]h)}(hyh]hy}(hj~ hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjz ubah}(h!]h#]h%]h']h)]hhuh+hhj^ ubh)}(hbeta_relevance=Noneh](h)}(hbeta_relevanceh]hbeta_relevance}(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj ubj)}(h=h]h=}(hj hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj ubj)}(hNoneh]hNone}(hj hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj ubeh}(h!]h#]h%]h']h)]hhuh+hhj^ ubeh}(h!]h#]h%]h']h)]hhuh+hhjK hhhj] hKubeh}(h!]jF ah#](jojpeh%]h']h)]jtcore.LinearRegressionjvj jwLinearModel.fitjxj LinearModelfitjzLinearModel.fit()uh+h|hj] hKhjH hhubj|)}(hhh](j)}(h$Fit a linear regression to the data.h]h$Fit a linear regression to the data.}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModel.fithKhj hhubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs1mse (core.LinearRegression.LinearModel attribute)%core.LinearRegression.LinearModel.msehNtauh+hWhj hhhNhNubhx)}(hhh](h})}(hmseh]h)}(hj h]hmse}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj hhhj hKubah}(h!]j ah#](jojpeh%]h']h)]jtj jvj jwLinearModel.msejxj LinearModelmsejzjuh+h|hj hKhj hhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(htypeh]hType}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj hKubj)}(hmean squared errorh]j)}(hj0h]j)}(hhh]hmean squared error}(hj5hhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetmean squared errorjKjj jj uh+jhj2hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hKhj.ubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj hKhjhhubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj hhhj hKubeh}(h!]h#](jC attributeeh%]h']h)]j jCj jij jij j j uh+hwhhhj hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs3betas (core.LinearRegression.LinearModel attribute)'core.LinearRegression.LinearModel.betashNtauh+hWhj hhhNhNubhx)}(hhh](h})}(hbetash]h)}(hjh]hbetas}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj~hhhj hK ubah}(h!]jyah#](jojpeh%]h']h)]jtj jvj jwLinearModel.betasjxj LinearModelbetasjzjuh+h|hj hK hj{hhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(htypeh]hType}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj hKubj)}(hregression coefficientsh]j)}(hjh]j)}(hhh]hregression coefficients}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetregression coefficientsjKjj jj uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hK hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj hK hjhhubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj{hhhj hK ubeh}(h!]h#](j attributeeh%]h']h)]j jj jj jj j j uh+hwhhhj hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs6betas_se (core.LinearRegression.LinearModel attribute)*core.LinearRegression.LinearModel.betas_sehNtauh+hWhj hhhNhNubhx)}(hhh](h})}(hbetas_seh]h)}(hjh]hbetas_se}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhj hKubah}(h!]jah#](jojpeh%]h']h)]jtj jvj jwLinearModel.betas_sejxj LinearModelbetas_sejzjuh+h|hj hKhjhhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(htypeh]hType}(hj$hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj!hj hKubj)}(hstandard error of the betash]j)}(hj4h](j)}(hhh]hstandard error}(hj9hhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetstandard errorjKjj jj uh+jhj6hhhNhNubh of }(hj6hhhNhNubj)}(hhh]h the betas}(hjPhhhNhNubah}(h!]h#]h%]h']h)] refdomainjG refexplicitreftypejv reftarget the betasjKjj jj uh+jhj6hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj hKhj2ubah}(h!]h#]h%]h']h)]uh+jhj!ubeh}(h!]h#]h%]h']h)]uh+jhj hKhjhhubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hjhhhj hKubeh}(h!]h#](jG attributeeh%]h']h)]j jGj jj jj j j uh+hwhhhj hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs:beta_pvalues (core.LinearRegression.LinearModel attribute).core.LinearRegression.LinearModel.beta_pvalueshNtauh+hWhj hhhNhNubhx)}(hhh](h})}(h beta_pvaluesh]h)}(hjh]h beta_pvalues}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhj hKubah}(h!]jah#](jojpeh%]h']h)]jtj jvj jwLinearModel.beta_pvaluesjxj LinearModel beta_pvaluesjzjuh+h|hj hKhjhhubj|)}(hhh]j)}(hhh]j)}(hhh](j)}(htypeh]hType}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj hKubj)}(h pvalue for significance of betash]j)}(hjh](j)}(hhh]hpvalue for significance}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetpvalue for significancejKjj jj uh+jhjhhhNhNubh of }(hjhhhNhNubj)}(hhh]hbetas}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetbetasjKjj jj uh+jhjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj hKhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj hKhjhhubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hjhhhj hKubeh}(h!]h#](j attributeeh%]h']h)]j jj jj jj j j uh+hwhhhj hNhNubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj"hj] hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hX (np.array) -- Input data.h](j)}(hXh]hX}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj<ubh (}(hj<hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjRubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjWjKjj jj uh+jhj<ubh)}(hj<hhhNhNubh – }(hj<hhhNhNubh Input data.}(hj<hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj9ubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hy (np.array) -- Output datah](j)}(hyh]hy}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjj refexplicitreftypejv reftargetjjKjj jj uh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubh Output data}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hbeta_relevance (list[float], optional) -- If set, the coefficient pvalues will be relative to the beta_relevance value.E.g. if t_crit = (beta[0] - beta_relevance[0])/seThe default is None.h](j)}(hbeta_relevanceh]hbeta_relevance}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hlisth]hlist}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjj refexplicitreftypejv reftargetjjKjj jj uh+jhjubj1)}(h[h]h[}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hfloath]hfloat}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjj refexplicitreftypejv reftargetjjKjj jj uh+jhjubj1)}(h]h]h]}(hj/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj1)}(h, h]h, }(hj=hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hoptionalh]hoptional}(hjNhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjKubah}(h!]h#]h%]h']h)] refdomainjj refexplicitreftypejv reftargetjPjKjj jj uh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubj)}(hMIf set, the coefficient pvalues will be relative to the beta_relevance value.h]hMIf set, the coefficient pvalues will be relative to the beta_relevance value.}(hjnhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hKhjhhubj)}(h1E.g. if t_crit = (beta[0] - beta_relevance[0])/seh]h1E.g. if t_crit = (beta[0] - beta_relevance[0])/se}(hj|hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hK"hjhhubj)}(hThe default is None.h]hThe default is None.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hK$hjhhubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj6ubeh}(h!]h#]h%]h']h)]uh+j hj3ubah}(h!]h#]h%]h']h)]uh+jhj"ubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj] hKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainjj refexplicitreftypejv reftargetNone.jKjj jj uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj hhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjH hhhj] hKubeh}(h!]h#](jjmethodeh%]h']h)]j jjj jj jj j j uh+hwhhhj' hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs4predict() (core.LinearRegression.LinearModel method))core.LinearRegression.LinearModel.predicthNtauh+hWhj' hhhNhNubhx)}(hhh](h})}(hMLinearModel.predict(Xnew, return_uncertainty=False, uncertainty='confidence')h](h)}(hpredicth]hpredict}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModel.predicthKubh)}(h8Xnew, return_uncertainty=False, uncertainty='confidence'h](h)}(hXnewh]h)}(hXnewh]hXnew}(hj1hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj-ubah}(h!]h#]h%]h']h)]hhuh+hhj)ubh)}(hreturn_uncertainty=Falseh](h)}(hreturn_uncertaintyh]hreturn_uncertainty}(hjIhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjEubj)}(h=h]h=}(hjWhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjEubj)}(hFalseh]hFalse}(hjehhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjEubeh}(h!]h#]h%]h']h)]hhuh+hhj)ubh)}(huncertainty='confidence'h](h)}(h uncertaintyh]h uncertainty}(hj~hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjzubj)}(h=h]h=}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjzubj)}(h 'confidence'h]h 'confidence'}(hjhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjzubeh}(h!]h#]h%]h']h)]hhuh+hhj)ubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhj(hKubeh}(h!]jah#](jojpeh%]h']h)]jtcore.LinearRegressionjvj jwLinearModel.predictjxj LinearModelpredictjzLinearModel.predict()uh+h|hj(hKhjhhubj|)}(hhh]j)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj(hKubj)}(hhh]j)}(harrayh]j)}(h:py:class:`~numpy.array`h]j)}(hjh]harray}(hjhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainjreftypeclass refexplicitrefwarnjjjj j numpy.arrayuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.LinearModel.predicthKhjhhubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhj(hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hXnew (np.array) -- h](j)}(hXnewh]hXnew}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj,ubh (}(hj,hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjEhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjBubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjGjKjjjj uh+jhj,ubh)}(hj,hhhNhNubh – }(hj,hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj)ubah}(h!]h#]h%]h']h)]uh+jhj&ubj)}(hhh]j)}(hreturn_uncertainty (bool, optional) -- If true, return both the prediction and the uncertainty of the prediction. The default is False.h](j)}(hreturn_uncertaintyh]hreturn_uncertainty}(hjyhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjuubh (}(hjuhhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjZ refexplicitreftypejv reftargetjjKjjjj uh+jhjuubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjuubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjZ refexplicitreftypejv reftargetjjKjjjj uh+jhjuubh)}(hjuhhhNhNubh – }(hjuhhhNhNubh`If true, return both the prediction and the uncertainty of the prediction. The default is False.}(hjuhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjrubah}(h!]h#]h%]h']h)]uh+jhj&ubj)}(hhh]j)}(hjuncertainty (str, optional) -- Can be "confidence" or "prediction" intervals. The default is 'confidence'.h](j)}(h uncertaintyh]h uncertainty}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjZ refexplicitreftypejv reftargetjjKjjjj uh+jhjubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hoptionalh]hoptional}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj)ubah}(h!]h#]h%]h']h)] refdomainjZ refexplicitreftypejv reftargetj.jKjjjj uh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubhWCan be “confidence” or “prediction” intervals. The default is ‘confidence’.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj&ubeh}(h!]h#]h%]h']h)]uh+j hj#ubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(hReturnsh]hReturns}(hjqhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjnhj(hKubj)}(hhh]j)}(hlprediction (np.array) If return_uncertainty is True also return the SE of the prediction. sigma (np.array)h]j )}(hhh](j)}(h**prediction** (*np.array*)h]j)}(hjh](h strong)}(h**prediction**h]h prediction}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubh emphasis)}(h *np.array*h]hnp.array}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh)}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjhK hjubah}(h!]h#]h%]h']h)]uh+jhjubj)}(hE*If return_uncertainty is True also return the SE of the prediction.*h]j)}(hjh]j)}(hjh]hCIf return_uncertainty is True also return the SE of the prediction.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjhK hjubah}(h!]h#]h%]h']h)]uh+jhjubj)}(h**sigma** (*np.array*)h]j)}(hjh](j)}(h **sigma**h]hsigma}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(h *np.array*h]hnp.array}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh)}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjhKhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]bullet*uh+j hjhK hjhhubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjnubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hjhhhj(hKubeh}(h!]h#](jZmethodeh%]h']h)]j jZj jDj jDj j j uh+hwhhhj' hNhNubeh}(h!]h#]h%]h']h)]uh+j{hj hhhj hKubeh}(h!]h#](j classeh%]h']h)]j j j jQj jQj j j uh+hwhhhjs hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs+Polynomial (class in core.LinearRegression) core.LinearRegression.PolynomialhNtauh+hWhjs hhhNhNubhx)}(hhh](h})}(h Polynomial(poly_order, **kwargs)h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjjhhhNhNubh)}(h h]h }(hjrhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjjubeh}(h!]h#]h%]h']h)]hhuh+hhjfhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PolynomialhKubh)}(hcore.LinearRegression.h]hcore.LinearRegression.}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjfhhhjhKubh)}(h Polynomialh]h Polynomial}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjfhhhjhKubh)}(hpoly_order, **kwargsh](h)}(h poly_orderh]h)}(h poly_orderh]h poly_order}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubah}(h!]h#]h%]h']h)]hhuh+hhjubh)}(h**kwargsh](j)}(h**h]h**}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubh)}(hkwargsh]hkwargs}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjfhhhjhKubeh}(h!]jaah#](jojpeh%]h']h)]jtcore.LinearRegressionjvhjwjjxjjjzjuh+h|hjhKhjchhubj|)}(hhh](j)}(h5Bases: :py:class:`~core.LinearRegression.LinearModel`h](hBases: }(hjhhhNhNubj)}(h.:py:class:`~core.LinearRegression.LinearModel`h]j)}(hjh]h LinearModel}(hjhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainj reftypeclass refexplicitrefwarnjjjjj!core.LinearRegression.LinearModeluh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PolynomialhKhjubeh}(h!]h#]h%]h']h)]uh+jhjhKhjhhubj)}(hNSets the parametric function form of the linear regression to be a polynomial.h]hNSets the parametric function form of the linear regression to be a polynomial.}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PolynomialhKhjhhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hj:hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj7hjhKubj)}(hhh]j)}(h%poly_order (int) -- Polynomial order.h](j)}(h poly_orderh]h poly_order}(hjOhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjKubh (}(hjKhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjdhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjaubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjfjKjjjjuh+jhjKubh)}(hjKhhhNhNubh – }(hjKhhhNhNubhPolynomial order.}(hjKhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjHubah}(h!]h#]h%]h']h)]uh+jhj7ubeh}(h!]h#]h%]h']h)]uh+jhj4ubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainjy refexplicitreftypejv reftargetNone.jKjjjjuh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhj4ubeh}(h!]h#]h%]h']h)]uh+jhjhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjchhhjhKubeh}(h!]h#](jyclasseh%]h']h)]j jyj jj jj j j uh+hwhhhjs hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs4PiecewisePolynomial (class in core.LinearRegression))core.LinearRegression.PiecewisePolynomialhNtauh+hWhjs hhhNhNubhx)}(hhh](h})}(h4PiecewisePolynomial(poly_order, n_knots=1, **kwargs)h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjhhhNhNubh)}(h h]h }(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomialhKubh)}(hcore.LinearRegression.h]hcore.LinearRegression.}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(hPiecewisePolynomialh]hPiecewisePolynomial}(hj*hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(hpoly_order, n_knots=1, **kwargsh](h)}(h poly_orderh]h)}(h poly_orderh]h poly_order}(hj@hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj<ubah}(h!]h#]h%]h']h)]hhuh+hhj8ubh)}(h n_knots=1h](h)}(hn_knotsh]hn_knots}(hjXhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjTubj)}(h=h]h=}(hjfhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjTubj)}(h1h]h1}(hjthhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjTubeh}(h!]h#]h%]h']h)]hhuh+hhj8ubh)}(h**kwargsh](j)}(h**h]h**}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubh)}(hkwargsh]hkwargs}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhj8ubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhjhKubeh}(h!]jah#](jojpeh%]h']h)]jtcore.LinearRegressionjvhjwj,jxjj,jzj,uh+h|hjhKhjhhubj|)}(hhh](j)}(h5Bases: :py:class:`~core.LinearRegression.LinearModel`h](hBases: }(hjhhhNhNubj)}(h.:py:class:`~core.LinearRegression.LinearModel`h]j)}(hjh]h LinearModel}(hjhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainjreftypeclass refexplicitrefwarnjjjj,j!core.LinearRegression.LinearModeluh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomialhKhjubeh}(h!]h#]h%]h']h)]uh+jhjhKhjhhubj)}(hSets the parametric function form of the linear regression to be a polynomial. However, add the ability to create piecewise knot points that discontinours change slope. L0 continuity and not L1 continuity.h]hSets the parametric function form of the linear regression to be a polynomial. However, add the ability to create piecewise knot points that discontinours change slope. L0 continuity and not L1 continuity.