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celinelee
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python_fn_calls

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cov.RBF()
lik.Gauss()
inf.Exact()
opt.Minimize(self)
setNoise(self,log_sigma)
lik.Gauss(log_sigma)
setOptimizer(self, method, num_restarts=None, min_threshold=None, meanRange=None, covRange=None, likRange=None)
if (num_restarts!=None)
or (min_threshold!=None)
pyGPs.Optimization.conf.random_init_conf(self.meanfunc,self.covfunc,self.likfunc)
opt.Minimize(self,conf)
opt.SCG(self,conf)
opt.CG(self,conf)
opt.BFGS(self,conf)
opt.Simplex(self, conf)
Exception('Optimization method is not set correctly in setOptimizer')
plot(self,axisvals=None)
plt.figure()
np.reshape(xs,(xs.shape[0],)
np.reshape(ym,(ym.shape[0],)
np.reshape(ys2,(ys2.shape[0],)
plt.plot(x, y, color=DATACOLOR, ls='None', marker='+',ms=12, mew=2)
plt.plot(xs, ym, color=MEANCOLOR, ls='-', lw=3.)
plt.fill_between(xss,ymm + 2.*np.sqrt(ys22)
np.sqrt(ys22)
plt.grid()
plt.axis(axisvals)
plt.xlabel('input x')
plt.ylabel('target y')
plt.show()
useInference(self, newInf)
inf.Laplace()
inf.EP()
Exception('Possible inf values are "Laplace", "EP".')
useLikelihood(self,newLik)
lik.Laplace()
inf.EP()
Exception('Possible lik values are "Laplace".')
GPC(GP)
__init__(self)
super(GPC, self)
__init__()
mean.Zero()
cov.RBF()
lik.Erf()
inf.EP()
opt.Minimize(self)
setOptimizer(self, method, num_restarts=None, min_threshold=None, meanRange=None, covRange=None, likRange=None)
if (num_restarts!=None)
or (min_threshold!=None)
pyGPs.Optimization.conf.random_init_conf(self.meanfunc,self.covfunc,self.likfunc)
opt.Minimize(self,conf)
opt.SCG(self,conf)
opt.CG(self,conf)
opt.BFGS(self,conf)
plot(self,x1,x2,t1,t2,axisvals=None)
are (only)
plt.figure()
plt.plot(x1[:,0], x1[:,1], 'b+', markersize = 12)
plt.plot(x2[:,0], x2[:,1], 'r+', markersize = 12)
plt.contour(t1, t2, np.reshape(np.exp(self.lp)
fig.colorbar(pc)
plt.grid()
plt.axis(axisvals)
plt.show()
useInference(self, newInf)
inf.Laplace()
Exception('Possible inf values are "Laplace".')
useLikelihood(self,newLik)
function. (Not used in this version)
Exception("Logistic likelihood is currently not implemented.")
lik.Logistic()
Exception('Possible lik values are "Logistic".')
GPMC(object)
__init__(self, n_class)
mean.Zero()
cov.RBF()
setPrior(self, mean=None, kernel=None)
class. (e.g. mean.Linear()
class. (e.g. cov.RBF()
isinstance(mean, pyGPs.mean.Mean)
isinstance(kernel, pyGPs.cov.Kernel)
type(kernel)
useInference(self, newInf)
inf.Laplace()
Exception('Possible inf values are "Laplace".')
useLikelihood(self,newLik)
function. (Not used in this version)
Exception("Logistic likelihood is currently not implemented.")
lik.Logistic()
Exception('Possible lik values are "Logistic".')
setData(self,x,y)
shape (n,D)
shape (n,1)
np.reshape(x, (x.shape[0],1)
np.reshape(y, (y.shape[0],1)
fitAndPredict(self, xs)
points (given by xs)
np.reshape(xs, (xs.shape[0],1)
np.zeros((xs.shape[0],self.n_class)