From 6959a905dc13380200cb0e05edd9ffd1384ab170 Mon Sep 17 00:00:00 2001 From: Nicolo Fusi Date: Tue, 29 Jan 2013 17:23:51 +0000 Subject: [PATCH] broken commit, working on cross terms for psi statistics --- GPy/kern/kern.py | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/GPy/kern/kern.py b/GPy/kern/kern.py index 6201df35..7da4926a 100644 --- a/GPy/kern/kern.py +++ b/GPy/kern/kern.py @@ -6,7 +6,7 @@ import numpy as np from ..core.parameterised import parameterised from functools import partial from kernpart import kernpart - +import itertools class kern(parameterised): def __init__(self,D,parts=[], input_slices=None): @@ -262,6 +262,15 @@ class kern(parameterised): target = np.zeros((mu.shape[0],Z.shape[0],Z.shape[0])) slices1, slices2 = self._process_slices(slices1,slices2) [p.psi2(Z[s2,i_s],mu[s1,i_s],S[s1,i_s],target[s1,s2,s2]) for p,i_s,s1,s2 in zip(self.parts,self.input_slices,slices1,slices2)] + + # MASSIVE TODO: do something smart for white + # "crossterms" + psi1_matrices = [np.zeros((mu.shape[0], Z.shape[0])) for p in self.parts] + [p.psi1(Z[s2],mu[s1],S[s1],psi1_target[s1,s2]) for p,s1,s2,psi1_target in zip(self.parts,slices1,slices2, psi1_matrices)] + for a,b in itertools.combinations(psi1_matrices, 2): + tmp = np.multiply(a,b) + target += tmp[:,None,:] + tmp[:, :,None] + return target def dpsi2_dtheta(self,partial,Z,mu,S,slices1=None,slices2=None): @@ -269,12 +278,27 @@ class kern(parameterised): slices1, slices2 = self._process_slices(slices1,slices2) target = np.zeros(self.Nparam) [p.dpsi2_dtheta(partial[s1,s2,s2],Z[s2,i_s],mu[s1,i_s],S[s1,i_s],target[ps]) for p,i_s,s1,s2,ps in zip(self.parts,self.input_slices,slices1,slices2,self.param_slices)] + + + # "crossterms" + # 1. get all the psi1 statistics + psi1_matrices = [np.zeros((mu.shape[0], Z.shape[0])) for p in self.parts] + [p.psi1(Z[s2],mu[s1],S[s1],psi1_target[s1,s2]) for p,s1,s2,psi1_target in zip(self.parts,slices1,slices2, psi1_matrices)] + # 2. get all the dpsi1/dtheta gradients + psi1_gradients = [np.zeros(self.Nparam) for p in self.parts] + [p.dpsi1_dtheta(partial[s2,s1],Z[s2,i_s],mu[s1,i_s],S[s1,i_s],target[ps]) for p,ps,s1,s2,i_s in zip(self.parts, self.param_slices,slices1,slices2,self.input_slices)] + # 3. multiply them somehow + for a,b in itertools.combinations(range(len(psi1_matrices)), 2): + psi2_cross = np.multiply(psi1, psi1_grad) # some newaxis of this + target += psi2_cross[:,None,:] + psi2_cross[:, :,None] + return target def dpsi2_dZ(self,partial,Z,mu,S,slices1=None,slices2=None): slices1, slices2 = self._process_slices(slices1,slices2) target = np.zeros_like(Z) [p.dpsi2_dZ(partial[s1,s2,s2],Z[s2,i_s],mu[s1,i_s],S[s1,i_s],target[s2,i_s]) for p,i_s,s1,s2 in zip(self.parts,self.input_slices,slices1,slices2)] + return target def dpsi2_dmuS(self,partial,Z,mu,S,slices1=None,slices2=None):