Class: Array

Inherits:
Object show all
Defined in:
docs/multiarray/lib/multiarray.rb,
docs/multiarray/lib/multiarray/operations.rb

Overview

The Array class is extended with a few methods

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.gauss_blur_filter(sigma, max_error = 1.0 / 0x100) ⇒ Array

Compute Gauss blur filter

Compute a filter for approximating a Gaussian blur. The size of the filter is determined by the given error bound.

Parameters:

  • sigma (Float) —

    Spread of blur filter.

  • max_error (Float) (defaults to: 1.0 / 0x100) —

    Upper bound for filter error.

Returns:

  • (Array) —

    An array with the filter elements.



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# File 'docs/multiarray/lib/multiarray.rb', line 615

def gauss_blur_filter( sigma, max_error = 1.0 / 0x100 )
  # Error function
  #
  # @param [Float] x Function argument
  # @param [Float] sigma Function parameter
  #
  # @private
  def erf(x, sigma)
    0.5 * Math.erf( x / ( Math.sqrt( 2.0 ) * sigma.abs ) )
  end
  raise 'Sigma must be greater than zero.' if sigma <= 0
  # Integral of Gauss-bell from -0.5 to +0.5.
  integral = erf( +0.5, sigma ) - erf( -0.5, sigma )
  retVal = [ integral ]
  while 1.0 - integral > max_error
    # Integral of Gauss-bell from -size2 to +size2.
    size2 = 0.5 * ( retVal.size + 2 )
    nIntegral = erf( +size2, sigma ) - erf( -size2, sigma )
    value = 0.5 * ( nIntegral - integral )
    retVal.unshift value
    retVal.push value
    integral = nIntegral
  end
  # Normalise result.
  retVal.collect { |element| element / integral }
end

.gauss_gradient_filter(sigma, max_error = 1.0 / 0x100) ⇒ Array

Compute Gauss gradient filter

Compute a filter for approximating a Gaussian gradient. The size of the filter is determined by the given error bound.

Parameters:

  • sigma (Float) —

    Spread of blur filter.

  • max_error (Float) (defaults to: 1.0 / 0x100) —

    Upper bound for filter error.

Returns:

  • (Array) —

    An array with the filter elements.



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# File 'docs/multiarray/lib/multiarray.rb', line 651

def gauss_gradient_filter( sigma, max_error = 1.0 / 0x100 )
  # Gaussian function
  #
  # @param [Float] x Function argument
  # @param [Float] sigma Function parameter
  #
  # @private
  def gauss(x, sigma)
    1.0 / ( Math.sqrt( 2.0 * Math::PI ) * sigma.abs ) *
      Math.exp( -x**2 / ( 2.0 * sigma**2 ) )
  end
  raise 'Sigma must be greater than zero.' if sigma <= 0
  # Integral of Gauss-gradient from -0.5 to +0.5.
  retVal = [ gauss( +0.5, sigma ) - gauss( -0.5, sigma ) ]
  # Absolute integral of Gauss-gradient from 0.5 to infinity.
  integral = gauss( 0.5, sigma )
  sumX = 0
  while 2.0 * integral > max_error
    size2 = 0.5 * ( retVal.size + 2 )
    nIntegral = gauss( size2, sigma )
    value = integral - nIntegral
    retVal.unshift +value
    retVal.push -value
    sumX += value * ( retVal.size - 1 )
    integral = nIntegral
  end
  retVal.collect { |element| element / sumX }
end

Instance Method Details

#collect_with_index(&action) ⇒ Array<Object>

Element-wise operation based on element and its index

Same as Array#collect but with index.

Parameters:

  • &action —

    Closure accepting an element and an index.

Returns:



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# File 'docs/multiarray/lib/multiarray.rb', line 689

def collect_with_index( &action )
  zip( ( 0 ... size ).to_a ).collect &action
end

#histogram(*ret_shape, options = {}) ⇒ Node

Compute histogram of this array

Parameters:

  • ret_shape (Array<Integer>) —

    Dimensions of resulting histogram.

