Class: TSNE::Model

Inherits:
Object
  • Object
show all
Defined in:
lib/tsne/model.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(n_components: 2, perplexity: 30.0, early_exaggeration: 12, learning_rate: 200, n_iter: 1000, n_iter_early_exag: 250, verbose: 0, random_state: -1,, angle: 0.5, n_jobs: 1, cheat_metric: true) ⇒ Model

Returns a new instance of Model.



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

def initialize(n_components: 2, perplexity: 30.0,
  early_exaggeration: 12, learning_rate: 200,
  n_iter: 1000, n_iter_early_exag: 250, verbose: 0,
  random_state: -1, angle: 0.5, n_jobs: 1, cheat_metric: true)

  @n_components = n_components
  @perplexity = perplexity
  @early_exaggeration = early_exaggeration
  @learning_rate = learning_rate
  @n_iter = n_iter
  @n_iter_early_exag = n_iter_early_exag
  @verbose = verbose
  @random_state = random_state
  @angle = angle
  @n_jobs = n_jobs
  @cheat_metric = cheat_metric
end

Instance Attribute Details

#kl_divergence ⇒ Object (readonly)

Returns the value of attribute kl_divergence.



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# File 'lib/tsne/model.rb', line 3

def kl_divergence
  @kl_divergence
end

#n_iter ⇒ Object (readonly)

Returns the value of attribute n_iter.



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# File 'lib/tsne/model.rb', line 3

def n_iter
  @n_iter
end

Instance Method Details

#fit(x) ⇒ Object 



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# File 'lib/tsne/model.rb', line 23

def fit(x)
  fit_transform(x)
  self
end

#fit_transform(x) ⇒ Object 



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# File 'lib/tsne/model.rb', line 28

def fit_transform(x)
  x = Numo::DFloat.cast(x) unless x.is_a?(Numo::NArray)
  x = x.cast_to(Numo::DFloat) unless x.is_a?(Numo::DFloat)
  n, d = x.shape

  x = Fiddle::Pointer[x.to_binary]
  y = Fiddle::Pointer.malloc(n * @n_components * Fiddle::SIZEOF_DOUBLE)
  final_error = Fiddle::Pointer.malloc(Fiddle::SIZEOF_DOUBLE)

  FFI.tsne_run_double(
    x, n, d, y, @n_components, @perplexity, @angle, @n_jobs,
    @n_iter, @n_iter_early_exag, @random_state, 0, @verbose, @early_exaggeration,
    @learning_rate, final_error, @cheat_metric ? 1 : 0
  )

  @kl_divergence = final_error[0, final_error.size].unpack1("d")

  Numo::DFloat.from_binary(y[0, y.size]).reshape(n, @n_components)
end