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some code to debug the sprase GP gradients with.

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James Hensman 2013-01-11 17:54:10 +00:00
parent f92ff10e32
commit 1a135ca9f7
4 changed files with 144 additions and 24 deletions
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37
grid_parameters.py
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@ -16,11 +16,14 @@ Y = np.sin(X) + np.random.randn(*X.shape)/np.sqrt(50.)
k = GPy.kern.rbf(1)
m = GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k)
m.constrain_fixed('iip')
models = [GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k),
GPy.models.sgp_debugB(X,Y,Z=Z,kernel=k),
GPy.models.sgp_debugC(X,Y,Z=Z,kernel=k),
GPy.models.sgp_debugE(X,Y,Z=Z,kernel=k)]
#[m.constrain_fixed('iip') for m in models]
#m.constrain_fixed('white',1e-6)
m.constrain_fixed('precision',50)
m.ensure_default_constraints()
#[m.constrain_fixed('precision',50) for m in models]
#[m.ensure_default_constraints() for m in models]
xx,yy = np.mgrid[1.5:4:0+resolution*1j,-2:2:0+resolution*1j]
@ -28,24 +31,16 @@ xx,yy = np.mgrid[1.5:4:0+resolution*1j,-2:2:0+resolution*1j]
lls = []
cgs = []
for l,v in zip(xx.flatten(),yy.flatten()):
m.set('lengthscale',l)
m.set('rbf_variance',10.**v)
lls.append(m.log_likelihood())
cgs.append(m.checkgrad())
#m.plot()
[m.set('lengthscale',l) for m in models]
[m.set('rbf_variance',10.**v) for m in models]
lls.append(models[0].log_likelihood())
cgs.append([m.checkgrad(verbose=0) for m in models])
lls = np.array(lls).reshape(resolution,resolution)
cgs = np.array(cgs,dtype=np.float64).reshape(resolution,resolution)
cgs = np.array(zip(*cgs),dtype=np.float64).reshape(-1,resolution,resolution)
pb.contourf(xx,yy,lls,np.linspace(-500,560,100),linewidths=2,cmap=pb.cm.jet)
pb.colorbar()
pb.scatter(xx.flatten(),yy.flatten(),10,cgs.flatten(),linewidth=0,cmap=pb.cm.gray)
pb.figure()
#pb.imshow(lls,origin='upper',cmap=pb.cm.jet,extent=[xx[0,0],xx[-1,0],yy[0].min(),yy[0].max()],vmin=-500)
pb.scatter(xx.flatten(),yy.flatten(),10,lls.flatten(),linewidth=0,cmap=pb.cm.jet)
pb.colorbar()
pb.figure()
#pb.imshow(cgs,origin='upper',cmap=pb.cm.jet,extent=[xx[0,0],xx[-1,0],yy[0].min(),yy[0].max()])
pb.scatter(xx.flatten(),yy.flatten(),10,cgs.flatten(),linewidth=0,cmap=pb.cm.jet)
pb.colorbar()
for cg in cgs:
pb.figure()
pb.contourf(xx,yy,lls,cmap=pb.cm.jet)
pb.scatter(xx.flatten(),yy.flatten(),12,cg.flatten(),cmap=pb.cm.gray)