How to use
============

Example
++++++++++++
(Data: https://github.com/RomiconEZ/CFLG/tree/main/tests/email-Eu-core-temporal-Dept3)

.. code:: python

    from pathlib import Path
    import pandas as pd
    from IPython.core.display_functions import display
    from sklearn import linear_model, pipeline, preprocessing
    from cflg import graph_features_auc_score_tables, features_for_edges_of_static_graph

    def test_graph_features_auc_score_tables() -> None:
        cls_model = pipeline.make_pipeline(
            preprocessing.StandardScaler(), linear_model.LogisticRegression(max_iter=10000, n_jobs=-1, random_state=42)
        )

        Networks = ["email-Eu-core-temporal-Dept3"]

        current_path = Path(__file__).parent
        networks_files_names = [str(current_path / name / f"out.{name}") for name in Networks]

        datasets_info = {
            "Network": Networks,
            "Label": ["EU"],
            "Category": ["Social"],
            "Edge type": ["Multi"],
            "Path": networks_files_names,
        }

        datasets_info = pd.DataFrame(datasets_info)
        datasets_info = datasets_info.iloc[0:1]

        (
            latex_feature_network_table_1,
            latex_feature_network_table_2,
            latex_feature_network_table_3,
            latex_feature_network_table_4,
            latex_auc_table,
        ) = graph_features_auc_score_tables(datasets_info, cls_model=cls_model, verbose=True)

        print(latex_feature_network_table_1)
        print(latex_feature_network_table_2)
        print(latex_feature_network_table_3)
        print(latex_feature_network_table_4)
        print(latex_auc_table)
        return


    def test_features_for_static_graph() -> None:
        def display_dataframe(df):
            with pd.option_context("display.max_columns", None):  # Показать все колонки
                display(df.head(5))  # Вывести первые 5 строк

        current_path = Path(__file__).parent
        name = "email-Eu-core-temporal-Dept3"
        path_to_data = str(current_path / name / f"out.{name}")

        X = features_for_edges_of_static_graph(path_to_data, verbose=True)

        return