Class: CmdStan::Model

Inherits:
Object
  • Object
show all
Includes:
Utils
Defined in:
lib/cmdstan/model.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(stan_file: nil, exe_file: nil, compile: true) ⇒ Model

Returns a new instance of Model.



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# File 'lib/cmdstan/model.rb', line 7

def initialize(stan_file: nil, exe_file: nil, compile: true)
  # convert to absolute path
  stan_file = File.expand_path(stan_file) if stan_file

  @stan_file = stan_file
  @exe_file = exe_file || stan_file.sub(/.stan\z/, extension)
  @name = File.basename(@exe_file, extension)

  if compile && !exe_file
    self.compile
  end
end

Instance Attribute Details

#exe_file ⇒ Object (readonly)

Returns the value of attribute exe_file.



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# File 'lib/cmdstan/model.rb', line 5

def exe_file
  @exe_file
end

#name ⇒ Object (readonly)

Returns the value of attribute name.



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# File 'lib/cmdstan/model.rb', line 5

def name
  @name
end

#stan_file ⇒ Object (readonly)

Returns the value of attribute stan_file.



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# File 'lib/cmdstan/model.rb', line 5

def stan_file
  @stan_file
end

Instance Method Details

#code ⇒ Object 



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# File 'lib/cmdstan/model.rb', line 30

def code
  File.read(stan_file)
end

#compile ⇒ Object 



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# File 'lib/cmdstan/model.rb', line 20

def compile
  unless ENV["CMDSTAN"] || CmdStan.cmdstan_installed?
    CmdStan.install_cmdstan
  end

  Dir.chdir(CmdStan.path) do
    run_command make_command, @exe_file, "PRECOMPILED_HEADERS=false"
  end
end

#optimize(data:, seed: nil, inits: nil, algorithm: nil, iter: nil) ⇒ Object 



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# File 'lib/cmdstan/model.rb', line 76

def optimize(data:, seed: nil, inits: nil, algorithm: nil, iter: nil)
  data_file = Tempfile.new(["cmdstan", ".json"])
  data_file.write(data.to_json)
  data_file.close

  output_file = Tempfile.new(["cmdstan", ".csv"])
  diagnostic_file = Tempfile.new(["cmdstan", ".csv"])

  args = [@exe_file]

  # random
  args += ["random", "seed=#{seed.to_i}"] if seed

  # data
  args += ["data", "file=#{data_file.path}"]
  if inits
    init_file = Tempfile.new(["cmdstan", ".json"])
    init_file.write(inits.to_json)
    init_file.close
    args << "init=#{init_file.path}"
  end

  # output
  args += ["output", "file=#{output_file.path}", "diagnostic_file=#{diagnostic_file.path}"]

  # method
  args << "method=optimize"
  args << "algorithm=#{algorithm.to_s.downcase}" if algorithm
  args << "iter=#{iter.to_i}" if iter

  run_command(*args)

  MLE.new(output_file)
end

#sample(data:, chains: nil, seed: nil, inits: nil, warmup_iters: nil, sampling_iters: nil) ⇒ Object 



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# File 'lib/cmdstan/model.rb', line 34

def sample(data:, chains: nil, seed: nil, inits: nil, warmup_iters: nil, sampling_iters: nil)
  data_file = Tempfile.new(["cmdstan", ".json"])
  data_file.write(data.to_json)
  data_file.close

  chains ||= 4

  output_files = []
  chains.times do |chain|
    output_file = Tempfile.new(["cmdstan", ".csv"])

    args = [@exe_file, "id=#{chain + 1}"]

    # random
    args += ["random", "seed=#{seed.to_i}"] if seed

    # data
    args += ["data", "file=#{data_file.path}"]
    if inits
      init_file = Tempfile.new(["cmdstan", ".json"])
      init_file.write(inits.to_json)
      init_file.close
      args << "init=#{init_file.path}"
    end

    # output
    args += ["output", "file=#{output_file.path}"]

    # method
    args += ["method=sample"]
    args << "num_warmup=#{warmup_iters.to_i}" if warmup_iters
    args << "num_samples=#{sampling_iters.to_i}" if sampling_iters
    args += ["algorithm=hmc", "adapt", "engaged=1"]

    run_command(*args)

    output_files << output_file
  end

  MCMC.new(output_files)
end