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diff --git a/docs/.buildinfo b/docs/.buildinfo
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-# Sphinx build info version 1
-# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 87e83150455399004cf3d149c3abeafb
-tags: 645f666f9bcd5a90fca523b33c5a78b7
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diff --git a/docs/.nojekyll b/docs/.nojekyll
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diff --git a/docs-out/Makefile b/docs/Makefile
similarity index 100%
rename from docs-out/Makefile
rename to docs/Makefile
diff --git a/docs-out/PyCTBN.PyCTBN.estimators.rst b/docs/PyCTBN.PyCTBN.estimators.rst
similarity index 52%
rename from docs-out/PyCTBN.PyCTBN.estimators.rst
rename to docs/PyCTBN.PyCTBN.estimators.rst
index 0994200..2340868 100644
--- a/docs-out/PyCTBN.PyCTBN.estimators.rst
+++ b/docs/PyCTBN.PyCTBN.estimators.rst
@@ -1,45 +1,45 @@
-PyCTBN.PyCTBN.estimators package
+pyctbn.legacy.estimators package
================================
Submodules
----------
-PyCTBN.PyCTBN.estimators.fam\_score\_calculator module
+pyctbn.legacy.estimators.fam\_score\_calculator module
------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.estimators.fam_score_calculator
+.. automodule:: pyctbn.legacy.estimators.fam_score_calculator
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.estimators.parameters\_estimator module
+pyctbn.legacy.estimators.parameters\_estimator module
-----------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.estimators.parameters_estimator
+.. automodule:: pyctbn.legacy.estimators.parameters_estimator
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.estimators.structure\_constraint\_based\_estimator module
+pyctbn.legacy.estimators.structure\_constraint\_based\_estimator module
-----------------------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator
+.. automodule:: pyctbn.legacy.estimators.structure_constraint_based_estimator
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.estimators.structure\_estimator module
+pyctbn.legacy.estimators.structure\_estimator module
----------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.estimators.structure_estimator
+.. automodule:: pyctbn.legacy.estimators.structure_estimator
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.estimators.structure\_score\_based\_estimator module
+pyctbn.legacy.estimators.structure\_score\_based\_estimator module
------------------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.estimators.structure_score_based_estimator
+.. automodule:: pyctbn.legacy.estimators.structure_score_based_estimator
:members:
:undoc-members:
:show-inheritance:
@@ -47,7 +47,7 @@ PyCTBN.PyCTBN.estimators.structure\_score\_based\_estimator module
Module contents
---------------
-.. automodule:: PyCTBN.PyCTBN.estimators
+.. automodule:: pyctbn.legacy.estimators
:members:
:undoc-members:
:show-inheritance:
diff --git a/docs/PyCTBN.PyCTBN.html b/docs/PyCTBN.PyCTBN.html
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diff --git a/docs-out/PyCTBN.PyCTBN.optimizers.rst b/docs/PyCTBN.PyCTBN.optimizers.rst
similarity index 53%
rename from docs-out/PyCTBN.PyCTBN.optimizers.rst
rename to docs/PyCTBN.PyCTBN.optimizers.rst
index 07942ec..4d4733d 100644
--- a/docs-out/PyCTBN.PyCTBN.optimizers.rst
+++ b/docs/PyCTBN.PyCTBN.optimizers.rst
@@ -1,37 +1,37 @@
-PyCTBN.PyCTBN.optimizers package
+pyctbn.legacy.optimizers package
================================
Submodules
----------
-PyCTBN.PyCTBN.optimizers.constraint\_based\_optimizer module
+pyctbn.legacy.optimizers.constraint\_based\_optimizer module
------------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.optimizers.constraint_based_optimizer
+.. automodule:: pyctbn.legacy.optimizers.constraint_based_optimizer
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.optimizers.hill\_climbing\_search module
+pyctbn.legacy.optimizers.hill\_climbing\_search module
------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.optimizers.hill_climbing_search
+.. automodule:: pyctbn.legacy.optimizers.hill_climbing_search
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.optimizers.optimizer module
+pyctbn.legacy.optimizers.optimizer module
-----------------------------------------
-.. automodule:: PyCTBN.PyCTBN.optimizers.optimizer
+.. automodule:: pyctbn.legacy.optimizers.optimizer
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.optimizers.tabu\_search module
+pyctbn.legacy.optimizers.tabu\_search module
--------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.optimizers.tabu_search
+.. automodule:: pyctbn.legacy.optimizers.tabu_search
:members:
:undoc-members:
:show-inheritance:
@@ -39,7 +39,7 @@ PyCTBN.PyCTBN.optimizers.tabu\_search module
Module contents
---------------
-.. automodule:: PyCTBN.PyCTBN.optimizers
+.. automodule:: pyctbn.legacy.optimizers
:members:
:undoc-members:
:show-inheritance:
diff --git a/docs-out/PyCTBN.PyCTBN.rst b/docs/PyCTBN.PyCTBN.rst
similarity index 50%
rename from docs-out/PyCTBN.PyCTBN.rst
rename to docs/PyCTBN.PyCTBN.rst
index 1496303..2182764 100644
--- a/docs-out/PyCTBN.PyCTBN.rst
+++ b/docs/PyCTBN.PyCTBN.rst
@@ -1,4 +1,4 @@
-PyCTBN.PyCTBN package
+pyctbn.legacy package
=====================
Subpackages
@@ -7,15 +7,15 @@ Subpackages
.. toctree::
:maxdepth: 4
- PyCTBN.PyCTBN.estimators
- PyCTBN.PyCTBN.optimizers
- PyCTBN.PyCTBN.structure_graph
- PyCTBN.PyCTBN.utility
+ pyctbn.legacy.estimators
+ pyctbn.legacy.optimizers
+ pyctbn.legacy.structure_graph
+ pyctbn.legacy.utility
Module contents
---------------
-.. automodule:: PyCTBN.PyCTBN
+.. automodule:: pyctbn.legacy
:members:
:undoc-members:
:show-inheritance:
diff --git a/docs-out/PyCTBN.PyCTBN.structure_graph.rst b/docs/PyCTBN.PyCTBN.structure_graph.rst
similarity index 51%
rename from docs-out/PyCTBN.PyCTBN.structure_graph.rst
rename to docs/PyCTBN.PyCTBN.structure_graph.rst
index f00477b..4b9aca2 100644
--- a/docs-out/PyCTBN.PyCTBN.structure_graph.rst
