diff options
Diffstat (limited to 'numpy/core/numeric.py')
| -rw-r--r-- | numpy/core/numeric.py | 39 |
1 files changed, 23 insertions, 16 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py index 6d25f864b..1e011e2e7 100644 --- a/numpy/core/numeric.py +++ b/numpy/core/numeric.py @@ -292,7 +292,7 @@ def full(shape, fill_value, dtype=None, order='C'): fill_value : scalar Fill value. dtype : data-type, optional - The desired data-type for the array The default, `None`, means + The desired data-type for the array The default, None, means `np.array(fill_value).dtype`. order : {'C', 'F'}, optional Whether to store multidimensional data in C- or Fortran-contiguous @@ -960,6 +960,9 @@ def tensordot(a, b, axes=2): 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. + The shape of the result consists of the non-contracted axes of the + first tensor, followed by the non-contracted axes of the second. + Examples -------- A "traditional" example: @@ -1781,19 +1784,19 @@ def _frombuffer(buf, dtype, shape, order): @set_module('numpy') -def isscalar(num): +def isscalar(element): """ - Returns True if the type of `num` is a scalar type. + Returns True if the type of `element` is a scalar type. Parameters ---------- - num : any + element : any Input argument, can be of any type and shape. Returns ------- val : bool - True if `num` is a scalar type, False if it is not. + True if `element` is a scalar type, False if it is not. See Also -------- @@ -1801,10 +1804,14 @@ def isscalar(num): Notes ----- - In almost all cases ``np.ndim(x) == 0`` should be used instead of this - function, as that will also return true for 0d arrays. This is how - numpy overloads functions in the style of the ``dx`` arguments to `gradient` - and the ``bins`` argument to `histogram`. Some key differences: + If you need a stricter way to identify a *numerical* scalar, use + ``isinstance(x, numbers.Number)``, as that returns ``False`` for most + non-numerical elements such as strings. + + In most cases ``np.ndim(x) == 0`` should be used instead of this function, + as that will also return true for 0d arrays. This is how numpy overloads + functions in the style of the ``dx`` arguments to `gradient` and the ``bins`` + argument to `histogram`. Some key differences: +--------------------------------------+---------------+-------------------+ | x |``isscalar(x)``|``np.ndim(x) == 0``| @@ -1852,9 +1859,9 @@ def isscalar(num): True """ - return (isinstance(num, generic) - or type(num) in ScalarType - or isinstance(num, numbers.Number)) + return (isinstance(element, generic) + or type(element) in ScalarType + or isinstance(element, numbers.Number)) @set_module('numpy') @@ -2091,9 +2098,9 @@ def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False): `atol` are added together to compare against the absolute difference between `a` and `b`. - If either array contains one or more NaNs, False is returned. - Infs are treated as equal if they are in the same place and of the same - sign in both arrays. + NaNs are treated as equal if they are in the same place and if + ``equal_nan=True``. Infs are treated as equal if they are in the same + place and of the same sign in both arrays. Parameters ---------- @@ -2105,7 +2112,7 @@ def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False): The absolute tolerance parameter (see Notes). equal_nan : bool Whether to compare NaN's as equal. If True, NaN's in `a` will be - considered equal to NaN's in `b`. + considered equal to NaN's in `b` in the output array. .. versionadded:: 1.10.0 |