Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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66 lines
2.5 KiB
66 lines
2.5 KiB
import json
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import typing
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import pandas as pd
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import numpy as np
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import sys
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sys.path.append('../')
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import utility.abstract_importer as ai
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class SampleImporter(ai.AbstractImporter):
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#TODO: Scrivere documentazione
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"""Implements the abstracts methods of AbstractImporter and adds all the necessary methods to process and prepare
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the data in json extension.
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:param file_path: the path of the file that contains tha data to be imported
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:type file_path: string
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:param samples_label: the reference key for the samples in the trajectories
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:type samples_label: string
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:param structure_label: the reference key for the structure of the network data
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:type structure_label: string
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:param variables_label: the reference key for the cardinalites of the nodes data
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:type variables_label: string
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:param time_key: the key used to identify the timestamps in each trajectory
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:type time_key: string
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:param variables_key: the key used to identify the names of the variables in the net
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:type variables_key: string
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:_array_indx: the index of the outer JsonArray to extract the data from
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:type _array_indx: int
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:_df_samples_list: a Dataframe list in which every dataframe contains a trajectory
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:_raw_data: The raw contents of the json file to import
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:type _raw_data: List
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"""
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def __init__(self, trajectory_list: typing.Union[pd.DataFrame, np.ndarray] = None,
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variables: pd.DataFrame = None, prior_net_structure: pd.DataFrame = None):
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super(SampleImporter, self).__init__(trajectory_list =trajectory_list,
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variables= variables,
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prior_net_structure=prior_net_structure)
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def import_data(self, header_column = None):
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if header_column is None:
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self._sorter = header_column
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else:
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self._sorter = self.build_sorter(self._df_samples_list[0])
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samples_list= self._df_samples_list
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if isinstance(samples_list, np.ndarray):
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samples_list = samples_list.tolist()
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self.compute_row_delta_in_all_samples_frames(samples_list)
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def build_sorter(self, sample_frame: pd.DataFrame) -> typing.List:
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"""Implements the abstract method build_sorter of the :class:`AbstractImporter` for this dataset.
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"""
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columns_header = list(sample_frame.columns.values)
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del columns_header[0]
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return columns_header
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def dataset_id(self) -> object:
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pass |