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< li class = "toctree-l2" > < a class = "reference internal" href = "#parameters-estimation-example" > Parameters Estimation Example< / a > < / li >
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< section id = "examples" >
< h1 > Examples< a class = "headerlink" href = "#examples" title = "Permalink to this headline" > ¶< / a > < / h1 >
< section id = "installation-usage" >
< h2 > Installation/Usage< a class = "headerlink" href = "#installation-usage" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Download the release in .tar.gz or .whl format and simply use pip install to install it:< / p >
< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > $pip install PyCTBN-1.0.tar.gz
< / pre > < / div >
< / div >
< / section >
< section id = "implementing-your-own-data-importer" >
< h2 > Implementing your own data importer< a class = "headerlink" href = "#implementing-your-own-data-importer" title = "Permalink to this headline" > ¶< / a > < / h2 >
< div class = "highlight-python notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "sd" > " " " This example demonstrates the implementation of a simple data importer the extends the class abstract importer to import data in csv format.< / span >
< span class = "sd" > The net in exam has three ternary nodes and no prior net structure.< / span >
< span class = "sd" > " " " < / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > AbstractImporter< / span >
< span class = "k" > class< / span > < span class = "nc" > CSVImporter< / span > < span class = "p" > (< / span > < span class = "n" > AbstractImporter< / span > < span class = "p" > ):< / span >
< span class = "k" > def< / span > < span class = "fm" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > file_path< / span > < span class = "p" > ):< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _df_samples_list< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > CSVImporter< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > (< / span > < span class = "n" > file_path< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > import_data< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > read_csv_file< / span > < span class = "p" > ()< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _sorter< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > build_sorter< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _df_samples_list< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ])< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > import_variables< / span > < span class = "p" > ()< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > compute_row_delta_in_all_samples_frames< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _df_samples_list< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > read_csv_file< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "n" > df< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > read_csv< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _file_path< / span > < span class = "p" > )< / span >
< span class = "n" > df< / span > < span class = "o" > .< / span > < span class = "n" > drop< / span > < span class = "p" > (< / span > < span class = "n" > df< / span > < span class = "o" > .< / span > < span class = "n" > columns< / span > < span class = "p" > [[< / span > < span class = "mi" > 0< / span > < span class = "p" > ]],< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > inplace< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _df_samples_list< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > df< / span > < span class = "p" > ]< / span >
< span class = "k" > def< / span > < span class = "nf" > import_variables< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "n" > values_list< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "mi" > 3< / span > < span class = "k" > for< / span > < span class = "n" > var< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _sorter< / span > < span class = "p" > ]< / span >
< span class = "c1" > # initialize dict of lists< / span >
< span class = "n" > data< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "s1" > ' Name' < / span > < span class = "p" > :< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _sorter< / span > < span class = "p" > ,< / span > < span class = "s1" > ' Value' < / span > < span class = "p" > :< / span > < span class = "n" > values_list< / span > < span class = "p" > }< / span >
< span class = "c1" > # Create the pandas DataFrame< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _df_variables< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > DataFrame< / span > < span class = "p" > (< / span > < span class = "n" > data< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > build_sorter< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > sample_frame< / span > < span class = "p" > :< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > DataFrame< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "n" > typing< / span > < span class = "o" > .< / span > < span class = "n" > List< / span > < span class = "p" > :< / span >
