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 src 2011-03-29 gulda [r83]
 .project 2011-02-14 gulda [r3]
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 README.txt 2011-03-29 gulda [r84]

Read Me

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###  WELCOME TO THE README.txt for GeneticAlgorithm Python project!!        ###      
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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.