From 27b3ad62dfc01f1d22d3e21ce1a538c0ae3c4a8e Mon Sep 17 00:00:00 2001 From: Andreas Date: Wed, 17 Jul 2013 17:05:11 +0100 Subject: [PATCH] Bgplvm_stick demo with rbf_inv --- GPy/examples/dimensionality_reduction.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index ac39fd66..a3b618d1 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -150,7 +150,7 @@ def BGPLVM_oil(optimize=True, N=200, Q=10, num_inducing=15, max_iters=50, plot=F m.data_labels = data['Y'][:N].argmax(axis=1) # m.constrain('variance|leng', logexp_clipped()) - m['.*lengt'] = 1. # m.X.var(0).max() / m.X.var(0) + m['.*lengt'] = 1. # 5./((np.max(m.X,0)-np.min(m.X,0))**2) # m.X.var(0).max() / m.X.var(0) m['noise'] = Yn.var() / 100. @@ -327,6 +327,7 @@ def brendan_faces(): # Y = data['Y'] Yn = Y - Y.mean() Yn /= Yn.std() + m.plot_latent() m = GPy.models.GPLVM(Yn, Q) # m = GPy.models.BayesianGPLVM(Yn, Q, num_inducing=100) @@ -373,11 +374,12 @@ def stick(): def stick_bgplvm(model=None): data = GPy.util.datasets.stick() Q = 6 - kernel = GPy.kern.rbf(Q, ARD=True) + GPy.kern.bias(Q, np.exp(-2)) + GPy.kern.white(Q, np.exp(-2)) - m = BayesianGPLVM(data['Y'], Q, init="PCA", num_inducing=20,kernel=kernel) + kernel = GPy.kern.rbf_inv(Q, ARD=True) + GPy.kern.bias(Q, np.exp(-2)) + GPy.kern.white(Q, np.exp(-2)) + m = BayesianGPLVM(data['Y'], Q, init="PCA", num_inducing=35,kernel=kernel) # optimize m.ensure_default_constraints() - m.optimize(messages=1, max_f_eval=3000,xtol=1e-300,ftol=1e-300) + m.constrain_bounded('.*rbf_inv',1e-5, 100) + m.optimize(messages=1, max_iters=3000,xtol=1e-300,ftol=1e-300) m._set_params(m._get_params()) plt.clf, (latent_axes, sense_axes) = plt.subplots(1, 2) plt.sca(latent_axes)