Tag: psp

Genetic Algorithms, News, Pyevolve, Time Waste

Travelling Salesman on Sony PSP using Stackless Python + Pyevolve

This is my first PoC of the Travelling Salesman Problem on PSP, since I’ve installed the Pyevolve on the Sony PSP,  I can optimize any problem while using the graphical interface of PSP (in that problem I’m using the 2D functions to plot the cities and the path) to show results in real-time. Here is the video, the quality is very low, I’ve used my cellphone 🙂

Here is the source code I’ve used, the Pyevolve version of this example is the development version r166, which in the future will be the 0.6 final release (I’m working on many new features yet, so it will take time to release), however, this PoC should work on 0.5 release too:

import psp2d, pspos

WHITE_COLOR = psp2d.Color(255,255,255)
CLEAR_COLOR = psp2d.Color(0,0,0,255)
RED_COLOR   = psp2d.Color(255, 0, 0)

cm     = []
coords = []
CITIES = 20

pspos.setclocks(333,166)
psp_scr  = psp2d.Screen()
psp_font = psp2d.Font('font.png')
psp_scr.clear(CLEAR_COLOR)
psp_font.drawText(psp_scr, 0, 5, "Loading Pyevolve modules...")
psp_scr.swap()

from pyevolve import G1DList
from pyevolve import GSimpleGA
from pyevolve import GAllele
from pyevolve import Mutators
from pyevolve import Crossovers
from pyevolve import Consts

from random import shuffle as rand_shuffle, randint as rand_randint
from math import sqrt

def cartesian_matrix(coords):
   """ A distance matrix """
   matrix={}
   for i,(x1,y1) in enumerate(coords):
      for j,(x2,y2) in enumerate(coords):
         dx, dy = x1-x2, y1-y2
         dist=sqrt(dx*dx + dy*dy)
         matrix[i,j] = dist
   return matrix

def tour_length(matrix, tour):
   """ Returns the total length of the tour """
   total = 0
   for i in range(CITIES):
      j      = (i+1)%CITIES
      total += matrix[tour[i], tour[j]]
   return total

def write_tour_to_img(coords, tour):
   """ The function to plot the graph """
   psp_scr.clear(CLEAR_COLOR)
   for i in range(CITIES):
      j      = (i+1)%CITIES
      city_i = tour[i]
      city_j = tour[j]
      x1, y1 = coords[city_i]
      x2, y2 = coords[city_j]
      psp_scr.drawLine(int(x1), int(y1), int(x2), int(y2), WHITE_COLOR)
      psp_font.drawText(psp_scr, int(x1)+7, int(y1)-5, str(i))
      psp_scr.fillRect(int(x1), int(y1), 6, 6, RED_COLOR)

   psp_scr.swap()

def G1DListTSPInitializator(genome, **args):
   """ The initializator for the TSP """
   lst = [i for i in xrange(genome.getListSize())]
   rand_shuffle(lst)
   genome.genomeList = lst

def evolve_callback(ga_engine):
   """ Callback called every generation by Pyevolve """
   write_tour_to_img(coords, ga_engine.bestIndividual())
   return False

def main_run():
   global cm, coords

   width, height = psp_scr.size
   coords = [(rand_randint(0, width),rand_randint(0, height))
                 for i in xrange(CITIES)]
   cm     = cartesian_matrix(coords)

   setOfAlleles = GAllele.GAlleles(homogeneous=True)
   range_allele = GAllele.GAlleleRange(0, len(coords)-1)
   setOfAlleles.add(range_allele)

   genome = G1DList.G1DList(len(coords))
   genome.setParams(allele=setOfAlleles)

   genome.evaluator.set(lambda chromosome: tour_length(cm, chromosome))
   genome.mutator.set(Mutators.G1DListMutatorSwap)
   genome.crossover.set(Crossovers.G1DListCrossoverOX)
   genome.initializator.set(G1DListTSPInitializator)

   ga = GSimpleGA.GSimpleGA(genome)
   ga.setMinimax(Consts.minimaxType["minimize"])
   ga.setGenerations(300)
   ga.setPopulationSize(200)
   ga.setCrossoverRate(1.0)
   ga.setMutationRate(0.1)
   ga.stepCallback.set(evolve_callback)

   ga.evolve()

if __name__ == "__main__":
   main_run()
Genetic Algorithms, Pyevolve, Python

Pyevolve on Sony PSP ! (genetic algorithms on PSP)

Sony PSP can be more interesting than funny sometimes. Few people know about the potential of the PSP port of Stackless Python 2.5.2. This great port of python was done by Carlos E. and you can find more information about the progress of the port on his blog.

Well, I’ve tested the Pyevolve GA framework on the Stackless Python for PSP and for my surprise, it worked without changing one single line of code on the framework due the fact of Pyevolve has been written in pure Python (except the platform specific issue like the Interactive Mode, but this issue is automaticly disabled on unsupported platforms).

So now, we have Genetic Algorithms on PSP.

Follow some screenshots (click to enlarge):

psp2psp1

The GA running on the PSP screenshot is the minimization of the Sphere function.

Here is the steps to install Pyevolve on PSP:

PSP Stackless Python Installation

1) First, create a directory called “python” on your PSP under the “/PSP/GAME” and the directory structure “/python/site-packages/” on the root of your memory stick (this last directory will be used to put Pyevolve later).
2) Copy the EBOOT.PBP and the python.zip files to this created directory;

Pyevolve Installation

3) Download the Pyevolve source and copy the directory called “pyevolve” to the created directory “/python/site-packages/”, the final directory structure will be: “/python/site-packages/pyevolve”

Ready ! Now you can import Pyevolve modules inside scripts on your PSP, of course you can’t use the graphical plotting tool or some DB Adapters of Pyevolve, but the GA Core it’s working very well.

Here is some basic usage of PSP Stackless Python port. I’ve used the psp2d module to show the information on screen. When I got more time, I’ll port the visualization of the TSP problem to use the psp2d, it will be nice to see Traveling Salesperson Problem running with real-time visualization on PSP =)

Related Links

Google Code Project of PSP Stackless Python

I'm starting a new course "Machine Learning: Foundations and Engineering" for 2024.