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomialhKhjhhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h%poly_order (int) -- Polynomial order.h](j)}(h poly_orderh]h poly_order}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hinth]hint}(hj4hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj1ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj6jKjjjj,uh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubhPolynomial order.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh]j)}(h,n_knots (int, optional) -- The default is 1.h](j)}(hn_knotsh]hn_knots}(hjlhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhubh (}(hjhhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj~ubah}(h!]h#]h%]h']h)] refdomainjI refexplicitreftypejv reftargetjjKjjjj,uh+jhjhubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjhubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainjI refexplicitreftypejv reftargetjjKjjjj,uh+jhjhubh)}(hjhhhhNhNubh – }(hjhhhhNhNubhThe default is 1.}(hjhhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjeubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+j hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainjI refexplicitreftypejv reftargetNone.jKjjjj,uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs>fit_knots() (core.LinearRegression.PiecewisePolynomial method)3core.LinearRegression.PiecewisePolynomial.fit_knotshNtauh+hWhjhhhNhNubhx)}(hhh](h})}(h#PiecewisePolynomial.fit_knots(X, y)h](h)}(h fit_knotsh]h fit_knots}(hjChhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj?hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomial.fit_knotshKubh)}(hX, yh](h)}(hXh]h)}(hXh]hX}(hjZhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjVubah}(h!]h#]h%]h']h)]hhuh+hhjRubh)}(hyh]h)}(hyh]hy}(hjrhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjnubah}(h!]h#]h%]h']h)]hhuh+hhjRubeh}(h!]h#]h%]h']h)]hhuh+hhj?hhhjQhKubeh}(h!]j:ah#](jojpeh%]h']h)]jtcore.LinearRegressionjvj,jwPiecewisePolynomial.fit_knotsjxjPiecewisePolynomial fit_knotsjzPiecewisePolynomial.fit_knots()uh+h|hjQhKhj<hhubj|)}(hhh](j)}(h(Find the optimal location for the knots.h]h(Find the optimal location for the knots.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomial.fit_knotshKhjhhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjQhKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hjh]hNone}(hjhhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainjreftypeobj refexplicitrefwarnjjjj,jNoneuh+jhjhKhjhhubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjQhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hX (np.array) -- h](j)}(hjBh]hX}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj)hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj&ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj+jKjjjj,uh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhj ubj)}(hhh]j)}(hy (np.array) -- h](j)}(hjh]hy}(hj]hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjYubh (}(hjYhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjqhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjnubah}(h!]h#]h%]h']h)] refdomainj> refexplicitreftypejv reftargetjsjKjjjj,uh+jhjYubh)}(hjYhhhNhNubh – }(hjYhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjVubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+j hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjQhKubj)}(hhh]j)}(hNoneh]j)}(hhh]hNone}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainj> refexplicitreftypejv reftargetNonejKjjjj,uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj<hhhjQhKubeh}(h!]h#](j>methodeh%]h']h)]j j>j jj jj j j uh+hwhhhjhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsIcheck_for_duplicates() (core.LinearRegression.PiecewisePolynomial method)>core.LinearRegression.PiecewisePolynomial.check_for_duplicateshNtauh+hWhjhhhNhNubhx)}(hhh](h})}(h1PiecewisePolynomial.check_for_duplicates(thelist)h](h)}(hcheck_for_duplicatesh]hcheck_for_duplicates}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.PiecewisePolynomial.check_for_duplicateshKubh)}(hthelisth]h)}(hthelisth]h)}(hthelisth]hthelist}(hj*hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj&ubah}(h!]h#]h%]h']h)]hhuh+hhj"ubah}(h!]h#]h%]h']h)]hhuh+hhjhhhj!hKubeh}(h!]j ah#](jojpeh%]h']h)]jtcore.LinearRegressionjvj,jw(PiecewisePolynomial.check_for_duplicatesjxjJPiecewisePolynomialcheck_for_duplicatesjz*PiecewisePolynomial.check_for_duplicates()uh+h|hj!hKhj hhubj|)}(hhh]h}(h!]h#]h%]h']h)]uh+j{hj hhhj!hKubeh}(h!]h#](pymethodeh%]h']h)]j j\j j]j j]j j j uh+hwhhhjhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjhhhjhKubeh}(h!]h#](jIclasseh%]h']h)]j jIj jjj jjj j j uh+hwhhhjs hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs,Exponential (class in core.LinearRegression)!core.LinearRegression.ExponentialhNtauh+hWhjs hhhNhNubhx)}(hhh](h})}(hExponential(**kwargs)h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjhhhNhNubh)}(h h]h }(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.ExponentialhKubh)}(hcore.LinearRegression.h]hcore.LinearRegression.}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(h Exponentialh]h Exponential}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(h**kwargsh]h)}(h**kwargsh](j)}(h**h]h**}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubh)}(hkwargsh]hkwargs}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjubah}(h!]h#]h%]h']h)]hhuh+hhjhhhjhKubeh}(h!]jzah#](jojpeh%]h']h)]jtcore.LinearRegressionjvhjwjjxjjjzjuh+h|hjhKhj|hhubj|)}(hhh](j)}(h5Bases: :py:class:`~core.LinearRegression.LinearModel`h](hBases: }(hjhhhNhNubj)}(h.:py:class:`~core.LinearRegression.LinearModel`h]j)}(hjh]h LinearModel}(hjhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]refdocj refdomainj reftypeclass refexplicitrefwarnjjjjj!core.LinearRegression.LinearModeluh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.ExponentialhKhjubeh}(h!]h#]h%]h']h)]uh+jhjhKhjhhubj)}(hMSets the parametric function form of the linear regression to be exponential.h]hMSets the parametric function form of the linear regression to be exponential.}(hj&hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\LinearRegression.py:docstring of core.LinearRegression.ExponentialhKhjhhubj)}(hhh]j)}(hhh](j)}(h Return typeh]h Return type}(hj;hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj8hjhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjPhhhNhNubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetNone.jKjjjjuh+jhjLubah}(h!]h#]h%]h']h)]uh+jhjIubah}(h!]h#]h%]h']h)]uh+jhj8ubeh}(h!]h#]h%]h']h)]uh+jhj5ubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj|hhhjhKubeh}(h!]h#](j^classeh%]h']h)]j j^j jj jj j j uh+hwhhhjs hNhNubeh}(h!](j core-linearregression-moduleeh#]h%]core.linearregression moduleah']h)]uh+h hh hhhh,hKubh )}(hhh](h)}(hcore.knn\_models moduleh]hcore.knn_models module}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+hhjhhhh,hKubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hdmodule; core.knn_modelsmodule-core.knn_modelshNtauh+hWhjhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs/QuantileKNNRegressor (class in core.knn_models)$core.knn_models.QuantileKNNRegressorhNtauh+hWhjhhhNhNubhx)}(hhh](h})}(h'QuantileKNNRegressor(tau=0.5, **kwargs)h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjhhhNhNubh)}(h h]h }(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.QuantileKNNRegressorhKubh)}(hcore.knn_models.h]hcore.knn_models.}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(hQuantileKNNRegressorh]hQuantileKNNRegressor}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhjhKubh)}(htau=0.5, **kwargsh](h)}(htau=0.5h](h)}(htauh]htau}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubj)}(h=h]h=}(hjhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjubj)}(h0.5h]h0.5}(hj!hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjubeh}(h!]h#]h%]h']h)]hhuh+hhjubh)}(h**kwargsh](j)}(h**h]h**}(hj:hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj6ubh)}(hkwargsh]hkwargs}(hjHhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj6ubeh}(h!]h#]h%]h']h)]hhuh+hhjubeh}(h!]h#]h%]h']h)]hhuh+hhjhhhjhKubeh}(h!]jah#](jojpeh%]h']h)]jtcore.knn_modelsjvhjwjjxjhjjzjuh+h|hjhKhjhhubj|)}(hhh](j)}(hEBases: 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supported.}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhKhjjhhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h_tau (float, optional) -- The percentile that is used when fitting the data. The default is 0.5.h](j)}(htauh]htau}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjubh (}(hjhhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjjKjjhjjuh+jhjubj1)}(h, h]h, }(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubj)}(hhh]j1)}(hoptionalh]hoptional}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetjjKjjhjjuh+jhjubh)}(hjhhhNhNubh – }(hjhhhNhNubhFThe percentile that is used when fitting the data. The default is 0.5.}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh]j)}(h-**kwargs -- Send any scikit specific options.h](j)}(h**kwargsh]h**kwargs}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjLubh – }(hjLhhhNhNubh!Send any scikit specific options.}(hjLhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjIubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+j hjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjhhhNhNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetNone.jKjjhjjuh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjjhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs7predict() (core.knn_models.QuantileKNNRegressor method),core.knn_models.QuantileKNNRegressor.predicthNtauh+hWhjjhhhNhNubhx)}(hhh](h})}(hQuantileKNNRegressor.predict(X)h](h)}(hpredicth]hpredict}(hjhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.QuantileKNNRegressor.predicthKubh)}(hjBh]h)}(hXh]h)}(hXh]hX}(hjhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjubah}(h!]h#]h%]h']h)]hhuh+hhjubah}(h!]h#]h%]h']h)]hhuh+hhjhhhjhKubeh}(h!]jah#](jojpeh%]h']h)]jtcore.knn_modelsjvjjwQuantileKNNRegressor.predictjxjQuantileKNNRegressorpredictjzQuantileKNNRegressor.predict()uh+h|hjhKhjhhubj|)}(hhh]j)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(harrayh]j)}(h:py:class:`~numpy.array`h]j)}(hj7h]harray}(hj9hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj5ubah}(h!]h#]h%]h']h)]refdocj refdomainjCreftypeclass refexplicitrefwarnjjjjj numpy.arrayuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.QuantileKNNRegressor.predicthKhj1hhubah}(h!]h#]h%]h']h)]uh+jhj.ubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Parametersh]h Parameters}(hjkhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhhjhKubj)}(hhh]j)}(h%X (np.array) -- (n data x n features)h](j)}(hjBh]hX}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj|ubh (}(hj|hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjjKjjjjuh+jhj|ubh)}(hj|hhhNhNubh – }(hj|hhhNhNubh(n data x n features)}(hj|hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjyubah}(h!]h#]h%]h']h)]uh+jhjhubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(hReturnsh]hReturns}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhjhKubj)}(hhh]j)}(hy_pred -- (n data x 1)h](j)}(h **y_pred**h]hy_pred}(hjhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhhhNhNubh – (n data x 1)}(hjhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjubah}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjubj)}(hhh](j)}(h Return typeh]h Return type}(hj hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj hjhKubj)}(hhh]j)}(hnp.arrayh]j)}(hhh]hnp.array}(hj hhhNhNubah}(h!]h#]h%]h']h)] refdomainj refexplicitreftypejv reftargetnp.arrayjKjjjjuh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubah}(h!]h#]h%]h']h)]uh+jhj ubeh}(h!]h#]h%]h']h)]uh+jhjubeh}(h!]h#]h%]h']h)]uh+jhjhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hjhhhjhKubeh}(h!]h#](jmethodeh%]h']h)]j jj jR j jR j j j uh+hwhhhjjhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjhhhjhKubeh}(h!]h#](jclasseh%]h']h)]j jj j_ j j_ j j j uh+hwhhhjhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs-OutlierKNNDetector (class in core.knn_models)"core.knn_models.OutlierKNNDetectorhNtauh+hWhjhhhNhNubhx)}(hhh](h})}(hOutlierKNNDetector(outlier_distance_threshold=None, outlier_percent_threshold=None, endog_idx=None, removal_iterations=10, **kwargs)h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjx hhhNhNubh)}(h h]h }(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjx ubeh}(h!]h#]h%]h']h)]hhuh+hhjt hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.OutlierKNNDetectorhKubh)}(hcore.knn_models.h]hcore.knn_models.}(hj hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjt hhhj hKubh)}(hOutlierKNNDetectorh]hOutlierKNNDetector}(hj hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjt hhhj hKubh)}(hpoutlier_distance_threshold=None, outlier_percent_threshold=None, endog_idx=None, removal_iterations=10, **kwargsh](h)}(houtlier_distance_threshold=Noneh](h)}(houtlier_distance_thresholdh]houtlier_distance_threshold}(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj ubj)}(h=h]h=}(hj hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj ubj)}(hNoneh]hNone}(hj hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubh)}(houtlier_percent_threshold=Noneh](h)}(houtlier_percent_thresholdh]houtlier_percent_threshold}(hj hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj ubj)}(h=h]h=}(hj hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj ubj)}(hNoneh]hNone}(hj !hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubh)}(hendog_idx=Noneh](h)}(h endog_idxh]h endog_idx}(hj#!hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj!ubj)}(h=h]h=}(hj1!hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj!ubj)}(hNoneh]hNone}(hj?!hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj!ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubh)}(hremoval_iterations=10h](h)}(hremoval_iterationsh]hremoval_iterations}(hjX!hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjT!ubj)}(h=h]h=}(hjf!hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjT!ubj)}(h10h]h10}(hjt!hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjT!ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubh)}(h**kwargsh](j)}(h**h]h**}(hj!hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj!ubh)}(hkwargsh]hkwargs}(hj!hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj!ubeh}(h!]h#]h%]h']h)]hhuh+hhj ubeh}(h!]h#]h%]h']h)]hhuh+hhjt hhhj hKubeh}(h!]jo ah#](jojpeh%]h']h)]jtcore.knn_modelsjvhjwj jxj!j jzj uh+h|hj hKhjq hhubj|)}(hhh](j)}(hDBases: :py:class:`~sklearn.neighbors._unsupervised.NearestNeighbors`h](hBases: }(hj!hhhNhNubj)}(h=:py:class:`~sklearn.neighbors._unsupervised.NearestNeighbors`h]j)}(hj!h]hNearestNeighbors}(hj!hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj!ubah}(h!]h#]h%]h']h)]refdocj refdomainj!reftypeclass refexplicitrefwarnjj!jj j0sklearn.neighbors._unsupervised.NearestNeighborsuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.OutlierKNNDetectorhKhj!ubeh}(h!]h#]h%]h']h)]uh+jhj!hKhj!hhubj)}(h9Automatically find outliers and remove from the data set.h]h9Automatically find outliers and remove from the data set.}(hj!hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.OutlierKNNDetectorhKhj!hhubj)}(hXMethod #1 ---- If outlier_percent_threshold is set to a value between 0 and 1, the endog_idx is checked. If None, a KDTree is generated to determine the distance between all points. The outliers are flagged as the points above and below the outlier_percent_threshold threshold.h]hXMethod #1 —- If outlier_percent_threshold is set to a value between 0 and 1, the endog_idx is checked. If None, a KDTree is generated to determine the distance between all points. The outliers are flagged as the points above and below the outlier_percent_threshold threshold.}(hj!hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj!hKhj!hhubj)}(hIf endog_idx is not None, then a QuantileKNNRegressor is used to relate all of the data to the endog_idx variable. All data points above and below the regressed outlier_percent_threshold of QuantileKNNRegressor will be removed from the data set.h]hIf endog_idx is not None, then a QuantileKNNRegressor is used to relate all of the data to the endog_idx variable. All data points above and below the regressed outlier_percent_threshold of QuantileKNNRegressor will be removed from the data set.}(hj "hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj!hK hj!hhubj)}(hMethod #2 ---- If outlier_distance_threshold is provided a QuantileKNNRegressor will be used to regress the endog_idx on to the remaining data. The residuals of prediction are calculated, i.e. r = y - yhat.h]hMethod #2 —- If outlier_distance_threshold is provided a QuantileKNNRegressor will be used to regress the endog_idx on to the remaining data. The residuals of prediction are calculated, i.e. r = y - yhat.}(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj!hKhj!hhubj)}(hAll data points exhibiting residuals larger than outlier_distance_threshold will be flagged as outliers (i.e. they are not following the behavior of surrounding data points.) This process is carried out removal_iterations number of times.h]hAll data points exhibiting residuals larger than outlier_distance_threshold will be flagged as outliers (i.e. they are not following the behavior of surrounding data points.) This process is carried out removal_iterations number of times.