+++ b/docs/PyCTBN.PyCTBN.structure_graph.rst
@@ -1,69 +1,69 @@
-PyCTBN.PyCTBN.structure\_graph package
+pyctbn.legacy.structure\_graph package
======================================
Submodules
----------
-PyCTBN.PyCTBN.structure\_graph.conditional\_intensity\_matrix module
+pyctbn.legacy.structure\_graph.conditional\_intensity\_matrix module
--------------------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix
+.. automodule:: pyctbn.legacy.structure_graph.conditional_intensity_matrix
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.network\_generator module
+pyctbn.legacy.structure\_graph.network\_generator module
--------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.network_generator
+.. automodule:: pyctbn.legacy.structure_graph.network_generator
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.network\_graph module
+pyctbn.legacy.structure\_graph.network\_graph module
----------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.network_graph
+.. automodule:: pyctbn.legacy.structure_graph.network_graph
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.sample\_path module
+pyctbn.legacy.structure\_graph.sample\_path module
--------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.sample_path
+.. automodule:: pyctbn.legacy.structure_graph.sample_path
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.set\_of\_cims module
+pyctbn.legacy.structure\_graph.set\_of\_cims module
---------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.set_of_cims
+.. automodule:: pyctbn.legacy.structure_graph.set_of_cims
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.structure module
+pyctbn.legacy.structure\_graph.structure module
-----------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.structure
+.. automodule:: pyctbn.legacy.structure_graph.structure
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.trajectory module
+pyctbn.legacy.structure\_graph.trajectory module
------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.trajectory
+.. automodule:: pyctbn.legacy.structure_graph.trajectory
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.structure\_graph.trajectory\_generator module
+pyctbn.legacy.structure\_graph.trajectory\_generator module
-----------------------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph.trajectory_generator
+.. automodule:: pyctbn.legacy.structure_graph.trajectory_generator
:members:
:undoc-members:
:show-inheritance:
@@ -71,7 +71,7 @@ PyCTBN.PyCTBN.structure\_graph.trajectory\_generator module
Module contents
---------------
-.. automodule:: PyCTBN.PyCTBN.structure_graph
+.. automodule:: pyctbn.legacy.structure_graph
:members:
:undoc-members:
:show-inheritance:
diff --git a/docs/PyCTBN.PyCTBN.utility.html b/docs/PyCTBN.PyCTBN.utility.html
deleted file mode 100644
index fe87d56..0000000
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+++ /dev/null
@@ -1,739 +0,0 @@
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PyCTBN.PyCTBN.utility package — PyCTBN 2.0 documentation
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-class PyCTBN.PyCTBN.utility.abstract_exporter.AbstractExporter( variables : pandas.core.frame.DataFrame = None dyn_str : pandas.core.frame.DataFrame = None dyn_cims : dict = None )
-Bases: abc.ABC
-Abstract class that exposes the methods to save in json format a network information
-along with one or more trajectories generated basing on it
-
-Parameters
-
-_variables (pandas.DataFrame ) – Dataframe containing the nodes labels and cardinalities
_dyn_str (pandas.DataFrame ) – Dataframe containing the structure of the network (edges)
_dyn_cims (dict ) – It contains, for every variable (label is the key), the SetOfCims object related to it
_trajectories (List ) – List of trajectories, that can be added subsequently
-
-
-
-add_trajectory( trajectory : list )
-Add a new trajectory to the current list
-
-Parameters
-trajectory (pandas.DataFrame ) – The trajectory to add
-
-
-
-
-
-abstract out_file( filename )
-
-Create a file in current directory and write on it the previously added data (variables, dyn_str, dyn_cims and trajectories)
-
-
-Parameters
-filename (string ) – Name of the output file (it must include json extension)
-
-
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-PyCTBN.PyCTBN.utility.abstract_importer module
-
-
-class PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter( file_path : str = None trajectory_list : Union[ pandas.core.frame.DataFrame, numpy.ndarray] = None variables : pandas.core.frame.DataFrame = None prior_net_structure : pandas.core.frame.DataFrame = None )
-Bases: abc.ABC
-Abstract class that exposes all the necessary methods to process the trajectories and the net structure.
-
-Parameters
-
-file_path (str ) – the file path, or dataset name if you import already processed data
trajectory_list (typing.Union [ pandas.DataFrame , numpy.ndarray ] ) – Dataframe or numpy array containing the concatenation of all the processed trajectories
variables (pandas.DataFrame ) – Dataframe containing the nodes labels and cardinalities
-Prior_net_structure
-Dataframe containing the structure of the network (edges)
-_sorter
-A list containing the variables labels in the SAME order as the columns in concatenated_samples
-
-
-
Warning
-
The parameters variables prior_net_structure concatenated_samples
-
-
Note
-
See :class:JsonImporter
-
-
-build_list_of_samples_array( concatenated_sample : pandas.core.frame.DataFrame ) → List
-Builds a List containing the the delta times numpy array, and the complete transitions matrix
-
-Parameters
-concatenated_sample (pandas.Dataframe ) – the dataframe/array from which the time, and transitions matrix have to be extracted
-and converted
-Returns
-the resulting list of numpy arrays
-Return type
-List
-
-
-
-
-
-abstract build_sorter( trajecory_header : object ) → List
-Initializes the _sorter
-
-Parameters
-trajecory_header (object ) – an object that will be used to define the header
-Returns
-A list containing the processed header.
