[Numpy-svn] r8158 - trunk/numpy/linalg
numpy-svn at scipy.org
numpy-svn at scipy.org
Sat Feb 20 13:11:21 EST 2010
Author: ptvirtan
Date: 2010-02-20 12:11:21 -0600 (Sat, 20 Feb 2010)
New Revision: 8158
Modified:
trunk/numpy/linalg/linalg.py
Log:
3K: linalg: fix some str/bytes issues
Modified: trunk/numpy/linalg/linalg.py
===================================================================
--- trunk/numpy/linalg/linalg.py 2010-02-20 18:11:07 UTC (rev 8157)
+++ trunk/numpy/linalg/linalg.py 2010-02-20 18:11:21 UTC (rev 8158)
@@ -22,7 +22,15 @@
from numpy.lib import triu
from numpy.linalg import lapack_lite
from numpy.matrixlib.defmatrix import matrix_power
+from numpy.compat import asbytes
+# For Python2/3 compatibility
+_N = asbytes('N')
+_V = asbytes('V')
+_A = asbytes('A')
+_S = asbytes('S')
+_L = asbytes('L')
+
fortran_int = intc
# Error object
@@ -503,7 +511,7 @@
lapack_routine = lapack_lite.zpotrf
else:
lapack_routine = lapack_lite.dpotrf
- results = lapack_routine('L', n, a, m, 0)
+ results = lapack_routine(_L, n, a, m, 0)
if results['info'] > 0:
raise LinAlgError, 'Matrix is not positive definite - \
Cholesky decomposition cannot be computed'
@@ -762,11 +770,11 @@
rwork = zeros((n,), real_t)
lwork = 1
work = zeros((lwork,), t)
- results = lapack_routine('N', 'N', n, a, n, w,
+ results = lapack_routine(_N, _N, n, a, n, w,
dummy, 1, dummy, 1, work, -1, rwork, 0)
lwork = int(abs(work[0]))
work = zeros((lwork,), t)
- results = lapack_routine('N', 'N', n, a, n, w,
+ results = lapack_routine(_N, _N, n, a, n, w,
dummy, 1, dummy, 1, work, lwork, rwork, 0)
else:
lapack_routine = lapack_lite.dgeev
@@ -774,11 +782,11 @@
wi = zeros((n,), t)
lwork = 1
work = zeros((lwork,), t)
- results = lapack_routine('N', 'N', n, a, n, wr, wi,
+ results = lapack_routine(_N, _N, n, a, n, wr, wi,
dummy, 1, dummy, 1, work, -1, 0)
lwork = int(work[0])
work = zeros((lwork,), t)
- results = lapack_routine('N', 'N', n, a, n, wr, wi,
+ results = lapack_routine(_N, _N, n, a, n, wr, wi,
dummy, 1, dummy, 1, work, lwork, 0)
if all(wi == 0.):
w = wr
@@ -838,6 +846,7 @@
array([ 0.17157288+0.j, 5.82842712+0.j])
"""
+ UPLO = asbytes(UPLO)
a, wrap = _makearray(a)
_assertRank2(a)
_assertSquareness(a)
@@ -854,24 +863,24 @@
work = zeros((lwork,), t)
lrwork = 1
rwork = zeros((lrwork,), real_t)
- results = lapack_routine('N', UPLO, n, a, n, w, work, -1,
+ results = lapack_routine(_N, UPLO, n, a, n, w, work, -1,
rwork, -1, iwork, liwork, 0)
lwork = int(abs(work[0]))
work = zeros((lwork,), t)
lrwork = int(rwork[0])
rwork = zeros((lrwork,), real_t)
- results = lapack_routine('N', UPLO, n, a, n, w, work, lwork,
+ results = lapack_routine(_N, UPLO, n, a, n, w, work, lwork,
rwork, lrwork, iwork, liwork, 0)
else:
lapack_routine = lapack_lite.dsyevd
w = zeros((n,), t)
lwork = 1