}(hj("hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj!hKhj!hhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hj<"hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj9"hj hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hDoutlier_distance_threshold (float, optional) -- The default is None.h](j)}(houtlier_distance_thresholdh]houtlier_distance_threshold}(hjW"hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjS"ubh (}(hjS"hhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hjl"hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hji"ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjn"jKjj!jj uh+jhjS"ubj1)}(h, h]h, }(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjS"ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj"ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj"jKjj!jj uh+jhjS"ubh)}(hjS"hhhNhNubh – }(hjS"hhhNhNubhThe default is None.}(hjS"hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjP"ubah}(h!]h#]h%]h']h)]uh+jhjM"ubj)}(hhh]j)}(hCoutlier_percent_threshold (float, optional) -- The default is None.h](j)}(houtlier_percent_thresholdh]houtlier_percent_threshold}(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj"ubh (}(hj"hhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj"ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj"jKjj!jj uh+jhj"ubj1)}(h, h]h, }(hj"hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj"ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj #hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj#ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj #jKjj!jj uh+jhj"ubh)}(hj"hhhNhNubh – }(hj"hhhNhNubhThe default is None.}(hj"hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj"ubah}(h!]h#]h%]h']h)]uh+jhjM"ubj)}(hhh]j)}(hQendog_idx (int, optional) -- Index of the response variable. The default is None.h](j)}(h endog_idxh]h endog_idx}(hjB#hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj>#ubh (}(hj>#hhhNhNubj)}(hhh]j1)}(hinth]hint}(hjW#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjT#ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetjY#jKjj!jj uh+jhj>#ubj1)}(h, h]h, }(hjo#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj>#ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj}#ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj#jKjj!jj uh+jhj>#ubh)}(hj>#hhhNhNubh – }(hj>#hhhNhNubh4Index of the response variable. The default is None.}(hj>#hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj;#ubah}(h!]h#]h%]h']h)]uh+jhjM"ubj)}(hhh]j)}(hremoval_iterations (int, optional) -- Small clusters of outliers with varying magnitudes may only flag the most extreme outlier. Repeating the method ensures surrounding outliers are also captured. The default is 10.h](j)}(hremoval_iterationsh]hremoval_iterations}(hj#hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj#ubh (}(hj#hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj#ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj#jKjj!jj uh+jhj#ubj1)}(h, h]h, }(hj#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj#ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj#hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj#ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetj#jKjj!jj uh+jhj#ubh)}(hj#hhhNhNubh – }(hj#hhhNhNubhSmall clusters of outliers with varying magnitudes may only flag the most extreme outlier. Repeating the method ensures surrounding outliers are also captured. The default is 10.}(hj#hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj#ubah}(h!]h#]h%]h']h)]uh+jhjM"ubj)}(hhh]j)}(h**kwargs (scikit arguments) -- h](j)}(h**kwargsh]h**kwargs}(hj,$hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj($ubh (}(hj($hhhNhNubj)}(hhh]j1)}(hscikit argumentsh]hscikit arguments}(hjA$hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj>$ubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetjC$jKjj!jj uh+jhj($ubh)}(hj($hhhNhNubh – }(hj($hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj%$ubah}(h!]h#]h%]h']h)]uh+jhjM"ubeh}(h!]h#]h%]h']h)]uh+j hjJ"ubah}(h!]h#]h%]h']h)]uh+jhj9"ubeh}(h!]h#]h%]h']h)]uh+jhj6"ubj)}(hhh](j)}(h Return typeh]h Return type}(hj$hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj$hj hKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hj$hhhNhNubah}(h!]h#]h%]h']h)] refdomainj" refexplicitreftypejv reftargetNone.jKjj!jj uh+jhj$ubah}(h!]h#]h%]h']h)]uh+jhj$ubah}(h!]h#]h%]h']h)]uh+jhj$ubeh}(h!]h#]h%]h']h)]uh+jhj6"ubeh}(h!]h#]h%]h']h)]uh+jhj!hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs=remove_outliers() (core.knn_models.OutlierKNNDetector method)2core.knn_models.OutlierKNNDetector.remove_outliershNtauh+hWhj!hhhNhNubhx)}(hhh](h})}(h5OutlierKNNDetector.remove_outliers(X, make_plot=True)h](h)}(hremove_outliersh]hremove_outliers}(hj$hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj$hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.OutlierKNNDetector.remove_outliershKubh)}(hX, make_plot=Trueh](h)}(hXh]h)}(hXh]hX}(hj$hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj$ubah}(h!]h#]h%]h']h)]hhuh+hhj$ubh)}(hmake_plot=Trueh](h)}(h make_ploth]h make_plot}(hj%hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj%ubj)}(h=h]h=}(hj%hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj%ubj)}(hTrueh]hTrue}(hj!%hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj%ubeh}(h!]h#]h%]h']h)]hhuh+hhj$ubeh}(h!]h#]h%]h']h)]hhuh+hhj$hhhj$hKubeh}(h!]j$ah#](jojpeh%]h']h)]jtcore.knn_modelsjvj jw"OutlierKNNDetector.remove_outliersjxjB%OutlierKNNDetectorremove_outliersjz$OutlierKNNDetector.remove_outliers()uh+h|hj$hKhj$hhubj|)}(hhh]j)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjQ%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjN%hj$hKubj)}(hhh]j)}(harrayh]j)}(h:py:class:`~numpy.array`h]j)}(hjh%h]harray}(hjj%hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjf%ubah}(h!]h#]h%]h']h)]refdocj refdomainjt%reftypeclass refexplicitrefwarnjjB%jj j numpy.arrayuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\knn_models.py:docstring of core.knn_models.OutlierKNNDetector.remove_outliershKhjb%hhubah}(h!]h#]h%]h']h)]uh+jhj_%ubah}(h!]h#]h%]h']h)]uh+jhjN%ubeh}(h!]h#]h%]h']h)]uh+jhjK%ubj)}(hhh](j)}(h Parametersh]h Parameters}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj%hj$hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hX (np.array) -- h](j)}(hjBh]hX}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj%ubh (}(hj%hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj%ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj%jKjjB%jj uh+jhj%ubh)}(hj%hhhNhNubh – }(hj%hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj%ubah}(h!]h#]h%]h']h)]uh+jhj%ubj)}(hhh]j)}(h2make_plot (bool, optional) -- The default is True.h](j)}(h make_ploth]h make_plot}(hj%hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj%ubh (}(hj%hhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hj&hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj&ubah}(h!]h#]h%]h']h)] refdomainj% refexplicitreftypejv reftargetj&jKjjB%jj uh+jhj%ubj1)}(h, h]h, }(hj,&hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj%ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj=&hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj:&ubah}(h!]h#]h%]h']h)] refdomainj% refexplicitreftypejv reftargetj?&jKjjB%jj uh+jhj%ubh)}(hj%hhhNhNubh – }(hj%hhhNhNubhThe default is True.}(hj%hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj%ubah}(h!]h#]h%]h']h)]uh+jhj%ubeh}(h!]h#]h%]h']h)]uh+j hj%ubah}(h!]h#]h%]h']h)]uh+jhj%ubeh}(h!]h#]h%]h']h)]uh+jhjK%ubj)}(hhh](j)}(hReturnsh]hReturns}(hj&hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj&hj$hKubj)}(hhh]j)}(hnewXh]j)}(h**newX**h]hnewX}(hj&hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj&hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj&ubah}(h!]h#]h%]h']h)]uh+jhj&ubeh}(h!]h#]h%]h']h)]uh+jhjK%ubj)}(hhh](j)}(h Return typeh]h Return type}(hj&hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj&hj$hKubj)}(hhh]j)}(hnp.arrayh]j)}(hhh]hnp.array}(hj&hhhNhNubah}(h!]h#]h%]h']h)] refdomainj% refexplicitreftypejv reftargetnp.arrayjKjjB%jj uh+jhj&ubah}(h!]h#]h%]h']h)]uh+jhj&ubah}(h!]h#]h%]h']h)]uh+jhj&ubeh}(h!]h#]h%]h']h)]uh+jhjK%ubeh}(h!]h#]h%]h']h)]uh+jhjH%hhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj$hhhj$hKubeh}(h!]h#](j%methodeh%]h']h)]j j%j j'j j'j j j uh+hwhhhj!hNhNubeh}(h!]h#]h%]h']h)]uh+j{hjq hhhj hKubeh}(h!]h#](j"classeh%]h']h)]j j"j j'j j'j j j uh+hwhhhjhNhNubeh}(h!](jcore-knn-models-moduleeh#]h%]core.knn_models moduleah']h)]uh+h hh hhhh,hKubh )}(hhh](h)}(h!core.neural\_network\_base moduleh]h!core.neural_network_base module}(hj'hhhNhNubah}(h!]h#]h%]h']h)]uh+hhj'hhhh,hK ubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hd module; core.neural_network_basemodule-core.neural_network_basehNtauh+hWhj'hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs7base_neural_network (class in core.neural_network_base),core.neural_network_base.base_neural_networkhNtauh+hWhj'hhhNhNubhx)}(hhh](h})}(hXbase_neural_network(AR=5, n_exog_variables=0, n_layers=1, hidden_units=64, activation='relu', lr=0.005, batch_size=32, validation_frac=0.1, epochs=10000, dropout_frac=0.0, optimize=False, include_endog=True, isfilter=False, scale_y=False, test_train_split_method='timeseries')h](h)}(h2[<#text: 'class'>, >]h](hclass}(hjO'hhhNhNubh)}(h h]h }(hjW'hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjO'ubeh}(h!]h#]h%]h']h)]hhuh+hhjK'hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_networkhKubh)}(hcore.neural_network_base.h]hcore.neural_network_base.}(hjl'hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjK'hhhjk'hKubh)}(hbase_neural_networkh]hbase_neural_network}(hjz'hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjK'hhhjk'hKubh)}(hAR=5, n_exog_variables=0, n_layers=1, hidden_units=64, activation='relu', lr=0.005, batch_size=32, validation_frac=0.1, epochs=10000, dropout_frac=0.0, optimize=False, include_endog=True, isfilter=False, scale_y=False, test_train_split_method='timeseries'h](h)}(hAR=5h](h)}(hARh]hAR}(hj'hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj'ubj)}(h=h]h=}(hj'hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj'ubj)}(h5h]h5}(hj'hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj'ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hn_exog_variables=0h](h)}(hn_exog_variablesh]hn_exog_variables}(hj'hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj'ubj)}(h=h]h=}(hj'hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj'ubj)}(h0h]h0}(hj'hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj'ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(h n_layers=1h](h)}(hn_layersh]hn_layers}(hj'hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj'ubj)}(h=h]h=}(hj(hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj'ubj)}(h1h]h1}(hj(hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj'ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hhidden_units=64h](h)}(h hidden_unitsh]h hidden_units}(hj/(hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj+(ubj)}(h=h]h=}(hj=(hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj+(ubj)}(h64h]h64}(hjK(hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj+(ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hactivation='relu'h](h)}(h activationh]h activation}(hjd(hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj`(ubj)}(h=h]h=}(hjr(hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj`(ubj)}(h'relu'h]h'relu'}(hj(hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj`(ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hlr=0.005h](h)}(hlrh]hlr}(hj(hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj(ubj)}(h=h]h=}(hj(hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj(ubj)}(h0.005h]h0.005}(hj(hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj(ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(h batch_size=32h](h)}(h batch_sizeh]h batch_size}(hj(hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj(ubj)}(h=h]h=}(hj(hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj(ubj)}(h32h]h32}(hj(hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj(ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hvalidation_frac=0.1h](h)}(hvalidation_frach]hvalidation_frac}(hj)hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj(ubj)}(h=h]h=}(hj)hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj(ubj)}(h0.1h]h0.1}(hj)hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj(ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(h epochs=10000h](h)}(hepochsh]hepochs}(hj8)hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj4)ubj)}(h=h]h=}(hjF)hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj4)ubj)}(h10000h]h10000}(hjT)hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj4)ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hdropout_frac=0.0h](h)}(h dropout_frach]h dropout_frac}(hjm)hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhji)ubj)}(h=h]h=}(hj{)hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhji)ubj)}(h0.0h]h0.0}(hj)hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhji)ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hoptimize=Falseh](h)}(hoptimizeh]hoptimize}(hj)hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj)ubj)}(h=h]h=}(hj)hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj)ubj)}(hFalseh]hFalse}(hj)hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj)ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hinclude_endog=Trueh](h)}(h include_endogh]h include_endog}(hj)hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj)ubj)}(h=h]h=}(hj)hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj)ubj)}(hTrueh]hTrue}(hj)hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj)ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(hisfilter=Falseh](h)}(hisfilterh]hisfilter}(hj *hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj*ubj)}(h=h]h=}(hj*hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj*ubj)}(hFalseh]hFalse}(hj(*hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj*ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(h scale_y=Falseh](h)}(hscale_yh]hscale_y}(hjA*hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj=*ubj)}(h=h]h=}(hjO*hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj=*ubj)}(hFalseh]hFalse}(hj]*hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj=*ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubh)}(h$test_train_split_method='timeseries'h](h)}(htest_train_split_methodh]htest_train_split_method}(hjv*hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjr*ubj)}(h=h]h=}(hj*hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjr*ubj)}(h 'timeseries'h]h 'timeseries'}(hj*hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjr*ubeh}(h!]h#]h%]h']h)]hhuh+hhj'ubeh}(h!]h#]h%]h']h)]hhuh+hhjK'hhhjk'hKubeh}(h!]jF'ah#](jojpeh%]h']h)]jtcore.neural_network_basejvhjwj|'jxj*j|'jzj|'uh+h|hjk'hKhjH'hhubj|)}(hhh](j)}(hBases: :py:class:`object`h](hBases: }(hj*hhhNhNubj)}(h:py:class:`object`h]j)}(hj*h]hobject}(hj*hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj*ubah}(h!]h#]h%]h']h)]refdocj refdomainj*reftypeclass refexplicitrefwarnjj*jj|'jobjectuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_networkhKhj*ubeh}(h!]h#]h%]h']h)]uh+jhj*hKhj*hhubj)}(hBase object used to define tensorflow objects. Other downstream TwinStat objects are built off of this object or users can create custom neural networks off of this object.h]hBase object used to define tensorflow objects. Other downstream TwinStat objects are built off of this object or users can create custom neural networks off of this object.}(hj*hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_networkhKhj*hhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hj*hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hjk'hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h\AR (int, optional) -- Number of autoregressive lags to include in the BNN. The default is 5.h](j)}(hARh]hAR}(hj+hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj+ubh (}(hj+hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj,+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj)+ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj.+jKjj*jj|'uh+jhj+ubj1)}(h, h]h, }(hjE+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj+ubj)}(hhh]j1)}(hoptionalh]hoptional}(hjV+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjS+ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjX+jKjj*jj|'uh+jhj+ubh)}(hj+hhhNhNubh – }(hj+hhhNhNubhFNumber of autoregressive lags to include in the BNN. The default is 5.}(hj+hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj+ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hrn_exog_variables (int, optional) -- Number of exogenous predictors to generate a ANN model size. The default is 0.h](j)}(hn_exog_variablesh]hn_exog_variables}(hj+hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj+ubh (}(hj+hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj+ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj+jKjj*jj|'uh+jhj+ubj1)}(h, h]h, }(hj+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj+ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj+hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj+ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj+jKjj*jj|'uh+jhj+ubh)}(hj+hhhNhNubh – }(hj+hhhNhNubhNNumber of exogenous predictors to generate a ANN model size. The default is 0.