-Return type
-List
-
-
-
-
-
-clear_concatenated_frame( ) → None
-Removes all values in the dataframe concatenated_samples.
-
-
-
-
-compute_row_delta_in_all_samples_frames( df_samples_list : List ) → None
-Calls the method compute_row_delta_sigle_samples_frame df_samples_list concatanated_samples
-
-Parameters
-df_samples_list (List ) – the datframe’s list to be processed and concatenated
-
-
-
Warning
-
The Dataframe sample_frame has to follow the column structure of this header:
-Header of sample_frame = [Time | Variable values]
-The class member self._sorter HAS to be properly INITIALIZED (See class members definition doc)
-
-
Note
-
After the call of this method the class member concatanated_samples
-
-
-
-
-compute_row_delta_sigle_samples_frame( sample_frame : pandas.core.frame.DataFrame columns_header : List shifted_cols_header : List ) → pandas.core.frame.DataFrame
-Computes the difference between each value present in th time column.
-Copies and shift by one position up all the values present in the remaining columns.
-
-Parameters
-
-sample_frame (pandas.Dataframe ) – the traj to be processed
columns_header (List ) – the original header of sample_frame
shifted_cols_header (List ) – a copy of columns_header with changed names of the contents
-Returns
-The processed dataframe
-Return type
-pandas.Dataframe
-
-
-
Warning
-
the Dataframe sample_frame
-
-
-
-
-property concatenated_samples
-
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-
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-abstract dataset_id( ) → object
-If the original dataset contains multiple dataset, this method returns a unique id to identify the current
-dataset
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-property file_path
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-property sorter
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-property structure
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-property variables
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-PyCTBN.PyCTBN.utility.cache module
-
-
-class PyCTBN.PyCTBN.utility.cache.Cache
-Bases: object
-This class acts as a cache of SetOfCims
-
-__list_of_sets_of_parents
-a list of Sets
-__actual_cache
-a list of setOfCims objects
-
-
-
-clear( )
-Clear the contents both of __actual_cache __list_of_sets_of_parents
-
-
-
-
-find( parents_comb : Set )
-Tries to find in cache given the symbolic parents combination parents_comb SetOfCims parents_comb
-
-Parameters
-parents_comb (Set ) – the parents related to that SetOfCims
-Returns
-A SetOfCims parents_comb __list_of_sets_of_parents
-Return type
-SetOfCims
-
-
-
-
-
-put( parents_comb : Set socim : PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims )
-Place in cache the SetOfCims parents_comb __list_of_sets_of_parents
-
-Parameters
-
-
-
-
-
-
-
-
-
-PyCTBN.PyCTBN.utility.json_exporter module
-
-
-class PyCTBN.PyCTBN.utility.json_exporter.JsonExporter( variables : pandas.core.frame.DataFrame = None dyn_str : pandas.core.frame.DataFrame = None dyn_cims : dict = None )
-Bases: PyCTBN.PyCTBN.utility.abstract_exporter.AbstractExporter
-Provides the methods to save in json format a network information
-along with one or more trajectories generated basing on it
-
-Parameters
-
-_variables (pandas.DataFrame ) – Dataframe containing the nodes labels and cardinalities
_dyn_str (pandas.DataFrame ) – Dataframe containing the structure of the network (edges)
_dyn_cims (dict ) – It contains, for every variable (label is the key), the SetOfCims object related to it
_trajectories (List ) – List of trajectories, that can be added subsequently
-
-
-
-cims_to_json( ) → dict
-
-
-
-
-out_file( filename )
-
-Create a file in current directory and write on it the previously added data (variables, dyn_str, dyn_cims and trajectories)
-
-
-Parameters
-filename (string ) – Name of the output file (it must include json extension)
-
-
-
-
-
-
-
-PyCTBN.PyCTBN.utility.json_importer module
-
-
-class PyCTBN.PyCTBN.utility.json_importer.JsonImporter( file_path : str samples_label : str structure_label : str variables_label : str time_key : str variables_key : str cims_label : str = None )
-Bases: PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter
-Implements the abstracts methods of AbstractImporter and adds all the necessary methods to process and prepare
-the data in json extension.
-
-Parameters
-
-file_path (string ) – the path of the file that contains tha data to be imported
samples_label (string ) – the reference key for the samples in the trajectories
structure_label (string ) – the reference key for the structure of the network data
variables_label (string ) – the reference key for the cardinalites of the nodes data
time_key (string ) – the key used to identify the timestamps in each trajectory
variables_key (string ) – the key used to identify the names of the variables in the net
-_array_indx
-the index of the outer JsonArray to extract the data from
-_df_samples_list
-a Dataframe list in which every dataframe contains a trajectory
-_raw_data
-The raw contents of the json file to import
-
-
-
-build_sorter( sample_frame : pandas.core.frame.DataFrame ) → List
-Implements the abstract method build_sorter of the AbstractImporter
-
-
-
-
-clear_data_frame_list( ) → None
-Removes all values present in the dataframes in the list _df_samples_list
-
-
-
-
-dataset_id( ) → object
-If the original dataset contains multiple dataset, this method returns a unique id to identify the current
-dataset
-
-
-
-
-import_data( indx : int = 0 ) → None
-Implements the abstract method of AbstractImporter
-
-Parameters
-indx (int ) – the index of the outer JsonArray to extract the data from, default to 0
-
-
-
-
-
-import_sampled_cims( raw_data : List indx : int cims_key : str ) → Dict
-Imports the synthetic CIMS in the dataset in a dictionary, using variables labels
-as keys for the set of CIMS of a particular node.
