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start of cythoning coregionalize

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James Hensman 2015-04-27 16:00:42 +01:00
parent 2e8ce34ee0
commit c00f76d250
3 changed files with 56 additions and 1 deletions
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10
GPy/kern/_src/coregionalize.py
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@ -111,6 +111,11 @@ class Coregionalize(Kern):
weave.inline(code, ['target', 'index', 'index2', 'N', 'num_inducing', 'B', 'output_dim'])
return target
def _K_cython(self, X, X2=None):
if X2 is None:
return coregionalize_cython.K_symmetric(self.B, X[:,0])
return coregionalize_cython.K_asymmetric(self.B, X[:,0], X2[:,0])
def Kdiag(self, X):
return np.diag(self.B)[np.asarray(X, dtype=np.int).flatten()]
@ -164,6 +169,11 @@ class Coregionalize(Kern):
dL_dK_small[j,i] = tmp1[:,index2==j].sum()
return dL_dK_small
def gradient_reduce_cython(self, dL_dK, index, index2):
index, index2 = index[:,0], index2[:,0]
return coregionalize_cython.gradient_reduce(self.output_dim, dL_dK, index, index2
def update_gradients_diag(self, dL_dKdiag, X):
index = np.asarray(X, dtype=np.int).flatten()
dL_dKdiag_small = np.array([dL_dKdiag[index==i].sum() for i in range(self.output_dim)])

41
GPy/kern/_src/coregionalize_cython.pyx Normal file
View file

@ -0,0 +1,41 @@
import cython
import numpy as np
cimport numpy as np
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.nonecheck(False)
def K_symmetric(np.ndarray[double, ndim=2] B, np.ndarray[int, ndim=1] X):
N = X.size
K = np.zeros((N, N))
for n in range(N):
for m in range(N):
K[n,m] = B[X[n],X[m]]
return K
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.nonecheck(False)
def K_asymmetric(np.ndarray[double, ndim=2] B, np.ndarray[int, ndim=1] X, np.ndarray[int, ndim=1] X2):
N = X.size
M = X2.size
K = np.zeros((N, M))
for n in range(N):
for m in range(M):
K[n,m] = B[X[n],X2[m]]
return K
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.nonecheck(False)
def gradient_reduce(int D, np.ndarray[double, ndim=2] dL_dK, np.ndarray[int, ndim=1] index, np.ndarray[int, ndim=1] index2):
dL_dK_small = np.zeros((D, D))
N = index.size
M = index2.size
for i in range(M):
for j in range(N):
dL_dK_small[index[j] + D*index2[i]] += dL_dK[i+j*M];
return dL_dK_small