Fix docs (2)
@@ -65,27 +65,30 @@ dtype=cp.float32))
def lu(a, permute_l=False, overwrite_a=False, check_finite=True):
"""LU decomposition.
+ Decomposes a given two-dimensional matrix into ``P @ L @ U``, where ``P``
+ is a permutation matrix, ``L`` is a lower triangular or trapezoidal matrix
+ with unit diagonal, and ``U`` is a upper triangular or trapezoidal matrix.
+
Args:
- a (cupy.ndarray): The input matrix with dimension ``(M, N)``
- permute_l (bool): If ``True``, perform the multiplication ``P * L``.
+ a (cupy.ndarray): The input matrix with dimension ``(M, N)``.
+ permute_l (bool): If ``True``, perform the multiplication ``P @ L``.
overwrite_a (bool): Allow overwriting data in ``a`` (may enhance
performance)
check_finite (bool): Whether to check that the input matrices contain
only finite numbers. Disabling may give a performance gain, but may
result in problems (crashes, non-termination) if the inputs do
contain infinities or NaNs.
- a (cupy.ndarray): Array to decompose
Returns:
tuple:
- ``(p, l, u)`` if ``permute_l == False``, otherwise ``(pl, u)``.
- ``p`` is a :class:`cupy.ndarray` storing permutation matrix with
- dimension ``(M, M)``. ``l`` is a :class:`cupy.ndarray` storing
+ ``(P, L, U)`` if ``permute_l == False``, otherwise ``(PL, U)``.
+ ``P`` is a :class:`cupy.ndarray` storing permutation matrix with
+ dimension ``(M, M)``. ``L`` is a :class:`cupy.ndarray` storing
lower triangular or trapezoidal matrix with unit diagonal with
- dimension ``(M, K)`` where ``K = min(M, N)``. ``u`` is a
+ dimension ``(M, K)`` where ``K = min(M, N)``. ``U`` is a
:class:`cupy.ndarray` storing upper triangular or trapezoidal
- matrix with dimension ``(K, N)``. ``pl`` is a :class:`cupy.ndarray`
- storing permuted ``l`` matrix with dimension ``(M, K)``.
+ matrix with dimension ``(K, N)``. ``PL`` is a :class:`cupy.ndarray`
+ storing permuted ``L`` matrix with dimension ``(M, K)``.
.. seealso:: :func:`scipy.linalg.lu`
"""