-
-Parameters
-
-raw_data (List ) – List of Dicts
indx (int ) – The index of the array from which the data have to be extracted
cims_key (string ) – the key where the json object cims are placed
-Returns
-a dictionary containing the sampled CIMS for all the variables in the net
-Return type
-Dictionary
-
-
-
-
-
-import_structure( raw_data : List ) → pandas.core.frame.DataFrame
-Imports in a dataframe the data in the list raw_data at the key _structure_label
-
-Parameters
-raw_data (List ) – List of Dicts
-Returns
-Dataframe containg the starting node a ending node of every arc of the network
-Return type
-pandas.Dataframe
-
-
-
-
-
-import_trajectories( raw_data : List ) → List
-Imports the trajectories from the list of dicts raw_data
-
-Parameters
-raw_data (List ) – List of Dicts
-Returns
-List of dataframes containing all the trajectories
-Return type
-List
-
-
-
-
-
-import_variables( raw_data : List ) → pandas.core.frame.DataFrame
-Imports the data in raw_data _variables_label
-
-Parameters
-raw_data (List ) – List of Dicts
-Returns
-Datframe containg the variables simbolic labels and their cardinalities
-Return type
-pandas.Dataframe
-
-
-
-
-
-normalize_trajectories( raw_data : List indx : int trajectories_key : str ) → List
-Extracts the trajectories in raw_data index trajectories key
-
-Parameters
-
-raw_data (List ) – List of Dicts
indx (int ) – The index of the array from which the data have to be extracted
trajectories_key (string ) – the key of the trajectories objects
-Returns
-A list of daframes containg the trajectories
-Return type
-List
-
-
-
-
-
-one_level_normalizing( raw_data : List indx : int key : str ) → pandas.core.frame.DataFrame
-Extracts the one-level nested data in the list raw_data indx key
-
-Parameters
-
-raw_data (List ) – List of Dicts
indx (int ) – The index of the array from which the data have to be extracted
key (string ) – the key for the Dicts from which exctract data
-Returns
-A normalized dataframe
-Return type
-pandas.Datframe
-
-
-
-
-
-read_json_file( ) → List
-Reads the JSON file in the path self.filePath.
-
-Returns
-The contents of the json file
-Return type
-List
-
-
-
-
-
-
-
-PyCTBN.PyCTBN.utility.sample_importer module
-
-
-class PyCTBN.PyCTBN.utility.sample_importer.SampleImporter( trajectory_list : Union[ pandas.core.frame.DataFrame, numpy.ndarray, List] = None variables : Union[ pandas.core.frame.DataFrame, numpy.ndarray, List] = None prior_net_structure : Union[ pandas.core.frame.DataFrame, numpy.ndarray, List] = None )
-Bases: PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter
-Implements the abstracts methods of AbstractImporter and adds all the necessary methods to process and prepare
-the data loaded directly by using DataFrame
-
-Parameters
-
-trajectory_list (typing.Union [ pd.DataFrame , np.ndarray , typing.List ] ) – the data that describes the trajectories
variables (typing.Union [ pd.DataFrame , np.ndarray , typing.List ] ) – the data that describes the variables with name and cardinality
prior_net_structure (typing.Union [ pd.DataFrame , np.ndarray , typing.List ] ) – the data of the real structure, if it exists
-_df_samples_list
-a Dataframe list in which every dataframe contains a trajectory
-_raw_data
-The raw contents of the json file to import
-
-
-
-build_sorter( sample_frame : pandas.core.frame.DataFrame ) → List
-Implements the abstract method build_sorter of the AbstractImporter
-
-
-
-
-dataset_id( ) → str
-If the original dataset contains multiple dataset, this method returns a unique id to identify the current
-dataset
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-import_data( header_column = None )
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diff --git a/docs-out/PyCTBN.PyCTBN.utility.rst b/docs/PyCTBN.PyCTBN.utility.rst
similarity index 53%
rename from docs-out/PyCTBN.PyCTBN.utility.rst
rename to docs/PyCTBN.PyCTBN.utility.rst
index d804edf..e661b1b 100644
--- a/docs-out/PyCTBN.PyCTBN.utility.rst
+++ b/docs/PyCTBN.PyCTBN.utility.rst
@@ -1,53 +1,53 @@
-PyCTBN.PyCTBN.utility package
+pyctbn.legacy.utility package
=============================
Submodules
----------
-PyCTBN.PyCTBN.utility.abstract\_exporter module
+pyctbn.legacy.utility.abstract\_exporter module
-----------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.abstract_exporter
+.. automodule:: pyctbn.legacy.utility.abstract_exporter
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.utility.abstract\_importer module
+pyctbn.legacy.utility.abstract\_importer module
-----------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.abstract_importer
+.. automodule:: pyctbn.legacy.utility.abstract_importer
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.utility.cache module
+pyctbn.legacy.utility.cache module
----------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.cache
+.. automodule:: pyctbn.legacy.utility.cache
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.utility.json\_exporter module
+pyctbn.legacy.utility.json\_exporter module
-------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.json_exporter
+.. automodule:: pyctbn.legacy.utility.json_exporter
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.utility.json\_importer module
+pyctbn.legacy.utility.json\_importer module
-------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.json_importer
+.. automodule:: pyctbn.legacy.utility.json_importer
:members:
:undoc-members:
:show-inheritance:
-PyCTBN.PyCTBN.utility.sample\_importer module
+pyctbn.legacy.utility.sample\_importer module
---------------------------------------------
-.. automodule:: PyCTBN.PyCTBN.utility.sample_importer
+.. automodule:: pyctbn.legacy.utility.sample_importer
:members:
:undoc-members:
:show-inheritance:
