import sys sys.path.append("./classes/") import json import typing import pandas as pd import abstract_importer as ai class JsonImporter(ai.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 :param file_path: the path of the file that contains tha data to be imported :type file_path: string :param samples_label: the reference key for the samples in the trajectories :type samples_label: string :param structure_label: the reference key for the structure of the network data :type structure_label: string :param variables_label: the reference key for the cardinalites of the nodes data :type variables_label: string :param time_key: the key used to identify the timestamps in each trajectory :type time_key: string :param variables_key: the key used to identify the names of the variables in the net :type variables_key: string :param array_indx: the index of the outer JsonArray to exctract the data from :type array_indx: int :_df_samples_list: a Dataframe list in which every dataframe contains a trajectory """ def __init__(self, file_path: str, samples_label: str, structure_label: str, variables_label: str, time_key: str, variables_key: str, array_indx: int): """Constructor method """ self._samples_label = samples_label self._structure_label = structure_label self._variables_label = variables_label self._time_key = time_key self._variables_key = variables_key self._df_samples_list = None self._array_indx = array_indx super(JsonImporter, self).__init__(file_path) def import_data(self) -> None: """Implements the abstract method of :class:`AbstractImporter` """ raw_data = self.read_json_file() self._df_samples_list = self.import_trajectories(raw_data) self._sorter = self.build_sorter(self._df_samples_list[0]) self.compute_row_delta_in_all_samples_frames(self._df_samples_list) self.clear_data_frame_list() self._df_structure = self.import_structure(raw_data) self._df_variables = self.import_variables(raw_data) def import_trajectories(self, raw_data: typing.List) -> typing.List: """Imports the trajectories from the list of dicts ``raw_data``. :param raw_data: List of Dicts :type raw_data: List :return: List of dataframes containing all the trajectories :rtype: List """ return self.normalize_trajectories(raw_data, self._array_indx, self._samples_label) def import_structure(self, raw_data: typing.List) -> pd.DataFrame: """Imports in a dataframe the data in the list raw_data at the key ``_structure_label`` :param raw_data: List of Dicts :type raw_data: List :return: Dataframe containg the starting node a ending node of every arc of the network :rtype: pandas.Dataframe """ return self.one_level_normalizing(raw_data, self._array_indx, self._structure_label) def import_variables(self, raw_data: typing.List) -> pd.DataFrame: """Imports the data in ``raw_data`` at the key ``_variables_label``. :param raw_data: List of Dicts :type raw_data: List :return: Datframe containg the variables simbolic labels and their cardinalities :rtype: pandas.Dataframe """ return self.one_level_normalizing(raw_data, self._array_indx, self._variables_label) def read_json_file(self) -> typing.List: """Reads the JSON file in the path self.filePath :return: The contents of the json file :rtype: List """ with open(self._file_path) as f: data = json.load(f) return data def one_level_normalizing(self, raw_data: typing.List, indx: int, key: str) -> pd.DataFrame: """Extracts the one-level nested data in the list ``raw_data`` at the index ``indx`` at the key ``key``. :param raw_data: List of Dicts :type raw_data: List :param indx: The index of the array from which the data have to be extracted :type indx: int :param key: the key for the Dicts from which exctract data :type key: string :return: A normalized dataframe :rtype: pandas.Datframe """ return pd.DataFrame(raw_data[indx][key]) def normalize_trajectories(self, raw_data: typing.List, indx: int, trajectories_key: str) -> typing.List: """ Extracts the trajectories in ``raw_data`` at the index ``index`` at the key ``trajectories key``. :param raw_data: List of Dicts :type raw_data: List :param indx: The index of the array from which the data have to be extracted :type indx: int :param trajectories_key: the key of the trajectories objects :type trajectories_key: string :return: A list of daframes containg the trajectories :rtype: List """ dataframe = pd.DataFrame smps = raw_data[indx][trajectories_key] df_samples_list = [dataframe(sample) for sample in smps] return df_samples_list def build_sorter(self, sample_frame: pd.DataFrame) -> typing.List: """Implements the abstract method build_sorter of the :class:`AbstractImporter` for this dataset """ columns_header = list(sample_frame.columns.values) columns_header.remove(self._time_key) return columns_header def clear_data_frame_list(self) -> None: """Removes all values present in the dataframes in the list ``_df_samples_list``. """ for indx in range(len(self._df_samples_list)): self._df_samples_list[indx] = self._df_samples_list[indx].iloc[0:0] def dataset_id(self) -> object: return self._array_indx def import_sampled_cims(self, raw_data: typing.List, indx: int, cims_key: str) -> typing.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. :param raw_data: List of Dicts :type raw_data: List :param indx: The index of the array from which the data have to be extracted :type indx: int :param cims_key: the key where the json object cims are placed :type cims_key: string :return: a dictionary containing the sampled CIMS for all the variables in the net :rtype: Dictionary """ cims_for_all_vars = {} for var in raw_data[indx][cims_key]: sampled_cims_list = [] cims_for_all_vars[var] = sampled_cims_list for p_comb in raw_data[indx][cims_key][var]: cims_for_all_vars[var].append(pd.DataFrame(raw_data[indx][cims_key][var][p_comb]).to_numpy()) return cims_for_all_vars