< span class = "k" > return< / span > < span class = "nb" > list< / span > < span class = "p" > (< / span > < span class = "n" > sample_frame< / span > < span class = "o" > .< / span > < span class = "n" > columns< / span > < span class = "p" > )[< / span > < span class = "mi" > 1< / span > < span class = "p" > :]< / span >
< span class = "k" > def< / span > < span class = "nf" > dataset_id< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "nb" > object< / span > < span class = "p" > :< / span >
< span class = "k" > pass< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "parameters-estimation-example" >
< h2 > Parameters Estimation Example< a class = "headerlink" href = "#parameters-estimation-example" title = "Permalink to this headline" > ¶< / a > < / h2 >
< div class = "highlight-python notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > JsonImporter< / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > SamplePath< / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > NetworkGraph< / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > ParametersEstimator< / span >
< span class = "k" > def< / span > < span class = "nf" > main< / span > < span class = "p" > ():< / span >
< span class = "n" > read_files< / span > < span class = "o" > =< / span > < span class = "n" > glob< / span > < span class = "o" > .< / span > < span class = "n" > glob< / span > < span class = "p" > (< / span > < span class = "n" > os< / span > < span class = "o" > .< / span > < span class = "n" > path< / span > < span class = "o" > .< / span > < span class = "n" > join< / span > < span class = "p" > (< / span > < span class = "s1" > ' ./data' < / span > < span class = "p" > ,< / span > < span class = "s2" > " *.json" < / span > < span class = "p" > ))< / span > < span class = "c1" > #Take all json files in this dir< / span >
< span class = "c1" > #import data< / span >
< span class = "n" > importer< / span > < span class = "o" > =< / span > < span class = "n" > JsonImporter< / span > < span class = "p" > (< / span > < span class = "n" > read_files< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "s1" > ' samples' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' dyn.str' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' variables' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' Time' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' Name' < / span > < span class = "p" > )< / span >
< span class = "n" > importer< / span > < span class = "o" > .< / span > < span class = "n" > import_data< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "c1" > #Create a SamplePath Obj passing an already filled AbstractImporter object< / span >
< span class = "n" > s1< / span > < span class = "o" > =< / span > < span class = "n" > SamplePath< / span > < span class = "p" > (< / span > < span class = "n" > importer< / span > < span class = "p" > )< / span >
< span class = "c1" > #Build The trajectries and the structural infos< / span >
< span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > build_trajectories< / span > < span class = "p" > ()< / span >
< span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > build_structure< / span > < span class = "p" > ()< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > structure< / span > < span class = "o" > .< / span > < span class = "n" > edges< / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > structure< / span > < span class = "o" > .< / span > < span class = "n" > nodes_values< / span > < span class = "p" > )< / span >
< span class = "c1" > #From The Structure Object build the Graph< / span >
< span class = "n" > g< / span > < span class = "o" > =< / span > < span class = "n" > NetworkGraph< / span > < span class = "p" > (< / span > < span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > structure< / span > < span class = "p" > )< / span >
< span class = "c1" > #Select a node you want to estimate the parameters< / span >
< span class = "n" > node< / span > < span class = "o" > =< / span > < span class = "n" > g< / span > < span class = "o" > .< / span > < span class = "n" > nodes< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ]< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s2" > " Node" < / span > < span class = "p" > ,< / span > < span class = "n" > node< / span > < span class = "p" > )< / span >
< span class = "c1" > #Init the _graph specifically for THIS node< / span >
< span class = "n" > g< / span > < span class = "o" > .< / span > < span class = "n" > fast_init< / span > < span class = "p" > (< / span > < span class = "n" > node< / span > < span class = "p" > )< / span >
< span class = "c1" > #Use SamplePath and Grpah to create a ParametersEstimator Object< / span >
< span class = "n" > p1< / span > < span class = "o" > =< / span > < span class = "n" > ParametersEstimator< / span > < span class = "p" > (< / span > < span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > trajectories< / span > < span class = "p" > ,< / span > < span class = "n" > g< / span > < span class = "p" > )< / span >