@@ -55,7 +55,7 @@ PyCTBN.PyCTBN.utility.sample\_importer module
Module contents
---------------
-.. automodule:: PyCTBN.PyCTBN.utility
+.. automodule:: pyctbn.legacy.utility
:members:
:undoc-members:
:show-inheritance:
diff --git a/docs/PyCTBN.html b/docs/PyCTBN.html
deleted file mode 100644
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+++ /dev/null
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diff --git a/docs-out/PyCTBN.rst b/docs/PyCTBN.rst
similarity index 96%
rename from docs-out/PyCTBN.rst
rename to docs/PyCTBN.rst
index 3aaa3ce..258a0a8 100644
--- a/docs-out/PyCTBN.rst
+++ b/docs/PyCTBN.rst
@@ -7,7 +7,7 @@ Subpackages
.. toctree::
:maxdepth: 4
- PyCTBN.PyCTBN
+ pyctbn.legacy
PyCTBN.tests
Submodules
diff --git a/docs-out/PyCTBN.tests.estimators.rst b/docs/PyCTBN.tests.estimators.rst
similarity index 100%
rename from docs-out/PyCTBN.tests.estimators.rst
rename to docs/PyCTBN.tests.estimators.rst
diff --git a/docs/PyCTBN.tests.html b/docs/PyCTBN.tests.html
deleted file mode 100644
index 7036b72..0000000
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+++ /dev/null
@@ -1,226 +0,0 @@
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PyCTBN.tests package — PyCTBN 2.0 documentation
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diff --git a/docs-out/PyCTBN.tests.optimizers.rst b/docs/PyCTBN.tests.optimizers.rst
similarity index 100%
rename from docs-out/PyCTBN.tests.optimizers.rst
rename to docs/PyCTBN.tests.optimizers.rst
diff --git a/docs-out/PyCTBN.tests.rst b/docs/PyCTBN.tests.rst
similarity index 100%
rename from docs-out/PyCTBN.tests.rst
rename to docs/PyCTBN.tests.rst
diff --git a/docs-out/PyCTBN.tests.structure_graph.rst b/docs/PyCTBN.tests.structure_graph.rst
similarity index 100%
rename from docs-out/PyCTBN.tests.structure_graph.rst
rename to docs/PyCTBN.tests.structure_graph.rst
diff --git a/docs-out/PyCTBN.tests.utility.rst b/docs/PyCTBN.tests.utility.rst
similarity index 100%
rename from docs-out/PyCTBN.tests.utility.rst
rename to docs/PyCTBN.tests.utility.rst
diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.doctree b/docs/_build/doctrees/PyCTBN.PyCTBN.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.PyCTBN.doctree
rename to docs/_build/doctrees/PyCTBN.PyCTBN.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree b/docs/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree
rename to docs/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.optimizers.doctree b/docs/_build/doctrees/PyCTBN.PyCTBN.optimizers.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.PyCTBN.optimizers.doctree
rename to docs/_build/doctrees/PyCTBN.PyCTBN.optimizers.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.structure_graph.doctree b/docs/_build/doctrees/PyCTBN.PyCTBN.structure_graph.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.PyCTBN.structure_graph.doctree
rename to docs/_build/doctrees/PyCTBN.PyCTBN.structure_graph.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.utility.doctree b/docs/_build/doctrees/PyCTBN.PyCTBN.utility.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.PyCTBN.utility.doctree
rename to docs/_build/doctrees/PyCTBN.PyCTBN.utility.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.doctree b/docs/_build/doctrees/PyCTBN.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.doctree
rename to docs/_build/doctrees/PyCTBN.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.tests.doctree b/docs/_build/doctrees/PyCTBN.tests.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.tests.doctree
rename to docs/_build/doctrees/PyCTBN.tests.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.tests.estimators.doctree b/docs/_build/doctrees/PyCTBN.tests.estimators.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.tests.estimators.doctree
rename to docs/_build/doctrees/PyCTBN.tests.estimators.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.tests.optimizers.doctree b/docs/_build/doctrees/PyCTBN.tests.optimizers.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.tests.optimizers.doctree
rename to docs/_build/doctrees/PyCTBN.tests.optimizers.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.tests.structure_graph.doctree b/docs/_build/doctrees/PyCTBN.tests.structure_graph.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.tests.structure_graph.doctree
rename to docs/_build/doctrees/PyCTBN.tests.structure_graph.doctree
diff --git a/docs-out/_build/doctrees/PyCTBN.tests.utility.doctree b/docs/_build/doctrees/PyCTBN.tests.utility.doctree
similarity index 100%
rename from docs-out/_build/doctrees/PyCTBN.tests.utility.doctree
rename to docs/_build/doctrees/PyCTBN.tests.utility.doctree
diff --git a/docs-out/_build/doctrees/basic_main.doctree b/docs/_build/doctrees/basic_main.doctree
similarity index 100%
rename from docs-out/_build/doctrees/basic_main.doctree
rename to docs/_build/doctrees/basic_main.doctree
diff --git a/docs-out/_build/doctrees/environment.pickle b/docs/_build/doctrees/environment.pickle
similarity index 100%
rename from docs-out/_build/doctrees/environment.pickle
rename to docs/_build/doctrees/environment.pickle
diff --git a/docs-out/_build/doctrees/example.doctree b/docs/_build/doctrees/example.doctree
similarity index 100%
rename from docs-out/_build/doctrees/example.doctree
rename to docs/_build/doctrees/example.doctree
diff --git a/docs-out/_build/doctrees/examples.doctree b/docs/_build/doctrees/examples.doctree
similarity index 100%
rename from docs-out/_build/doctrees/examples.doctree
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diff --git a/docs-out/_build/doctrees/index.doctree b/docs/_build/doctrees/index.doctree
similarity index 100%
rename from docs-out/_build/doctrees/index.doctree
rename to docs/_build/doctrees/index.doctree
