Visualization module

class visualization.Dataset_visualise(data_set, name='dataset', columns=None)

Bases: object

A class for visualizing datasets.

Parameters:

• data_set (dict): The dataset containing the data, labels, weights, and detailed labels.

• name (str): The name of the dataset (default: “dataset”).

• columns (list): The list of column names to consider (default: None, which includes all columns).

Attributes:

• dfall (DataFrame): The dataset.

• target (Series): The labels.

• weights (Series): The weights.

• detailed_label (ndarray): The detailed labels.

• columns (list): The list of column names.

• name (str): The name of the dataset.

• keys (ndarray): The unique detailed labels.

• weight_keys (dict): The weights for each detailed label.

Methods:

• examine_dataset(): Prints information about the dataset.

• histogram_dataset(columns=None): Plots histograms of the dataset features.

• correlation_plots(columns=None): Plots correlation matrices of the dataset features.

• pair_plots(sample_size=10, columns=None): Plots pair plots of the dataset features.

• stacked_histogram(field_name, mu_hat=1.0, bins=30): Plots a stacked histogram of a specific field in the dataset.

• pair_plots_syst(df_syst, sample_size=10): Plots pair plots between the dataset and a system dataset.

correlation_plots(columns=None)

Plots correlation matrices of the dataset features.

Args: * columns (list): The list of column names to consider (default: None, which includes all columns).

event_vise_syst(df_syst, columns=None, sample_size=100)

event_vise_syst_arrow(df_syst, columns=None, sample_size=100)

examine_dataset()

Prints information about the dataset.

histogram_dataset(columns=None, nbin=25)

Plots histograms of the dataset features.

Args:

• columns (list): The list of column names to consider (default: None, which includes all columns).

• nbin (int): The number of bins for the histogram (default: 25).

histogram_syst(df_syst, weight_syst, columns=None, nbin=25)

pair_plots(sample_size=10, columns=None)

Plots pair plots of the dataset features.

Args:

• sample_size (int): The number of samples to consider (default: 10).

• columns (list): The list of column names to consider (default: None, which includes all columns).

pair_plots_syst(df_syst, sample_size=100)

Plots pair plots between the dataset and a system dataset.

Args:

• df_syst (DataFrame): The system dataset.

• sample_size (int): The number of samples to consider (default: 10).

..images:: ../images/pair_plot_syst.png

stacked_histogram(field_name, mu_hat=1.0, bins=30, y_scale='linear')

Plots a stacked histogram of a specific field in the dataset.

Args:

• field_name (str): The name of the field to plot.

• mu_hat (float): The value of mu (default: 1.0).

• bins (int): The number of bins for the histogram (default: 30).

visualization.custom_pretty_print(d)

visualization.roc_curve_wrapper(score, labels, weights, plot_label='model', color='b', lw=2)

Plots the ROC curve.

Args:

• score (ndarray): The score.

• labels (ndarray): The labels.

• weights (ndarray): The weights.

• plot_label (str, optional): The plot label. Defaults to “model”.

• color (str, optional): The color. Defaults to “b”.

• lw (int, optional): The line width. Defaults to 2.

visualization.visualize_coverage(ingestion_result_dict, ground_truth_mus)

Plots a coverage plot of the mu values.

Args:

• ingestion_result_dict (dict): A dictionary containing the ingestion results.

• ground_truth_mus (dict): A dictionary of ground truth mu values.

visualization.visualize_scatter(ingestion_result_dict, ground_truth_mus)

Plots a scatter Plot of ground truth vs. predicted mu values.

Args:

• ingestion_result_dict (dict): A dictionary containing the ingestion results.

• ground_truth_mus (dict): A dictionary of ground truth mu values.