Class: Evopop::Population

Inherits:
Object
  • Object
show all
Defined in:
lib/evopop/population.rb

Overview

Represents the population that is being trained. Has various methods relevant to training.

Examples

population = Evopop::Population.new
... initialize population with parameters ...
population.train
population.crossover
population.mutate

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize ⇒ Population

Initializes the attributes with default values. This is not guaranteed to reach maxima.



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# File 'lib/evopop/population.rb', line 22

def initialize
  Evopop.config.instance_variables.each do |iv|
    instance_variable_set(
      iv,
      Evopop.config.instance_variable_get(iv)
    )
  end
  create
  self
end

Instance Attribute Details

#average_fitness ⇒ Object

Returns the value of attribute average_fitness.



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# File 'lib/evopop/population.rb', line 15

def average_fitness
  @average_fitness
end

#candidates ⇒ Object

Returns the value of attribute candidates.



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# File 'lib/evopop/population.rb', line 15

def candidates
  @candidates
end

#crossover_function ⇒ Object

Returns the value of attribute crossover_function.



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# File 'lib/evopop/population.rb', line 15

def crossover_function
  @crossover_function
end

#crossover_params ⇒ Object

Returns the value of attribute crossover_params.



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# File 'lib/evopop/population.rb', line 15

def crossover_params
  @crossover_params
end

#dna_len ⇒ Object

Returns the value of attribute dna_len.



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# File 'lib/evopop/population.rb', line 15

def dna_len
  @dna_len
end

#fitness_function ⇒ Object

Returns the value of attribute fitness_function.



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# File 'lib/evopop/population.rb', line 15

def fitness_function
  @fitness_function
end

#initial_range_max ⇒ Object

Returns the value of attribute initial_range_max.



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# File 'lib/evopop/population.rb', line 15

def initial_range_max
  @initial_range_max
end

#initial_range_min ⇒ Object

Returns the value of attribute initial_range_min.



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# File 'lib/evopop/population.rb', line 15

def initial_range_min
  @initial_range_min
end

#max_generations ⇒ Object

Returns the value of attribute max_generations.



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# File 'lib/evopop/population.rb', line 15

def max_generations
  @max_generations
end

#mutation_num ⇒ Object

Returns the value of attribute mutation_num.



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# File 'lib/evopop/population.rb', line 15

def mutation_num
  @mutation_num
end

#mutation_range_max ⇒ Object

Returns the value of attribute mutation_range_max.



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# File 'lib/evopop/population.rb', line 15

def mutation_range_max
  @mutation_range_max
end

#mutation_range_min ⇒ Object

Returns the value of attribute mutation_range_min.



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# File 'lib/evopop/population.rb', line 15

def mutation_range_min
  @mutation_range_min
end

#population_size ⇒ Object

Returns the value of attribute population_size.



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# File 'lib/evopop/population.rb', line 15

def population_size
  @population_size
end

Instance Method Details

#create ⇒ Object

Creates a new set of population. Should be called after all the parameters have been set to the attributes.



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# File 'lib/evopop/population.rb', line 35

def create
  @candidates = Array.new(@population_size) do
    dna = Evopop::Dna.new(
      @initial_range_min,
      @initial_range_max,
      @mutation_range_min,
      @mutation_range_max,
      @dna_len
    )
    candidate = Evopop::Candidate.new(dna)
    candidate
  end
end

#crossover ⇒ Object

Performs simple mechanism of crossover - in this case picks two random candidates in from a top percentile of the population and performs one point crossover, producing new offspring equal to the population size attribute.



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# File 'lib/evopop/population.rb', line 70

def crossover
  new_generation = []

  # For all the top candidates, take the top 2 and crossover
  (0...@population_size).each do
    children = @crossover_function.call(top_candidates.sample(2), @crossover_params)
    new_generation += children

    if new_generation.length >= population_size
      new_generation = new_generation.take(population_size)
      break
    end
  end

  @candidates = new_generation
end

#mutate ⇒ Object

Performs simple mutation over the next generation. In this case, it either adds or substracts an amount to each dimension given the mutation range attributes.



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# File 'lib/evopop/population.rb', line 90

def mutate
  mutated_candidates.each do |c|
    c.dna.dna_len_range.each do |i|
      c.dna.mutate(i)
    end
  end
end

#train ⇒ Object

Determines the fitness of the population and thereafter sorts it based on fitness descdending (high fitness first, low fitness last).



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# File 'lib/evopop/population.rb', line 51

def train
  average_fitness = 0
  @candidates.each do |c|
    c.fitness = fitness_function.call(c.dna)
    average_fitness += + c.fitness
  end

  average_fitness /= @population_size

  @average_fitness << average_fitness

  @candidates = @candidates.sort_by(&:fitness)
  @candidates = @candidates.reverse
end