Class: GitFit::Elevation::Train::Collector

Inherits:
Object
  • Object
show all
Defined in:
lib/git_fit/elevation/train/collector.rb

Constant Summary collapse

SPACINGS = 
[2000, 1236, 764, 472, 292, 181].freeze
BUDGET = 
2.0

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(sources: nil) ⇒ Collector

Returns a new instance of Collector.



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# File 'lib/git_fit/elevation/train/collector.rb', line 13

def initialize(sources: nil)
  @sources = sources
  @samples = []
end

Instance Attribute Details

#samples ⇒ Object (readonly)

Returns the value of attribute samples.



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# File 'lib/git_fit/elevation/train/collector.rb', line 18

def samples
  @samples
end

Instance Method Details

#all_adapters ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 45

def all_adapters
  Sync::Base.adapters
end

#count_samples ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 20

def count_samples
  total = 0
  each_source_sample do |_sample|
    total += 1
  end
  total
end

#each_sample ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 28

def each_sample
  each_source_sample do |sample|
    result = evaluate_sample(sample)
    @samples << result if result
    yield result
  end
end

#each_source_sample(&block) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 36

def each_source_sample(&block)
  adapters = @sources ? resolve_sources(@sources) : all_adapters
  adapters.each do |adapter|
    adapter.training_samples.each(&block)
  rescue StandardError => e
    warn "Collector: #{adapter.name} failed: #{e.message}"
  end
end

#elevation_gain(alts) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 137

def elevation_gain(alts)
  total = 0.0
  (1...alts.size).each do |i|
    diff = alts[i] - alts[i - 1]
    total += diff if diff > 0
  end
  total
end

#evaluate_sample(sample) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 55

def evaluate_sample(sample)
  altitudes = sample[:altitudes]
  distances = sample[:distances]
  locations = sample[:locations]
  source = sample[:source]
  id = sample[:id]

  return nil if altitudes.size < 2
  return nil if distances.empty? || distances.last < 1000

  cache_before = DemCache.load_batch(locations)
  dem = TerrainCoeff.elevations_for(locations)
  return nil if dem.empty? || dem.compact.size < 2

  cache_hit = !cache_before.empty? && cache_before.values.all? { |v| !v.nil? }

  truth_min = dem.compact.min
  truth_max = dem.compact.max
  sm = smooth(altitudes)

  best = nil
  (2.0..3.0).step(0.1).each do |h|
    h = h.round(2)
    segs = segments(sm, h)
    chosen = nil
    SPACINGS.each do |sp|
      sel = sample_indices(sm, segs, distances, sp)
      lmin, lmax, npts = layered_estimate(dem, sel)
      err = [(lmin - truth_min).abs, (lmax - truth_max).abs].max
      if err <= BUDGET
        chosen = { h: h, spacing: sp, err: err, npts: npts }
        break
      end
    end
    unless chosen
      sel = sample_indices(sm, segs, distances, SPACINGS.last)
      lmin, lmax, npts = layered_estimate(dem, sel)
      err = [(lmin - truth_min).abs, (lmax - truth_max).abs].max
      chosen = { h: h, spacing: SPACINGS.last, err: err, npts: npts }
    end
    best = chosen if best.nil? || chosen[:npts] < best[:npts]
  end

  return nil unless best

  f = features(altitudes, distances, locations)
  {
    id: id,
    source: source,
    truth_min: truth_min,
    truth_max: truth_max,
    h_opt: best[:h],
    spacing_opt: best[:spacing],
    err: best[:err].round(2),
    npts: best[:npts],
    gain_per_km: f[:gain_per_km],
    range_per_km: f[:range_per_km],
    seg_density: f[:seg_density],
    cache_hit: cache_hit,
  }
end

#features(altitudes, distances, _locations) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 117

def features(altitudes, distances, _locations)
  return nil if altitudes.empty? || distances.empty?

  dm = distances.last
  km = [dm / 1000.0, 1e-6].max
  gain = elevation_gain(altitudes)
  range = altitudes.empty? ? 0.0 : (altitudes.max - altitudes.min)
  gain_per_km = gain / km
  range_per_km = range / km
  seg_density = segments(smooth(altitudes), 2.5).size / km

  {
    gain_per_km: gain_per_km,
    range_per_km: range_per_km,
    seg_density: seg_density,
    distance_m: dm,
    npts: altitudes.size,
  }
end

#layered_estimate(dem, sel) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 239

def layered_estimate(dem, sel)
  vals = sel.map { |i| dem[i] }.compact
  return [nil, nil, 0] if vals.empty?
  [vals.min, vals.max, vals.size]
end

#moving_avg(vals, window) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 159

def moving_avg(vals, window)
  half = window / 2
  (0...vals.size).map do |i|
    lo = [0, i - half].max
    hi = [vals.size - 1, i + half].min
    vals[lo..hi].sum.to_f / (hi - lo + 1)
  end
end

#moving_median(vals, window) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 150

def moving_median(vals, window)
  half = window / 2
  (0...vals.size).map do |i|
    lo = [0, i - half].max
    hi = [vals.size - 1, i + half].min
    vals[lo..hi].sort[(hi - lo) / 2]
  end
end

#resolve_sources(names) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 49

def resolve_sources(names)
  names.map do |name|
    Sync::Base.adapters.find { |a| a.config_key == name.to_s }
  end.compact
end

#sample_indices(smooth, segs, dist, spacing) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 215

def sample_indices(smooth, segs, dist, spacing)
  sel = Set.new
  segs.each do |a, b|
    sel << a
    sel << b
    next if b - a < 2

    d0 = dist[a].to_f
    d1 = dist[b].to_f
    len = d1 - d0
    seg_range = smooth[a..b].max - smooth[a..b].min
    next unless len > 500 && seg_range < 3.0

    k = 1
    while d0 + k * spacing < d1
      target = d0 + k * spacing
      idx = a + ((b - a) * (target - d0) / len).round
      sel << idx
      k += 1
    end
  end
  sel.to_a.sort
end

#segments(smooth, threshold, min_len: 20) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 168

def segments(smooth, threshold, min_len: 20)
  n = smooth.size
  return [[0, n - 1]] if n < 2

  segs = []
  seg_start = 0
  ext_val = smooth[0]
  ext_idx = 0
  rising = nil
  (1...n).each do |i|
    v = smooth[i]
    if rising.nil?
      if v > ext_val
        ext_val = v
        ext_idx = i
        rising = true
      elsif v < ext_val
        ext_val = v
        ext_idx = i
        rising = false
      end
    elsif rising
      if v > ext_val
        ext_val = v
        ext_idx = i
      elsif ext_val - v >= threshold
        segs << [seg_start, ext_idx] if ext_idx - seg_start >= min_len
        seg_start = ext_idx if ext_idx - seg_start >= min_len
        rising = false
        ext_val = v
        ext_idx = i
      end
    elsif v < ext_val
      ext_val = v
      ext_idx = i
    elsif v - ext_val >= threshold
      segs << [seg_start, ext_idx] if ext_idx - seg_start >= min_len
      seg_start = ext_idx if ext_idx - seg_start >= min_len
      rising = true
      ext_val = v
      ext_idx = i
    end
  end
  segs << [seg_start, n - 1] if n - 1 - seg_start >= min_len
  segs.empty? ? [[0, n - 1]] : segs
end

#smooth(vals) ⇒ Object 



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# File 'lib/git_fit/elevation/train/collector.rb', line 146

def smooth(vals)
  moving_avg(moving_median(vals, 9), 9)
end