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various hackday stuff, including scale factor in sparse GP

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James Hensman 2013-01-18 17:47:50 +00:00
parent 194d3ebda7
commit 0fb8ab91bb
5 changed files with 32 additions and 32 deletions
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21
grid_parameters.py
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@ -6,8 +6,8 @@ import GPy
pb.close('all')
N = 1000
M = 10
N = 200
M = 15
resolution=5
X = np.linspace(0,12,N)[:,None]
@ -16,15 +16,22 @@ Y = np.sin(X) + np.random.randn(*X.shape)/np.sqrt(50.)
#k = GPy.kern.rbf(1)
k = GPy.kern.Matern32(1) + GPy.kern.white(1)
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)]#,
models = [GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k)
,GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k)
,GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k)
,GPy.models.sparse_GP_regression(X,Y,Z=Z,kernel=k)]
models[0].scale_factor = 1.
models[1].scale_factor = 10.
models[2].scale_factor = 100.
models[3].scale_factor = 1000.
#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('white',0.001) for m in models]
[m.constrain_fixed('white',0.1) for m in models]
#xx,yy = np.mgrid[1.5:4:0+resolution*1j,-2:2:0+resolution*1j]
xx,yy = np.mgrid[3:16:0+resolution*1j,-2:2:0+resolution*1j]
xx,yy = np.mgrid[3:16:0+resolution*1j,-2:1:0+resolution*1j]
lls = []
cgs = []