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Merge branch 'devel' into saul_merge

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Alan Saul 2015-03-27 14:17:34 +00:00
commit 3c7a1b9a91
23 changed files with 372 additions and 389 deletions
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42
GPy/testing/inference_tests.py
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@ -11,39 +11,38 @@ import GPy
class InferenceXTestCase(unittest.TestCase):
def genData(self):
D1,D2,N = 12,12,50
np.random.seed(1234)
x = np.linspace(0, 4 * np.pi, N)[:, None]
s1 = np.vectorize(lambda x: np.sin(x))
s2 = np.vectorize(lambda x: np.cos(x)**2)
s3 = np.vectorize(lambda x:-np.exp(-np.cos(2 * x)))
sS = np.vectorize(lambda x: np.cos(x))
s1 = s1(x)
s2 = s2(x)
s3 = s3(x)
sS = sS(x)
s1 -= s1.mean(); s1 /= s1.std(0)
s2 -= s2.mean(); s2 /= s2.std(0)
s3 -= s3.mean(); s3 /= s3.std(0)
sS -= sS.mean(); sS /= sS.std(0)
S1 = np.hstack([s1, sS])
S2 = np.hstack([s3, sS])
P1 = np.random.randn(S1.shape[1], D1)
P2 = np.random.randn(S2.shape[1], D2)
Y1 = S1.dot(P1)
Y2 = S2.dot(P2)
Y1 += .01 * np.random.randn(*Y1.shape)
Y2 += .01 * np.random.randn(*Y2.shape)
Y1 -= Y1.mean(0)
Y2 -= Y2.mean(0)
Y1 /= Y1.std(0)
@ -52,33 +51,34 @@ class InferenceXTestCase(unittest.TestCase):
slist = [s1, s2, s3, sS]
slist_names = ["s1", "s2", "s3", "sS"]
Ylist = [Y1, Y2]
return Ylist
def test_inferenceX_BGPLVM(self):
Ys = self.genData()
m = GPy.models.BayesianGPLVM(Ys[0],5,kernel=GPy.kern.Linear(5,ARD=True))
x,mi = m.infer_newX(m.Y, optimize=False)
self.assertTrue(mi.checkgrad())
m.optimize(max_iters=10000)
x,mi = m.infer_newX(m.Y)
self.assertTrue(np.allclose(m.X.mean, mi.X.mean))
self.assertTrue(np.allclose(m.X.variance, mi.X.variance))
m.optimize(max_iters=10000)
x, mi = m.infer_newX(m.Y)
print m.X.mean - mi.X.mean
self.assertTrue(np.allclose(m.X.mean, mi.X.mean, rtol=1e-4, atol=1e-4))
self.assertTrue(np.allclose(m.X.variance, mi.X.variance, rtol=1e-4, atol=1e-4))
def test_inferenceX_GPLVM(self):
Ys = self.genData()
m = GPy.models.GPLVM(Ys[0],3,kernel=GPy.kern.RBF(3,ARD=True))
x,mi = m.infer_newX(m.Y, optimize=False)
self.assertTrue(mi.checkgrad())
# m.optimize(max_iters=10000)
# x,mi = m.infer_newX(m.Y)
# self.assertTrue(np.allclose(m.X, x))
if __name__ == "__main__":
unittest.main()

34
GPy/testing/svgp_tests.py Normal file
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@ -0,0 +1,34 @@
import numpy as np
import scipy as sp
import GPy
class SVGP_nonconvex(np.testing.TestCase):
"""
Inference in the SVGP with a student-T likelihood
"""
def setUp(self):
X = np.linspace(0,10,100).reshape(-1,1)
Z = np.linspace(0,10,10).reshape(-1,1)
Y = np.sin(X) + np.random.randn(*X.shape)*0.1
Y[50] += 3
lik = GPy.likelihoods.StudentT(deg_free=2)
k = GPy.kern.RBF(1, lengthscale=5.) + GPy.kern.White(1, 1e-6)
self.m = GPy.core.SVGP(X, Y, Z=Z, likelihood=lik, kernel=k)
def test_grad(self):
assert self.m.checkgrad(step=1e-4)
class SVGP_classification(np.testing.TestCase):
"""
Inference in the SVGP with a Bernoulli likelihood
"""
def setUp(self):
X = np.linspace(0,10,100).reshape(-1,1)
Z = np.linspace(0,10,10).reshape(-1,1)
Y = np.where((np.sin(X) + np.random.randn(*X.shape)*0.1)>0, 1,0)
lik = GPy.likelihoods.Bernoulli()
k = GPy.kern.RBF(1, lengthscale=5.) + GPy.kern.White(1, 1e-6)
self.m = GPy.core.SVGP(X, Y, Z=Z, likelihood=lik, kernel=k)
def test_grad(self):
assert self.m.checkgrad(step=1e-4)