#!/usr/bin/python

#

# Josh Lifton 2004

#

# Permission is hereby granted to use and abuse this document

# so long as proper attribution is given.

#

# This Python script demonstrates how to use the numarray package

# to generate and handle large arrays of data and how to use the

# matplotlib package to generate plots from the data and then save

# those plots as images. These images are then stitched together

# by Mencoder to create a movie of the plotted data. This script

# is for demonstration purposes only and is not intended to be

# for general use. In particular, you will likely need to modify

# the script to suit your own needs.

#

import matplotlib

matplotlib.use('Agg')

import matplotlib.pyplot as plt # For plotting graphs.

from pylab import *

import numpy as np

import subprocess # For issuing commands to the OS.

import os

import sys # For determining the Python version.

from ssga import SSGA

import libpycec2005 as cec2005

import aspects

#

# Print the version information for the machine, OS,

# Python interpreter, and matplotlib. The version of

# Mencoder is printed when it is called.

#

print 'Executing on', os.uname()

print 'Python version', sys.version

print 'matplotlib version', matplotlib.__version__

not_found_msg = """

"""

try:

subprocess.check_call(['mencoder'])

except subprocess.CalledProcessError:

print "mencoder command was found"

pass # mencoder is found, but returns non-zero exit as expected

# This is a quick and dirty check; it leaves some spurious output

# for the user to puzzle over.

except OSError:

print not_found_msg

sys.exit("quitting\n")

#

# First, let's create some data to work with. In this example

# we'll use a normalized Gaussian waveform whose mean and

# standard deviation both increase linearly with time. Such a

# waveform can be thought of as a propagating system that loses

# coherence over time, as might happen to the probability

# distribution of a clock subjected to independent, identically

# distributed Gaussian noise at each time step.

#

print 'Initializing data set...' # Let the user know what's happening.

eval = 0

def fitness_sphere(sol):

return np.sqrt(sol[0]**2+sol[1]**2)

def fitness_rosenbrock(sol):

return F

if len(sys.argv)<=1:

sys.exit("Lacking the function value")

fun = int(sys.argv[1])

if (fun <= 0 or fun > 25):

sys.exit("Function %d non valide" %fun)

if len(sys.argv)>2:

fname = sys.argv[2]

else:

fname = 'output'

# Init cec2005

dim=2

cec2005.config(fun, dim)

domain = cec2005.domain(fun)

#domain = [-5,5]

#function_fitness = fitness_sphere

#function_fitness = fitness_rosenbrock

function_fitness = cec2005.evaluate

def algorithm_fitness(sol):

return function_fitness(sol)

ea = SSGA(domain=domain, size=50, dim=dim, fitness=algorithm_fitness)

# Initialize variables needed to create and store the example data set.

numberOfTimeSteps = 100

stepframe=5 # Number of frames we want in the movie.

# Create an array of zeros and fill it with the example data.

frame=0

def save():

print 'Wrote file', filename

line = None

fig = None

def scale_var(value):

return (value-minvar)*rangevar

# Now that we have an example data set (x,y) to work with, we can

# start graphing it and saving the images.

def measureFitness(*args, **kwargs):

save()

def plot_function(minimum, maximum, dif):

plt.clf()

scale = 100/(domain[1]-domain[0])

plot_function(domain[0], domain[1], scale)

# Now that we have graphed images of the dataset, we will stitch them

# together using Mencoder to create a movie. Each image will become

# a single frame in the movie.

#

# We want to use Python to make what would normally be a command line

# call to Mencoder. Specifically, the command line call we want to

# emulate is (without the initial '#'):

# mencoder mf://*.png -mf type=png:w=800:h=600:fps=25 -ovc lavc -lavcopts vcodec=mpeg4 -oac copy -o output.avi

# See the MPlayer and Mencoder documentation for details.

command = ('mencoder',

'%s.avi' %fname)

#os.spawnvp(os.P_WAIT, 'mencoder', command)

print "\n\nabout to execute:\n%s\n\n" % ' '.join(command)

subprocess.check_call(command)

print "\n\n The movie was written to '%s.avi'" %fname

print "\n\n You may want to delete *.png now.\n\n"