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Removed SSM functionality - updated Kronecker grid case

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kcutajar 2016-05-01 21:50:34 +02:00
parent 3d346cbdd6
commit 83bd94185d
18 changed files with 765 additions and 624 deletions
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GPy/testing/grid_tests.py Normal file
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# Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
# Kurt Cutajar
import unittest
import numpy as np
import GPy
class GridModelTest(unittest.TestCase):
def setUp(self):
######################################
# # 3 dimensional example
# sample inputs and outputs
self.X = np.array([[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]])
self.Y = np.random.randn(8, 1) * 100
self.dim = self.X.shape[1]
def test_alpha_match(self):
kernel = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m = GPy.models.GPRegressionGrid(self.X, self.Y, kernel)
kernel2 = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m2 = GPy.models.GPRegression(self.X, self.Y, kernel2)
np.testing.assert_almost_equal(m.posterior.alpha, m2.posterior.woodbury_vector)
def test_gradient_match(self):
kernel = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m = GPy.models.GPRegressionGrid(self.X, self.Y, kernel)
kernel2 = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m2 = GPy.models.GPRegression(self.X, self.Y, kernel2)
np.testing.assert_almost_equal(kernel.variance.gradient, kernel2.variance.gradient)
np.testing.assert_almost_equal(kernel.lengthscale.gradient, kernel2.lengthscale.gradient)
np.testing.assert_almost_equal(m.likelihood.variance.gradient, m2.likelihood.variance.gradient)
def test_prediction_match(self):
kernel = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m = GPy.models.GPRegressionGrid(self.X, self.Y, kernel)
kernel2 = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True)
m2 = GPy.models.GPRegression(self.X, self.Y, kernel2)
test = np.array([[0,0,2],[-1,3,-4]])
np.testing.assert_almost_equal(m.predict(test), m2.predict(test))