physbo.gp.predictor module¶
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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 --
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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)
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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
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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
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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
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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
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