Module: DataLayerProcessorNoiseRemoval

Included in:
DataLayerProcessor
Defined in:
lib/technical_graph/data_layer_processor_noise_removal.rb

Constant Summary collapse

DEFAULT_NOISE_REMOVAL_LEVEL = 
3
DEFAULT_NOISE_REMOVAL_WINDOW_SIZE = 
10
NOISE_COEFF = 
1000
NOISE_POWER_COEFF = 
8

Instance Attribute Summary collapse

Instance Method Summary collapse

Instance Attribute Details

#noise_removal ⇒ Object

Returns the value of attribute noise_removal.



20
21
22
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 20

def noise_removal
  @noise_removal
end

#noise_removal_level ⇒ Object

Returns the value of attribute noise_removal_level.



20
21
22
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 20

def noise_removal_level
  @noise_removal_level
end

#noise_removal_window_size ⇒ Object

Returns the value of attribute noise_removal_window_size.



20
21
22
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 20

def noise_removal_window_size
  @noise_removal_window_size
end

#noise_threshold ⇒ Object

Returns the value of attribute noise_threshold.



20
21
22
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 20

def noise_threshold
  @noise_threshold
end

Instance Method Details

#calc_avg_derivative(i_from, i_to) ⇒ Object 



87
88
89
90
91
92
93
94
95
96
97
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 87

def calc_avg_derivative(i_from, i_to)
  part_array = data.clone_partial_w_fill(i_from, i_to)
  derivatives = Array.new
  (1...part_array.size).each do |i|
    x_len = (part_array[i].x - part_array[i - 1].x).abs
    y_len = (part_array[i].y - part_array[i - 1].y).abs
    derivatives << (x_len / y_len).abs if x_len.abs > 0
  end
  avg_der = derivatives.float_mean
  return avg_der
end

#noise?(i) ⇒ Boolean

Check if data at index is noisy



57
58
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
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 57

def noise?(i)
  i_from = noise_removal_window_from(i)
  i_to = noise_removal_window_to(i)


  # y_mean = part_array.collect { |p| p.y }.float_mean
  # # another algorithm
  # noise_strength = (data[i].y - y_mean).abs / y_mean
  # return noise_strength_enough?(noise_strength)

  # calc. avg 'derivative'
  avg_der = calc_avg_derivative(i_from, i_to)
  current_der = calc_avg_derivative(i-1, i+1)

  # safety
  return false if avg_der == 0 or current_der == 0

  begin
    current_level = Math.log((current_der / avg_der) ** NOISE_POWER_COEFF).abs
  rescue Errno::EDOM
    # can not calculate logarithm
    return false
  rescue Errno::ERANGE
    # can not calculate logarithm
    return false
  end
  logger.debug "noise removal, avg der #{avg_der}, current #{current_der}, current lev #{current_level}, threshold #{noise_threshold}"
  return current_level > noise_threshold
end

#noise_removal_initialize(options) ⇒ Object 



12
13
14
15
16
17
18
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 12

def noise_removal_initialize(options)
  @noise_removal = options[:noise_removal] == true
  @noise_removal_level = options[:noise_removal_level] || DEFAULT_NOISE_REMOVAL_LEVEL
  @noise_removal_window_size = options[:noise_removal_window_size] || DEFAULT_NOISE_REMOVAL_WINDOW_SIZE

  @noise_threshold = Math.log(NOISE_COEFF / @noise_removal_level)
end

#noise_removal_process ⇒ Object

Smooth values



23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 23

def noise_removal_process
  return if noise_removal == false

  t = Time.now
  new_data = Array.new

  @noises_removed_count = 0

  logger.debug "Noise removal started"

  (0...data.size).each do |i|
    if not noise?(i)
      new_data << data[i]
    else
      @noises_removed_count += 1
    end
  end

  logger.debug "Noise removal completed, removed #{@noises_removed_count}"
  logger.debug " TIME COST #{Time.now - t}"

  @data = new_data
  return new_data
end

#noise_removal_window_from(i) ⇒ Object 



48
49
50
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 48

def noise_removal_window_from(i)
  return i - (noise_removal_window_size.to_f / 2.0).ceil
end

#noise_removal_window_to(i) ⇒ Object 



52
53
54
 
# File 'lib/technical_graph/data_layer_processor_noise_removal.rb', line 52

def noise_removal_window_to(i)
  return i + (noise_removal_window_size.to_f / 2.0).ceil
end