Class: SciYAG::Backends::StandardDeviationFilter

Inherits:
Filter
  • Object
show all
Includes:
Dobjects
Defined in:
lib/SciYAG/Backends/filters/average.rb

Instance Method Summary collapse

Methods inherited from Filter

describe

Methods included from Descriptions::DescriptionExtend

#base_ancestor?, #description, #description_hash, #description_hash_base, #description_list, #description_list_base, extend_object, #inherit, #init_param, #init_params, #lookup_description_extend_ancestor, #param, #param_noaccess, #register_description, #set_description, #set_description_hash_base, #set_description_list_base

Methods included from Descriptions::DescriptionInclude

#description, #fill_parser, #long_name, #parser_banner, #parser_options

Constructor Details

#initialize ⇒ StandardDeviationFilter

Returns a new instance of StandardDeviationFilter.



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# File 'lib/SciYAG/Backends/filters/average.rb', line 73

def initialize
end

Instance Method Details

#apply(f) ⇒ Object 



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# File 'lib/SciYAG/Backends/filters/average.rb', line 76

def apply(f)
  last_x = nil    
  current_y = []
  x_values = Dvector.new
  y_values = []
  f.x.size.times do |i|
    xval = f.x[i]
    if (last_x && xval == last_x)
      current_y << f.y[i]
    else
      if last_x
        y_values << current_y
        x_values << last_x
      end
      current_y = [f.y[i]]
      last_x = f.x[i]
    end
  end
  if last_x
    y_values << current_y
    x_values << last_x
  end

  target_y = Dvector.new(x_values.size)
  ymin = target_y.dup
  ymax = target_y.dup
  x_values.size.times do |i|
    sum = 0.0
    sq_sum = 0.0
    for y in y_values[i]
      sum += y
      sq_sum += y**2
    end
    nb = y_values[i].size
    target_y[i] = sum/nb
    stddev = Math::sqrt((sq_sum/nb) - target_y[i]**2)
    ymin[i] = target_y[i] - stddev
    ymax[i] = target_y[i] + stddev
  end
  
  errors = f.errors.dup.merge!({:ymin => ymin, :ymax => ymax,
                               :x => x_values, :y => target_y})

  return DataSet2D.new(f.creation_context, 
                       Function.new(x_values, target_y), 
                       errors, f.meta_data) 
end

#apply!(f) ⇒ Object

We simply replace the old vectors by the new ones.



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# File 'lib/SciYAG/Backends/filters/average.rb', line 125

def apply!(f)
  new_f = apply(f)
  f.x.replace(new_f.x)
  f.y.replace(new_f.y)
  f.errors = new_f.errors
end