< span class = "c1" > #Init the peEst specifically for THIS node< / span >
< span class = "n" > p1< / span > < span class = "o" > .< / span > < span class = "n" > fast_init< / span > < span class = "p" > (< / span > < span class = "n" > node< / span > < span class = "p" > )< / span >
< span class = "c1" > #Compute the parameters< / span >
< span class = "n" > sofc1< / span > < span class = "o" > =< / span > < span class = "n" > p1< / span > < span class = "o" > .< / span > < span class = "n" > compute_parameters_for_node< / span > < span class = "p" > (< / span > < span class = "n" > node< / span > < span class = "p" > )< / span >
< span class = "c1" > #The est CIMS are inside the resultant SetOfCIms Obj< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > sofc1< / span > < span class = "o" > .< / span > < span class = "n" > actual_cims< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "structure-estimation-example" >
< h2 > Structure Estimation Example< a class = "headerlink" href = "#structure-estimation-example" title = "Permalink to this headline" > ¶< / a > < / h2 >
< div class = "highlight-python notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > JsonImporter< / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > SamplePath< / span >
< span class = "kn" > from< / span > < span class = "nn" > PyCTBN< / span > < span class = "kn" > import< / span > < span class = "n" > StructureEstimator< / span >
< span class = "k" > def< / span > < span class = "nf" > structure_estimation_example< / span > < span class = "p" > ():< / span >
< span class = "c1" > # read the json files in ./data path< / span >
< span class = "n" > read_files< / span > < span class = "o" > =< / span > < span class = "n" > glob< / span > < span class = "o" > .< / span > < span class = "n" > glob< / span > < span class = "p" > (< / span > < span class = "n" > os< / span > < span class = "o" > .< / span > < span class = "n" > path< / span > < span class = "o" > .< / span > < span class = "n" > join< / span > < span class = "p" > (< / span > < span class = "s1" > ' ./data' < / span > < span class = "p" > ,< / span > < span class = "s2" > " *.json" < / span > < span class = "p" > ))< / span >
< span class = "c1" > # initialize a JsonImporter object for the first file< / span >
< span class = "n" > importer< / span > < span class = "o" > =< / span > < span class = "n" > JsonImporter< / span > < span class = "p" > (< / span > < span class = "n" > read_files< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "s1" > ' samples' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' dyn.str' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' variables' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' Time' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' Name' < / span > < span class = "p" > )< / span >
< span class = "c1" > # import the data at index 0 of the outer json array< / span >
< span class = "n" > importer< / span > < span class = "o" > .< / span > < span class = "n" > import_data< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "c1" > # construct a SamplePath Object passing a filled AbstractImporter< / span >
< span class = "n" > s1< / span > < span class = "o" > =< / span > < span class = "n" > SamplePath< / span > < span class = "p" > (< / span > < span class = "n" > importer< / span > < span class = "p" > )< / span >
< span class = "c1" > # build the trajectories< / span >
< span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > build_trajectories< / span > < span class = "p" > ()< / span >
< span class = "c1" > # build the real structure< / span >
< span class = "n" > s1< / span > < span class = "o" > .< / span > < span class = "n" > build_structure< / span > < span class = "p" > ()< / span >
< span class = "c1" > # construct a StructureEstimator object< / span >
< span class = "n" > se1< / span > < span class = "o" > =< / span > < span class = "n" > StructureEstimator< / span > < span class = "p" > (< / span > < span class = "n" > s1< / span > < span class = "p" > ,< / span > < span class = "mf" > 0.1< / span > < span class = "p" > ,< / span > < span class = "mf" > 0.1< / span > < span class = "p" > )< / span >
< span class = "c1" > # call the ctpc algorithm< / span >
< span class = "n" > se1< / span > < span class = "o" > .< / span > < span class = "n" > ctpc_algorithm< / span > < span class = "p" > ()< / span >
< span class = "c1" > # the adjacency matrix of the estimated structure< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > se1< / span > < span class = "o" > .< / span > < span class = "n" > adjacency_matrix< / span > < span class = "p" > ())< / span >
< span class = "c1" > # save results to a json file< / span >
< span class = "n" > se1< / span > < span class = "o" > .< / span > < span class = "n" > save_results< / span > < span class = "p" > ()< / span >
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