diff --git a/docs-out/_build/doctrees/modules.doctree b/docs/_build/doctrees/modules.doctree
similarity index 100%
rename from docs-out/_build/doctrees/modules.doctree
rename to docs/_build/doctrees/modules.doctree
diff --git a/docs-out/_build/doctrees/setup.doctree b/docs/_build/doctrees/setup.doctree
similarity index 100%
rename from docs-out/_build/doctrees/setup.doctree
rename to docs/_build/doctrees/setup.doctree
diff --git a/docs-out/_build/html/.buildinfo b/docs/_build/html/.buildinfo
similarity index 100%
rename from docs-out/_build/html/.buildinfo
rename to docs/_build/html/.buildinfo
diff --git a/docs/PyCTBN.PyCTBN.estimators.html b/docs/_build/html/PyCTBN.PyCTBN.estimators.html
similarity index 83%
rename from docs/PyCTBN.PyCTBN.estimators.html
rename to docs/_build/html/PyCTBN.PyCTBN.estimators.html
index 744c567..abc5b0a 100644
--- a/docs/PyCTBN.PyCTBN.estimators.html
+++ b/docs/_build/html/PyCTBN.PyCTBN.estimators.html
@@ -8,7 +8,7 @@
-
PyCTBN.PyCTBN.estimators package — PyCTBN 2.0 documentation
+
pyctbn.legacy.estimators package — PyCTBN 2.0 documentation
@@ -27,9 +27,9 @@
href="genindex.html"/>
-
-
-
+
+
+
@@ -63,9 +63,9 @@
Contents:
-PyCTBN.PyCTBN package
-Subpackages Module contents pyctbn.legacy package
Examples
@@ -116,20 +116,20 @@
-PyCTBN.PyCTBN.estimators package
+pyctbn.legacy.estimators package
-
-PyCTBN.PyCTBN.estimators.fam_score_calculator module
+
+pyctbn.legacy.estimators.fam_score_calculator module
-
-class PyCTBN.PyCTBN.estimators.fam_score_calculator.FamScoreCalculator
+
+class pyctbn.legacy.estimators.fam_score_calculator.FamScoreCalculator
Bases: object
Has the task of calculating the FamScore of a node by using a Bayesian score function
-
-get_fam_score( cims : numpy.array tau_xu : float = 0.1 alpha_xu : float = 1 )
+
+get_fam_score( cims : numpy.array tau_xu : float = 0.1 alpha_xu : float = 1 )
Calculate the FamScore value of the node
Parameters
@@ -149,8 +149,8 @@
-
-marginal_likelihood_q( cims : numpy.array tau_xu : float = 0.1 alpha_xu : float = 1 )
+
+marginal_likelihood_q( cims : numpy.array tau_xu : float = 0.1 alpha_xu : float = 1 )
Calculate the value of the marginal likelihood over q of the node identified by the label node_id
Parameters
@@ -170,8 +170,8 @@
-
-marginal_likelihood_theta( cims : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
+
+marginal_likelihood_theta( cims : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
Calculate the FamScore value of the node identified by the label node_id
Parameters
@@ -191,8 +191,8 @@
-
-single_cim_xu_marginal_likelihood_q( M_xu_suff_stats : float T_xu_suff_stats : float tau_xu : float = 0.1 alpha_xu : float = 1 )
+
+single_cim_xu_marginal_likelihood_q( M_xu_suff_stats : float T_xu_suff_stats : float tau_xu : float = 0.1 alpha_xu : float = 1 )
Calculate the marginal likelihood on q of the node when assumes a specif value
and a specif parents’s assignment
@@ -215,8 +215,8 @@ and a specif parents’s assignment
-
-single_cim_xu_marginal_likelihood_theta( index : int cim : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
+
+single_cim_xu_marginal_likelihood_theta( index : int cim : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
Calculate the marginal likelihood on q of the node when assumes a specif value
and a specif parents’s assignment
@@ -237,8 +237,8 @@ and a specif parents’s assignment
-
-single_internal_cim_xxu_marginal_likelihood_theta( M_xxu_suff_stats : float alpha_xxu : float = 1 )
+
+single_internal_cim_xxu_marginal_likelihood_theta( M_xxu_suff_stats : float alpha_xxu : float = 1 )
Calculate the second part of the marginal likelihood over theta formula
Parameters
@@ -257,8 +257,8 @@ and a specif parents’s assignment
-
-variable_cim_xu_marginal_likelihood_q( cim : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix tau_xu : float = 0.1 alpha_xu : float = 1 )
+
+variable_cim_xu_marginal_likelihood_q( cim : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix tau_xu : float = 0.1 alpha_xu : float = 1 )
Calculate the value of the marginal likelihood over q given a cim
Parameters
@@ -278,8 +278,8 @@ and a specif parents’s assignment
-
-variable_cim_xu_marginal_likelihood_theta( cim : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
+
+variable_cim_xu_marginal_likelihood_theta( cim : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix alpha_xu : float alpha_xxu : float )
Calculate the value of the marginal likelihood over theta given a cim
Parameters
@@ -301,19 +301,19 @@ and a specif parents’s assignment
-
-PyCTBN.PyCTBN.estimators.parameters_estimator module
+
+pyctbn.legacy.estimators.parameters_estimator module
-
-class PyCTBN.PyCTBN.estimators.parameters_estimator.ParametersEstimator( trajectories : PyCTBN.PyCTBN.structure_graph.trajectory.Trajectory net_graph : PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph )
+
+class pyctbn.legacy.estimators.parameters_estimator.ParametersEstimator( trajectories : pyctbn.legacy.structure_graph.trajectory.Trajectory net_graph : pyctbn.legacy.structure_graph.network_graph.NetworkGraph )
Bases: object
Has the task of computing the cims of particular node given the trajectories and the net structure
in the graph _net_graph
Parameters
_single_set_of_cims
@@ -321,8 +321,8 @@ in the graph _net_g
-
-compute_parameters_for_node( node_id : str ) → PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims
+
+compute_parameters_for_node( node_id : str ) → pyctbn.legacy.structure_graph.set_of_cims.SetOfCims
Compute the CIMS of the node identified by the label node_id
Parameters
@@ -332,14 +332,14 @@ in the graph _net_g
A SetOfCims object filled with the computed CIMS
Return type
-SetOfCims
+SetOfCims
-
-static compute_state_res_time_for_node( times : numpy.ndarray trajectory : numpy.ndarray cols_filter : numpy.ndarray scalar_indexes_struct : numpy.ndarray T : numpy.ndarray ) → None
