GMCA_optimisation_problem/GMCA_plot_main.py at main · vj2Sheffield/GMCA_optimisation_problem · GitHub

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# -*- coding: utf-8 -*-
"""
Created on Tue Jan  7 15:32:40 2025

@author: Victoria Johnson
"""

import numpy as np
import pandas as pd

from GMCA_plotting_functions import plot_scatter_exploded, plot_boxplot_funding, plot_3d_scatter, plot_boxplot_percentages, plot_key_parcoord, violin_plot, get_max_min
from plot_hypervolume_progress import get_median_hypervolume

def plot_results_fcn(F, X, u_transformed):
    # Plotting funding for each of the subsystems
    plot_boxplot_funding(X)

    # Plotting objective space for nondominated solutions
    plot_3d_scatter(F)

    # Boxplot for post-optimisation PLW and SQ % points
    plot_boxplot_percentages(u_transformed)

    # Plot exploded scatter plot for objective-space solutions
    plot_scatter_exploded(F)

    # Plot parallel coordinate plot for key solutions
    plot_key_parcoord(F, X)

    # Plot violin plot for funding
    violin_plot(X)

if __name__ == "__main__":
    rep_no = get_median_hypervolume()
    F = np.array(pd.read_csv(f'Results/rep{str(rep_no)}_F.csv'))
    X = np.array(pd.read_csv(f'Results/rep{str(rep_no)}_X.csv'))
    PLW = np.array(pd.read_csv(f'Results/rep{str(rep_no)}_PLW.csv'))
    SAQ = np.array(pd.read_csv(f'Results/rep{str(rep_no)}_SAQ.csv'))
    u_transformed = np.zeros((X.shape[0], 20))
    u_transformed[:, 0:20:2] = PLW
    u_transformed[:, 1:20:2] = SAQ

    plot_results_fcn(F, X, u_transformed)

    get_max_min()