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tests passing (cython)

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This commit is contained in:
James Hensman 2015-04-28 14:57:00 +01:00
parent e1c2eeb25d
commit 9e4c33910f
11 changed files with 6899 additions and 1256 deletions
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358
GPy/util/choleskies_cython.c
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1
GPy/util/choleskies_cython.pyx
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@ -11,7 +11,6 @@ def flat_to_triang(np.ndarray[double, ndim=2] flat, int M):
N = M(M+1)/2
the lower triangluar portion of the d'th slice of the result is filled by the d'th column of flat.
This is the weave implementation
"""
cdef int N = flat.shape[0]
cdef int D = flat.shape[1]

111
GPy/util/linalg.py
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@ -15,11 +15,7 @@ import warnings
import os
from .config import config
import logging
try:
from scipy import weave
except ImportError:
config.set('weave', 'working', 'False')
import linalg_cython
_scipyversion = np.float64((scipy.__version__).split('.')[:2])
@ -422,114 +418,33 @@ def DSYR(*args, **kwargs):
def symmetrify(A, upper=False):
"""
Take the square matrix A and make it symmetrical by copting elements from the lower half to the upper
Take the square matrix A and make it symmetrical by copting elements from
the lower half to the upper
works IN PLACE.
note: tries to use weave, falls back to a slower numpy version
note: tries to use cython, falls back to a slower numpy version
"""
if config.getboolean('weave', 'working'):
try:
symmetrify_weave(A, upper)
except:
print("\n Weave compilation failed. Falling back to (slower) numpy implementation\n")
config.set('weave', 'working', 'False')
symmetrify_numpy(A, upper)
if config.getboolean('cython', 'working'):
_symmetrify_cython(A, upper)
else:
symmetrify_numpy(A, upper)
_symmetrify_numpy(A, upper)
def symmetrify_weave(A, upper=False):
"""
Take the square matrix A and make it symmetrical by copting elements from the lower half to the upper
def _symmetrify_cython(A, upper=False):
return linalg_cython.symmetrify(A, upper)
works IN PLACE.
"""
N, M = A.shape
assert N == M
c_contig_code = """
int iN;
for (int i=1; i<N; i++){
iN = i*N;
for (int j=0; j<i; j++){
A[i+j*N] = A[iN+j];
}
}
"""
f_contig_code = """
int iN;
for (int i=1; i<N; i++){
iN = i*N;
for (int j=0; j<i; j++){
A[iN+j] = A[i+j*N];
}
}
"""
N = int(N) # for safe type casting
if A.flags['C_CONTIGUOUS'] and upper:
weave.inline(f_contig_code, ['A', 'N'], extra_compile_args=['-O3'])
elif A.flags['C_CONTIGUOUS'] and not upper:
weave.inline(c_contig_code, ['A', 'N'], extra_compile_args=['-O3'])
elif A.flags['F_CONTIGUOUS'] and upper:
weave.inline(c_contig_code, ['A', 'N'], extra_compile_args=['-O3'])
elif A.flags['F_CONTIGUOUS'] and not upper:
weave.inline(f_contig_code, ['A', 'N'], extra_compile_args=['-O3'])
else:
if upper:
tmp = np.tril(A.T)
else:
tmp = np.tril(A)
A[:] = 0.0
A += tmp
A += np.tril(tmp, -1).T
def symmetrify_numpy(A, upper=False):
"""
Force a matrix to be symmetric
"""
def _symmetrify_numpy(A, upper=False):
triu = np.triu_indices_from(A,k=1)
if upper:
A.T[triu] = A[triu]
else:
A[triu] = A.T[triu]
#This function appears to be unused. It's use of weave makes it problematic
#Commenting out for now
#def cholupdate(L, x):
# """
# update the LOWER cholesky factor of a pd matrix IN PLACE
#
# if L is the lower chol. of K, then this function computes L\_
# where L\_ is the lower chol of K + x*x^T
# """
# support_code = """
# #include <math.h>
# """
# code = """
# double r,c,s;
# int j,i;
# for(j=0; j<N; j++){
# r = sqrt(L(j,j)*L(j,j) + x(j)*x(j));
# c = r / L(j,j);
# s = x(j) / L(j,j);
# L(j,j) = r;
# for (i=j+1; i<N; i++){
# L(i,j) = (L(i,j) + s*x(i))/c;
# x(i) = c*x(i) - s*L(i,j);
# }
# }
# """
# x = x.copy()
# N = x.size
# weave.inline(code, support_code=support_code, arg_names=['N', 'L', 'x'], type_converters=weave.converters.blitz)
def backsub_both_sides(L, X, transpose='left'):
""" Return L^-T * X * L^-1, assumuing X is symmetrical and L is lower cholesky"""
"""
Return L^-T * X * L^-1, assumuing X is symmetrical and L is lower cholesky
"""
if transpose == 'left':
tmp, _ = dtrtrs(L, X, lower=1, trans=1)
return dtrtrs(L, tmp.T, lower=1, trans=1)[0].T

6191
GPy/util/linalg_cython.c Normal file
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34
GPy/util/linalg_cython.pyx Normal file
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@ -0,0 +1,34 @@
cimport numpy as np
from cpython cimport bool
import cython
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.nonecheck(False)
def symmetrify(np.ndarray[double, ndim=2] A, bool upper):
cdef int N = A.shape[0]
if not upper:
for i in xrange(N):
for j in xrange(i):
A[j, i] = A[i, j]
else:
for j in xrange(N):
for i in xrange(j):
A[j, i] = A[i, j]
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.nonecheck(False)
def cholupdate(np.ndarray[double, ndim=1] x, np.ndarray[double, ndim=2] L, int N):
cdef double r
cdef double c
cdef double s
for j in xrange(N):
r = np.sqrt(L[j,j]*L[j,j] + x[j]*x[j])
c = r / L[j,j]
s = x[j] / L[j,j]
L[j,j] = r
for i in xrange(j):
L[i,j] = (L[i,j] + s*x[i])/c
x[i] = c*x[i] - s*L[i,j];
r = np.sqrt(L[j,j])

9
GPy/util/misc.py
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@ -133,10 +133,11 @@ def kmm_init(X, m = 10):
### make a parameter to its corresponding array:
def param_to_array(*param):
"""
Convert an arbitrary number of parameters to :class:ndarray class objects. This is for
converting parameter objects to numpy arrays, when using scipy.weave.inline routine.
In scipy.weave.blitz there is no automatic array detection (even when the array inherits
from :class:ndarray)"""
Convert an arbitrary number of parameters to :class:ndarray class objects.
This is for converting parameter objects to numpy arrays, when using
scipy.weave.inline routine. In scipy.weave.blitz there is no automatic
array detection (even when the array inherits from :class:ndarray)
"""
import warnings
warnings.warn("Please use param.values, as this function will be deprecated in the next release.", DeprecationWarning)
assert len(param) > 0, "At least one parameter needed"