+
+static compute_state_res_time_for_node( times : numpy.ndarray trajectory : numpy.ndarray cols_filter : numpy.ndarray scalar_indexes_struct : numpy.ndarray T : numpy.ndarray ) → None
Compute the state residence times for a node and fill the matrix T
Parameters
@@ -356,8 +356,8 @@ in the graph _net_g
-
-static compute_state_transitions_for_a_node( node_indx : int trajectory : numpy.ndarray cols_filter : numpy.ndarray scalar_indexing : numpy.ndarray M : numpy.ndarray ) → None
+
+static compute_state_transitions_for_a_node( node_indx : int trajectory : numpy.ndarray cols_filter : numpy.ndarray scalar_indexing : numpy.ndarray M : numpy.ndarray ) → None
Compute the state residence times for a node and fill the matrices M
Parameters
@@ -373,8 +373,8 @@ in the graph _net_g
-
-fast_init( node_id : str ) → None
+
+fast_init( node_id : str ) → None
Initializes all the necessary structures for the parameters estimation for the node node_id
Parameters
@@ -386,17 +386,17 @@ in the graph _net_g
-
-PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator module
+
+pyctbn.legacy.estimators.structure_constraint_based_estimator module
-
-class PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator( sample_path : PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath exp_test_alfa : float chi_test_alfa : float known_edges : List = [] thumb_threshold : int = 25 )
-Bases: PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator
+
+class pyctbn.legacy.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator( sample_path : pyctbn.legacy.structure_graph.sample_path.SamplePath exp_test_alfa : float chi_test_alfa : float known_edges : List = [] thumb_threshold : int = 25 )
+Bases: pyctbn.legacy.estimators.structure_estimator.StructureEstimator
Has the task of estimating the network structure given the trajectories in samplepath by using a constraint-based approach.
Parameters
-sample_path (SamplePath
sample_path (SamplePath
exp_test_alfa (float ) – the significance level for the exponential Hp test
chi_test_alfa (float ) – the significance level for the chi Hp test
known_edges (List ) – the prior known edges in the net structure if present
_net_g
-
-complete_test( test_parent : str test_child : str parent_set : List child_states_numb : int tot_vars_count : int parent_indx child_indx ) → bool
+
+complete_test( test_parent : str test_child : str parent_set : List child_states_numb : int tot_vars_count : int parent_indx child_indx ) → bool
Performs a complete independence test on the directed graphs G1 = {test_child U parent_set}
G2 = {G1 U test_parent} (added as an additional parent of the test_child).
Generates all the necessary structures and datas to perform the tests.
@@ -445,8 +445,8 @@ Generates all the necessary structures and datas to perform the tests.
-
-compute_thumb_value( parent_val child_val parent_set_vals )
+
+compute_thumb_value( parent_val child_val parent_set_vals )
Compute the value to test against the thumb_threshold.
Parameters
@@ -466,8 +466,8 @@ Generates all the necessary structures and datas to perform the tests.
-
-ctpc_algorithm( disable_multiprocessing : bool = False processes_number : int = None )
+
+ctpc_algorithm( disable_multiprocessing : bool = False processes_number : int = None )
Compute the CTPC algorithm over the entire net.
Parameters
@@ -482,8 +482,8 @@ Generates all the necessary structures and datas to perform the tests.
-
-estimate_structure( disable_multiprocessing : bool = False processes_number : int = None )
+
+estimate_structure( disable_multiprocessing : bool = False processes_number : int = None )
Compute the constraint-based algorithm to find the optimal structure
Parameters
@@ -498,8 +498,8 @@ Generates all the necessary structures and datas to perform the tests.
-
-independence_test( child_states_numb : int cim1 : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix cim2 : PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix thumb_value : float parent_indx child_indx ) → bool
+
+independence_test( child_states_numb : int cim1 : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix cim2 : pyctbn.legacy.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix thumb_value : float parent_indx child_indx ) → bool
Compute the actual independence test using two cims.
It is performed first the exponential test and if the null hypothesis is not rejected,
it is performed also the chi_test.
@@ -507,8 +507,8 @@ it is performed also the chi_test.
Parameters
Returns
@@ -521,8 +521,8 @@ it is performed also the chi_test.
-
-one_iteration_of_CTPC_algorithm( var_id : str tot_vars_count : int ) → List
+
+one_iteration_of_CTPC_algorithm( var_id : str tot_vars_count : int ) → List
Performs an iteration of the CTPC algorithm using the node var_id test_child
Parameters
@@ -534,17 +534,17 @@ it is performed also the chi_test.
-
-PyCTBN.PyCTBN.estimators.structure_estimator module
+
+pyctbn.legacy.estimators.structure_estimator module
-
-class PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator( sample_path : PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath known_edges : List = None )
+
+class pyctbn.legacy.estimators.structure_estimator.StructureEstimator( sample_path : pyctbn.legacy.structure_graph.sample_path.SamplePath known_edges : List = None )
Bases: object
Has the task of estimating the network structure given the trajectories in samplepath
Parameters
-sample_path (SamplePath
sample_path (SamplePath
known_edges (List ) – the prior known edges in the net structure if present
-
-adjacency_matrix( ) → numpy.ndarray
+
+adjacency_matrix( ) → numpy.ndarray
Converts the estimated structure _complete_graph
Returns
@@ -576,8 +576,8 @@ it is performed also the chi_test.