}(hj+hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj+ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(h?n_layers (int, optional) -- Depth of the ANN. The default is 1.h](j)}(hn_layersh]hn_layers}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj+ubh (}(hj+hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj,ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj,jKjj*jj|'uh+jhj+ubj1)}(h, h]h, }(hj/,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj+ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj@,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj=,ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjB,jKjj*jj|'uh+jhj+ubh)}(hj+hhhNhNubh – }(hj+hhhNhNubh#Depth of the ANN. The default is 1.}(hj+hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj+ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hDhidden_units (int, optional) -- Width of the ANN. The default is 64.h](j)}(h hidden_unitsh]h hidden_units}(hjw,hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjs,ubh (}(hjs,hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj,ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj,jKjj*jj|'uh+jhjs,ubj1)}(h, h]h, }(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjs,ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj,ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj,jKjj*jj|'uh+jhjs,ubh)}(hjs,hhhNhNubh – }(hjs,hhhNhNubh$Width of the ANN. The default is 64.}(hjs,hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjp,ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hactivation (str, optional) -- Activation function used after each dense layer. Accepts all tensorflow input. The default is "relu".h](j)}(h activationh]h activation}(hj,hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj,ubh (}(hj,hhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj,ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj-jKjj*jj|'uh+jhj,ubj1)}(h, h]h, }(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj,ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj*-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj'-ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj,-jKjj*jj|'uh+jhj,ubh)}(hj,hhhNhNubh – }(hj,hhhNhNubhiActivation function used after each dense layer. Accepts all tensorflow input. The default is “relu”.}(hj,hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj,ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hElr (float, optional) -- Optimizer learning rate. The default is 5e-3.h](j)}(hlrh]hlr}(hja-hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj]-ubh (}(hj]-hhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hjv-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjs-ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjx-jKjj*jj|'uh+jhj]-ubj1)}(h, h]h, }(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj]-ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj-ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj-jKjj*jj|'uh+jhj]-ubh)}(hj]-hhhNhNubh – }(hj]-hhhNhNubh-Optimizer learning rate. The default is 5e-3.}(hj]-hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjZ-ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(h@batch_size (int, optional) -- SGD batch size. The default is 32.h](j)}(h batch_sizeh]h batch_size}(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj-ubh (}(hj-hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj-hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj-ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj-jKjj*jj|'uh+jhj-ubj1)}(h, h]h, }(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj-ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj.jKjj*jj|'uh+jhj-ubh)}(hj-hhhNhNubh – }(hj-hhhNhNubh"SGD batch size. The default is 32.}(hj-hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj-ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hkvalidation_frac (float, optional) -- Fraction of data to be used in the validation set. The default is 0.1.h](j)}(hvalidation_frach]hvalidation_frac}(hjK.hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjG.ubh (}(hjG.hhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hj`.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj].ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjb.jKjj*jj|'uh+jhjG.ubj1)}(h, h]h, }(hjx.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjG.ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj.jKjj*jj|'uh+jhjG.ubh)}(hjG.hhhNhNubh – }(hjG.hhhNhNubhFFraction of data to be used in the validation set. The default is 0.1.}(hjG.hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjD.ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(h;epochs (int, optional) -- SGD epochs. The default is 10000.h](j)}(hepochsh]hepochs}(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj.ubh (}(hj.hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj.jKjj*jj|'uh+jhj.ubj1)}(h, h]h, }(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj.hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj/jKjj*jj|'uh+jhj.ubh)}(hj.hhhNhNubh – }(hj.hhhNhNubh!SGD epochs. The default is 10000.}(hj.hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj.ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hkdropout_frac (float, optional) -- Fraction of dropout ANN nodes. Only used in training. The default is 0.0.h](j)}(h dropout_frach]h dropout_frac}(hj5/hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj1/ubh (}(hj1/hhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hjJ/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjG/ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjL/jKjj*jj|'uh+jhj1/ubj1)}(h, h]h, }(hjb/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj1/ubj)}(hhh]j1)}(hoptionalh]hoptional}(hjs/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjp/ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetju/jKjj*jj|'uh+jhj1/ubh)}(hj1/hhhNhNubh – }(hj1/hhhNhNubhIFraction of dropout ANN nodes. Only used in training. The default is 0.0.}(hj1/hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj./ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hoptimize (bool, optional (not setup yet)) -- If true, the NN will be optimized with a bayesian optimizer to find the best depth, width, learning rate, and activation function for the provided data. The default is False.h](j)}(hoptimizeh]hoptimize}(hj/hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj/ubh (}(hj/hhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hj/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj/ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj/jKjj*jj|'uh+jhj/ubj1)}(h, h]h, }(hj/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj/ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj/hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj/ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj/jKjj*jj|'uh+jhj/ubj1)}(h (h]h (}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj/ubj)}(hhh]j1)}(h not setup yeth]h not setup yet}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj0ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj0jKjj*jj|'uh+jhj/ubj1)}(h)h]h)}(hj)0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj/ubh)}(hj/hhhNhNubh – }(hj/hhhNhNubhIf true, the NN will be optimized with a bayesian optimizer to find the best depth, width, learning rate, and activation function for the provided data. The default is False.}(hj/hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj/ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hinclude_endog (bool, optional) -- If true, the lagged endogenous variable will be included as a predictor. The default is True.h](j)}(h include_endogh]h include_endog}(hjV0hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjR0ubh (}(hjR0hhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hjk0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjh0ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetjm0jKjj*jj|'uh+jhjR0ubj1)}(h, h]h, }(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjR0ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj0ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj0jKjj*jj|'uh+jhjR0ubh)}(hjR0hhhNhNubh – }(hjR0hhhNhNubh]If true, the lagged endogenous variable will be included as a predictor. The default is True.}(hjR0hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjO0ubah}(h!]h#]h%]h']h)]uh+jhj +ubj)}(hhh]j)}(hX2isfilter (bool, optional) -- If true, the current time endogenous variable will be included as a predictor. Warning, this is useful when creating a filter, but otherwise the neural network will overfit by learning to simply pass the current time through the graph and to the output to achieve perfect accuracy. The default is False. scale_y bool, optional Scale the response variable prior to training and prediction. The default is False. test_train_split_method str, optional If 'timeseries' the split is a cut in the timeseries in which the first (1-validation_frac) is used for training and the last validation_frac is used for validation. If 'random' the split is a randomly selected (1 - validation_frac) for training and the remaining validation_frac used for validation. The default is 'timeseries'.h](j)}(hisfilterh]hisfilter}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj0ubh (}(hj0hhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj0ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj0jKjj*jj|'uh+jhj0ubj1)}(h, h]h, }(hj0hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj0ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj 1hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj1ubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetj 1jKjj*jj|'uh+jhj0ubh)}(hj0hhhNhNubh – }(hj0hhhNhNubh definition_list)}(hhh](h definition_list_item)}(hX0If true, the current time endogenous variable will be included as a predictor. Warning, this is useful when creating a filter, but otherwise the neural network will overfit by learning to simply pass the current time through the graph and to the output to achieve perfect accuracy. The default is False.h](h term)}(h5If true, the current time endogenous variable will beh]h5If true, the current time endogenous variable will be}(hj61hhhNhNubah}(h!]h#]h%]h']h)]uh+j41hj*hK,hj01ubh definition)}(hhh]j)}(hincluded as a predictor. Warning, this is useful when creating a filter, but otherwise the neural network will overfit by learning to simply pass the current time through the graph and to the output to achieve perfect accuracy. The default is False.h]hincluded as a predictor. Warning, this is useful when creating a filter, but otherwise the neural network will overfit by learning to simply pass the current time through the graph and to the output to achieve perfect accuracy. The default is False.}(hjI1hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hK)hjF1ubah}(h!]h#]h%]h']h)]uh+jD1hj01ubeh}(h!]h#]h%]h']h)]uh+j.1hj*hK,hj+1ubj/1)}(hlscale_y : bool, optional Scale the response variable prior to training and prediction. The default is False.h](j51)}(hscale_yh]hscale_y}(hjg1hhhNhNubah}(h!]h#]h%]h']h)]uh+j41hj*hK/hjc1ubh classifier)}(hbool, optionalh]hbool, optional}(hjw1hhhNhNubah}(h!]h#]h%]h']h)]uh+ju1hjc1hj*ubjE1)}(hhh]j)}(hSScale the response variable prior to training and prediction. The default is False.h]hSScale the response variable prior to training and prediction. The default is False.}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hK/hj1ubah}(h!]h#]h%]h']h)]uh+jD1hjc1ubeh}(h!]h#]h%]h']h)]uh+j.1hj*hK/hj+1ubj/1)}(hXttest_train_split_method : str, optional If 'timeseries' the split is a cut in the timeseries in which the first (1-validation_frac) is used for training and the last validation_frac is used for validation. If 'random' the split is a randomly selected (1 - validation_frac) for training and the remaining validation_frac used for validation. The default is 'timeseries'.h](j51)}(htest_train_split_methodh]htest_train_split_method}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+j41hj*hK9hj1ubjv1)}(h str, optionalh]h str, optional}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+ju1hj1hj*ubjE1)}(hhh](j)}(hIf 'timeseries' the split is a cut in the timeseries in which the first (1-validation_frac) is used for training and the last validation_frac is used for validation.h]hIf ‘timeseries’ the split is a cut in the timeseries in which the first (1-validation_frac) is used for training and the last validation_frac is used for validation.}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hK2hj1ubj)}(hIf 'random' the split is a randomly selected (1 - validation_frac) for training and the remaining validation_frac used for validation.h]hIf ‘random’ the split is a randomly selected (1 - validation_frac) for training and the remaining validation_frac used for validation.}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hK6hj1ubj)}(hThe default is 'timeseries'.h]h The default is ‘timeseries’.}(hj1hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj*hK:hj1ubeh}(h!]h#]h%]h']h)]uh+jD1hj1ubeh}(h!]h#]h%]h']h)]uh+j.1hj*hK9hj+1ubeh}(h!]h#]h%]h']h)]uh+j)1hj0hK)hhhNubeh}(h!]h#]h%]h']h)]uh+jhj0ubah}(h!]h#]h%]h']h)]uh+jhj +ubeh}(h!]h#]h%]h']h)]uh+j hj +ubah}(h!]h#]h%]h']h)]uh+jhj*ubeh}(h!]h#]h%]h']h)]uh+jhj*ubj)}(hhh](j)}(h Return typeh]h Return type}(hj"2hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj2hjk'hKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hj72hhhNhNubah}(h!]h#]h%]h']h)] refdomainjA+ refexplicitreftypejv reftargetNone.jKjj*jj|'uh+jhj32ubah}(h!]h#]h%]h']h)]uh+jhj02ubah}(h!]h#]h%]h']h)]uh+jhj2ubeh}(h!]h#]h%]h']h)]uh+jhj*ubeh}(h!]h#]h%]h']h)]uh+jhj*hhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsHtrain_test_split() (core.neural_network_base.base_neural_network method)=core.neural_network_base.base_neural_network.train_test_splithNtauh+hWhj*hhhNhNubhx)}(hhh](h})}(h*base_neural_network.train_test_split(y, X)h](h)}(htrain_test_splith]htrain_test_split}(hjv2hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjr2hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.train_test_splithKubh)}(hy, Xh](h)}(hyh]h)}(hyh]hy}(hj2hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj2ubah}(h!]h#]h%]h']h)]hhuh+hhj2ubh)}(hXh]h)}(hXh]hX}(hj2hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj2ubah}(h!]h#]h%]h']h)]hhuh+hhj2ubeh}(h!]h#]h%]h']h)]hhuh+hhjr2hhhj2hKubeh}(h!]jm2ah#](jojpeh%]h']h)]jtcore.neural_network_basejvj|'jw$base_neural_network.train_test_splitjxj2base_neural_networktrain_test_splitjz&base_neural_network.train_test_split()uh+h|hj2hKhjo2hhubj|)}(hhh](j)}(hTimeseries train/test splitting uses the first (1-validation_frac) for the training set and the last validation_frac for the test set.h]hTimeseries train/test splitting uses the first (1-validation_frac) for the training set and the last validation_frac for the test set.}(hj2hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.train_test_splithKhj2hhubj)}(hlUnless the 'test_train_split_method' is set to random in which the (1-validation_frac) is randomly selected.h]hpUnless the ‘test_train_split_method’ is set to random in which the (1-validation_frac) is randomly selected.