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| author | Charles Harris <charlesr.harris@gmail.com> | 2013-08-15 11:31:08 -0600 |
|---|---|---|
| committer | Charles Harris <charlesr.harris@gmail.com> | 2013-08-15 11:31:08 -0600 |
| commit | 31f526ef39dfe3dd079d9534530ba80aa32f8e79 (patch) | |
| tree | 13b734353f44b758254ce529713cbeeb3ade28e2 /numpy/core | |
| parent | 3c9c31b19038dbe49c145aa014aa45e0b29b5d4c (diff) | |
| download | numpy-31f526ef39dfe3dd079d9534530ba80aa32f8e79.tar.gz | |
DOC: Merge doc updates from http://docs.scipy.org/numpy/patch/.
Preparatory to 1.8.0 branch.
Diffstat (limited to 'numpy/core')
| -rw-r--r-- | numpy/core/numeric.py | 32 |
1 files changed, 16 insertions, 16 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py index 9ae1af654..e2c020ced 100644 --- a/numpy/core/numeric.py +++ b/numpy/core/numeric.py @@ -978,13 +978,16 @@ def outer(a,b): Parameters ---------- - a, b : array_like, shape (M,), (N,) - First and second input vectors. Inputs are flattened if they - are not already 1-dimensional. + a : (M,) array_like + First input vector. Input is flattened if + not already 1-dimensional. + b : (N,) array_like + Second input vector. Input is flattened if + not already 1-dimensional. Returns ------- - out : ndarray, shape (M, N) + out : (M, N) ndarray ``out[i, j] = a[i] * b[j]`` See also @@ -1057,27 +1060,24 @@ def tensordot(a, b, axes=2): Compute tensor dot product along specified axes for arrays >= 1-D. Given two tensors (arrays of dimension greater than or equal to one), - ``a`` and ``b``, and an array_like object containing two array_like - objects, ``(a_axes, b_axes)``, sum the products of ``a``'s and ``b``'s + `a` and `b`, and an array_like object containing two array_like + objects, ``(a_axes, b_axes)``, sum the products of `a`'s and `b`'s elements (components) over the axes specified by ``a_axes`` and ``b_axes``. The third argument can be a single non-negative integer_like scalar, ``N``; if it is such, then the last ``N`` - dimensions of ``a`` and the first ``N`` dimensions of ``b`` are summed + dimensions of `a` and the first ``N`` dimensions of `b` are summed over. Parameters ---------- a, b : array_like, len(shape) >= 1 Tensors to "dot". - axes : variable type - - * integer_like scalar - Number of axes to sum over (applies to both arrays); or - - * array_like, shape = (2,), both elements array_like - Axes to be summed over, first sequence applying to ``a``, second - to ``b``. + * integer_like scalar + Number of axes to sum over (applies to both arrays); or + * (2,) array_like, both elements array_like of the same length + List of axes to be summed over, first sequence applying to `a`, + second to `b`. See Also -------- @@ -1086,7 +1086,7 @@ def tensordot(a, b, axes=2): Notes ----- When there is more than one axis to sum over - and they are not the last - (first) axes of ``a`` (``b``) - the argument ``axes`` should consist of + (first) axes of `a` (`b`) - the argument `axes` should consist of two sequences of the same length, with the first axis to sum over given first in both sequences, the second axis second, and so forth. |