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input_sensitivity and ard plotting

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Max Zwiessele 2014-02-24 14:47:43 +00:00
parent d90d67a8c1
commit b200b9fa90
11 changed files with 108 additions and 83 deletions
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24
GPy/kern/_src/add.py
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@ -83,7 +83,7 @@ class Add(Kern):
from white import White
from rbf import RBF
#from rbf_inv import RBFInv
#from bias import Bias
from bias import Bias
from linear import Linear
#ffrom fixed import Fixed
@ -131,11 +131,11 @@ class Add(Kern):
def gradients_Z_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, mu, S, Z):
from white import white
from rbf import rbf
from white import White
from rbf import RBF
#from rbf_inv import rbfinv
#from bias import bias
from linear import linear
from bias import Bias
from linear import Linear
#ffrom fixed import fixed
target = np.zeros(Z.shape)
@ -146,15 +146,15 @@ class Add(Kern):
for p2, is2 in zip(self._parameters_, self.input_slices):
if p2 is p1:
continue
if isinstance(p2, white):
if isinstance(p2, White):
continue
elif isinstance(p2, bias):
elif isinstance(p2, Bias):
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.variance * 2.
else:
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(z[:,is2], mu[:,is2], s[:,is2]) * 2.
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z[:,is2], mu[:,is2], S[:,is2]) * 2.
target += p1.gradients_z_variational(dL_dkmm, dL_dpsi0, eff_dL_dpsi1, dL_dpsi2, mu[:,is1], s[:,is1], z[:,is1])
target += p1.gradients_z_variational(dL_dKmm, dL_dpsi0, eff_dL_dpsi1, dL_dpsi2, mu[:,is1], S[:,is1], Z[:,is1])
return target
def gradients_muS_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, mu, S, Z):
@ -195,6 +195,12 @@ class Add(Kern):
from ..plotting.matplot_dep import kernel_plots
kernel_plots.plot(self,*args)
def input_sensitivity(self):
in_sen = np.zeros((self.input_dim, self.num_params))
for i, [p, i_s] in enumerate(zip(self._parameters_, self.input_slices)):
in_sen[i_s, i] = p.input_sensitivity()
return in_sen
def _getstate(self):
"""
Get the current state of the class,