}(hj2hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj2hKhj2hhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj2hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj2hj2hKubj)}(hhh]j)}(harrayh]j)}(h:py:class:`~numpy.array`h]j)}(hj3h]harray}(hj 3hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj3ubah}(h!]h#]h%]h']h)]refdocj refdomainj3reftypeclass refexplicitrefwarnjj2jj|'j numpy.arrayuh+jhj2hKhj3hhubah}(h!]h#]h%]h']h)]uh+jhj2ubah}(h!]h#]h%]h']h)]uh+jhj2ubeh}(h!]h#]h%]h']h)]uh+jhj2ubj)}(hhh](j)}(h Parametersh]h Parameters}(hj;3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj83hj2hKubj)}(hhh]j)}(hdata (np.array) -- h](j)}(hdatah]hdata}(hjP3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjL3ubh (}(hjL3hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hje3hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjb3ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjg3jKjj2jj|'uh+jhjL3ubh)}(hjL3hhhNhNubh – }(hjL3hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjI3ubah}(h!]h#]h%]h']h)]uh+jhj83ubeh}(h!]h#]h%]h']h)]uh+jhj2ubj)}(hhh](j)}(hReturnsh]hReturns}(hj3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj3hj2hKubj)}(hhh]j)}(hLtrain_y (np.array) train_X (np.array) test_y (np.array) test_X (np.array)h]j )}(hhh](j)}(h**train_y** (*np.array*)h]j)}(hj3h](j)}(h **train_y**h]htrain_y}(hj3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj3ubh (}(hj3hhhNhNubj)}(h *np.array*h]hnp.array}(hj3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj3ubh)}(hj3hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj2hK hj3ubah}(h!]h#]h%]h']h)]uh+jhj3ubj)}(h**train_X** (*np.array*)h]j)}(hj3h](j)}(h **train_X**h]htrain_X}(hj3hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj3ubh (}(hj3hhhNhNubj)}(h *np.array*h]hnp.array}(hj4hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj3ubh)}(hj3hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj2hKhj3ubah}(h!]h#]h%]h']h)]uh+jhj3ubj)}(h**test_y** (*np.array*)h]j)}(hj#4h](j)}(h **test_y**h]htest_y}(hj(4hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj%4ubh (}(hj%4hhhNhNubj)}(h *np.array*h]hnp.array}(hj:4hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj%4ubh)}(hj%4hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj2hKhj!4ubah}(h!]h#]h%]h']h)]uh+jhj3ubj)}(h**test_X** (*np.array*)h]j)}(hjZ4h](j)}(h **test_X**h]htest_X}(hj_4hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj\4ubh (}(hj\4hhhNhNubj)}(h *np.array*h]hnp.array}(hjq4hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj\4ubh)}(hj\4hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj2hKhjX4ubah}(h!]h#]h%]h']h)]uh+jhj3ubeh}(h!]h#]h%]h']h)]j!j"uh+j hj2hK hj3hhubah}(h!]h#]h%]h']h)]uh+jhj3ubah}(h!]h#]h%]h']h)]uh+jhj3ubeh}(h!]h#]h%]h']h)]uh+jhj2ubeh}(h!]h#]h%]h']h)]uh+jhj2hhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjo2hhhj2hKubeh}(h!]h#](jz3methodeh%]h']h)]j jz3j j4j j4j j j uh+hwhhhj*hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs=train() (core.neural_network_base.base_neural_network method)2core.neural_network_base.base_neural_network.trainhNtauh+hWhj*hhhNhNubhx)}(hhh](h})}(h@base_neural_network.train(y, X=None, patience=500, weights=None)h](h)}(htrainh]htrain}(hj4hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj4hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.trainhKubh)}(h%y, X=None, patience=500, weights=Noneh](h)}(hyh]h)}(hyh]hy}(hj4hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj4ubah}(h!]h#]h%]h']h)]hhuh+hhj4ubh)}(hX=Noneh](h)}(hXh]hX}(hj4hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj4ubj)}(h=h]h=}(hj 5hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj4ubj)}(hNoneh]hNone}(hj5hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj4ubeh}(h!]h#]h%]h']h)]hhuh+hhj4ubh)}(h patience=500h](h)}(hpatienceh]hpatience}(hj35hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj/5ubj)}(h=h]h=}(hjA5hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj/5ubj)}(h500h]h500}(hjO5hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj/5ubeh}(h!]h#]h%]h']h)]hhuh+hhj4ubh)}(h weights=Noneh](h)}(hweightsh]hweights}(hjh5hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjd5ubj)}(h=h]h=}(hjv5hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjd5ubj)}(hNoneh]hNone}(hj5hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjd5ubeh}(h!]h#]h%]h']h)]hhuh+hhj4ubeh}(h!]h#]h%]h']h)]hhuh+hhj4hhhj4hKubeh}(h!]j4ah#](jojpeh%]h']h)]jtcore.neural_network_basejvj|'jwbase_neural_network.trainjxj5base_neural_networktrainjzbase_neural_network.train()uh+h|hj4hKhj4hhubj|)}(hhh](j)}(hTrain the neural network.h]hTrain the neural network.}(hj5hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.trainhKhj5hhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj5hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj5hj4hKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hj5h]hNone}(hj5hhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhj5ubah}(h!]h#]h%]h']h)]refdocj refdomainj5reftypeobj refexplicitrefwarnjj5jj|'jNoneuh+jhj5hKhj5hhubah}(h!]h#]h%]h']h)]uh+jhj5ubah}(h!]h#]h%]h']h)]uh+jhj5ubeh}(h!]h#]h%]h']h)]uh+jhj5ubj)}(hhh](j)}(h Parametersh]h Parameters}(hj 6hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj 6hj4hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hy (np.array) -- h](j)}(hjh]hy}(hj(6hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj$6ubh (}(hj$6hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj<6hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj96ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj>6jKjj5jj|'uh+jhj$6ubh)}(hj$6hhhNhNubh – }(hj$6hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj!6ubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hX (np.array, optional) -- h](j)}(hjBh]hX}(hjp6hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjl6ubh (}(hjl6hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj6hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj6ubah}(h!]h#]h%]h']h)] refdomainjQ6 refexplicitreftypejv reftargetj6jKjj5jj|'uh+jhjl6ubj1)}(h, h]h, }(hj6hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjl6ubj)}(hhh]j1)}(hoptionalh]hoptional}(hj6hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj6ubah}(h!]h#]h%]h']h)] refdomainjQ6 refexplicitreftypejv reftargetj6jKjj5jj|'uh+jhjl6ubh)}(hjl6hhhNhNubh – }(hjl6hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhji6ubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hpatience -- Early stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.h](j)}(hpatienceh]hpatience}(hj6hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj6ubh – }(hj6hhhNhNubhEarly stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.}(hj6hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj6ubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hint -- Early stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.h](j)}(hinth]hint}(hj 7hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj7ubh – }(hj7hhhNhNubhEarly stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.}(hj7hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj7ubah}(h!]h#]h%]h']h)]uh+jhj6ubj)}(hhh]j)}(hoptional -- Early stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.h](j)}(hoptionalh]hoptional}(hj27hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj.7ubh – }(hj.7hhhNhNubhEarly stoppage criteria. Number of iterations with no improvement in the validation set. The model with best validation score is kept.}(hj.7hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj+7ubah}(h!]h#]h%]h']h)]uh+jhj6ubeh}(h!]h#]h%]h']h)]uh+j hj6ubah}(h!]h#]h%]h']h)]uh+jhj 6ubeh}(h!]h#]h%]h']h)]uh+jhj5ubeh}(h!]h#]h%]h']h)]uh+jhj5hhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj4hhhj4hKubeh}(h!]h#](jQ6methodeh%]h']h)]j jQ6j ju7j ju7j j j uh+hwhhhj*hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsDget_estimate() (core.neural_network_base.base_neural_network method)9core.neural_network_base.base_neural_network.get_estimatehNtauh+hWhj*hhhNhNubhx)}(hhh](h})}(h0base_neural_network.get_estimate(y=None, X=None)h](h)}(h get_estimateh]h get_estimate}(hj7hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj7hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.get_estimatehKubh)}(hy=None, X=Noneh](h)}(hy=Noneh](h)}(hyh]hy}(hj7hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj7ubj)}(h=h]h=}(hj7hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj7ubj)}(hNoneh]hNone}(hj7hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj7ubeh}(h!]h#]h%]h']h)]hhuh+hhj7ubh)}(hX=Noneh](h)}(hXh]hX}(hj7hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj7ubj)}(h=h]h=}(hj7hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj7ubj)}(hNoneh]hNone}(hj7hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj7ubeh}(h!]h#]h%]h']h)]hhuh+hhj7ubeh}(h!]h#]h%]h']h)]hhuh+hhj7hhhj7hKubeh}(h!]j7ah#](jojpeh%]h']h)]jtcore.neural_network_basejvj|'jw base_neural_network.get_estimatejxj8base_neural_network get_estimatejz"base_neural_network.get_estimate()uh+h|hj7hKhj7hhubj|)}(hhh](j)}(hMake a prediction with ANN.h]hMake a prediction with ANN.}(hj 8hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\neural_network_base.py:docstring of core.neural_network_base.base_neural_network.get_estimatehKhj8hhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj58hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj28hj7hKubj)}(hhh]j)}(harrayh]j)}(h:py:class:`~numpy.array`h]j)}(hjL8h]harray}(hjN8hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjJ8ubah}(h!]h#]h%]h']h)]refdocj refdomainjX8reftypeclass refexplicitrefwarnjj8jj|'j numpy.arrayuh+jhj.8hKhjF8hhubah}(h!]h#]h%]h']h)]uh+jhjC8ubah}(h!]h#]h%]h']h)]uh+jhj28ubeh}(h!]h#]h%]h']h)]uh+jhj/8ubj)}(hhh](j)}(h Parametersh]h Parameters}(hj8hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj|8hj7hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h#y (np.array) -- Endogenous Variableh](j)}(hjh]hy}(hj8hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj8ubh (}(hj8hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj8hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj8ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj8jKjj8jj|'uh+jhj8ubh)}(hj8hhhNhNubh – }(hj8hhhNhNubhEndogenous Variable}(hj8hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj8ubah}(h!]h#]h%]h']h)]uh+jhj8ubj)}(hhh]j)}(h#X (np.array) -- Exogenous Variablesh](j)}(hjBh]hX}(hj8hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj8ubh (}(hj8hhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj8hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj8ubah}(h!]h#]h%]h']h)] refdomainj8 refexplicitreftypejv reftargetj8jKjj8jj|'uh+jhj8ubh)}(hj8hhhNhNubh – }(hj8hhhNhNubhExogenous Variables}(hj8hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj8ubah}(h!]h#]h%]h']h)]uh+jhj8ubeh}(h!]h#]h%]h']h)]uh+j hj8ubah}(h!]h#]h%]h']h)]uh+jhj|8ubeh}(h!]h#]h%]h']h)]uh+jhj/8ubj)}(hhh](j)}(hReturnsh]hReturns}(hj?9hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj<9hj7hKubj)}(hhh]j)}(h predictionsh]j)}(h**predictions**h]h predictions}(hjT9hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjP9hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjM9ubah}(h!]h#]h%]h']h)]uh+jhj<9ubeh}(h!]h#]h%]h']h)]uh+jhj/8ubj)}(hhh](j)}(h Return typeh]h Return type}(hjw9hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjt9hj7hKubj)}(hhh]j)}(hnp.arrayh]j)}(hhh]hnp.array}(hj9hhhNhNubah}(h!]h#]h%]h']h)] refdomainj8 refexplicitreftypejv reftargetnp.arrayjKjj8jj|'uh+jhj9ubah}(h!]h#]h%]h']h)]uh+jhj9ubah}(h!]h#]h%]h']h)]uh+jhjt9ubeh}(h!]h#]h%]h']h)]uh+jhj/8ubeh}(h!]h#]h%]h']h)]uh+jhj8hhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj7hhhj7hKubeh}(h!]h#](j8methodeh%]h']h)]j j8j j9j j9j j j uh+hwhhhj*hNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs, >]h](hclass}(hj=hhhNhNubh)}(h h]h }(hj=hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj=ubeh}(h!]h#]h%]h']h)]hhuh+hhj=hhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\optimization.py:docstring of core.optimization.GeneticAlgorithmhKubh)}(hcore.optimization.h]hcore.optimization.}(hj=hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj=hhhj=hKubh)}(hGeneticAlgorithmh]hGeneticAlgorithm}(hj=hhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj=hhhj=hKubh)}(hfitness_function, population_size, generations, bounds, record_method='csv', sql_info={}, mutation_rate=0.1, best_fraction=0.5, crossover_method='chromosome'h](h)}(hfitness_functionh]h)}(hfitness_functionh]hfitness_function}(hj=hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj=ubah}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hpopulation_sizeh]h)}(hpopulation_sizeh]hpopulation_size}(hj=hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj=ubah}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(h generationsh]h)}(h generationsh]h generations}(hj>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj >ubah}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hboundsh]h)}(hboundsh]hbounds}(hj'>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj#>ubah}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hrecord_method='csv'h](h)}(h record_methodh]h record_method}(hj?>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj;>ubj)}(h=h]h=}(hjM>hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj;>ubj)}(h'csv'h]h'csv'}(hj[>hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj;>ubeh}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(h sql_info={}h](h)}(hsql_infoh]hsql_info}(hjt>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjp>ubj)}(h=h]h=}(hj>hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjp>ubj)}(h{}h]h{}}(hj>hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjp>ubeh}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hmutation_rate=0.1h](h)}(h mutation_rateh]h mutation_rate}(hj>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj>ubj)}(h=h]h=}(hj>hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj>ubj)}(h0.1h]h0.1}(hj>hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj>ubeh}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hbest_fraction=0.5h](h)}(h best_fractionh]h best_fraction}(hj>hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj>ubj)}(h=h]h=}(hj>hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj>ubj)}(h0.5h]h0.5}(hj>hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj>ubeh}(h!]h#]h%]h']h)]hhuh+hhj=ubh)}(hcrossover_method='chromosome'h](h)}(hcrossover_methodh]hcrossover_method}(hj?hhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj?ubj)}(h=h]h=}(hj!?hhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj?ubj)}(h 'chromosome'h]h 'chromosome'}(hj/?hhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj?ubeh}(h!]h#]h%]h']h)]hhuh+hhj=ubeh}(h!]h#]h%]h']h)]hhuh+hhj=hhhj=hKubeh}(h!]j=ah#](jojpeh%]h']h)]jtcore.optimizationjvhjwj=jxjP?j=jzj=uh+h|hj=hKhj=hhubj|)}(hhh](j)}(hBases: :py:class:`object`h](hBases: }(hjU?hhhNhNubj)}(h:py:class:`object`h]j)}(hj_?h]hobject}(hja?hhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj]?ubah}(h!]h#]h%]h']h)]refdocj refdomainjk?reftypeclass refexplicitrefwarnjjP?jj=jobjectuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\optimization.py:docstring of core.optimization.GeneticAlgorithmhKhjU?ubeh}(h!]h#]h%]h']h)]uh+jhj}?hKhjR?hhubj)}(hBCreate object for genetic algorithm global heuristic optimization.h]hBCreate object for genetic algorithm global heuristic optimization.}(hj?hhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\optimization.py:docstring of core.optimization.GeneticAlgorithmhKhjR?hhubj)}(hhh]j)}(hhh](j)}(h Parametersh]h Parameters}(hj?hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj?hj=hKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hfitness_function -- Python exectuable function that accepts an array X and ouputs a fitness score. The algorithm seeks to minimize this function. To perform a maximization, users should output the negative score.h](j)}(hfitness_functionh]hfitness_function}(hj?hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj?ubh – }(hj?hhhNhNubhPython exectuable function that accepts an array X and ouputs a fitness score. The algorithm seeks to minimize this function. To perform a maximization, users should output the negative score.}(hj?hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj?ubah}(h!]h#]h%]h']h)]uh+jhj?ubj)}(hhh]j)}(hEpopulation_size (int) -- Total sample size for individual chromosomesh](j)}(hpopulation_sizeh]hpopulation_size}(hj?hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj?ubh (}(hj?hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj?hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj?ubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj?jKjjP?jj=uh+jhj?ubh)}(hj?hhhNhNubh – }(hj?hhhNhNubh,Total sample size for individual chromosomes}(hj?hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj?ubah}(h!]h#]h%]h']h)]uh+jhj?ubj)}(hhh]j)}(hCgenerations (int) -- Number of generations to refine the populationh](j)}(h generationsh]h generations}(hj*@hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj&@ubh (}(hj&@hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj?@hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj<@ubah}(h!]h#]h%]h']h)] refdomainj@ refexplicitreftypejv reftargetjA@jKjjP?jj=uh+jhj&@ubh)}(hj&@hhhNhNubh – }(hj&@hhhNhNubh.Number of generations to refine the population}(hj&@hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj#@ubah}(h!]h#]h%]h']h)]uh+jhj?ubj)}(hhh]j)}(hbounds (list[tuple]) -- The population will be prevented from going outside of these bounds. The location in the list must correspond to the input variables.E.g. bounds = [(0,1)]h](j)}(hboundsh]hbounds}(hjv@hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjr@ubh (}(hjr@hhhNhNubj)}(hhh]j1)}(hlisth]hlist}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj@ubah}(h!]h#]h%]h']h)] refdomainj@ refexplicitreftypejv reftargetj@jKjjP?jj=uh+jhjr@ubj1)}(hjh]h[}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjr@ubj)}(hhh]j1)}(htupleh]htuple}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj@ubah}(h!]h#]h%]h']h)] refdomainj@ refexplicitreftypejv reftargetj@jKjjP?jj=uh+jhjr@ubj1)}(hj1h]h]}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjr@ubh)}(hjr@hhhNhNubh – }(hjr@hhhNhNubj)}(hThe population will be prevented from going outside of these bounds. The location in the list must correspond to the input variables.h]hThe population will be prevented from going outside of these bounds. The location in the list must correspond to the input variables.