Class: Prophet::StanBackend

Inherits:
Object
  • Object
show all
Defined in:
lib/prophet/stan_backend.rb

Instance Method Summary collapse

Constructor Details

#initialize(logger) ⇒ StanBackend

Returns a new instance of StanBackend.



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# File 'lib/prophet/stan_backend.rb', line 3

def initialize(logger)
  @model = load_model
  @logger = logger
end

Instance Method Details

#fit(stan_init, stan_data, **kwargs) ⇒ Object 



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# File 'lib/prophet/stan_backend.rb', line 14

def fit(stan_init, stan_data, **kwargs)
  stan_init, stan_data = prepare_data(stan_init, stan_data)

  if !kwargs[:inits] && kwargs[:init]
    kwargs[:inits] = prepare_data(kwargs.delete(:init), stan_data)[0]
  end

  kwargs[:algorithm] ||= stan_data["T"] < 100 ? "Newton" : "LBFGS"
  iterations = 10000

  args = {
    data: stan_data,
    inits: stan_init,
    iter: iterations
  }
  args.merge!(kwargs)

  stan_fit = nil
  begin
    stan_fit = @model.optimize(**args)
  rescue => e
    if kwargs[:algorithm] != "Newton"
      @logger.warn "Optimization terminated abnormally. Falling back to Newton."
      kwargs[:algorithm] = "Newton"
      stan_fit = @model.optimize(
        data: stan_data,
        inits: stan_init,
        iter: iterations,
        **kwargs
      )
    else
      raise e
    end
  end

  params = stan_to_numo(stan_fit.column_names, Numo::NArray.asarray(stan_fit.optimized_params.values))
  params.each_key do |par|
    params[par] = params[par].reshape(1, *params[par].shape)
  end
  params
end

#load_model ⇒ Object

Raises:



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# File 'lib/prophet/stan_backend.rb', line 8

def load_model
  model_file = File.expand_path("../../vendor/#{platform}/bin/prophet", __dir__)
  raise Error, "Platform not supported yet" unless File.exist?(model_file)
  CmdStan::Model.new(exe_file: model_file)
end

#sampling(stan_init, stan_data, samples, **kwargs) ⇒ Object 



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# File 'lib/prophet/stan_backend.rb', line 56

def sampling(stan_init, stan_data, samples, **kwargs)
  stan_init, stan_data = prepare_data(stan_init, stan_data)

  if !kwargs[:inits] && kwargs[:init]
    kwargs[:inits] = prepare_data(kwargs.delete(:init), stan_data)[0]
  end

  kwargs[:chains] ||= 4
  kwargs[:warmup_iters] ||= samples / 2

  stan_fit = @model.sample(
    data: stan_data,
    inits: stan_init,
    sampling_iters: samples,
    **kwargs
  )
  res = Numo::NArray.asarray(stan_fit.sample)
  samples, c, columns = res.shape
  res = res.reshape(samples * c, columns)
  params = stan_to_numo(stan_fit.column_names, res)

  params.each_key do |par|
    s = params[par].shape

    if s[1] == 1
      params[par] = params[par].reshape(s[0])
    end

    if ["delta", "beta"].include?(par) && s.size < 2
      params[par] = params[par].reshape(-1, 1)
    end
  end

  params
end