quantificationlib.plot module

Visualization related functions

plot_boxes(ax, error_matrix, vert=None, y_title=None, x_title=None, labels=None, colors=None)

Function to build a boxplot to visually show the error distribution of experiments

Parameters:

• ax (Axes) – The axes to draw to

• error_matrix (ndarray, shape(number_of_experiments, number_of_systems)) – Error values of the experiments

• vert (bool, default: True) – If True, draws vertical boxes. If False, draw horizontal boxes.

• y_title (str, optional) – y-axis title

• x_title (str, optional) – x-axis title

• labels (list, optional) – Label for each system

• colors (list, optional) – List of colors for boxes. If None default colors are used

plot_line_prevalences(ax, prevalence_matrix, order=None, colors=None)

Function to build a graph to represent prevalences of experiments in a linear form. Each horizontal line corresponds to one experiment, each color is a class and its horizontal length corresponds to its proportion (prevalence).

Parameters:

• ax (Axes) – The axes to draw to

• prevalence_matrix (ndarray, shape(number_of_experiments, number_of_clases)) – Prevalences of the experiments

• order (str, optional) – To sort matrix based on the first column in order “ascending”, “desdending” or None

• colors (list, optional) – List of colors for classes. If None list(mcolors.TABLEAU_COLORS) are used