}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj?hK hjr@hhubj)}(hE.g. bounds = [(0,1)]h]hE.g. bounds = [(0,1)]}(hj@hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj?hKhjr@hhubeh}(h!]h#]h%]h']h)]uh+jhjo@ubah}(h!]h#]h%]h']h)]uh+jhj?ubj)}(hhh]j)}(hrecord_method (str, optional) -- Only csv file record is setup. All data saved to 'GA_generation_data.csv'. Eventually SQL support will be added. The default is 'csv'.h](j)}(h record_methodh]h record_method}(hjAhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj Aubh (}(hj AhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hj$AhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj!Aubah}(h!]h#]h%]h']h)] refdomainj@ refexplicitreftypejv reftargetj&AjKjjP?jj=uh+jhj Aubj1)}(h, h]h, }(hjEhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\optimization.py:docstring of core.optimization.GeneticAlgorithm.create_imageshKubh)}(honly_convergence=Falseh]h)}(honly_convergence=Falseh](h)}(honly_convergenceh]honly_convergence}(hjYEhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjUEubj)}(h=h]h=}(hjgEhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjUEubj)}(hFalseh]hFalse}(hjuEhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjUEubeh}(h!]h#]h%]h']h)]hhuh+hhjQEubah}(h!]h#]h%]h']h)]hhuh+hhj>EhhhjPEhKubeh}(h!]j9Eah#](jojpeh%]h']h)]jtcore.optimizationjvj=jwGeneticAlgorithm.create_imagesjxjEGeneticAlgorithm create_imagesjz GeneticAlgorithm.create_images()uh+h|hjPEhKhj;Ehhubj|)}(hhh]j)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjEhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhjPEhKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hjEh]hNone}(hjEhhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhjEubah}(h!]h#]h%]h']h)]refdocj refdomainjEreftypeobj refexplicitrefwarnjjEjj=jNoneuh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\optimization.py:docstring of core.optimization.GeneticAlgorithm.create_imageshKhjEhhubah}(h!]h#]h%]h']h)]uh+jhjEubah}(h!]h#]h%]h']h)]uh+jhjEubeh}(h!]h#]h%]h']h)]uh+jhjEubj)}(hhh](j)}(h Parametersh]h Parameters}(hjEhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhjPEhKubj)}(hhh]j)}(honly_convergence (bool, optional) -- If false, a scatter plot is created for each generation of the optimization.In additional the minimum fitness score is plotted for each generation.If true, only the convergence figure is generated.The default is False.h](j)}(honly_convergenceh]honly_convergence}(hjFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjFubh (}(hjFhhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hjFhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjFubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjFjKjjEjj=uh+jhjFubj1)}(h, h]h, }(hj3FhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjFubj)}(hhh]j1)}(hoptionalh]hoptional}(hjDFhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjAFubah}(h!]h#]h%]h']h)] refdomainj/F refexplicitreftypejv reftargetjFFjKjjEjj=uh+jhjFubh)}(hjFhhhNhNubh – }(hjFhhhNhNubj)}(hLIf false, a scatter plot is created for each generation of the optimization.h]hLIf false, a scatter plot is created for each generation of the optimization.}(hjdFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhKhjFhhubj)}(hGIn additional the minimum fitness score is plotted for each generation.h]hGIn additional the minimum fitness score is plotted for each generation.}(hjrFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhKhjFhhubj)}(h2If true, only the convergence figure is generated.h]h2If true, only the convergence figure is generated.}(hjFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhK hjFhhubj)}(hThe default is False.h]hThe default is False.}(hjFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjEhK hjFhhubeh}(h!]h#]h%]h']h)]uh+jhjEubah}(h!]h#]h%]h']h)]uh+jhjEubeh}(h!]h#]h%]h']h)]uh+jhjEubj)}(hhh](j)}(h Return typeh]h Return type}(hjFhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjFhjPEhKubj)}(hhh]j)}(hNone.h]j)}(hhh]hNone.}(hjFhhhNhNubah}(h!]h#]h%]h']h)] refdomainj/F refexplicitreftypejv reftargetNone.jKjjEjj=uh+jhjFubah}(h!]h#]h%]h']h)]uh+jhjFubah}(h!]h#]h%]h']h)]uh+jhjFubeh}(h!]h#]h%]h']h)]uh+jhjEubeh}(h!]h#]h%]h']h)]uh+jhjEhhhNhNubah}(h!]h#]h%]h']h)]uh+j{hj;EhhhjPEhKubeh}(h!]h#](j/Fmethodeh%]h']h)]j j/Fj jFj jFj j j uh+hwhhhjR?hNhNubeh}(h!]h#]h%]h']h)]uh+j{hj=hhhj=hKubeh}(h!]h#](j@classeh%]h']h)]j j@j jGj jGj j j uh+hwhhhjj=hNhNubeh}(h!](j=core-optimization-moduleeh#]h%]core.optimization moduleah']h)]uh+h hh hhhh,hK(ubh )}(hhh](h)}(h!core.sensitivity\_analysis moduleh]h!core.sensitivity_analysis module}(hjGhhhNhNubah}(h!]h#]h%]h']h)]uh+hhjGhhhh,hK0ubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hd!module; core.sensitivity_analysis module-core.sensitivity_analysishNtauh+hWhjGhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs;shapely_sensitivity() (in module core.sensitivity_analysis)-core.sensitivity_analysis.shapely_sensitivityhNtauh+hWhjGhhhNhNubhx)}(hhh](h})}(h(shapely_sensitivity(inputs, outputs, df)h](h)}(hcore.sensitivity_analysis.h]hcore.sensitivity_analysis.}(hjFGhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjBGhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\sensitivity_analysis.py:docstring of core.sensitivity_analysis.shapely_sensitivityhKubh)}(hshapely_sensitivityh]hshapely_sensitivity}(hjUGhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjBGhhhjTGhKubh)}(hinputs, outputs, dfh](h)}(hinputsh]h)}(hinputsh]hinputs}(hjkGhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjgGubah}(h!]h#]h%]h']h)]hhuh+hhjcGubh)}(houtputsh]h)}(houtputsh]houtputs}(hjGhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjGubah}(h!]h#]h%]h']h)]hhuh+hhjcGubh)}(hdfh]h)}(hdfh]hdf}(hjGhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjGubah}(h!]h#]h%]h']h)]hhuh+hhjcGubeh}(h!]h#]h%]h']h)]hhuh+hhjBGhhhjTGhKubeh}(h!]j=Gah#](jojpeh%]h']h)]jtcore.sensitivity_analysisjvhjwjWGjxjGjWGjzshapely_sensitivity()uh+h|hjTGhKhj?Ghhubj|)}(hhh](j)}(h>Determine the shapely sensitivities of each 'output' variable.h]hBDetermine the shapely sensitivities of each ‘output’ variable.}(hjGhhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\sensitivity_analysis.py:docstring of core.sensitivity_analysis.shapely_sensitivityhKhjGhhubj)}(h{A TwinStat Gaussian Process is used to map the inputs to outputs and shapely sampling is performed on the Gaussian Process.h]h{A TwinStat Gaussian Process is used to map the inputs to outputs and shapely sampling is performed on the Gaussian Process.}(hjGhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjGhKhjGhhubj)}(h`The package shap is used for the shap sampling. https://shap.readthedocs.io/en/latest/index.htmlh](h0The package shap is used for the shap sampling. }(hjGhhhNhNubj)}(h0https://shap.readthedocs.io/en/latest/index.htmlh]h0https://shap.readthedocs.io/en/latest/index.html}(hjGhhhNhNubah}(h!]h#]h%]h']h)]refurijGuh+jhjGubeh}(h!]h#]h%]h']h)]uh+jhjGhKhjGhhubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjGhjTGhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h2inputs (list[str]) -- List of the names of inputs.h](j)}(hinputsh]hinputs}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjHubh (}(hjHhhhNhNubj)}(hhh]j1)}(hlisth]hlist}(hj1HhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj.Hubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetj3HjKjjGjNuh+jhjHubj1)}(hjh]h[}(hjJHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubj)}(hhh]j1)}(hstrh]hstr}(hjZHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjWHubah}(h!]h#]h%]h']h)] refdomainjFH refexplicitreftypejv reftargetj\HjKjjGjNuh+jhjHubj1)}(hj1h]h]}(hjrHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubh)}(hjHhhhNhNubh – }(hjHhhhNhNubhList of the names of inputs.}(hjHhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjHubah}(h!]h#]h%]h']h)]uh+jhjHubj)}(hhh]j)}(houtputs (list[str]) -- List of the names of outputs. The sensivitiy of the inputs to each output will be calculated and a new gaussian process made for each input/output combination.h](j)}(houtputsh]houtputs}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjHubh (}(hjHhhhNhNubj)}(hhh]j1)}(hlisth]hlist}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubah}(h!]h#]h%]h']h)] refdomainjFH refexplicitreftypejv reftargetjHjKjjGjNuh+jhjHubj1)}(hjh]h[}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubj)}(hhh]j1)}(hstrh]hstr}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubah}(h!]h#]h%]h']h)] refdomainjFH refexplicitreftypejv reftargetjHjKjjGjNuh+jhjHubj1)}(hj1h]h]}(hjHhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHubh)}(hjHhhhNhNubh – }(hjHhhhNhNubhList of the names of outputs. The sensivitiy of the inputs to each output will be calculated and a new gaussian process made for each input/output combination.}(hjHhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjHubah}(h!]h#]h%]h']h)]uh+jhjHubj)}(hhh]j)}(hdata (pandas.DataFrame) -- h](j)}(hdatah]hdata}(hjIhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjIubh (}(hjIhhhNhNubj)}(hhh]j1)}(hpandas.DataFrameh]hpandas.DataFrame}(hj4IhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj1Iubah}(h!]h#]h%]h']h)] refdomainjFH refexplicitreftypejv reftargetj6IjKjjGjNuh+jhjIubh)}(hjIhhhNhNubh – }(hjIhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjIubah}(h!]h#]h%]h']h)]uh+jhjHubeh}(h!]h#]h%]h']h)]uh+j hjHubah}(h!]h#]h%]h']h)]uh+jhjGubeh}(h!]h#]h%]h']h)]uh+jhjGubj)}(hhh](j)}(hReturnsh]hReturns}(hjuIhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjrIhjTGhKubj)}(hhh]j)}(hNkeys: output variables values: list of shapely values normalized to sum to 1.0h]hNkeys: output variables values: list of shapely values normalized to sum to 1.0}(hjIhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjIubah}(h!]h#]h%]h']h)]uh+jhjrIubeh}(h!]h#]h%]h']h)]uh+jhjGubj)}(hhh](j)}(h Return typeh]h Return type}(hjIhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjIhjTGhKubj)}(hhh]j)}(h dictionaryh]j)}(hhh]h dictionary}(hjIhhhNhNubah}(h!]h#]h%]h']h)] refdomainjFH refexplicitreftypejv reftarget dictionaryjKjjGjNuh+jhjIubah}(h!]h#]h%]h']h)]uh+jhjIubah}(h!]h#]h%]h']h)]uh+jhjIubeh}(h!]h#]h%]h']h)]uh+jhjGubeh}(h!]h#]h%]h']h)]uh+jhjGhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj?GhhhjTGhKubeh}(h!]h#](jFHfunctioneh%]h']h)]j jFHj jIj jIj j j uh+hwhhhjGhNhNubeh}(h!](j/G core-sensitivity-analysis-moduleeh#]h%] core.sensitivity_analysis moduleah']h)]uh+h hh hhhh,hK0ubh )}(hhh](h)}(hcore.statistical\_tests moduleh]hcore.statistical_tests module}(hjIhhhNhNubah}(h!]h#]h%]h']h)]uh+hhjIhhhh,hK8ubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hdmodule; core.statistical_testsmodule-core.statistical_testshNtauh+hWhjIhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsDdistribution_difference_MC_test() (in module core.statistical_tests)6core.statistical_tests.distribution_difference_MC_testhNtauh+hWhjIhhhNhNubhx)}(hhh](h})}(hndistribution_difference_MC_test(X, Y, n_mixtures_X=50, n_mixtures_Y=50, gmm_type='standard', n_samples=500000)h](h)}(hcore.statistical_tests.h]hcore.statistical_tests.}(hj+JhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj'JhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\statistical_tests.py:docstring of core.statistical_tests.distribution_difference_MC_testhKubh)}(hdistribution_difference_MC_testh]hdistribution_difference_MC_test}(hj:JhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhj'Jhhhj9JhKubh)}(hMX, Y, n_mixtures_X=50, n_mixtures_Y=50, gmm_type='standard', n_samples=500000h](h)}(hXh]h)}(hXh]hX}(hjPJhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjLJubah}(h!]h#]h%]h']h)]hhuh+hhjHJubh)}(hYh]h)}(hYh]hY}(hjhJhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjdJubah}(h!]h#]h%]h']h)]hhuh+hhjHJubh)}(hn_mixtures_X=50h](h)}(h n_mixtures_Xh]h n_mixtures_X}(hjJhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj|Jubj)}(h=h]h=}(hjJhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhj|Jubj)}(h50h]h50}(hjJhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhj|Jubeh}(h!]h#]h%]h']h)]hhuh+hhjHJubh)}(hn_mixtures_Y=50h](h)}(h n_mixtures_Yh]h n_mixtures_Y}(hjJhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjJubj)}(h=h]h=}(hjJhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjJubj)}(h50h]h50}(hjJhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjJubeh}(h!]h#]h%]h']h)]hhuh+hhjHJubh)}(hgmm_type='standard'h](h)}(hgmm_typeh]hgmm_type}(hjJhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjJubj)}(h=h]h=}(hjJhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjJubj)}(h 'standard'h]h 'standard'}(hjKhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjJubeh}(h!]h#]h%]h']h)]hhuh+hhjHJubh)}(hn_samples=500000h](h)}(h n_samplesh]h n_samples}(hjKhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjKubj)}(h=h]h=}(hj-KhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjKubj)}(h500000h]h500000}(hj;KhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjKubeh}(h!]h#]h%]h']h)]hhuh+hhjHJubeh}(h!]h#]h%]h']h)]hhuh+hhj'Jhhhj9JhKubeh}(h!]j"Jah#](jojpeh%]h']h)]jtcore.statistical_testsjvhjwj:py:class:`~sklearn.mixture._gaussian_mixture.GaussianMixture`h]j)}(hjKh]hGaussianMixture}(hjKhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjKubah}(h!]h#]h%]h']h)]refdocj refdomainjKreftypeclass refexplicitrefwarnjj\KjNj1sklearn.mixture._gaussian_mixture.GaussianMixtureuh+jhjpKhKhjKhhubah}(h!]h#]h%]h']h)]uh+jhjKubah}(h!]h#]h%]h']h)]uh+jhjKubeh}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh](j)}(h Parametersh]h Parameters}(hjKhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjKhj9JhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h0X (np.array) -- Data set 1 (n data X n features)h](j)}(hjBh]hX}(hjKhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjKubh (}(hjKhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjKhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjKubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjLjKjj\KjNuh+jhjKubh)}(hjKhhhNhNubh – }(hjKhhhNhNubh Data set 1 (n data X n features)}(hjKhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjKubah}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh]j)}(h0Y (np.array) -- Data set 2 (n data X n features)h](j)}(hYh]hY}(hj6LhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj2Lubh (}(hj2LhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjKLhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjHLubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjMLjKjj\KjNuh+jhj2Lubh)}(hj2LhhhNhNubh – }(hj2LhhhNhNubh Data set 2 (n data X n features)}(hj2LhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj/Lubah}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh]j)}(hn_mixtures_X (int, optional) -- If using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using "bayesian", this is the max clusters that could be used. The default is 50.h](j)}(h n_mixtures_Xh]h n_mixtures_X}(hjLhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj~Lubh (}(hj~LhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjLhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjLubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjLjKjj\KjNuh+jhj~Lubj1)}(h, h]h, }(hjLhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj~Lubj)}(hhh]j1)}(hoptionalh]hoptional}(hjLhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjLubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjLjKjj\KjNuh+jhj~Lubh)}(hj~LhhhNhNubh – }(hj~LhhhNhNubhIf using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using “bayesian”, this is the max clusters that could be used. The default is 50.}(hj~LhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj{Lubah}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh]j)}(hn_mixtures_Y (int, optional) -- If using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using "bayesian", this is the max clusters that could be used. The default is 50.h](j)}(h n_mixtures_Yh]h n_mixtures_Y}(hjLhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjLubh (}(hjLhhhNhNubj)}(hhh]j1)}(hinth]hint}(hj MhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj Mubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjMjKjj\KjNuh+jhjLubj1)}(h, h]h, }(hj$MhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjLubj)}(hhh]j1)}(hoptionalh]hoptional}(hj5MhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj2Mubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetj7MjKjj\KjNuh+jhjLubh)}(hjLhhhNhNubh – }(hjLhhhNhNubhIf using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using “bayesian”, this is the max clusters that could be used. The default is 50.}(hjLhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjLubah}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh]j)}(hPgmm_type (str, optional) -- "standard" or "bayesian". The default is "standard".h](j)}(hgmm_typeh]hgmm_type}(hjlMhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjhMubh (}(hjhMhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjMhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj~Mubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjMjKjj\KjNuh+jhjhMubj1)}(h, h]h, }(hjMhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjhMubj)}(hhh]j1)}(hoptionalh]hoptional}(hjMhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjMubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjMjKjj\KjNuh+jhjhMubh)}(hjhMhhhNhNubh – }(hjhMhhhNhNubh@“standard” or “bayesian”. The default is “standard”.}(hjhMhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjeMubah}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh]j)}(hln_samples (int, optional) -- Number of monte carlo samples to use in the integration. The default is 500000.h](j)}(h n_samplesh]h n_samples}(hjMhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjMubh (}(hjMhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjMhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjMubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetjMjKjj\KjNuh+jhjMubj1)}(h, h]h, }(hjNhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjMubj)}(hhh]j1)}(hoptionalh]hoptional}(hjNhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjNubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftargetj!NjKjj\KjNuh+jhjMubh)}(hjMhhhNhNubh – }(hjMhhhNhNubhONumber of monte carlo samples to use in the integration. The default is 500000.