ó BªVCc@sHdZddlZddlZddlmZdefd„ƒYZdS(sòImplement Roulette Wheel selection on a population. This implements Roulette Wheel selection in which individuals are selected from a population randomly, with their proportion of selection based on their relative fitness in the population. iÿÿÿÿN(tAbstractSelectiontRouletteWheelSelectioncBs,eZdZdd„Zd„Zd„ZRS(sçRoulette wheel selection proportional to individuals fitness. The implements a roulette wheel selector that selects individuals from the population, and performs mutation and crossover on the selected individuals. cCstj||||ƒdS(sØInitialize the selector. Arguments: o mutator -- A Mutation object which will perform mutation on an individual. o crossover -- A Crossover object which will take two individuals and produce two new individuals which may have had crossover occur. o repairer -- A class which can do repair on rearranged genomes to eliminate infeasible individuals. If set at None, so repair will be done. N(Rt__init__(tselftmutatort crossovertrepairer((s‘/oak/stanford/groups/akundaje/marinovg/programs/biopython-1.50.tar.gz/biopython-1.50/build/lib.linux-x86_64-2.7/Bio/GA/Selection/RouletteWheel.pyRscCs6|j|ƒ}|jƒ}|jƒg}xtt|ƒdƒD]ì}tjƒ}tjƒ}d}d} d} x^|D]V} || kr¤|| kr¤|| }n|| krÉ|| krÉ|| } n| } qyW|dk sëtdƒ‚| dk stdƒ‚|j|| ƒ\} } |j | | gƒqBW|S(sPerform selection on the population based using a Roulette model. Arguments: o population -- A population of organisms on which we will perform selection. The individuals are assumed to have fitness values which are due to their current genome. iisDidn't select organism onesDidn't select organism twoN( t _set_up_wheeltkeystsorttrangetlentrandomtNonetAssertionErrortmutate_and_crossovertextend(Rt populationt prob_wheeltprobstnew_populationt pair_spint choice_num_1t choice_num_2t chosen_org_1t chosen_org_2t prev_probtcur_probt new_org_1t new_org_2((s‘/oak/stanford/groups/akundaje/marinovg/programs/biopython-1.50.tar.gz/biopython-1.50/build/lib.linux-x86_64-2.7/Bio/GA/Selection/RouletteWheel.pytselect's,          cCsd}x|D]}||j7}q Wi}d}xH|D]@}t|jƒt|ƒ}tj|ƒ|||<||7}q7W|S(sòSet up the roulette wheel based on the fitnesses. This creates a fitness proportional 'wheel' that will be used for selecting based on random numbers. Returns: o A dictionary where the keys are the 'high' value that an individual will be selected. The low value is determined by the previous key in a sorted list of keys. For instance, if we have a sorted list of keys like: [.1, .3, .7, 1] Then the individual whose key is .1 will be selected if a number between 0 and .1 is chosen, the individual whose key is .3 will be selected if the number is between .1 and .3, and so on. The values of the dictionary are the organism instances. i(tfitnesstfloattcopy(RRt total_fitnesstorgt wheel_dictttotal_percentagetorg_percentage((s‘/oak/stanford/groups/akundaje/marinovg/programs/biopython-1.50.tar.gz/biopython-1.50/build/lib.linux-x86_64-2.7/Bio/GA/Selection/RouletteWheel.pyRUs  N(t__name__t __module__t__doc__R RRR(((s‘/oak/stanford/groups/akundaje/marinovg/programs/biopython-1.50.tar.gz/biopython-1.50/build/lib.linux-x86_64-2.7/Bio/GA/Selection/RouletteWheel.pyRs  .(R)R R!tAbstractRR(((s‘/oak/stanford/groups/akundaje/marinovg/programs/biopython-1.50.tar.gz/biopython-1.50/build/lib.linux-x86_64-2.7/Bio/GA/Selection/RouletteWheel.pyts