apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-11 13:02:38 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

getting examples running

Browse source
This commit is contained in:
Max Zwiessele 2013-06-05 13:58:55 +01:00
parent 2e5e8ac026
commit 7238b62f4a
3 changed files with 7 additions and 7 deletions
Download patch file Download diff file Expand all files Collapse all files

2
GPy/examples/dimensionality_reduction.py
View file

@ -297,7 +297,7 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw):
if optimize: if optimize:
print "Optimizing Model:" print "Optimizing Model:"
m.optimize('scg', messages=1, max_iters=5e4, max_f_eval=5e4) m.optimize('scg', messages=1, max_iters=5e4, max_f_eval=5e4, gtol=.05)
if plot: if plot:
m.plot_X_1d("MRD Latent Space 1D") m.plot_X_1d("MRD Latent Space 1D")
m.plot_scales("MRD Scales") m.plot_scales("MRD Scales")

8
GPy/examples/tutorials.py
View file

@ -19,7 +19,7 @@ def tuto_GP_regression():
kernel = GPy.kern.rbf(D=1, variance=1., lengthscale=1.) kernel = GPy.kern.rbf(D=1, variance=1., lengthscale=1.)
m = GPy.models.GP_regression(X,Y,kernel) m = GPy.models.GPRegression(X, Y, kernel)
print m print m
m.plot() m.plot()
@ -47,7 +47,7 @@ def tuto_GP_regression():
ker = GPy.kern.Matern52(2,ARD=True) + GPy.kern.white(2) ker = GPy.kern.Matern52(2,ARD=True) + GPy.kern.white(2)
# create simple GP model # create simple GP model
m = GPy.models.GP_regression(X,Y,ker) m = GPy.models.GPRegression(X, Y, ker)
# contrain all parameters to be positive # contrain all parameters to be positive
m.constrain_positive('') m.constrain_positive('')
@ -145,7 +145,7 @@ def tuto_kernel_overview():
Y = 0.5*X[:,:1] + 0.5*X[:,1:] + 2*np.sin(X[:,:1]) * np.sin(X[:,1:]) Y = 0.5*X[:,:1] + 0.5*X[:,1:] + 2*np.sin(X[:,:1]) * np.sin(X[:,1:])
# Create GP regression model # Create GP regression model
m = GPy.models.GP_regression(X,Y,Kanova) m = GPy.models.GPRegression(X, Y, Kanova)
pb.figure(figsize=(5,5)) pb.figure(figsize=(5,5))
m.plot() m.plot()
@ -196,5 +196,5 @@ def model_interaction():
X = np.random.randn(20,1) X = np.random.randn(20,1)
Y = np.sin(X) + np.random.randn(*X.shape)*0.01 + 5. Y = np.sin(X) + np.random.randn(*X.shape)*0.01 + 5.
k = GPy.kern.rbf(1) + GPy.kern.bias(1) k = GPy.kern.rbf(1) + GPy.kern.bias(1)
return GPy.models.GP_regression(X,Y,kernel=k) return GPy.models.GPRegression(X, Y, kernel=k)

4
GPy/models/mrd.py
View file

@ -273,8 +273,8 @@ class MRD(model):
else: else:
return pylab.gcf() return pylab.gcf()
def plot_X_1d(self): def plot_X_1d(self, *a, **kw):
return self.gref.plot_X_1d() return self.gref.plot_X_1d(*a, **kw)
def plot_X(self, fignum=None, ax=None): def plot_X(self, fignum=None, ax=None):
fig = self._handle_plotting(fignum, ax, lambda i, g, ax: ax.imshow(g.X)) fig = self._handle_plotting(fignum, ax, lambda i, g, ax: ax.imshow(g.X))