DIGNEA / DIGNEApy / 26040537195

coverage: 91.886% (-0.1%) from 91.988%
26040537195

push

github

amarrerod 
All tests passing in local. Updating examples to new interfaces.

2 of 2 new or added lines in 2 files covered. (100.0%)

24 existing lines in 9 files now uncovered.

1778 of 1935 relevant lines covered (91.89%)

1.84 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

96.0
/digneapy/visualize/_map_elites_evolution_plot.py
1 
#!/usr/bin/env python
2 
# -*-coding:utf-8 -*-
3 
"""
4 
@File    :   _map_elites_evolution_plot.py
5 
@Time    :   2024/09/18 11:04:14
6 
@Author  :   Alejandro Marrero
7 
@Version :   1.0
8 
@Contact :   amarrerd@ull.edu.es
9 
@License :   (C)Copyright 2024, Alejandro Marrero
10 
@Desc    :   None
11 
"""
12 









13



from typing import Optional




2✔





14












15



import matplotlib




2✔





16












17



matplotlib.use("Agg")  # Non-interactive backend




2✔





18



from pathlib import Path




2✔





19












20



import matplotlib.pyplot as plt




2✔





21



import pandas as pd




2✔





22



import seaborn as sns




2✔





23












24












25



def map_elites_evolution_plot(logbook=None, filename: Optional[str | Path] = ""):




2✔





26



    df = pd.DataFrame(logbook.select("avg"), columns=["avg"])




2✔





27



    df["min"] = logbook.select("min")




2✔





28



    df["max"] = logbook.select("max")




2✔





29



    df["Generation"] = logbook.select("gen")




2✔





30



    # Plot configuration










31



    plt.rcParams["font.family"] = "serif"




2✔





32



    plt.rcParams["font.sans-serif"] = [




2✔





33



        "Tahoma",










34



        "DejaVu Sans",










35



        "Lucida Grande",










36



        "Verdana",










37



    ]










38



    plt.rcParams["font.size"] = 16




2✔





39



    plt.figure(figsize=(12, 8))




2✔





40



    for key, color in zip(["avg", "min", "max"], ["blue", "green", "red"]):




2✔





41



        sns.lineplot(data=df, x="Generation", y=key, color=color, label=key)




2✔





42



    plt.legend(loc="best")




2✔





43



    plt.title(r"Evolution of fitness in the Map-Elites generator")




2✔





44



    plt.ylabel("Fitness")




2✔





45



    if filename:




2✔





46



        plt.savefig(filename)




2✔





47



    else:











UNCOV

48



        plt.show()




×








49



    plt.close()




2✔



















    

  • 

    •