}(hjMhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjMubah}(h!]h#]h%]h']h)]uh+jhjKubeh}(h!]h#]h%]h']h)]uh+j hjKubah}(h!]h#]h%]h']h)]uh+jhjKubeh}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh](j)}(hReturnsh]hReturns}(hjdNhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjaNhj9JhKubj)}(hhh]j)}(hThe dictionary includes the pvalues for each clustered distribution, in which a large p-value means it is likely data from Y came from X and a low pvalue means there is little evidence that Y came from X.h]hThe dictionary includes the pvalues for each clustered distribution, in which a large p-value means it is likely data from Y came from X and a low pvalue means there is little evidence that Y came from X.}(hjuNhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjrNubah}(h!]h#]h%]h']h)]uh+jhjaNubeh}(h!]h#]h%]h']h)]uh+jhjKubj)}(hhh](j)}(h Return typeh]h Return type}(hjNhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjNhj9JhKubj)}(hhh]j)}(h,dict and GaussianMixture and GaussianMixtureh]j)}(hhh]h,dict and GaussianMixture and GaussianMixture}(hjNhhhNhNubah}(h!]h#]h%]h']h)] refdomainjL refexplicitreftypejv reftarget,dict and GaussianMixture and GaussianMixturejKjj\KjNuh+jhjNubah}(h!]h#]h%]h']h)]uh+jhjNubah}(h!]h#]h%]h']h)]uh+jhjNubeh}(h!]h#]h%]h']h)]uh+jhjKubeh}(h!]h#]h%]h']h)]uh+jhj_KhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hj$Jhhhj9JhKubeh}(h!]h#](jLfunctioneh%]h']h)]j jLj jNj jNj j j uh+hwhhhjIhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsKdistribution_difference_hotelling_test() (in module core.statistical_tests)=core.statistical_tests.distribution_difference_hotelling_testhNtauh+hWhjIhhhNhNubhx)}(hhh](h})}(h\distribution_difference_hotelling_test(X, Y, alpha=0.05, n_mixtures=50, gmm_type='standard')h](h)}(hcore.statistical_tests.h]hcore.statistical_tests.}(hjNhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjNhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\statistical_tests.py:docstring of core.statistical_tests.distribution_difference_hotelling_testhKubh)}(h&distribution_difference_hotelling_testh]h&distribution_difference_hotelling_test}(hjOhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjNhhhjOhKubh)}(h4X, Y, alpha=0.05, n_mixtures=50, gmm_type='standard'h](h)}(hXh]h)}(hXh]hX}(hjOhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjOubah}(h!]h#]h%]h']h)]hhuh+hhjOubh)}(hYh]h)}(hYh]hY}(hj0OhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj,Oubah}(h!]h#]h%]h']h)]hhuh+hhjOubh)}(h alpha=0.05h](h)}(halphah]halpha}(hjHOhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjDOubj)}(h=h]h=}(hjVOhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjDOubj)}(h0.05h]h0.05}(hjdOhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjDOubeh}(h!]h#]h%]h']h)]hhuh+hhjOubh)}(h n_mixtures=50h](h)}(h n_mixturesh]h n_mixtures}(hj}OhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjyOubj)}(h=h]h=}(hjOhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjyOubj)}(h50h]h50}(hjOhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjyOubeh}(h!]h#]h%]h']h)]hhuh+hhjOubh)}(hgmm_type='standard'h](h)}(hgmm_typeh]hgmm_type}(hjOhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjOubj)}(h=h]h=}(hjOhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjOubj)}(h 'standard'h]h 'standard'}(hjOhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjOubeh}(h!]h#]h%]h']h)]hhuh+hhjOubeh}(h!]h#]h%]h']h)]hhuh+hhjNhhhjOhKubeh}(h!]jNah#](jojpeh%]h']h)]jtcore.statistical_testsjvhjwjOjxjOjOjz(distribution_difference_hotelling_test()uh+h|hjOhKhjNhhubj|)}(hhh](j)}(hFit a Gaussian Mixture Model to the input data sets. Determine the Hotelling T^2 and p-values to determine if two data sets are different.h]hFit a Gaussian Mixture Model to the input data sets. Determine the Hotelling T^2 and p-values to determine if two data sets are different.}(hjOhhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\statistical_tests.py:docstring of core.statistical_tests.distribution_difference_hotelling_testhKhjOhhubj)}(hXNote this method is determining if the means of multivariate distributions are difference and accounting for the variance in both distributions. It will likely flag all IoT data has being different from the original X data if you looking at sub regions of the original sample set. Hence, this can be used for comparing overal distributions, not individual data from peripherial regions.h]hXNote this method is determining if the means of multivariate distributions are difference and accounting for the variance in both distributions. It will likely flag all IoT data has being different from the original X data if you looking at sub regions of the original sample set. Hence, this can be used for comparing overal distributions, not individual data from peripherial regions.}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjPhKhjOhhubj)}(hhh]j)}(hhh](j)}(h Return typeh]h Return type}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjPhjOhKubj)}(hhh]j)}(hGaussianMixtureh]j)}(h>:py:class:`~sklearn.mixture._gaussian_mixture.GaussianMixture`h]j)}(hj/Ph]hGaussianMixture}(hj1PhhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhj-Pubah}(h!]h#]h%]h']h)]refdocj refdomainj;Preftypeclass refexplicitrefwarnjjOjNj1sklearn.mixture._gaussian_mixture.GaussianMixtureuh+jhjPhK hj)Phhubah}(h!]h#]h%]h']h)]uh+jhj&Pubah}(h!]h#]h%]h']h)]uh+jhjPubeh}(h!]h#]h%]h']h)]uh+jhjPubah}(h!]h#]h%]h']h)]uh+jhjOhhhNhNubj*1)}(hhh]j/1)}(hOReference: https://en.wikipedia.org/wiki/Hotelling%27s_T-squared_distribution h](j51)}(h Reference:h]h Reference:}(hjlPhhhNhNubah}(h!]h#]h%]h']h)]uh+j41hjPhKhjhPubjE1)}(hhh]j)}(hBhttps://en.wikipedia.org/wiki/Hotelling%27s_T-squared_distributionh]j)}(hjPh]hBhttps://en.wikipedia.org/wiki/Hotelling%27s_T-squared_distribution}(hjPhhhNhNubah}(h!]h#]h%]h']h)]refurijPuh+jhj}Pubah}(h!]h#]h%]h']h)]uh+jhjPhK hjzPubah}(h!]h#]h%]h']h)]uh+jD1hjhPubeh}(h!]h#]h%]h']h)]uh+j.1hjPhKhjePubah}(h!]h#]h%]h']h)]uh+j)1hjOhhhjPhK ubj)}(hhh](j)}(hhh](j)}(h Parametersh]h Parameters}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjPhjOhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h0X (np.array) -- Data set 1 (n data X n features)h](j)}(hjBh]hX}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjPubh (}(hjPhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjPhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjPubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjPjKjjOjNuh+jhjPubh)}(hjPhhhNhNubh – }(hjPhhhNhNubh Data set 1 (n data X n features)}(hjPhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjPubah}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh]j)}(h0Y (np.array) -- Data set 2 (n data X n features)h](j)}(hj8Lh]hY}(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjQubh (}(hjQhhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hj(QhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj%Qubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetj*QjKjjOjNuh+jhjQubh)}(hjQhhhNhNubh – }(hjQhhhNhNubh Data set 2 (n data X n features)}(hjQhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj Qubah}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh]j)}(hOalpha (float, optional) -- Statistical significance level. The default is 0.05.h](j)}(halphah]halpha}(hj_QhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj[Qubh (}(hj[QhhhNhNubj)}(hhh]j1)}(hfloath]hfloat}(hjtQhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjqQubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetjvQjKjjOjNuh+jhj[Qubj1)}(h, h]h, }(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj[Qubj)}(hhh]j1)}(hoptionalh]hoptional}(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjQubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetjQjKjjOjNuh+jhj[Qubh)}(hj[QhhhNhNubh – }(hj[QhhhNhNubh4Statistical significance level. The default is 0.05.}(hj[QhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjXQubah}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh]j)}(hn_mixtures_Y (int, optional) -- If using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using "bayesian", this is the max clusters that could be used. The default is 50.h](j)}(h n_mixtures_Yh]h n_mixtures_Y}(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjQubh (}(hjQhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjQhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjQubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetjQjKjjOjNuh+jhjQubj1)}(h, h]h, }(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjQubj)}(hhh]j1)}(hoptionalh]hoptional}(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjRubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetjRjKjjOjNuh+jhjQubh)}(hjQhhhNhNubh – }(hjQhhhNhNubhIf using a standard Gaussian Mixture Model, the number of clusters must be inputed. When using “bayesian”, this is the max clusters that could be used. The default is 50.}(hjQhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjQubah}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh]j)}(hPgmm_type (str, optional) -- "standard" or "bayesian". The default is "standard".h](j)}(hgmm_typeh]hgmm_type}(hjIRhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjERubh (}(hjERhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hj^RhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj[Rubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetj`RjKjjOjNuh+jhjERubj1)}(h, h]h, }(hjvRhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjERubj)}(hhh]j1)}(hoptionalh]hoptional}(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjRubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftargetjRjKjjOjNuh+jhjERubh)}(hjERhhhNhNubh – }(hjERhhhNhNubh@“standard” or “bayesian”. The default is “standard”.}(hjERhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjBRubah}(h!]h#]h%]h']h)]uh+jhjPubeh}(h!]h#]h%]h']h)]uh+j hjPubah}(h!]h#]h%]h']h)]uh+jhjPubeh}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh](j)}(hReturnsh]hReturns}(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjRhjOhKubj)}(hhh]j)}(hThe dictionary includes the pvalues for each clustered distribution, in which a large p-value means it is likely data from Y came from X and a low pvalue means there is little evidence that Y came from X.h]hThe dictionary includes the pvalues for each clustered distribution, in which a large p-value means it is likely data from Y came from X and a low pvalue means there is little evidence that Y came from X.}(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjRubah}(h!]h#]h%]h']h)]uh+jhjRubeh}(h!]h#]h%]h']h)]uh+jhjPubj)}(hhh](j)}(h Return typeh]h Return type}(hjRhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjRhjOhKubj)}(hhh]j)}(h,dict and GaussianMixture and GaussianMixtureh]j)}(hhh]h,dict and GaussianMixture and GaussianMixture}(hjShhhNhNubah}(h!]h#]h%]h']h)] refdomainjP refexplicitreftypejv reftarget,dict and GaussianMixture and GaussianMixturejKjjOjNuh+jhj Subah}(h!]h#]h%]h']h)]uh+jhjSubah}(h!]h#]h%]h']h)]uh+jhjRubeh}(h!]h#]h%]h']h)]uh+jhjPubeh}(h!]h#]h%]h']h)]uh+jhjOhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjNhhhjOhKubeh}(h!]h#](jPfunctioneh%]h']h)]j jPj jBSj jBSj j j uh+hwhhhjIhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hs:get_optimal_n_cluster() (in module core.statistical_tests),core.statistical_tests.get_optimal_n_clusterhNtauh+hWhjIhhhNhNubhx)}(hhh](h})}(h9get_optimal_n_cluster(X, max_cluster=20, make_plot=False)h](h)}(hcore.statistical_tests.h]hcore.statistical_tests.}(hj[ShhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjWShhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\statistical_tests.py:docstring of core.statistical_tests.get_optimal_n_clusterhKubh)}(hget_optimal_n_clusterh]hget_optimal_n_cluster}(hjjShhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjWShhhjiShKubh)}(h"X, max_cluster=20, make_plot=Falseh](h)}(hXh]h)}(hXh]hX}(hjShhhNhNubah}(h!]h#]hah%]h']h)]uh+hhj|Subah}(h!]h#]h%]h']h)]hhuh+hhjxSubh)}(hmax_cluster=20h](h)}(h max_clusterh]h max_cluster}(hjShhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjSubj)}(h=h]h=}(hjShhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjSubj)}(h20h]h20}(hjShhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjSubeh}(h!]h#]h%]h']h)]hhuh+hhjxSubh)}(hmake_plot=Falseh](h)}(h make_ploth]h make_plot}(hjShhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjSubj)}(h=h]h=}(hjShhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjSubj)}(hFalseh]hFalse}(hjShhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjSubeh}(h!]h#]h%]h']h)]hhuh+hhjxSubeh}(h!]h#]h%]h']h)]hhuh+hhjWShhhjiShKubeh}(h!]jRSah#](jojpeh%]h']h)]jtcore.statistical_testsjvhjwjlSjxj TjlSjzget_optimal_n_cluster()uh+h|hjiShKhjTShhubj|)}(hhh](j)}(hUse the silhouette score to find the optimal number of clusters in the data. This function leverages KMeans unsupervised clustering.h]hUse the silhouette score to find the optimal number of clusters in the data. This function leverages KMeans unsupervised clustering.}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\statistical_tests.py:docstring of core.statistical_tests.get_optimal_n_clusterhKhj Thhubj)}(h(This method looks for 2 or more clustersh]h(This method looks for 2 or more clusters}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+jhjThKhj Thhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hj3ThhhNhNubah}(h!]h#]h%]h']h)]uh+jhj0ThjiShKubj)}(hhh]j)}(hinth]j)}(h:py:class:`int`h]j)}(hjJTh]hint}(hjLThhhNhNubah}(h!]h#](jpypy-classeh%]h']h)]uh+jhjHTubah}(h!]h#]h%]h']h)]refdocj refdomainjVTreftypeclass refexplicitrefwarnjj TjNjintuh+jhjThKhjDThhubah}(h!]h#]h%]h']h)]uh+jhjATubah}(h!]h#]h%]h']h)]uh+jhj0Tubeh}(h!]h#]h%]h']h)]uh+jhj-Tubj)}(hhh](j)}(h Parametersh]h Parameters}(hj}ThhhNhNubah}(h!]h#]h%]h']h)]uh+jhjzThjiShKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(h,X (np.array) -- Data to look for clustering.h](j)}(hjBh]hX}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+jhjTubh (}(hjThhhNhNubj)}(hhh]j1)}(hnp.arrayh]hnp.array}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjTubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjTjKjj TjNuh+jhjTubh)}(hjThhhNhNubh – }(hjThhhNhNubhData to look for clustering.}(hjThhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjTubah}(h!]h#]h%]h']h)]uh+jhjTubj)}(hhh]j)}(h1max_cluster (int, optional) -- The default is 20.h](j)}(h max_clusterh]h max_cluster}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+jhjTubh (}(hjThhhNhNubj)}(hhh]j1)}(hinth]hint}(hjThhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjTubah}(h!]h#]h%]h']h)] refdomainjT refexplicitreftypejv reftargetjTjKjj TjNuh+jhjTubj1)}(h, h]h, }(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjTubj)}(hhh]j1)}(hoptionalh]hoptional}(hj"UhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjUubah}(h!]h#]h%]h']h)] refdomainjT refexplicitreftypejv reftargetj$UjKjj TjNuh+jhjTubh)}(hjThhhNhNubh – }(hjThhhNhNubhThe default is 20.}(hjThhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjTubah}(h!]h#]h%]h']h)]uh+jhjTubj)}(hhh]j)}(himake_plot (bool, optional) -- Plot the silhouette score for all number of clusters. The default is False.h](j)}(h make_ploth]h make_plot}(hjYUhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjUUubh (}(hjUUhhhNhNubj)}(hhh]j1)}(hboolh]hbool}(hjnUhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjkUubah}(h!]h#]h%]h']h)] refdomainjT refexplicitreftypejv reftargetjpUjKjj TjNuh+jhjUUubj1)}(h, h]h, }(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjUUubj)}(hhh]j1)}(hoptionalh]hoptional}(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjUubah}(h!]h#]h%]h']h)] refdomainjT refexplicitreftypejv reftargetjUjKjj TjNuh+jhjUUubh)}(hjUUhhhNhNubh – }(hjUUhhhNhNubhKPlot the silhouette score for all number of clusters. The default is False.}(hjUUhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjRUubah}(h!]h#]h%]h']h)]uh+jhjTubeh}(h!]h#]h%]h']h)]uh+j hjTubah}(h!]h#]h%]h']h)]uh+jhjzTubeh}(h!]h#]h%]h']h)]uh+jhj-Tubj)}(hhh](j)}(hReturnsh]hReturns}(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjUhjiShKubj)}(hhh]j)}(h5Number of clusters with the maximum silhouette score.h]h5Number of clusters with the maximum silhouette score.}(hjUhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjUubah}(h!]h#]h%]h']h)]uh+jhjUubeh}(h!]h#]h%]h']h)]uh+jhj-Tubj)}(hhh](j)}(h Return typeh]h Return type}(hj VhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjVhjiShKubj)}(hhh]j)}(hinth]j)}(hhh]hint}(hjVhhhNhNubah}(h!]h#]h%]h']h)] refdomainjT refexplicitreftypejv reftargetintjKjj TjNuh+jhjVubah}(h!]h#]h%]h']h)]uh+jhjVubah}(h!]h#]h%]h']h)]uh+jhjVubeh}(h!]h#]h%]h']h)]uh+jhj-Tubeh}(h!]h#]h%]h']h)]uh+jhj ThhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjTShhhjiShKubeh}(h!]h#](jTfunctioneh%]h']h)]j jTj jRVj jRVj j j uh+hwhhhjIhNhNubeh}(h!](jJcore-statistical-tests-moduleeh#]h%]core.statistical_tests moduleah']h)]uh+h hh hhhh,hK8ubh )}(hhh](h)}(h$core.uncertainty\_propagation moduleh]h$core.uncertainty_propagation module}(hjaVhhhNhNubah}(h!]h#]h%]h']h)]uh+hhj^Vhhhh,hK@ubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hd$module; core.uncertainty_propagation#module-core.uncertainty_propagationhNtauh+hWhj^VhhhNhNubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hsBuncertainty_propagation() (in module core.uncertainty_propagation)4core.uncertainty_propagation.uncertainty_propagationhNtauh+hWhj^VhhhNhNubhx)}(hhh](h})}(h}uncertainty_propagation(evaluate_data, config, pce_degree=6, method='monte_carlo', sampling_method='latin_hypercube', seed=0)h](h)}(hcore.uncertainty_propagation.h]hcore.uncertainty_propagation.