plot_boxplot.py

import numpy as np
import pandas as pd 
import matplotlib.pyplot as plt

def run(results_directory, optimizer, objectivefunc, Iterations):
    plt.ioff()
    
    fileResultsDetailsData = pd.read_csv(results_directory + '/experiment_details.csv')
    for j in range (0, len(objectivefunc)):
            
        #Box Plot
        data = []      
            
        for i in range(len(optimizer)): 
            objective_name = objectivefunc[j]
            optimizer_name = optimizer[i]
            
            detailedData = fileResultsDetailsData[(fileResultsDetailsData["Optimizer"] == optimizer_name) & (fileResultsDetailsData["objfname"] == objective_name)]
            detailedData = detailedData["Iter" + str(Iterations)]
            detailedData = np.array(detailedData).T.tolist()
            data.append(detailedData)

        #, notch=True
        box=plt.boxplot(data,patch_artist=True,labels=optimizer)
        

        colors = ['#5c9eb7','#f77199', '#cf81d2','#4a5e6a','#f45b18',
        '#ffbd35','#6ba5a1','#fcd1a1','#c3ffc1','#68549d',
        '#1c8c44','#a44c40','#404636']
        for patch, color in zip(box['boxes'], colors):
            patch.set_facecolor(color)
         
        plt.legend(handles= box['boxes'], labels=optimizer, 
            loc="top right", bbox_to_anchor=(1.2,1.02))
        fig_name = results_directory + "/boxplot-" + objective_name + ".png"
        plt.savefig(fig_name, bbox_inches='tight')
        plt.clf()
        #plt.show()