-
-static build_complete_graph( node_ids : List ) → networkx.classes.digraph.DiGraph
+
+static build_complete_graph( node_ids : List ) → networkx.classes.digraph.DiGraph
Builds a complete directed graph (no self loops) given the nodes labels in the list node_ids
Parameters
@@ -593,8 +593,8 @@ it is performed also the chi_test.
-
-build_removable_edges_matrix( known_edges : List )
+
+build_removable_edges_matrix( known_edges : List )
Builds a boolean matrix who shows if a edge could be removed or not, based on prior knowledge given:
Parameters
@@ -610,8 +610,8 @@ it is performed also the chi_test.
-
-abstract estimate_structure( ) → List
+
+abstract estimate_structure( ) → List
Abstract method to estimate the structure
Returns
@@ -624,8 +624,8 @@ it is performed also the chi_test.
-
-static generate_possible_sub_sets_of_size( u : List size : int parent_label : str )
+
+static generate_possible_sub_sets_of_size( u : List size : int parent_label : str )
Creates a list containing all possible subsets of the list u size parent_label
@@ -646,8 +646,8 @@ that do not contains a the node identified by
-
-save_plot_estimated_structure_graph( file_path : str ) → None
+
+save_plot_estimated_structure_graph( file_path : str ) → None
Plot the estimated structure in a graphical model style, use .png extension.
Parameters
@@ -660,8 +660,8 @@ that do not contains a the node identified by
-
-save_results( file_path : str ) → None
+
+save_results( file_path : str ) → None
Save the estimated Structure to a .json file in file_path.
Parameters
@@ -671,8 +671,8 @@ that do not contains a the node identified by
-
-spurious_edges( ) → List
+
+spurious_edges( ) → List
Return the spurious edges present in the estimated structure, if a prior net structure is present in _sample_path.structure
-PyCTBN.PyCTBN.estimators.structure_score_based_estimator module
+
+pyctbn.legacy.estimators.structure_score_based_estimator module
-
-class PyCTBN.PyCTBN.estimators.structure_score_based_estimator.StructureScoreBasedEstimator( sample_path : PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath tau_xu : int = 0.1 alpha_xu : int = 1 known_edges : List = [] )
-Bases: PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator
+
+class pyctbn.legacy.estimators.structure_score_based_estimator.StructureScoreBasedEstimator( sample_path : pyctbn.legacy.structure_graph.sample_path.SamplePath tau_xu : int = 0.1 alpha_xu : int = 1 known_edges : List = [] )
+Bases: pyctbn.legacy.estimators.structure_estimator.StructureEstimator
Has the task of estimating the network structure given the trajectories in samplepath by
using a score based approach and differt kinds of optimization algorithms.
Parameters
-sample_path (SamplePath
sample_path (SamplePath
tau_xu (float , optional ) – hyperparameter over the CTBN’s q parameters, default to 0.1
alpha_xu (float , optional ) – hyperparameter over the CTBN’s q parameters, default to 1
known_edges (List , optional ) – List of known edges, default to []
-
-estimate_parents( node_id : str max_parents : int = None iterations_number : int = 40 patience : int = 10 tabu_length : int = None tabu_rules_duration : int = 5 optimizer : str = 'hill' )
+
+estimate_parents( node_id : str max_parents : int = None iterations_number : int = 40 patience : int = 10 tabu_length : int = None tabu_rules_duration : int = 5 optimizer : str = 'hill' )
Use the FamScore of a node in order to find the best parent nodes
Parameters
@@ -734,8 +734,8 @@ using a score based approach and differt kinds of optimization algorithms.
-
-estimate_structure( max_parents : int = None iterations_number : int = 40 patience : int = None tabu_length : int = None tabu_rules_duration : int = None optimizer : str = 'tabu' disable_multiprocessing : bool = False processes_number : int = None )
+
+estimate_structure( max_parents : int = None iterations_number : int = 40 patience : int = None tabu_length : int = None tabu_rules_duration : int = None optimizer : str = 'tabu' disable_multiprocessing : bool = False processes_number : int = None )
Compute the score-based algorithm to find the optimal structure
Parameters
@@ -756,8 +756,8 @@ using a score based approach and differt kinds of optimization algorithms.
-
-get_score_from_graph( graph : PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph node_id : str )
+
+get_score_from_graph( graph : pyctbn.legacy.structure_graph.network_graph.NetworkGraph node_id : str )
Get the FamScore of a node
Parameters
@@ -778,8 +778,8 @@ using a score based approach and differt kinds of optimization algorithms.
-
@@ -789,10 +789,10 @@ using a score based approach and differt kinds of optimization algorithms.
diff --git a/docs-out/_build/html/PyCTBN.PyCTBN.html b/docs/_build/html/PyCTBN.PyCTBN.html
similarity index 50%
rename from docs-out/_build/html/PyCTBN.PyCTBN.html
rename to docs/_build/html/PyCTBN.PyCTBN.html
index 29ef30a..4f020cc 100644
--- a/docs-out/_build/html/PyCTBN.PyCTBN.html
+++ b/docs/_build/html/PyCTBN.PyCTBN.html
@@ -8,7 +8,7 @@
PyCTBN.PyCTBN package — PyCTBN 2.0 documentation
+ pyctbn.legacy package — PyCTBN 2.0 documentation
@@ -27,7 +27,7 @@
href="genindex.html"/>
Contents: