def setUp(self):
SP.random.seed(1)
self.n_dimensions = 2
self.n_samples = 100
self.setXy()
#self.X = SP.rand(self.n_samples,self.n_dimensions)
covar = dlimix.CCovSqexpARD(self.n_dimensions)
ll = dlimix.CLikNormalIso()
covar_params = SP.array([1, 1, 1])
lik_params = SP.array([0.5])
hyperparams0 = dlimix.CGPHyperParams()
hyperparams0['covar'] = covar_params
hyperparams0['lik'] = lik_params
self.constrainU = dlimix.CGPHyperParams()
self.constrainL = dlimix.CGPHyperParams()
self.constrainU['covar'] = +10 * SP.ones_like(covar_params)
self.constrainL['covar'] = 0 * SP.ones_like(covar_params)
self.constrainU['lik'] = +5 * SP.ones_like(lik_params)
self.constrainL['lik'] = 0 * SP.ones_like(lik_params)
self.gp = dlimix.CGPbase(covar, ll)
self.gp.setX(self.X)
self.gp.setParams(hyperparams0)
#self.genY()
self.gp.setY(self.y)
def setUp(self):
SP.random.seed(1)
#1. simulate
self.settings = {'K': 5, 'N': 100, 'D': 80}
self.simulation = self.simulate()
N = self.settings['N']
K = self.settings['K']
D = self.settings['D']
#2. setup GP
covar = dlimix.CCovLinearISO(K)
ll = dlimix.CLikNormalIso()
#create hyperparm
covar_params = SP.array([1.0])
lik_params = SP.array([1.0])
hyperparams = dlimix.CGPHyperParams()
hyperparams['covar'] = covar_params
hyperparams['lik'] = lik_params
hyperparams['X'] = self.simulation['X0']
#cretae GP
self.gp = dlimix.CGPbase(covar, ll)
#set data
self.gp.setY(self.simulation['Y'])
self.gp.setX(self.simulation['X0'])
self.gp.setParams(hyperparams)
pass
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.CLikNormalIso()
self.name = 'CLikNormalIso'
self.C.setX(X)
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)
#1. simulate
self.settings = {'K': 5, 'N': 100, 'D': 80}
self.simulation = self.simulate()
N = self.settings['N']
K = self.settings['K']
D = self.settings['D']
#2. setup GP
K0 = SP.dot(self.simulation['S'], self.simulation['S'].T)
K0[:] = 0
covar1 = dlimix.CFixedCF(K0)
covar2 = dlimix.CCovLinearISO(K)
covar = dlimix.CSumCF()
covar.addCovariance(covar1)
covar.addCovariance(covar2)
ll = dlimix.CLikNormalIso()
#create hyperparm
covar_params = SP.array([0.0, 1.0])
lik_params = SP.array([0.1])
hyperparams = dlimix.CGPHyperParams()
hyperparams['covar'] = covar_params
hyperparams['lik'] = lik_params
hyperparams['X'] = self.simulation['X0']
#cretae GP
self.gp = dlimix.CGPbase(covar, ll)
#set data
self.gp.setY(self.simulation['Y'])
self.gp.setX(self.simulation['X0'])
self.gp.setParams(hyperparams)
pass