PythonGeneticAlgorithm Code
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File | Date | Author | Commit |
---|---|---|---|
src | 2011-03-29 | gulda | [r83] |
.project | 2011-02-14 | gulda | [r3] |
.pydevproject | 2011-02-14 | gulda | [r3] |
README.txt | 2011-03-29 | gulda | [r84] |
############################################################################### ### ### ### WELCOME TO THE README.txt for GeneticAlgorithm Python project!! ### ### ### ############################################################################### DEPENDENCIES: To execute these applications you must have installed these python libraries: .matplotlib .numpy .pylab EXECUTABLES: There are 2 executables: .TestGA_FXY.py : Description: Simple script to run the GA to minimize a XY function. To run: prompt>python TestGA_FXY.py Output: During the execution the program show a plot of the current population evolving painted over the contour plot of the function.In the path of execution the application saves the last plot as a png file. On the console appears statistics of every generation .TestArgon3D.py : Description: Runs GA to obtain the optimal particle disposition of a system In this case 3 dimensions and 3 particles. To change these values, edit TestArgon.py and change the parameters. to run: prompt>python TestArgon.py output: during the execution the program show a plot of the better disposition of the current population. In 2 dimensions the plot is painted over the contour plot of the potential of the system. In the path of execution the application saves the last plot as a png file. On the console appears statistics of every generation .TestArgon2D.py : Description: The same as above but in 2 dimensions. 2 more executables are used to generate statistics of the performance of the algorithm depending on the parameters values(probability of mutation, probability of crossover...). These scripts are: TestGA.py TestGA_statistics.py These scripts should only be used to gather statistics but not to be used by the final user.