Module: StairCar::PMatrixMatrixMath

Included in:
PMatrix
Defined in:
lib/stair_car/pmatrix/matrix_math.rb

Defined Under Namespace

Classes: MatrixMathError

Instance Method Summary collapse

Instance Method Details

#*(val) ⇒ Object 



55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 55

def *(val)
  n = self.rows
  m = self.cols

  p = val.rows
  q = val.cols

  if m != p
    raise MatrixMathError, "matricies can not be multiplied"
  end

  # Build a like matrix to receive
  c = @data.like(n, q)

  @data.z_mult(val.data, c)

  return PMatrix.new(c)
end

#**(val) ⇒ Object 



47
48
49
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 47

def **(val)
  perform(val) { |a,b| a * b }
end

#+(val) ⇒ Object 



38
39
40
41
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 38

def +(val)
  perform(val) { |a,b| a + b }
  # perform(val, Java::cern.jet.math.tdouble.DoubleFunctions.plus)
end

#-(val) ⇒ Object 



43
44
45
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 43

def -(val)
  perform(val) { |a,b| a - b }
end

#/(val) ⇒ Object 



51
52
53
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 51

def /(val)
  perform(val) { |a,b| a / b }
end

#max(dimension = nil) ⇒ Object 



86
87
88
89
90
91
92
93
94
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 86

def max(dimension=nil)
  if dimension
    value = aggrate_on_dimension(:max, dimension)
  else
    value, row, col = @data.max_location
  end

  return value
end

#mean(dimension = nil) ⇒ Object 



106
107
108
109
110
111
112
113
114
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 106

def mean(dimension=nil)
  if dimension
    value = aggrate_on_dimension(:mean, dimension)
  else
    value = self.sum / self.size
  end

  return value
end

#min(dimension = nil) ⇒ Object 



96
97
98
99
100
101
102
103
104
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 96

def min(dimension=nil)
  if dimension
    value = aggrate_on_dimension(:min, dimension)
  else
    value, row, col = @data.min_location
  end

  return value
end

#perform(val, &block) ⇒ Object 



6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 6

def perform(val, &block)
  result = @data.copy
  if val.is_a?(PMatrix)
    if rows == val.rows && cols == val.cols
      # Another matrix of the same size
      result = result.assign(val.data, &block)
    elsif rows == val.rows && val.cols == 1
      # Vector on column (vertical)
      PMatrix.new(result).each_column do |row|
        row.data.assign(val.data, &block)
      end
    elsif cols == val.cols && val.rows == 1
      # Vector on rows (horizontal)
      PMatrix.new(result).each_row do |col|
        col.data.assign(val.data, &block)
      end
    else
      # Incorrect size
      raise MatrixMathError, "matrix dimensions incorrect"
    end
  else
    # Passed in a number
    perform_on_val = Proc.new do |cell_value|
      yield(cell_value, val)
    end

    result.assign(perform_on_val)
  end

  return PMatrix.new(result)
end

#std(dimension = nil, sample = false) ⇒ Object 



136
137
138
139
140
141
142
143
144
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 136

def std(dimension=nil, sample=false)
  if dimension
    value = aggrate_on_dimension(:variance, dimension, sample)
  else
    value = Math.sqrt(self.variance(dimension, sample))
  end

  return value
end

#sum(dimension = nil) ⇒ Object 



74
75
76
77
78
79
80
81
82
83
84
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 74

def sum(dimension=nil)
  if dimension == 0
    # Sum rows
    return PMatrix.ones(1, rows) * self
  elsif dimension == 1
    # Sum cols
    return self * PMatrix.ones(cols, 1)
  else
    return @data.z_sum
  end
end

#variance(dimension = nil, sample = false) ⇒ Object 



116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
 
# File 'lib/stair_car/pmatrix/matrix_math.rb', line 116

def variance(dimension=nil, sample=false)
  if dimension
    value = aggrate_on_dimension(:variance, dimension, sample)
  else
    mean = self.mean
    total = 0
    self.each_non_zero do |v|
      total += (mean - v) ** 2
    end

    if sample
      value = total / (self.size - 1)
    else
      value = total / self.size
    end
  end

  return value
end