diff options
Diffstat (limited to 'numpy/linalg/linalg.py')
| -rw-r--r-- | numpy/linalg/linalg.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 2b686839a..0c27e0631 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -30,7 +30,7 @@ from numpy.core.multiarray import normalize_axis_index from numpy.core.overrides import set_module from numpy.core import overrides from numpy.lib.twodim_base import triu, eye -from numpy.linalg import lapack_lite, _umath_linalg +from numpy.linalg import _umath_linalg array_function_dispatch = functools.partial( @@ -1680,7 +1680,7 @@ def cond(x, p=None): x : (..., M, N) array_like The matrix whose condition number is sought. p : {None, 1, -1, 2, -2, inf, -inf, 'fro'}, optional - Order of the norm: + Order of the norm used in the condition number computation: ===== ============================ p norm for matrices @@ -1695,7 +1695,7 @@ def cond(x, p=None): -2 smallest singular value ===== ============================ - inf means the numpy.inf object, and the Frobenius norm is + inf means the `numpy.inf` object, and the Frobenius norm is the root-of-sum-of-squares norm. Returns @@ -1864,7 +1864,7 @@ def matrix_rank(A, tol=None, hermitian=False): References ---------- - .. [1] MATLAB reference documention, "Rank" + .. [1] MATLAB reference documentation, "Rank" https://www.mathworks.com/help/techdoc/ref/rank.html .. [2] W. H. Press, S. A. Teukolsky, W. T. Vetterling and B. P. Flannery, "Numerical Recipes (3rd edition)", Cambridge University Press, 2007, @@ -2159,7 +2159,7 @@ def lstsq(a, b, rcond="warn"): r""" Return the least-squares solution to a linear matrix equation. - Computes the vector `x` that approximatively solves the equation + Computes the vector `x` that approximately solves the equation ``a @ x = b``. The equation may be under-, well-, or over-determined (i.e., the number of linearly independent rows of `a` can be less than, equal to, or greater than its number of linearly independent columns). |