Class: SQA::GeneticProgram

Inherits:
Object
  • Object
show all
Defined in:
lib/sqa/gp.rb

Defined Under Namespace

Classes: Individual

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(stock:, population_size: 50, generations: 100, mutation_rate: 0.15, crossover_rate: 0.7, elitism_count: 2) ⇒ GeneticProgram

Returns a new instance of GeneticProgram.



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# File 'lib/sqa/gp.rb', line 57

def initialize(stock:, population_size: 50, generations: 100, mutation_rate: 0.15, crossover_rate: 0.7, elitism_count: 2)
  @stock = stock
  @population_size = population_size
  @generations = generations
  @mutation_rate = mutation_rate
  @crossover_rate = crossover_rate
  @elitism_count = elitism_count

  @population = []
  @best_individual = nil
  @generation = 0
  @history = []
  @gene_constraints = {}
  @fitness_evaluator = nil
end

Instance Attribute Details

#best_individual ⇒ Object (readonly)

Returns the value of attribute best_individual.



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# File 'lib/sqa/gp.rb', line 54

def best_individual
  @best_individual
end

#crossover_rate ⇒ Object

Returns the value of attribute crossover_rate.



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# File 'lib/sqa/gp.rb', line 55

def crossover_rate
  @crossover_rate
end

#elitism_count ⇒ Object

Returns the value of attribute elitism_count.



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# File 'lib/sqa/gp.rb', line 55

def elitism_count
  @elitism_count
end

#generation ⇒ Object (readonly)

Returns the value of attribute generation.



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# File 'lib/sqa/gp.rb', line 54

def generation
  @generation
end

#generations ⇒ Object

Returns the value of attribute generations.



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# File 'lib/sqa/gp.rb', line 55

def generations
  @generations
end

#history ⇒ Object (readonly)

Returns the value of attribute history.



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# File 'lib/sqa/gp.rb', line 54

def history
  @history
end

#mutation_rate ⇒ Object

Returns the value of attribute mutation_rate.



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# File 'lib/sqa/gp.rb', line 55

def mutation_rate
  @mutation_rate
end

#population ⇒ Object (readonly)

Returns the value of attribute population.



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# File 'lib/sqa/gp.rb', line 54

def population
  @population
end

#population_size ⇒ Object

Returns the value of attribute population_size.



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# File 'lib/sqa/gp.rb', line 55

def population_size
  @population_size
end

#stock ⇒ Object (readonly)

Returns the value of attribute stock.



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# File 'lib/sqa/gp.rb', line 54

def stock
  @stock
end

Instance Method Details

#define_genes(**constraints) ⇒ Object

Define the parameter space for evolution

Example:

gp.define_genes(
  indicator: [:rsi, :macd, :stoch],
  period: (5..30).to_a,
  buy_threshold: (20..40).to_a,
  sell_threshold: (60..80).to_a
)



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# File 'lib/sqa/gp.rb', line 82

def define_genes(**constraints)
  @gene_constraints = constraints
  self
end

#evolve ⇒ Object

Run the genetic algorithm evolution



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# File 'lib/sqa/gp.rb', line 108

def evolve
  raise "Gene constraints not defined. Call define_genes first." if @gene_constraints.empty?
  raise "Fitness evaluator not defined. Call fitness with a block." unless @fitness_evaluator

  initialize_population

  @generations.times do |gen|
    @generation = gen + 1

    # Evaluate fitness for each individual
    evaluate_population

    # Track best individual
    current_best = @population.max_by(&:fitness)
    if @best_individual.nil? || current_best.fitness > @best_individual.fitness
      @best_individual = current_best.clone
    end

    # Record history
    avg_fitness = @population.sum(&:fitness) / @population.size.to_f
    @history << {
      generation: @generation,
      best_fitness: current_best.fitness,
      avg_fitness: avg_fitness,
      best_genes: current_best.genes.dup
    }

    # Print progress
    puts "Generation #{@generation}: Best=#{current_best.fitness.round(2)}%, Avg=#{avg_fitness.round(2)}%"

    # Create next generation
    @population = create_next_generation
  end

  # Final evaluation
  evaluate_population
  current_best = @population.max_by(&:fitness)
  if @best_individual.nil? || current_best.fitness > @best_individual.fitness
    @best_individual = current_best.clone
  end

  puts "\nEvolution complete!"
  puts "Best individual: #{@best_individual}"

  @best_individual
end

#fitness(&block) ⇒ Object

Define how to evaluate fitness for an individual

The block receives an individual’s genes hash and should return a numeric fitness value (higher is better)

Example:

gp.fitness do |genes|
  backtest = SQA::Backtest.new(
    stock: stock,
    strategy: create_strategy_from_genes(genes),
    initial_capital: 10_000
  )
  results = backtest.run
  results.total_return # Higher return = higher fitness
end



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# File 'lib/sqa/gp.rb', line 102

def fitness(&block)
  @fitness_evaluator = block
  self
end