Options Hash (options):

  • :weight (Node) — default: Hornetseye::UINT(1) —

    Weights for computing the histogram.

  • :safe (Boolean) — default: true —

    Do a boundary check before creating the histogram.

Returns:

  • (Node) —

    The histogram.



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# File 'docs/multiarray/lib/multiarray/operations.rb', line 968

def histogram( *ret_shape )
  options = ret_shape.last.is_a?( Hash ) ? ret_shape.pop : {}
  options = { :weight => Hornetseye::UINT. new( 1 ), :safe => true }.merge options
  unless options[:weight].matched?
    options[:weight] =
      Hornetseye::Node.match( options[ :weight ] ).maxint.new options[ :weight ]
  end
  weight = options[ :weight ]
  if options[ :safe ]
    if size != ret_shape.size
      raise "Number of arrays for histogram (#{size}) differs from number of " +
            "dimensions of histogram (#{ret_shape.size})"
    end
    source_type = inject { |a,b| a.dimension > b.dimension ? a : b }
    source_type.check_shape *self
    source_type.check_shape options[ :weight ]
    for i in 0 ... size
      range = self[ i ].range 0 ... ret_shape[ i ]
      if range.begin < 0
        raise "#{i+1}th dimension of index must be in 0 ... #{ret_shape[i]} " +
              "(but was #{range.begin})"
      end
      if range.end >= ret_shape[ i ]
        raise "#{i+1}th dimension of index must be in 0 ... #{ret_shape[i]} " +
              "(but was #{range.end})"
      end
    end
  end
  left = Hornetseye::MultiArray(weight.typecode, ret_shape.size).new *ret_shape
  left[] = 0
  block = Hornetseye::Histogram.new left, weight, *self
  if block.compilable?
    Hornetseye::GCCFunction.run block
  else
    block.demand
  end
  left
end

#lut(table, options = {}) ⇒ Node

Perform element-wise lookup

Parameters:

  • table (Node) —

    The lookup table (LUT).

  • options (Hash) (defaults to: {}) —

    a customizable set of options

Options Hash (options):

  • :safe (Boolean) — default: true —

    Do a boundary check before creating the element-wise lookup.

Returns:

  • (Node) —

    The result of the lookup operation.



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# File 'docs/multiarray/lib/multiarray/operations.rb', line 1014

def lut( table, options = {} )
  options = { :safe => true }.merge options
  if options[ :safe ]
    if size > table.dimension
      raise "Number of arrays for lookup (#{size}) is greater than the " +
            "number of dimensions of LUT (#{table.dimension})"
    end
    source_type = inject { |a,b| a.dimension > b.dimension ? a : b }
    source_type.check_shape *self
    for i in 0 ... size
      offset = table.dimension - size
      range = self[ i ].range 0 ... table.shape[ i + offset ]
      if range.begin < 0
        raise "#{i+1}th index must be in 0 ... #{table.shape[i]} " +
              "(but was #{range.begin})"
      end
      if range.end >= table.shape[ i + offset ]
        raise "#{i+1}th index must be in 0 ... " +
              "#{table.shape[ i + offset ]} (but was #{range.end})"
      end
    end
  end
  if all? { |source| source.dimension == 0 and source.variables.empty? }
    result = table
    ( table.dimension - 1 ).downto( 0 ) do |i|
      result = result.element( self[ i ].demand ).demand
    end
    result
  else
    Hornetseye::Lut.new( *( self + [ table ] ) ).force
  end
end

#strip ⇒ Object 



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# File 'docs/multiarray/lib/multiarray.rb', line 693

def strip
  collect { |arg| arg.strip }.inject [[], [], []] do |retval,s|
    [retval[0] + s[0], retval[1] + s[1], retval[2] + [s[2]]]
  end
end