Class: TrailGuide::Calculators::Bayesian

Inherits:
Calculator
  • Object
show all
Defined in:
lib/trail_guide/calculators/bayesian.rb

Instance Attribute Summary collapse

Attributes inherited from Calculator

#choice, #experiment, #goal, #probability

Class Method Summary collapse

Instance Method Summary collapse

Methods inherited from Calculator

#base, #best, #variants, #variants_with_conversion, #worst

Constructor Details

#initialize(*args, beta: nil, **opts) ⇒ Bayesian

Returns a new instance of Bayesian.

Raises:

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# File 'lib/trail_guide/calculators/bayesian.rb', line 10

def initialize(*args, beta: nil, **opts)
  raise NoIntegrationLibrary if !defined?(::Integration)

  if beta.nil?
    # prefer rubystats if not specified
    if defined?(::Rubystats)
      beta = :rubystats
    elsif defined?(::Distribution)
      beta = :distribution
    else
      raise NoBetaDistributionLibrary
    end
  end

  case beta.to_sym
  when :distribution
    raise NoBetaDistributionLibrary, beta unless defined?(::Distribution)
    TrailGuide.logger.debug "Using Distribution::Beta to calculate beta distributions"
    TrailGuide.logger.debug "GSL detected, Distribution::Beta will use GSL for better performance" if defined?(::GSL)
  when :rubystats
    raise NoBetaDistributionLibrary, beta unless defined?(::Rubystats)
    TrailGuide.logger.debug "Using Rubystats::BetaDistribution to calculate beta distributions"
  else
    raise UnknownBetaDistributionLibrary, beta
  end

  super(*args, **opts)
  @beta = beta.to_sym
end

Instance Attribute Details

#beta ⇒ Object (readonly)

Returns the value of attribute beta.


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# File 'lib/trail_guide/calculators/bayesian.rb', line 8

def beta
  @beta
end

Class Method Details

.enabled? ⇒ Boolean

Returns:

  • (Boolean)
[View source]

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# File 'lib/trail_guide/calculators/bayesian.rb', line 4

def self.enabled?
  !!(defined?(::Integration) && (defined?(::Rubystats) || defined?(::Distribution)))
end

Instance Method Details

#calculate! ⇒ Object

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# File 'lib/trail_guide/calculators/bayesian.rb', line 71

def calculate!
  variants_with_conversion.each do |variant|
    expvar = experiment.variants.find { |var| var.name == variant.name }
    vprob = variant_probability(variant)
    variant.probability = vprob
    variant.significance = TrailGuide::Calculators::SIGNIFICANT_PROBABILITIES.reverse.find { |pct| vprob >= pct } || 0

    #if worst && variant.measure > worst.measure
    #  variant.difference = (variant.measure - worst.measure) / worst.measure * 100
    #end
    if base
      if variant.measure > base.measure
        variant.difference = (variant.measure - base.measure) / base.measure * 100
      elsif base.measure > variant.measure
        variant.difference = -((base.measure - variant.measure) / base.measure * 100)
      else
        variant.difference = 0
      end
    end
  end

  @choice = best && best.probability >= probability ? best : nil

  self
end

#cdf(variant, z) ⇒ Object

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# File 'lib/trail_guide/calculators/bayesian.rb', line 50

def cdf(variant, z)
  x = variant.subset
  n = variant.superset
  if beta == :distribution
    Distribution::Beta.cdf(z, x+1, n-x+1)
  else
    Rubystats::BetaDistribution.new(x+1, n-x+1).cdf(z)
  end
end

#pdf(variant, z) ⇒ Object

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# File 'lib/trail_guide/calculators/bayesian.rb', line 40

def pdf(variant, z)
  x = variant.subset
  n = variant.superset
  if beta == :distribution
    Distribution::Beta.pdf(z, x+1, n-x+1)
  else
    Rubystats::BetaDistribution.new(x+1, n-x+1).pdf(z)
  end
end

#variant_probability(variant) ⇒ Object

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# File 'lib/trail_guide/calculators/bayesian.rb', line 60

def variant_probability(variant)
  Integration.integrate(0, 1, tolerance: 1e-4) do |z|
    vpdf = pdf(variant, z)
    variants.each do |var|
      next if var == variant
      vpdf = vpdf * cdf(var, z)
    end
    vpdf
  end * 100.0
end