diff options
| -rw-r--r-- | numpy/linalg/linalg.py | 22 | ||||
| -rw-r--r-- | numpy/linalg/tests/test_regression.py | 9 |
2 files changed, 31 insertions, 0 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 2831a2dd0..c423d5e4e 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -124,6 +124,18 @@ def _commonType(*arrays): _fastCT = fastCopyAndTranspose +def _to_native_byte_order(*arrays): + ret = [] + for arr in arrays: + if arr.dtype.byteorder not in ('=', '|'): + ret.append(asarray(arr, dtype=arr.dtype.newbyteorder('='))) + else: + ret.append(arr) + if len(ret) == 1: + return ret[0] + else: + return ret + def _fastCopyAndTranspose(type, *arrays): cast_arrays = () for a in arrays: @@ -309,6 +321,7 @@ def solve(a, b): else: lapack_routine = lapack_lite.dgesv a, b = _fastCopyAndTranspose(t, a, b) + a, b = _to_native_byte_order(a, b) pivots = zeros(n_eq, fortran_int) results = lapack_routine(n_eq, n_rhs, a, n_eq, pivots, b, n_eq, 0) if results['info'] > 0: @@ -505,6 +518,7 @@ def cholesky(a): _assertSquareness(a) t, result_t = _commonType(a) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) m = a.shape[0] n = a.shape[1] if isComplexType(t): @@ -623,6 +637,7 @@ def qr(a, mode='full'): m, n = a.shape t, result_t = _commonType(a) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) mn = min(m, n) tau = zeros((mn,), t) if isComplexType(t): @@ -762,6 +777,7 @@ def eigvals(a): t, result_t = _commonType(a) real_t = _linalgRealType(t) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) n = a.shape[0] dummy = zeros((1,), t) if isComplexType(t): @@ -853,6 +869,7 @@ def eigvalsh(a, UPLO='L'): t, result_t = _commonType(a) real_t = _linalgRealType(t) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) n = a.shape[0] liwork = 5*n+3 iwork = zeros((liwork,), fortran_int) @@ -1008,6 +1025,7 @@ def eig(a): _assertSquareness(a) _assertFinite(a) a, t, result_t = _convertarray(a) # convert to double or cdouble type + a = _to_native_byte_order(a) real_t = _linalgRealType(t) n = a.shape[0] dummy = zeros((1,), t) @@ -1144,6 +1162,7 @@ def eigh(a, UPLO='L'): t, result_t = _commonType(a) real_t = _linalgRealType(t) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) n = a.shape[0] liwork = 5*n+3 iwork = zeros((liwork,), fortran_int) @@ -1254,6 +1273,7 @@ def svd(a, full_matrices=1, compute_uv=1): t, result_t = _commonType(a) real_t = _linalgRealType(t) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) s = zeros((min(n, m),), real_t) if compute_uv: if full_matrices: @@ -1594,6 +1614,7 @@ def slogdet(a): _assertSquareness(a) t, result_t = _commonType(a) a = _fastCopyAndTranspose(t, a) + a = _to_native_byte_order(a) n = a.shape[0] if isComplexType(t): lapack_routine = lapack_lite.zgetrf @@ -1752,6 +1773,7 @@ def lstsq(a, b, rcond=-1): bstar = zeros((ldb, n_rhs), t) bstar[:b.shape[0],:n_rhs] = b.copy() a, bstar = _fastCopyAndTranspose(t, a, bstar) + a, bstar = _to_native_byte_order(a, bstar) s = zeros((min(m, n),), real_t) nlvl = max( 0, int( math.log( float(min(m, n))/2. ) ) + 1 ) iwork = zeros((3*min(m, n)*nlvl+11*min(m, n),), fortran_int) diff --git a/numpy/linalg/tests/test_regression.py b/numpy/linalg/tests/test_regression.py index ab31d9960..b3188f99c 100644 --- a/numpy/linalg/tests/test_regression.py +++ b/numpy/linalg/tests/test_regression.py @@ -57,6 +57,15 @@ class TestRegression(TestCase): TypeError.""" self.assertRaises(ValueError, linalg.norm, array([1., 2., 3.]), 'fro') + def test_lapack_endian(self): + # For bug #1482 + a = array([[5.7998084, -2.1825367 ], + [-2.1825367, 9.85910595]], dtype='>f8') + b = array(a, dtype='<f8') + + ap = linalg.cholesky(a) + bp = linalg.cholesky(b) + assert_array_equal(ap, bp) if __name__ == '__main__': run_module_suite() |