Class: Charty::Plotters::EstimateAggregator

Inherits:
Object
  • Object
show all
Defined in:
lib/charty/plotters/line_plotter.rb

Instance Method Summary collapse

Constructor Details

#initialize(estimator, error_bar, n_boot, random) ⇒ EstimateAggregator

Returns a new instance of EstimateAggregator.


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# File 'lib/charty/plotters/line_plotter.rb', line 4

def initialize(estimator, error_bar, n_boot, random)
  @estimator = estimator
  @method, @level = error_bar
  @n_boot = n_boot
  @random = random
end

Instance Method Details

#aggregate(data, var_name) ⇒ Object

Perform aggregation

Parameters:

  • data (Hash<Any, Charty::Table>)
  • var_name (Symbol, String)

    A column name to be aggregated


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# File 'lib/charty/plotters/line_plotter.rb', line 15

def aggregate(data, var_name)
  values = data[var_name]
  estimation = case @estimator
               when :count
                 values.length
               when :mean
                 values.mean
               end

  n = values.length
  case
  # No error bars
  when @method.nil?
    err_min = err_max = Float::NAN
  when n <= 1
    err_min = err_max = Float::NAN

  # User-defined method
  when @method.respond_to?(:call)
    err_min, err_max = @method.call(values)

  # Parametric
  when @method == :sd
    err_radius = values.stdev * @level
    err_min = estimation - err_radius
    err_max = estimation + err_radius
  when @method == :se
    err_radius = values.stdev / Math.sqrt(n)
    err_min = estimation - err_radius
    err_max = estimation + err_radius

  # Nonparametric
  when @method == :pi
    err_min, err_max = percentile_interval(values, @level)
  when @method == :ci
    # TODO: Support units
    err_min, err_max =
      Statistics.bootstrap_ci(values, @level, units: nil, func: @estimator,
                              n_boot: @n_boot, random: @random)
  end

  {
    var_name => estimation,
    "#{var_name}_min" => err_min,
    "#{var_name}_max" => err_max
  }
end

#percentile_interval(values, width) ⇒ Object


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# File 'lib/charty/plotters/line_plotter.rb', line 63

def percentile_interval(values, width)
  q = [50 - width / 2, 50 + width / 2]
  Statistics.percentile(values, q)
end