}(hjVhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjVhhhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\uncertainty_propagation.py:docstring of core.uncertainty_propagation.uncertainty_propagationhKubh)}(huncertainty_propagationh]huncertainty_propagation}(hjVhhhNhNubah}(h!]h#](hheh%]h']h)]hhuh+hhjVhhhjVhKubh)}(hdevaluate_data, config, pce_degree=6, method='monte_carlo', sampling_method='latin_hypercube', seed=0h](h)}(h evaluate_datah]h)}(h evaluate_datah]h evaluate_data}(hjVhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjVubah}(h!]h#]h%]h']h)]hhuh+hhjVubh)}(hconfigh]h)}(hconfigh]hconfig}(hjVhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjVubah}(h!]h#]h%]h']h)]hhuh+hhjVubh)}(h pce_degree=6h](h)}(h pce_degreeh]h pce_degree}(hjVhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjVubj)}(h=h]h=}(hjVhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjVubj)}(h6h]h6}(hjWhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjVubeh}(h!]h#]h%]h']h)]hhuh+hhjVubh)}(hmethod='monte_carlo'h](h)}(hmethodh]hmethod}(hjWhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjWubj)}(h=h]h=}(hj*WhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjWubj)}(h 'monte_carlo'h]h 'monte_carlo'}(hj8WhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjWubeh}(h!]h#]h%]h']h)]hhuh+hhjVubh)}(h!sampling_method='latin_hypercube'h](h)}(hsampling_methodh]hsampling_method}(hjQWhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjMWubj)}(h=h]h=}(hj_WhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjMWubj)}(h'latin_hypercube'h]h'latin_hypercube'}(hjmWhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjMWubeh}(h!]h#]h%]h']h)]hhuh+hhjVubh)}(hseed=0h](h)}(hseedh]hseed}(hjWhhhNhNubah}(h!]h#]hah%]h']h)]uh+hhjWubj)}(h=h]h=}(hjWhhhNhNubah}(h!]h#]j ah%]h']h)]uh+hhjWubj)}(h0h]h0}(hjWhhhNhNubah}(h!]h#]jah%]h']h)]support_smartquotesuh+jhjWubeh}(h!]h#]h%]h']h)]hhuh+hhjVubeh}(h!]h#]h%]h']h)]hhuh+hhjVhhhjVhKubeh}(h!]jVah#](jojpeh%]h']h)]jtcore.uncertainty_propagationjvhjwjVjxjWjVjzuncertainty_propagation()uh+h|hjVhKhjVhhubj|)}(hhh](j)}(hZchaospy provides utility functions for generating joint probablity sampling distributions.h]hZchaospy provides utility functions for generating joint probablity sampling distributions.}(hjWhhhNhNubah}(h!]h#]h%]h']h)]uh+jhC:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\uncertainty_propagation.py:docstring of core.uncertainty_propagation.uncertainty_propagationhKhjWhhubj)}(hThe actual creation of a the PCE becomes exponentially slower with the number of variables and thus basic MC might be needed for higher dimension count.h]hThe actual creation of a the PCE becomes exponentially slower with the number of variables and thus basic MC might be needed for higher dimension count.}(hjWhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjWhhubj)}(hAAlso, if the objective function runtime is fast, no need for PCE.h]hAAlso, if the objective function runtime is fast, no need for PCE.}(hjWhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjWhhubj)}(hFunction assumes the TwinModules function 'setup_uncertainty_propagation_db' was used to setup an RDS database for data storage.h]hFunction assumes the TwinModules function ‘setup_uncertainty_propagation_db’ was used to setup an RDS database for data storage.}(hjWhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK hjWhhubj)}(hUpon completion of the posterior distribution calculation, this function will automatically run the 'shapely_sensitivity' to determine which inputs have the greatest impact on the outputs.h]hUpon completion of the posterior distribution calculation, this function will automatically run the ‘shapely_sensitivity’ to determine which inputs have the greatest impact on the outputs.}(hjXhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK hjWhhubj)}(hhh](j)}(hhh](j)}(h Return typeh]h Return type}(hjXhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjXhjVhKubj)}(hhh]j)}(hNoneh]j)}(h:py:obj:`None`h]j)}(hj-Xh]hNone}(hj/XhhhNhNubah}(h!]h#](jpypy-objeh%]h']h)]uh+jhj+Xubah}(h!]h#]h%]h']h)]refdocj refdomainj9Xreftypeobj refexplicitrefwarnjjWjNjNoneuh+jhjWhKhj'Xhhubah}(h!]h#]h%]h']h)]uh+jhj$Xubah}(h!]h#]h%]h']h)]uh+jhjXubeh}(h!]h#]h%]h']h)]uh+jhjXubj)}(hhh](j)}(h Parametersh]h Parameters}(hj`XhhhNhNubah}(h!]h#]h%]h']h)]uh+jhj]XhjVhKubj)}(hhh]j )}(hhh](j)}(hhh]j)}(hCevaluate_data (function) -- Python function that accepts a vector Xh](j)}(h evaluate_datah]h evaluate_data}(hj{XhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjwXubh (}(hjwXhhhNhNubj)}(hhh]j1)}(hfunctionh]hfunction}(hjXhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjXubah}(h!]h#]h%]h']h)] refdomainpy refexplicitreftypejv reftargetjXjKjjWjNuh+jhjwXubh)}(hjwXhhhNhNubh – }(hjwXhhhNhNubh'Python function that accepts a vector X}(hjwXhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjtXubah}(h!]h#]h%]h']h)]uh+jhjqXubj)}(hhh]j)}(hXiconfig (dict) -- Contains: 'num_samples': int, number of sobel samples 'sample_dist_input_#': list, [str, float] C:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\uncertainty_propagation.py:docstring of core.uncertainty_propagation.uncertainty_propagation:25: (ERROR/3) Unexpected indentation. [sampling distribution, inputs into sampling distribution] C:\Users\rpivovar\Desktop\workingfolder\projects\brainbox\twinstat\core\uncertainty_propagation.py:docstring of core.uncertainty_propagation.uncertainty_propagation:26: (WARNING/2) Block quote ends without a blank line; unexpected unindent. 'result_#': str, outputs of the evaluate_data function 'secret_name' : str, AWS secret name providing security credentials 'region_name' : str, AWS region of the RDS database 'mysql_db_endpoint' : str, location of SQL database such as AWS RDS endpoint Example: { 'num_samples': int, number of sobel samples 'sample_dist_input_0': ["TruncNormal", 1e-3, 100, 0, 0.01], "sample_dist_input_1" : ["Uniform", 1e-3, 0.3], "result_0" : "deg", "result_1" : "ms", "result_2" : "LoadCellTension1_N_1", }h](j)}(hconfigh]hconfig}(hjXhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjXubh (}(hjXhhhNhNubj)}(hhh]j1)}(hdicth]hdict}(hjXhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjXubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjXjKjjWjNuh+jhjXubh)}(hjXhhhNhNubh – }(hjXhhhNhNubj*1)}(hhh]j/1)}(hXContains: 'num_samples': int, number of sobel samples 'sample_dist_input_#': list, [str, float] [sampling distribution, inputs into sampling distribution] 'result_#': str, outputs of the evaluate_data function 'secret_name' : str, AWS secret name providing security credentials 'region_name' : str, AWS region of the RDS database 'mysql_db_endpoint' : str, location of SQL database such as AWS RDS endpoint Example: .. code-block:: python { 'num_samples': int, number of sobel samples 'sample_dist_input_0': ["TruncNormal", 1e-3, 100, 0, 0.01], "sample_dist_input_1" : ["Uniform", 1e-3, 0.3], "result_0" : "deg", "result_1" : "ms", "result_2" : "LoadCellTension1_N_1", }h](j51)}(h Contains:h]h Contains:}(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+j41hjWhK)hjYubjE1)}(hhh](j)}(hU'num_samples': int, number of sobel samples 'sample_dist_input_#': list, [str, float]h]h]’num_samples’: int, number of sobel samples ‘sample_dist_input_#’: list, [str, float]}(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjYubje:)}(h:[sampling distribution, inputs into sampling distribution]h]j)}(hj%Yh]h:[sampling distribution, inputs into sampling distribution]}(hj'YhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhj#Yubah}(h!]h#]h%]h']h)]uh+jd:hjWhKhjYubj)}(h'result_#': str, outputs of the evaluate_data function 'secret_name' : str, AWS secret name providing security credentials 'region_name' : str, AWS region of the RDS database 'mysql_db_endpoint' : str, location of SQL database such as AWS RDS endpointh]hX ’result_#’: str, outputs of the evaluate_data function ‘secret_name’ : str, AWS secret name providing security credentials ‘region_name’ : str, AWS region of the RDS database ‘mysql_db_endpoint’ : str, location of SQL database such as AWS RDS endpoint}(hj:YhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjYubj)}(hExample:h]hExample:}(hjHYhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjYubh literal_block)}(h{ 'num_samples': int, number of sobel samples 'sample_dist_input_0': ["TruncNormal", 1e-3, 100, 0, 0.01], "sample_dist_input_1" : ["Uniform", 1e-3, 0.3], "result_0" : "deg", "result_1" : "ms", "result_2" : "LoadCellTension1_N_1", }h]h{ 'num_samples': int, number of sobel samples 'sample_dist_input_0': ["TruncNormal", 1e-3, 100, 0, 0.01], "sample_dist_input_1" : ["Uniform", 1e-3, 0.3], "result_0" : "deg", "result_1" : "ms", "result_2" : "LoadCellTension1_N_1", }}(hjXYhhhNhNubah}(h!]h#]h%]h']h)]hhforcelanguagepythonhighlight_args}uh+jVYhjWhK!hjYubeh}(h!]h#]h%]h']h)]uh+jD1hjYubeh}(h!]h#]h%]h']h)]uh+j.1hjWhK)hjXubah}(h!]h#]h%]h']h)]uh+j)1hjXhKhhhNubeh}(h!]h#]h%]h']h)]uh+jhjXubah}(h!]h#]h%]h']h)]uh+jhjqXubj)}(hhh]j)}(hEpce_degree (int, optional) -- PCE polynomial order. The default is 6.h](j)}(h pce_degreeh]h pce_degree}(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjYubh (}(hjYhhhNhNubj)}(hhh]j1)}(hinth]hint}(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjYubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjYjKjjWjNuh+jhjYubj1)}(h, h]h, }(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjYubj)}(hhh]j1)}(hoptionalh]hoptional}(hjYhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjYubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjYjKjjWjNuh+jhjYubh)}(hjYhhhNhNubh – }(hjYhhhNhNubh'PCE polynomial order. The default is 6.}(hjYhhhNhNubeh}(h!]h#]h%]h']h)]uh+jhjYubah}(h!]h#]h%]h']h)]uh+jhjqXubj)}(hhh]j)}(hXmethod (str, optional) -- Either 'monte_carlo' or 'pce'.Both methods will use use sobol sampling of the user provided sampling distributions.'pce' polynomial chaos expansion requires appreciably less samples than traditional monte carlo methods to determine the posterior distribution. However, the complexity of the mapping polynomial scales poorly. Depending on the user defined sampling distribution, pce may become prohibitively slow for higher dimensions, e.g. > ~20'monte_carlo' :The default is 'monte_carlo'.h](j)}(hmethodh]hmethod}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjZubh (}(hjZhhhNhNubj)}(hhh]j1)}(hstrh]hstr}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjZubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjZjKjjWjNuh+jhjZubj1)}(h, h]h, }(hj2ZhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjZubj)}(hhh]j1)}(hoptionalh]hoptional}(hjCZhhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj@Zubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjEZjKjjWjNuh+jhjZubh)}(hjZhhhNhNubh – }(hjZhhhNhNubj)}(hEither 'monte_carlo' or 'pce'.h]h&Either ‘monte_carlo’ or ‘pce’.}(hjcZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK/hjZhhubj)}(hUBoth methods will use use sobol sampling of the user provided sampling distributions.h]hUBoth methods will use use sobol sampling of the user provided sampling distributions.}(hjqZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK1hjZhhubj*1)}(hhh]j/1)}(hXM'pce' : polynomial chaos expansion requires appreciably less samples than traditional monte carlo methods to determine the posterior distribution. However, the complexity of the mapping polynomial scales poorly. Depending on the user defined sampling distribution, pce may become prohibitively slow for higher dimensions, e.g. > ~20 h](j51)}(h'pce'h]h ’pce’}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+j41hjWhK8hjZubjv1)}(hApolynomial chaos expansion requires appreciably less samples thanh]hApolynomial chaos expansion requires appreciably less samples than}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+ju1hjZhjWubjE1)}(hhh]j)}(hXtraditional monte carlo methods to determine the posterior distribution. However, the complexity of the mapping polynomial scales poorly. Depending on the user defined sampling distribution, pce may become prohibitively slow for higher dimensions, e.g. > ~20h]hXtraditional monte carlo methods to determine the posterior distribution. However, the complexity of the mapping polynomial scales poorly. Depending on the user defined sampling distribution, pce may become prohibitively slow for higher dimensions, e.g. > ~20}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK5hjZubah}(h!]h#]h%]h']h)]uh+jD1hjZubeh}(h!]h#]h%]h']h)]uh+j.1hjWhK8hjZubah}(h!]h#]h%]h']h)]uh+j)1hjZhK5hhhNubj)}(h'monte_carlo' :h]h’monte_carlo’ :}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK:hjZhhubj)}(hThe default is 'monte_carlo'.h]h!The default is ‘monte_carlo’.}(hjZhhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKhjZhhubj)}(hsUsing purely random sampling is typically not advisable due to the inefficiency associated with natural clustering.h]hsUsing purely random sampling is typically not advisable due to the inefficiency associated with natural clustering.}(hj`[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhK@hjZhhubj)}(hBA space filling method is recommended, but there are many options.h]hBA space filling method is recommended, but there are many options.}(hjn[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKChjZhhubj)}(h1References discussing Sobol and Latin Hyper Cube:h]h1References discussing Sobol and Latin Hyper Cube:}(hj|[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKEhjZhhubj)}(hGMainly discussing integration; concludes Sobol is best for integration:h]hGMainly discussing integration; concludes Sobol is best for integration:}(hj[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKGhjZhhubje:)}(h7https://arxiv.org/ftp/arxiv/papers/1505/1505.02350.pdf h]j)}(h6https://arxiv.org/ftp/arxiv/papers/1505/1505.02350.pdfh]j)}(hj[h]h6https://arxiv.org/ftp/arxiv/papers/1505/1505.02350.pdf}(hj[hhhNhNubah}(h!]h#]h%]h']h)]refurij[uh+jhj[ubah}(h!]h#]h%]h']h)]uh+jhjWhKJhj[ubah}(h!]h#]h%]h']h)]uh+jd:hjWhKJhjZhhubj)}(h}Specifically discussing uncertainty propagation; concludes Latin Hyper Cube generally is best for uncertainty quantification:h]h}Specifically discussing uncertainty propagation; concludes Latin Hyper Cube generally is best for uncertainty quantification:}(hj[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKLhjZhhubje:)}(h*https://www.osti.gov/servlets/purl/806696 h]j)}(h)https://www.osti.gov/servlets/purl/806696h]j)}(hj[h]h)https://www.osti.gov/servlets/purl/806696}(hj[hhhNhNubah}(h!]h#]h%]h']h)]refurij[uh+jhj[ubah}(h!]h#]h%]h']h)]uh+jhjWhKOhj[ubah}(h!]h#]h%]h']h)]uh+jd:hjWhKOhjZhhubj)}(h.For a sample size of 100,000 with 9 dimensionsh]h.For a sample size of 100,000 with 9 dimensions}(hj[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKQhjZhhubj)}(hgLatin Hyper Cube is ~21.0% slower than brute Monte Carlo Sobol is ~438.0% slower than brute Monte Carloh]hgLatin Hyper Cube is ~21.0% slower than brute Monte Carlo Sobol is ~438.0% slower than brute Monte Carlo}(hj[hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKShjZhhubj)}(h!The default is 'latin_hypercube'.h]h%The default is ‘latin_hypercube’.}(hj\hhhNhNubah}(h!]h#]h%]h']h)]uh+jhjWhKVhjZhhubeh}(h!]h#]h%]h']h)]uh+jhjZubah}(h!]h#]h%]h']h)]uh+jhjqXubj)}(hhh]j)}(h)seed (int, optional) -- The default is 0.h](j)}(hseedh]hseed}(hj'\hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj#\ubh (}(hj#\hhhNhNubj)}(hhh]j1)}(hinth]hint}(hj<\hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj9\ubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetj>\jKjjWjNuh+jhj#\ubj1)}(h, h]h, }(hjT\hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hj#\ubj)}(hhh]j1)}(hoptionalh]hoptional}(hje\hhhNhNubah}(h!]h#]h%]h']h)]uh+j0hjb\ubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetjg\jKjjWjNuh+jhj#\ubh)}(hj#\hhhNhNubh – }(hj#\hhhNhNubhThe default is 0.}(hj#\hhhNhNubeh}(h!]h#]h%]h']h)]uh+jhj \ubah}(h!]h#]h%]h']h)]uh+jhjqXubeh}(h!]h#]h%]h']h)]uh+j hjnXubah}(h!]h#]h%]h']h)]uh+jhj]Xubeh}(h!]h#]h%]h']h)]uh+jhjXubj)}(hhh](j)}(h Return typeh]h Return type}(hj\hhhNhNubah}(h!]h#]h%]h']h)]uh+jhj\hjVhKubj)}(hhh]j)}(hNoneh]j)}(hhh]hNone}(hj\hhhNhNubah}(h!]h#]h%]h']h)] refdomainjX refexplicitreftypejv reftargetNonejKjjWjNuh+jhj\ubah}(h!]h#]h%]h']h)]uh+jhj\ubah}(h!]h#]h%]h']h)]uh+jhj\ubeh}(h!]h#]h%]h']h)]uh+jhjXubeh}(h!]h#]h%]h']h)]uh+jhjWhhhNhNubeh}(h!]h#]h%]h']h)]uh+j{hjVhhhjVhKubeh}(h!]h#](jXfunctioneh%]h']h)]j jXj j\j j\j j j uh+hwhhhj^VhNhNubeh}(h!](j{V#core-uncertainty-propagation-moduleeh#]h%]#core.uncertainty_propagation moduleah']h)]uh+h hh hhhh,hK@ubh )}(hhh](h)}(hcore.util moduleh]hcore.util module}(hj]hhhNhNubah}(h!]h#]h%]h']h)]uh+hhj\hhhh,hKHubhX)}(hhh]h}(h!]h#]h%]h']h)]entries](hdmodule; 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