Merge pull request #24 from krzysztofarendt/dev

Dev

README.md

@@ -14,6 +14,8 @@ Main features:
 By **default** `modestga.minimize()` runs on all CPUs and divides the population into smaller subpopulations (1 per CPU)
 which exchange genes among one another at each generation. Alternatively, it can be run in a simplified parallel mode in which an exact copy of the initial population runs in parallel on each CPU and the best result among all is returned (`modestga.parallel.simple.minimize()`).
 
+[![Downloads](https://pepy.tech/badge/modestga)](https://pepy.tech/project/modestga)
+
 ## Installation
 ```
 pip install modestga
@@ -138,4 +140,4 @@ The performance of the parallel optimization was evaluated using a 128-dimension
 <p align="center">
 <img src="modestga/benchmark/results/comparison_parallel.png" align="center">
 <div align="center">Figure 3: Parallel minimization performance</div>
-</p>
+</p>

modestga/benchmark/functions/rastrigin.py

@@ -2,7 +2,7 @@
 import time
 
 
-def rastrigin(x):
+def rastrigin(x, *args):
     """Rastrigin function to be minimized.
 
     Global minimum y=0 at x=[0, 0, ..., 0].
@@ -13,7 +13,7 @@ def rastrigin(x):
     y = A * n + np.sum(x ** 2 - A * np.cos(2 * np.pi * x))
     return y
 
-def rastrigin_delayed(x):
+def rastrigin_delayed(x, *args):
     """Rastrigin function to be minimized.
 
     Global minimum y=0 at x=[0, 0, ..., 0].

setup.py

@@ -2,7 +2,7 @@
 import setuptools
 
 setup(name='modestga',
-      version='0.5.5',
+      version='0.5.6',
       description='Genetic Algorithm minimization',
       url='https://github.com/krzysztofarendt/modestga',
       keywords='genetic algorithm optimization',