def setUp(self):
SP.random.seed(1)
nr = 3
nc = 5
n_dim1 = 8
n_dim2 = 12
#truncation of soft kronecker
self.n_trunk = 10
Xr = SP.rand(nr, n_dim1)
Xc = SP.rand(nc, n_dim2)
Cr = dlimix.CCovSqexpARD(n_dim1)
Cr.setX(Xr)
Cc = dlimix.CCovLinearARD(n_dim2)
Cc.setX(Xc)
self.C = dlimix.CKroneckerCF()
self.C.setRowCovariance(Cr)
self.C.setColCovariance(Cc)
#set kronecker index
self.kronecker_index = dlimix.CKroneckerCF.createKroneckerIndex(nc, nr)
self.n = self.C.Kdim()
self.n_dim = self.C.getNumberDimensions()
self.name = 'CKroneckerCF'
self.n_params = self.C.getNumberParams()
params = SP.exp(SP.randn(self.n_params))
self.C.setParams(params)
def setUp(self):
SP.random.seed(1)
self.n = 10
self.n_dim = 10
X = SP.rand(self.n, self.n_dim)
self.C = dlimix.CCovLinearARD(self.n_dim)
self.name = 'CCovLinearARD'
self.C.setX(X)
self.n_params = self.C.getNumberParams()
K = self.C.K()
params = SP.exp(SP.randn(self.n_params))
self.C.setParams(params)
def setUp(self):
SP.random.seed(1)
self.n=10
n_dim1=8
n_dim2=12
self.C=dlimix.CProductCF()
self.C.addCovariance(dlimix.CCovSqexpARD(n_dim1));
self.C.addCovariance(dlimix.CCovLinearARD(n_dim2));
self.n_dim=self.C.getNumberDimensions()
X=SP.rand(self.n,self.n_dim)
self.C.setX(X)
self.name = 'CProductCF'
self.n_params=self.C.getNumberParams()
params=SP.exp(SP.randn(self.n_params))
self.C.setParams(params)
def setUp(self):
SP.random.seed(1)
self.n=10
n_dim2=12
K0 = SP.eye(self.n)
self.C=dlimix.CSumCF()
#sum of fixed CF and linearARD
covar1 = dlimix.CFixedCF(K0)
covar2 = dlimix.CCovLinearARD(n_dim2)
self.C.addCovariance(covar1)
self.C.addCovariance(covar2)
self.n_dim=self.C.getNumberDimensions()
self.X=SP.rand(self.n,self.n_dim)
self.C.setX(self.X)
self.name = 'CSumCF'
self.n_params=self.C.getNumberParams()
params=SP.exp(SP.randn(self.n_params))
self.C.setParams(params)
def setUp(self):
SP.random.seed(1)
n1=3
n2=5
n_dim1=8
n_dim2=12
X1 = SP.rand(n1,n_dim1)
X2 = SP.rand(n2,n_dim2)
C1 = dlimix.CCovSqexpARD(n_dim1); C1.setX(X1)
C2 = dlimix.CCovLinearARD(n_dim2); C2.setX(X2)
self.C = dlimix.CKroneckerCF()
self.C.setRowCovariance(C1)
self.C.setColCovariance(C2)
self.n = self.C.Kdim()
self.n_dim=self.C.getNumberDimensions()
self.name = 'CKroneckerCF'
self.n_params=self.C.getNumberParams()
params=SP.exp(SP.randn(self.n_params))
self.C.setParams(params)