Class: GitFit::Elevation::Train::Runner

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

Constant Summary collapse

CACHE_DIR = 
'data/cache/dem_fit'
MODEL_FILE = 
'dem_model.msgpack'

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(sources: nil, output: nil) ⇒ Runner

Returns a new instance of Runner.



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# File 'lib/git_fit/elevation/train/runner.rb', line 14

def initialize(sources: nil, output: nil)
  @sources = sources
  @output = output || default_output_path
end

Class Method Details

.run!(sources: nil, output: nil) ⇒ Object 



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# File 'lib/git_fit/elevation/train/runner.rb', line 96

def self.run!(sources: nil, output: nil)
  runner = new(sources: sources, output: output)
  runner.run
end

Instance Method Details

#default_output_path ⇒ Object 



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# File 'lib/git_fit/elevation/train/runner.rb', line 92

def default_output_path
  File.join(CACHE_DIR, MODEL_FILE)
end

#print_progress(collected, cached, missed, total) ⇒ Object 



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# File 'lib/git_fit/elevation/train/runner.rb', line 71

def print_progress(collected, cached, missed, total)
  pct = (collected.to_f / total * 100).round(1)
  bar_len = 30
  filled = (collected.to_f / total * bar_len).round
  bar = '=' * filled + '-' * (bar_len - filled)
  $stdout.write "\r  [#{bar}] #{pct}% #{collected}/#{total} (h:#{cached} m:#{missed})"
  $stdout.flush
end

#print_summary(model) ⇒ Object 



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# File 'lib/git_fit/elevation/train/runner.rb', line 80

def print_summary(model)
  meta = model[:meta]
  puts
  puts '=== Model Trained ==='
  puts "  samples:     #{meta['n_samples']}"
  puts "  sources:     #{meta['sources'].join(', ')}"
  puts "  trained_at:  #{meta['trained_at']}"
  puts "  ridge_h:     #{model[:ridge_h].map { |w| format('%.3f', w) }.join(', ')}"
  puts "  norms:       #{model[:norms].map { |n| format('%.2f', n) }.join(', ')}"
  puts "  output:      #{@output}"
end

#run ⇒ Object 



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# File 'lib/git_fit/elevation/train/runner.rb', line 19

def run
  collector = Collector.new(sources: @sources)
  total = collector.count_samples
  puts "Collecting samples (#{total} total)..."

  collected = 0
  cached = 0
  missed = 0
  skipped = 0

  collector.each_sample do |result|
    if result
      collected += 1
      if result[:cache_hit]
        cached += 1
      else
        missed += 1
      end
      print_progress(collected, cached, missed, total)
    else
      skipped += 1
    end
  end

  puts
  puts "Collected: #{collected} samples (#{cached} hit / #{missed} miss / #{skipped} skipped)"

  if collected.zero?
    warn 'No valid samples collected'
    return false
  end

  puts 'Fitting model...'
  fitter = Fitter.new(collector.samples)
  model = fitter.fit

  unless model
    warn 'Fitting failed'
    return false
  end

  puts "Writing model to #{@output}..."
  unless fitter.write_msgpack(@output)
    warn 'Failed to write model'
    return false
  end

  print_summary(model)

  true
end