Module: Analytica::Computation

Includes:
Strict
Included in:
DataSet
Defined in:
lib/computation.rb

Defined Under Namespace

Classes: InvalidInputException

Instance Method Summary collapse

Instance Method Details

#average_filter(params = {}) ⇒ Object Also known as: avg 



92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
 
# File 'lib/computation.rb', line 92

def average_filter(params={})
  enforce_map!({
    :decay => [:simple, :linear, :exponential],
    :offset => :natural_number, # offset from latest data point
    :samples => :natural_number}, params)

  if !(params[:offset] <= size)
    c = InvalidInputException.new(:simple_average, 
                                 size,
                                 params,
                                 [":offset <= :size"])
    raise c, c.inspect, caller
  end

  if !(params[:offset] >= params[:samples])
    c = InvalidInputException.new(:simple_average, 
                                 size,
                                 params,
                                 [":offset >= :samples"])
    raise c, c.inspect, caller
  end
  
  i = size - params[:offset]
  j = i + params[:samples]-1

  d = DataSet.new(self[i..j])

  case params[:decay]
  when :simple
    d.mean
  when :linear
    d.linear_mean(:bias => :last, :samples => d.size)
  when :exponential
    enforce_exists!(:alpha, params)
    enforce!(:numeric, params[:alpha])
    d.exponential_mean(:bias => :first, :samples => d.size, :alpha => params[:alpha])
  end
end

#exponential_mean(params = {}) ⇒ Object 



59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
 
# File 'lib/computation.rb', line 59

def exponential_mean(params={})
  enforce_map!({
    :bias => [:last, :first],
    :alpha => :numeric,
    :samples => :integer}, params)

    data = self
    data.reverse! if params[:bias] == :last

    params[:samples] = [params[:samples], data.size].min

    ema = 0
    counter = 0
    alpha = params[:alpha]

    data.each do |sample|

      if counter > params[:samples]
        break
      end

      if counter == 0
        ema += sample
      else
        ema += sample * (1-alpha)**counter
      end
      
      counter += 1
    end
    alpha*ema
end

#exponential_moving_average(params = {}) ⇒ Object Also known as: ema 



169
170
171
172
173
174
175
 
# File 'lib/computation.rb', line 169

def exponential_moving_average(params={})
  enforce_map!({
    :samples => :integer,
    :alpha => :float}, params)

    moving_average(:decay => :exponential, :samples => params[:samples], :alpha => params[:alpha])
end

#linear_mean(params = {}) ⇒ Object 



35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
 
# File 'lib/computation.rb', line 35

def linear_mean(params={})
  enforce_map!({
    :bias => [:last, :first],
    :samples => :natural_number}, params)

  data = self
  data.reverse! if params[:bias] == :last
  
  params[:samples] = [params[:samples], data.size].min
  
  n = params[:samples] + 1
  numerator = 0.0
  denominator = 0.0

  data.each do |sample|
    n -= 1
    n = n > 0 ? n : 0

    numerator += n*sample
    denominator += n
  end
  numerator / denominator
end

#linear_moving_average(params = {}) ⇒ Object Also known as: lma 



161
162
163
164
165
 
# File 'lib/computation.rb', line 161

def linear_moving_average(params={})
  enforce_map!({
    :samples => :natural_number}, params)
  moving_average(:decay => :linear, :samples => params[:samples])
end

#mean ⇒ Object 



31
32
33
 
# File 'lib/computation.rb', line 31

def mean
  sum.to_f / size
end

#moving_average(params = {}) ⇒ Object 



133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
 
# File 'lib/computation.rb', line 133

def moving_average(params={})
  enforce_map!({
    :decay => [:simple, :linear, :exponential],
    :samples => :natural_number}, params)

  if !(size >= (2*params[:samples]-1))
    c = InvalidInputException.new(:moving_average, 
                                 size,
                                 params,
                                 ["size >= (2*:samples-1)"])
    raise c, c.inspect, caller
  end

  d = DataSet.new
  (1..params[:samples]).each do |offset|
    d << average_filter(:decay => params[:decay], :alpha => params[:alpha], :offset => offset+params[:samples]-1, :samples => params[:samples])
  end
  d.reverse
end

#piecewise_derivative(n = 1) ⇒ Object Also known as: dydx 



179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
 
# File 'lib/computation.rb', line 179

def piecewise_derivative(n=1)
  enforce!(:natural_number, n)

  d = self
  n.times do
    d = d.inject([]) do |result, item|
      if result.size == 0
        result << item
      else
        d_y = (item - result.last).to_f
        d_x = 1.0 #account for d_x eventually
        deriv = d_y/d_x
        result.pop
        result << deriv
        result << item unless (result.size) == (d.size-1)
        result
      end
    end
  end
  DataSet.new(d)
end

#savitzky_golay(n = 1) ⇒ Object 



203
204
205
206
207
 
# File 'lib/computation.rb', line 203

def savitzky_golay(n=1)
  enforce!(:natural_number, n)

  raise "savitzy_golay filter not yet implemented!"
end

#simple_moving_average(params = {}) ⇒ Object Also known as: sma 



153
154
155
156
157
 
# File 'lib/computation.rb', line 153

def simple_moving_average(params={})
  enforce_map!({
    :samples => :natural_number}, params)
  moving_average(:decay => :simple, :samples => params[:samples])
end

#sum ⇒ Object 



26
27
28
29
 
# File 'lib/computation.rb', line 26

def sum
  sum = inject { |sum, x| sum + x }
  sum ? sum : 0
end