Class: Statsample::Reliability::MultiScaleAnalysis

Inherits:
Object
  • Object
show all
Includes:
Summarizable
Defined in:
lib/statsample/reliability/multiscaleanalysis.rb

Overview

DSL for analysis of multiple scales analysis. Retrieves reliability analysis for each scale and provides fast accessors to correlations matrix, PCA and Factor Analysis.

Usage

@x1 = Daru::Vector.new([1,1,1,1,2,2,2,2,3,3,3,30])
@x2 = Daru::Vector.new([1,1,1,2,2,3,3,3,3,4,4,50])
@x3 = Daru::Vector.new([2,2,1,1,1,2,2,2,3,4,5,40])
@x4 = Daru::Vector.new([1,2,3,4,4,4,4,3,4,4,5,30])
ds  = Daru::DataFrame.new({:x1 => @x1,:x2 => @x2,:x3 => @x3,:x4 => @x4})
opts={:name=>"Scales", # Name of analysis
      :summary_correlation_matrix=>true, # Add correlation matrix
      :summary_pca } # Add PCA between scales
msa=Statsample::Reliability::MultiScaleAnalysis.new(opts) do |m|
  m.scale :s1, ds.clone([:x1, :x2])
  m.scale :s2, ds.clone([:x3, :x4]), {:name=>"Scale 2"}
end
# Retrieve summary
puts msa.summary

Instance Attribute Summary collapse

Instance Method Summary collapse

Methods included from Summarizable

#summary

Constructor Details

#initialize(opts = Hash.new, &block) ⇒ MultiScaleAnalysis

Generates a new MultiScaleAnalysis Opts could be any accessor of the class

  • :name,

  • :summary_correlation_matrix

  • :summary_pca

  • :summary_principal_axis

  • :summary_map

  • :pca_options

  • :factor_analysis_options

  • :map_options

If block given, all methods should be called inside object environment.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 64

def initialize(opts=Hash.new, &block)
  @scales=Hash.new
  @scales_keys=Array.new
  opts_default={  :name=>_("Multiple Scale analysis"),
                  :summary_correlation_matrix=>false,
                  :summary_pca=>false,
                  :summary_principal_axis=>false,
                  :summary_parallel_analysis=>false,
                  :summary_map=>false,
                  :pca_options=>Hash.new,
                  :principal_axis_options=>Hash.new,
                  :parallel_analysis_options=>Hash.new,
                  :map_options=>Hash.new
  }
  @opts=opts_default.merge(opts)
  @opts.each{|k,v|
    self.send("#{k}=",v) if self.respond_to? k
  }

  if block
    block.arity<1 ? instance_eval(&block) : block.call(self)
  end
end

Instance Attribute Details

#map_optionsObject

Options for MAP


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 48

def map_options
  @map_options
end

#nameObject

Name of analysis


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 28

def name
  @name
end

#parallel_analysis_optionsObject

Options for Parallel Analysis


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 43

def parallel_analysis_options
  @parallel_analysis_options
end

#pca_optionsObject

Options for Factor::PCA object


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 36

def pca_options
  @pca_options
end

#principal_axis_optionsObject

Options for Factor::PrincipalAxis


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 38

def principal_axis_options
  @principal_axis_options
end

#scalesObject (readonly)

Hash with scales


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 26

def scales
  @scales
end

#summary_correlation_matrixObject

Add a correlation matrix on summary


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 30

def summary_correlation_matrix
  @summary_correlation_matrix
end

#summary_mapObject

Add MPA to summary


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 46

def summary_map
  @summary_map
end

#summary_parallel_analysisObject

Add Parallel Analysis to summary


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 41

def summary_parallel_analysis
  @summary_parallel_analysis
end

#summary_pcaObject

Add PCA to summary


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 32

def summary_pca
  @summary_pca
end

#summary_principal_axisObject

Add Principal Axis to summary


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 34

def summary_principal_axis
  @summary_principal_axis
end

Instance Method Details

#correlation_matrixObject

Retrieves a Correlation Matrix between scales.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 141

def correlation_matrix
  Statsample::Bivariate.correlation_matrix(dataset_from_scales)
end

#dataset_from_scalesObject


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 125

def dataset_from_scales
  ds = Daru::DataFrame.new({}, order: @scales_keys.map(&:to_sym))
  @scales.each_pair do |code,scale|
    ds[code.to_sym] = scale.ds.vector_sum
  end
  
  ds.update
  ds
end

#delete_scale(code) ⇒ Object

Delete ScaleAnalysis named code


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 103

def delete_scale(code)
  @scales_keys.delete code
  @scales.delete code
end

#map(opts = nil) ⇒ Object

Retrieve Velicer's MAP using all scales.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 115

def map(opts=nil)
  opts||=map_options
  Statsample::Factor::MAP.new(correlation_matrix, opts)
end

#parallel_analysis(opts = nil) ⇒ Object


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 135

def parallel_analysis(opts=nil)
  opts||=parallel_analysis_options
  Statsample::Factor::ParallelAnalysis.new(dataset_from_scales, opts)
end

#pca(opts = nil) ⇒ Object

Retrieves a Principal Component Analysis (Factor::PCA) using all scales, using opts a options.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 109

def pca(opts=nil)
  opts ||= pca_options        
  Statsample::Factor::PCA.new(correlation_matrix, opts)
end

#principal_axis_analysis(opts = nil) ⇒ Object

Retrieves a PrincipalAxis Analysis (Factor::PrincipalAxis) using all scales, using opts a options.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 121

def principal_axis_analysis(opts=nil)
  opts||=principal_axis_options
  Statsample::Factor::PrincipalAxis.new(correlation_matrix, opts)
end

#report_building(b) ⇒ Object

:nodoc:


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 145

def report_building(b) # :nodoc:
  b.section(:name=>name) do |s|
    s.section(:name=>_("Reliability analysis of scales")) do |s2|
      @scales.each_pair do |k, scale|
        s2.parse_element(scale)
      end
    end
    if summary_correlation_matrix
      s.section(:name=>_("Correlation matrix for %s") % name) do |s2|
        s2.parse_element(correlation_matrix)
      end
    end
    if summary_pca
      s.section(:name=>_("PCA for %s") % name) do |s2|
        s2.parse_element(pca)
      end
    end
    if summary_principal_axis
      s.section(:name=>_("Principal Axis for %s") % name) do |s2|
        s2.parse_element(principal_axis_analysis)
      end
    end
    
    if summary_parallel_analysis
      s.section(:name=>_("Parallel Analysis for %s") % name) do |s2|
        s2.parse_element(parallel_analysis)
      end
    end 
    if summary_map
      s.section(:name=>_("MAP for %s") % name) do |s2|
        s2.parse_element(map)
      end
    end           
  end
end

#scale(code, ds = nil, opts = nil) ⇒ Object

Add or retrieve a scale to analysis. If second parameters is a dataset, generates a ScaleAnalysis for ds, named code with options opts.

If second parameters is empty, returns the ScaleAnalysis code.


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# File 'lib/statsample/reliability/multiscaleanalysis.rb', line 93

def scale(code, ds=nil, opts=nil)
  if ds.nil?
    @scales[code]
  else
    opts={:name=>_("Scale %s") % code} if opts.nil?
    @scales_keys.push(code)
    @scales[code]=ScaleAnalysis.new(ds, opts)
  end
end