From 10b5a511ca70fe3831475e066aa07be787c91fd7 Mon Sep 17 00:00:00 2001 From: Krzysztof Rudnicki Date: Wed, 12 Apr 2023 19:21:12 +0200 Subject: [PATCH] feat: add counting generating time --- lab3/main.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/lab3/main.py b/lab3/main.py index 2bac542d..0723edc9 100644 --- a/lab3/main.py +++ b/lab3/main.py @@ -4,6 +4,7 @@ Program that optimizes Rastrigin function: f (x, y) = Using Evolutionary Strategy (μ, λ). """ import sys +import time import numpy as np @@ -51,7 +52,7 @@ def evolution_strategy( low=min_max[0], high=min_max[1], size=( size_of_population, 2)) - # Iterate untill we reach max number of generate and terminate + # Iterate untill we reach max number of generate and terminate for generation_number in range(number_of_generations): fitness, population = generate( generation_number, @@ -129,12 +130,19 @@ def user_input(): if __name__ == "__main__": # Run the Evolutionary Strategy algorithm ARGUMENTS = user_input() + start_time = time.perf_counter() best_individual, best_fitness = evolution_strategy( ARGUMENTS["number_of_parents"], ARGUMENTS["size_of_population"], ARGUMENTS["mutation_strength"], ARGUMENTS["number_of_generations"], (ARGUMENTS["min"], ARGUMENTS["max"])) + end_time = time.perf_counter() + total_generation_time = end_time - start_time + time_per_generation = total_generation_time / \ + ARGUMENTS["number_of_generations"] print("Best individual found:", best_individual) print("Best fitness found:", best_fitness) + print("total_generation_time: ", total_generation_time) + print("time_per_generation: ", time_per_generation)