isscalar(element)
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
<SubstitutionRef: |value: '|``isscalar(x)``|``np.ndim(x) == 0``|' |>+======================================+===============+===================+ | PEP 3141 numeric objects (including |
True
| True
| | builtins) | | | +--------------------------------------+---------------+-------------------+ | builtin string and buffer objects | True
| True
| +--------------------------------------+---------------+-------------------+ | other builtin objects, like | False
| True
| | pathlib.Path
, :None:None:`Exception`, | | | | the result of re.compile
| | | +--------------------------------------+---------------+-------------------+ | third-party objects like | False
| True
| | matplotlib.figure.Figure
| | | +--------------------------------------+---------------+-------------------+ | zero-dimensional numpy arrays | False
| True
| +--------------------------------------+---------------+-------------------+ | other numpy arrays | False
| False
| +--------------------------------------+---------------+-------------------+ | :None:None:`list`, :None:None:`tuple`, and other sequence | False
| False
| | objects | | | +--------------------------------------+---------------+-------------------+
Input argument, can be of any type and shape.
True if :None:None:`element` is a scalar type, False if it is not.
Returns True if the type of :None:None:`element` is a scalar type.
ndim
Get the number of dimensions of an array
>>> np.isscalar(3.1) True
>>> np.isscalar(np.array(3.1)) False
>>> np.isscalar([3.1]) False
>>> np.isscalar(False) True
>>> np.isscalar('numpy') True
NumPy supports PEP 3141 numbers:
>>> from fractions import Fraction
... np.isscalar(Fraction(5, 17)) True
>>> from numbers import NumberSee :
... np.isscalar(Number()) True
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