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Neil Lawrence 2013-05-05 07:59:07 +01:00
parent e941c949e5
commit b6bac53da8
2 changed files with 6 additions and 5 deletions
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7
GPy/core/model.py
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@ -416,9 +416,10 @@ class model(parameterised):
""" """
return an array describing the sesitivity of the model to each input return an array describing the sesitivity of the model to each input
NB. Right now, we're basing this on the lengthscales (or variances) of the kernel. NB. Right now, we're basing this on the lengthscales (or
TODO: proper sensitivity analysis variances) of the kernel. TODO: proper sensitivity analysis
""" where we integrate across the model inputs and evaluate the
effect on the variance of the model output. """
if not hasattr(self, 'kern'): if not hasattr(self, 'kern'):
raise ValueError, "this model has no kernel" raise ValueError, "this model has no kernel"

4
GPy/examples/dimensionality_reduction.py
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@ -82,11 +82,11 @@ def BGPLVM_oil(optimize=True, N=100, Q=10, M=15, max_f_eval=300):
m.ensure_default_constraints() m.ensure_default_constraints()
y = m.likelihood.Y[0, :] y = m.likelihood.Y[0, :]
fig,(latent_axes,hist_axes) = plt.subplots(1,2) fig,(latent_axes,sense_axes) = plt.subplots(1,2)
plt.sca(latent_axes) plt.sca(latent_axes)
m.plot_latent() m.plot_latent()
data_show = GPy.util.visualize.vector_show(y) data_show = GPy.util.visualize.vector_show(y)
lvm_visualizer = GPy.util.visualize.lvm_dimselect(m.X[0, :], m, data_show, latent_axes=latent_axes, hist_axes=hist_axes) lvm_visualizer = GPy.util.visualize.lvm_dimselect(m.X[0, :], m, data_show, latent_axes=latent_axes, sense_axes=sense_axes)
raw_input('Press enter to finish') raw_input('Press enter to finish')
plt.close('all') plt.close('all')
# # plot # # plot