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Changes in plotting functions.

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This commit is contained in:
Ricardo Andrade 2013-02-01 17:58:21 +00:00
parent f7d2fc6ca4
commit 5e2baf1919
5 changed files with 71 additions and 31 deletions
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59
GPy/models/GP.py
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@ -7,7 +7,7 @@ import pylab as pb
from .. import kern
from ..core import model
from ..util.linalg import pdinv,mdot
from ..util.plot import gpplot,x_frame, Tango
from ..util.plot import gpplot,x_frame1D,x_frame2D, Tango
from ..likelihoods import EP
class GP(model):
@ -175,7 +175,7 @@ class GP(model):
return mean, _5pc, _95pc
def plot_GP(self,samples=0,plot_limits=None,which_data='all',which_functions='all',resolution=None,full_cov=False):
def plot_internal(self,samples=0,plot_limits=None,which_data='all',which_functions='all',resolution=None,full_cov=False):
"""
Plot the GP's view of the world, where the data is normalised and the likelihood is Gaussian
@ -200,22 +200,49 @@ class GP(model):
if which_data=='all':
which_data = slice(None)
Xnew, xmin, xmax = x_frame(self.X, plot_limits=plot_limits)
if self.X.shape[1] == 1:
Xnew, xmin, xmax = x_frame1D(self.X, plot_limits=plot_limits)
m,v = self._raw_predict(Xnew, slices=which_functions)
gpplot(Xnew,m,m-np.sqrt(v),m+np.sqrt(v))
pb.plot(self.X[which_data],self.likelihood.Y[which_data],'kx',mew=1.5)
pb.xlim(xmin,xmax)
elif X.shape[1]==2:
resolution = resolution or 50
Xnew, xmin, xmax,xx,yy = x_frame2D(self.X, plot_limits=plot_limits)
m,v = self._raw_predict(Xnew, slices=which_functions)
m = m.reshape(resolution,resolution)
pb.contour(xx,yy,zz,vmin=zz.min(),vmax=zz.max(),cmap=pb.cm.jet)
pb.scatter(Xorig[:,0],Xorig[:,1],40,Yorig,linewidth=0,cmap=pb.cm.jet,vmin=zz.min(),vmax=zz.max())
pb.xlim(xmin[0],xmax[0])
pb.ylim(xmin[1],xmax[1])
else:
raise NotImplementedError, "Cannot define a frame with more than two input dimensions"
m,v = self._raw_predict(Xnew, slices=which_functions)
gpplot(Xnew,m,m-np.sqrt(v),m+np.sqrt(v))
pb.plot(self.X[which_data],self.likelihood.Y[which_data],'kx',mew=1.5)
pb.xlim(xmin,xmax)
def plot_output(self,samples=0,plot_limits=None,which_data='all',which_functions='all',resolution=None,full_cov=False):
def plot(self,samples=0,plot_limits=None,which_data='all',which_functions='all',resolution=None,full_cov=False):
if which_functions=='all':
which_functions = [True]*self.kern.Nparts
if which_data=='all':
which_data = slice(None)
Xnew, xmin, xmax = x_frame(self.X, plot_limits=plot_limits)
m, lower, upper = self.predict(Xnew, slices=which_functions)
gpplot(Xnew,m, lower, upper)
pb.plot(self.X[which_data],self.likelihood.data[which_data],'kx',mew=1.5)
ymin,ymax = self.likelihood.data.min()*1.2,self.likelihood.data.max()*1.2
pb.xlim(xmin,xmax)
pb.ylim(ymin,ymax)
if self.X.shape[1] == 1:
Xnew, xmin, xmax = x_frame1D(self.X, plot_limits=plot_limits)
m, lower, upper = self.predict(Xnew, slices=which_functions)
gpplot(Xnew,m, lower, upper)
pb.plot(self.X[which_data],self.likelihood.data[which_data],'kx',mew=1.5)
ymin,ymax = self.likelihood.data.min()*1.2,self.likelihood.data.max()*1.2
pb.xlim(xmin,xmax)
pb.ylim(ymin,ymax)
elif X.shape[1]==2:
resolution = resolution or 50
Xnew, xmin, xmax,xx,yy = x_frame2D(self.X, plot_limits=plot_limits)
m,v = self.predict(Xnew, slices=which_functions)
m = m.reshape(resolution,resolution)
pb.contour(xx,yy,zz,vmin=zz.min(),vmax=zz.max(),cmap=pb.cm.jet)
pb.scatter(Xorig[:,0],Xorig[:,1],40,Yorig,linewidth=0,cmap=pb.cm.jet,vmin=zz.min(),vmax=zz.max())
pb.xlim(xmin[0],xmax[0])
pb.ylim(xmin[1],xmax[1])
else:
raise NotImplementedError, "Cannot define a frame with more than two input dimensions"