json_importer module

class json_importer.JsonImporter(file_path: str, samples_label: str, structure_label: str, variables_label: str, time_key: str, variables_key: str, array_indx: int)

Bases: abstract_importer.AbstractImporter

Implements the abstracts methods of AbstractImporter and adds all the necessary methods to process and prepare the data in json ext. with the following structure: [0]

|_ dyn.cims |_ dyn.str |_ samples |_ variabels

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 (int) – the index of the outer JsonArray to exctract the data from

_df_samples_list

a Dataframe list in which every dataframe contains a trajectory

build_sorter(sample_frame: pandas.core.frame.DataFrame) → List

Implements the abstract method build_sorter of the AbstractImporter for this dataset

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() → None

Implements the abstract method of AbstractImporter

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 at the key _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 at the index index at the key 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 at the index indx at the key 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