Class: NArray

Inherits:
Object
  • Object
show all
Defined in:
lib/narray_ext.rb

Overview

Numerical Array Extention for Ruby

  (C) Copyright 2000-2008 by Masahiro TANAKA

This program is free software.
You can distribute/modify this program
under the same terms as Ruby itself.
NO WARRANTY.

Direct Known Subclasses

NMatrix, NVector

Instance Method Summary collapse

Instance Method Details

#==(other) ⇒ Object

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# File 'lib/narray_ext.rb', line 33

def ==(other)
  if other.kind_of?(NArray)
    (shape == other.shape) && eq(other).all?
  else
    false
  end
end

#all?Boolean

Returns:

  • (Boolean)
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# File 'lib/narray_ext.rb', line 21

def all?
  where.size == size
end

#any?Boolean

Returns:

  • (Boolean)
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# File 'lib/narray_ext.rb', line 25

def any?
  where.size > 0
end

#complex?Boolean

Returns:

  • (Boolean)
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# File 'lib/narray_ext.rb', line 16

def complex?
  self.typecode==NArray::DCOMPLEX ||
  self.typecode==NArray::SCOMPLEX
end

#integer?Boolean

Returns:

  • (Boolean)
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# File 'lib/narray_ext.rb', line 11

def integer?
  self.typecode==NArray::BYTE ||
  self.typecode==NArray::SINT ||
  self.typecode==NArray::LINT
end

#mean(*ranks) ⇒ Object

Statistics

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# File 'lib/narray_ext.rb', line 56

def mean(*ranks)
  if integer?
    a = self.to_type(NArray::DFLOAT)
  else
    a = self
  end
  a = NArray.ref(a)
  a.sum(*ranks) / (rank_total(*ranks))
end

#median(rank = nil) ⇒ Object

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# File 'lib/narray_ext.rb', line 111

def median(rank=nil)
  shape = self.shape
  rank = shape.size-1 if rank==nil
  s = sort(rank).reshape!(true,*shape[rank+1..-1])
  n = s.shape[0]
  if n%2==1
    s[n/2,false]
  else
    s[n/2-1..n/2,false].sum(0)/2
  end
end

#none?Boolean

Returns:

  • (Boolean)
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# File 'lib/narray_ext.rb', line 29

def none?
  where.size == 0
end

#randomnObject Also known as: randomn!

Normal distributed random number; valid for floating point types

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# File 'lib/narray_ext.rb', line 125

def randomn
  size = self.size
  case type = self.typecode
  when COMPLEX; type=FLOAT
  when SCOMPLEX; type=SFLOAT
  when FLOAT
  when SFLOAT
  else
    raise TypeError, "NArray type must be (S)FLOAT or (S)COMPLEX."
  end
  rr = NArray.new(type,size)
  xx = NArray.new(type,size)
  i = 0
  while i < size
    n = size-i
    m = ((n+Math::sqrt(n))*1.27).to_i
    x = NArray.new(type,m).random!(1) * 2 - 1
    y = NArray.new(type,m).random!(1) * 2 - 1
    r = x**2 + y**2
    idx = (r<1).where
    idx = idx[0...n] if idx.size > n
    if idx.size>0
	rr[i] = r[idx]
	xx[i] = x[idx]
	i += idx.size
    end
  end
  # Box-Muller transform
  rr = ( xx * NMath::sqrt( -2 * NMath::log(rr) / rr ) )
  # finish
  rr.reshape!(*self.shape) if self.rank > 1
  rr = rr.to_type(self.typecode) if type!=self.typecode
  if RUBY_VERSION < "1.8.0"
    self.type.refer(rr)
  else
    self.class.refer(rr)
  end
end

#rank_total(*ranks) ⇒ Object

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# File 'lib/narray_ext.rb', line 41

def rank_total(*ranks)
  if ranks.size>0
    idx = []
    ranks.each{|i| idx.push(*i)}
    # ranks is expected to be, e.g., [1, 3..5, 7]
    a = self.shape
    n = 1
    idx.each{|i| n *= a[i]}
    n
  else
    self.total
  end
end

#rms(*ranks) ⇒ Object

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# File 'lib/narray_ext.rb', line 81

def rms(*ranks)
  if integer?
    a = self.to_type(NArray::DFLOAT)
  else
    a = self
  end
  a = NArray.ref(a)
  n = rank_total(*ranks)
  if complex?
    NMath::sqrt( (a.abs**2).sum(*ranks)/n )
  else
    NMath::sqrt( (a**2).sum(*ranks)/n )
  end
end

#rmsdev(*ranks) ⇒ Object

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# File 'lib/narray_ext.rb', line 96

def rmsdev(*ranks)
  if integer?
    a = self.to_type(NArray::DFLOAT)
  else
    a = self
  end
  a = NArray.ref(a)
  n = rank_total(*ranks)
  if complex?
    NMath::sqrt( (( a-a.accum(*ranks).div!(n) ).abs**2).sum(*ranks)/n )
  else
    NMath::sqrt( (( a-a.accum(*ranks).div!(n) )**2).sum(*ranks)/n )
  end
end

#stddev(*ranks) ⇒ Object

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# File 'lib/narray_ext.rb', line 66

def stddev(*ranks)
  if integer?
    a = self.to_type(NArray::DFLOAT)
  else
    a = self
  end
  a = NArray.ref(a)
  n = rank_total(*ranks)
  if complex?
    NMath::sqrt( (( a-a.accum(*ranks).div!(n) ).abs**2).sum(*ranks)/(n-1) )
  else
    NMath::sqrt( (( a-a.accum(*ranks).div!(n) )**2).sum(*ranks)/(n-1) )
  end
end