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#!/usr/bin/env python
"""Tests for Genetic Algorithm classes that provide selection capabilities.
# standard library
import sys
import random

# biopython
from Bio.Seq import MutableSeq

# local stuff
from Bio.GA.Organism import Organism
from Bio.GA.Selection.Diversity import DiversitySelection
from Bio.GA.Selection.Tournament import TournamentSelection
from Bio.GA.Selection.RouletteWheel import RouletteWheelSelection

# PyUnit
import unittest

def run_tests(argv):
    ALL_TESTS = [DiversitySelectionTest, TournamentSelectionTest,
    runner = unittest.TextTestRunner(sys.stdout, verbosity = 2)
    test_loader = unittest.TestLoader()
    test_loader.testMethodPrefix = 't_'
    for test in ALL_TESTS:
        cur_suite = test_loader.loadTestsFromTestCase(test)

# --- helper classes and functions

00034 class TestAlphabet:
    """Simple test alphabet.
    letters = ["0", "1", "2", "3"]

def test_fitness(genome):
    """Simple class for calculating fitnesses.
    genome_seq = genome.toseq()
    return int(genome_seq.data)

00045 class NoSelection:
    """A simple 'selection' class that just returns the generated population.
    def select(self, population):
        return population

00051 class NoMutation:
    """Simple 'mutation' class that doesn't do anything.
    def mutate(self, org):
        return org.copy()

00057 class NoCrossover:
    """Simple 'crossover' class that doesn't do anything.
    def do_crossover(self, org_1, org_2):
        return org_1.copy(), org_2.copy()

00063 class NoRepair:
    """Simple 'repair' class that doesn't do anything.
    def repair(self, org):
        return org.copy()

def random_genome():
    """Return a random genome string.
    alphabet = TestAlphabet()

    new_genome = ""
    for letter in range(3):
        new_genome += random.choice(alphabet.letters)

    return MutableSeq(new_genome, alphabet)

def random_organism():
    """Generate a random organism.
    genome = random_genome()
    return Organism(genome, test_fitness)

# --- the actual test classes

00088 class AbstractSelectionTest(unittest.TestCase):
    """Some base tests that all selection classes should pass.
    def setUp(self):
        raise NotImplementError("Need to subclass and define a selector.")

00094     def t_selection(self):
        """Test basic selection on a small population.
        pop = []
        for org_num in range(50):

        new_pop = self.selector.select(pop)

        assert len(new_pop) == len(pop), "Did not maintain population size."

00105 class DiversitySelectionTest(AbstractSelectionTest):
    """Test selection trying to maximize diversity.
    def setUp(self):
        self.selector = DiversitySelection(NoSelection(), random_genome)

00111     def t_get_new_organism(self):
        """Getting a new organism not in the new population.
        org = random_organism()
        old_pop = [org]
        new_pop = []

        new_org = self.selector._get_new_organism(new_pop, old_pop)
        assert new_org == org, "Got an unexpected organism %s" % new_org

00121     def t_no_retrive_organism(self):
        """Test not getting an organism already in the new population.
        org = random_organism()
        old_pop = [org]
        new_pop = [org]

        new_org = self.selector._get_new_organism(new_pop, old_pop)
        assert new_org != org, "Got organism already in the new population."

00131 class TournamentSelectionTest(AbstractSelectionTest):
    """Test selection based on a tournament style scheme.
    def setUp(self):
        self.selector = TournamentSelection(NoMutation(), NoCrossover(),
                                            NoRepair(), 2)

00138     def t_select_best(self):
        """Ensure selection of the best organism in a population of 2.
        org_1 = random_organism()
        while 1:
            org_2 = random_organism()

            if org_2.fitness < org_1.fitness:

        pop = [org_1, org_2]

        new_pop = self.selector.select(pop)

        for org in new_pop:
            assert org == org_1, "Got a worse organism selected."

00155 class RouletteWheelSelectionTest(AbstractSelectionTest):
    """Test selection using a roulette wheel selection scheme.
    def setUp(self):
        self.selector = RouletteWheelSelection(NoMutation(), NoCrossover(),

00162     def t_select_best(self):
        """Ensure selection of a best organism in a population of 2.
        worst_genome = MutableSeq("0", TestAlphabet())
        worst_org = Organism(worst_genome, test_fitness)

        better_genome = MutableSeq("1", TestAlphabet())
        better_org = Organism(better_genome, test_fitness)

        new_pop = self.selector.select([worst_org, better_org])
        for org in new_pop:
            assert org == better_org, "Worse organism unexpectly selected."
if __name__ == "__main__":

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