Class: CrossEntropy::AbstractProblem

Inherits:
Object
  • Object
show all
Defined in:
lib/cross_entropy/abstract_problem.rb

Overview

Base class for specific problem types.

Direct Known Subclasses

BetaProblem, ContinuousProblem, MatrixProblem

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(params) {|_self| ... } ⇒ AbstractProblem

Returns a new instance of AbstractProblem.

Parameters:

  • params (Array)

Yields:

  • (_self)

Yield Parameters:



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# File 'lib/cross_entropy/abstract_problem.rb', line 11

def initialize(params)
  @params = params

  @max_iters = nil
  @track_overall_min = false
  @overall_min_score = 1.0 / 0.0
  @overall_min_score_sample = nil

  @generate_samples = proc { raise 'no generating function provided' }
  @score_sample     = proc { |_sample| raise 'no score block provided' }
  @estimate         = proc { |_elite| raise 'no estimate block provided' }
  @update           = proc { |estimated_params| estimated_params }
  @stop_decision    = proc do
    raise 'no max_iters provided' unless max_iters
    num_iters >= max_iters
  end

  yield(self) if block_given?
end

Instance Attribute Details

#elite_score ⇒ Object (readonly)

Returns the value of attribute elite_score.



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# File 'lib/cross_entropy/abstract_problem.rb', line 59

def elite_score
  @elite_score
end

#max_iters ⇒ Object

Returns the value of attribute max_iters.



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# File 'lib/cross_entropy/abstract_problem.rb', line 35

def max_iters
  @max_iters
end

#min_score ⇒ Object (readonly)

Returns the value of attribute min_score.



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# File 'lib/cross_entropy/abstract_problem.rb', line 58

def min_score
  @min_score
end

#num_elite ⇒ Object

Returns the value of attribute num_elite.



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# File 'lib/cross_entropy/abstract_problem.rb', line 34

def num_elite
  @num_elite
end

#num_iters ⇒ Object (readonly)

Returns the value of attribute num_iters.



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# File 'lib/cross_entropy/abstract_problem.rb', line 57

def num_iters
  @num_iters
end

#num_samples ⇒ Object

Returns the value of attribute num_samples.



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# File 'lib/cross_entropy/abstract_problem.rb', line 33

def num_samples
  @num_samples
end

#overall_min_score ⇒ Object (readonly)

Keep track of the best sample we’ve ever seen; if the scoring function is deterministic, then this is a quantity of major interest.



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# File 'lib/cross_entropy/abstract_problem.rb', line 63

def overall_min_score
  @overall_min_score
end

#overall_min_score_sample ⇒ Object (readonly)

Returns the value of attribute overall_min_score_sample.



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# File 'lib/cross_entropy/abstract_problem.rb', line 64

def overall_min_score_sample
  @overall_min_score_sample
end

#params ⇒ Object

Returns the value of attribute params.



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# File 'lib/cross_entropy/abstract_problem.rb', line 31

def params
  @params
end

#track_overall_min ⇒ Object

Returns the value of attribute track_overall_min.



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# File 'lib/cross_entropy/abstract_problem.rb', line 65

def track_overall_min
  @track_overall_min
end

Instance Method Details

#for_stop_decision(&block) ⇒ Object 



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# File 'lib/cross_entropy/abstract_problem.rb', line 53

def for_stop_decision(&block)
  @stop_decision = block
end

#solve ⇒ Object

Generic cross entropy routine.



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# File 'lib/cross_entropy/abstract_problem.rb', line 70

def solve
  @num_iters = 0

  loop do
    @min_score   = nil
    @elite_score = nil

    samples = @generate_samples.call

    # Score each sample.
    scores = NArray.float(num_samples)
    (0...num_samples).each do |i|
      sample_i = samples[i, true]
      score_i  = @score_sample.call(sample_i)

      # Keep track of best ever if requested.
      if track_overall_min && score_i < overall_min_score
        @overall_min_score        = score_i
        @overall_min_score_sample = sample_i
      end

      scores[i] = score_i
    end

    # Find elite quantile (gamma).
    scores_sorted = scores.sort
    @min_score   = scores_sorted[0]
    @elite_score = scores_sorted[num_elite - 1]

    # Take all samples with scores below (or equal to) gamma; note that
    # there may be more than num_elite, due to ties.
    elite = samples[(scores <= elite_score).where, true]

    # Compute new parameter estimates.
    estimated_params = @estimate.call(elite)

    # Update main parameter estimates.
    self.params = @update.call(estimated_params)

    @num_iters += 1
    break if @stop_decision.call
  end
end

#to_estimate(&block) ⇒ Object 



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# File 'lib/cross_entropy/abstract_problem.rb', line 45

def to_estimate(&block)
  @estimate = block
end

#to_generate_samples(&block) ⇒ Object 



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# File 'lib/cross_entropy/abstract_problem.rb', line 37

def to_generate_samples(&block)
  @generate_samples = block
end

#to_score_sample(&block) ⇒ Object 



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# File 'lib/cross_entropy/abstract_problem.rb', line 41

def to_score_sample(&block)
  @score_sample = block
end

#to_update(&block) ⇒ Object 



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# File 'lib/cross_entropy/abstract_problem.rb', line 49

def to_update(&block)
  @update = block
end