physbo.gp.predictor module

class physbo.gp.predictor.predictor(config, model=None)[ソース]

ベースクラス: physbo.predictor.base_predictor

delete_stats()[ソース]

Default function to delete status This function must be overwritten in each model.

パラメータ:
  • args --
  • kwds --
fit(training, num_basis=None)[ソース]

Fitting model to training dataset

パラメータ:
  • training (physbo.variable) -- dataset for training
  • num_basis (int) -- the number of basis (default: self.config.predict.num_basis)
get_basis(*args, **kwds)[ソース]
パラメータ:
  • args --
  • kwds --
get_post_fcov(training, test, diag=True)[ソース]

Calculating posterior variance-covariance matrix of model

パラメータ:
  • training (physbo.variable) -- training dataset. If already trained, the model does not use this.
  • test (physbo.variable) -- inputs
  • diag (bool) -- Diagonlization flag in physbo.exact.get_post_fcov function.
戻り値:
戻り値の型:

numpy.ndarray
get_post_fmean(training, test)[ソース]

Calculating posterior mean value of model

パラメータ:
  • training (physbo.variable) -- training dataset. If already trained, the model does not use this.
  • test (physbo.variable) -- inputs
戻り値:
戻り値の型:

numpy.ndarray
get_post_params(*args, **kwds)[ソース]
パラメータ:
  • args --
  • kwds --
get_post_samples(training, test, alpha=1)[ソース]

Drawing samples of mean values of model

パラメータ:
  • training (physbo.variable) -- training dataset. If already trained, the model does not use this.
  • test (physbo.variable) -- inputs (not used)
  • alpha (float) -- tuning parameter of the covariance by multiplying alpha**2 for np.random.multivariate_normal.
戻り値:
戻り値の型:

numpy.ndarray
get_predict_samples(training, test, N=1)[ソース]

Drawing samples of values of model

パラメータ:
  • training (physbo.variable) -- training dataset. If already trained, the model does not use this.
  • test (physbo.variable) -- inputs
  • N (int) -- number of samples (default: 1)
戻り値:
戻り値の型:

numpy.ndarray
prepare(training)[ソース]

Initializing model by using training data set

パラメータ:training (physbo.variable) -- dataset for training