work = zeros((lwork,), t)
- results = lapack_routine('N', UPLO, n, a, n, w, work, -1,
+ results = lapack_routine(_N, UPLO, n, a, n, w, work, -1,
iwork, liwork, 0)
lwork = int(work[0])
work = zeros((lwork,), t)
- results = lapack_routine('N', UPLO, n, a, n, w, work, lwork,
+ results = lapack_routine(_N, UPLO, n, a, n, w, work, lwork,
iwork, liwork, 0)
if results['info'] > 0:
raise LinAlgError, 'Eigenvalues did not converge'
@@ -1010,11 +1019,11 @@
lwork = 1
work = zeros((lwork,), t)
rwork = zeros((2*n,), real_t)
- results = lapack_routine('N', 'V', n, a, n, w,
+ results = lapack_routine(_N, _V, n, a, n, w,
dummy, 1, v, n, work, -1, rwork, 0)
lwork = int(abs(work[0]))
work = zeros((lwork,), t)
- results = lapack_routine('N', 'V', n, a, n, w,
+ results = lapack_routine(_N, _V, n, a, n, w,
dummy, 1, v, n, work, lwork, rwork, 0)
else:
lapack_routine = lapack_lite.dgeev
@@ -1023,11 +1032,11 @@
vr = zeros((n, n), t)
lwork = 1
work = zeros((lwork,), t)
- results = lapack_routine('N', 'V', n, a, n, wr, wi,
+ results = lapack_routine(_N, _V, n, a, n, wr, wi,
dummy, 1, vr, n, work, -1, 0)
lwork = int(work[0])
work = zeros((lwork,), t)
- results = lapack_routine('N', 'V', n, a, n, wr, wi,
+ results = lapack_routine(_N, _V, n, a, n, wr, wi,
dummy, 1, vr, n, work, lwork, 0)
if all(wi == 0.0):
w = wr
@@ -1128,6 +1137,7 @@
[ 0.00000000+0.38268343j, 0.00000000-0.92387953j]])
"""
+ UPLO = asbytes(UPLO)
a, wrap = _makearray(a)
_assertRank2(a)
_assertSquareness(a)
@@ -1144,24 +1154,24 @@
work = zeros((lwork,), t)
lrwork = 1
rwork = zeros((lrwork,), real_t)
- results = lapack_routine('V', UPLO, n, a, n, w, work, -1,
+ results = lapack_routine(_V, UPLO, n, a, n, w, work, -1,
rwork, -1, iwork, liwork, 0)
lwork = int(abs(work[0]))
work = zeros((lwork,), t)
lrwork = int(rwork[0])
rwork = zeros((lrwork,), real_t)
- results = lapack_routine('V', UPLO, n, a, n, w, work, lwork,
+ results = lapack_routine(_V, UPLO, n, a, n, w, work, lwork,
rwork, lrwork, iwork, liwork, 0)
else:
lapack_routine = lapack_lite.dsyevd
w = zeros((n,), t)
lwork = 1
work = zeros((lwork,), t)
- results = lapack_routine('V', UPLO, n, a, n, w, work, -1,
+ results = lapack_routine(_V, UPLO, n, a, n, w, work, -1,
iwork, liwork, 0)
lwork = int(work[0])
work = zeros((lwork,), t)
- results = lapack_routine('V', UPLO, n, a, n, w, work, lwork,
+ results = lapack_routine(_V, UPLO, n, a, n, w, work, lwork,
iwork, liwork, 0)
if results['info'] > 0:
raise LinAlgError, 'Eigenvalues did not converge'
@@ -1249,15 +1259,15 @@
if full_matrices:
nu = m
nvt = n
- option = 'A'
+ option = _A
else:
nu = min(n, m)
nvt = min(n, m)
- option = 'S'
+ option = _S
u = zeros((nu, m), t)
vt = zeros((n, nvt), t)
else:
- option = 'N'
+ option = _N
nu = 1
nvt = 1
u = empty((1, 1), t)
More information about the Numpy-svn
mailing list