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Fonction isinf - module numpy.matlib

Signature de la fonction isinf

Description

isinf.__doc__

isinf(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Test element-wise for positive or negative infinity.

Returns a boolean array of the same shape as `x`, True where ``x ==
+/-inf``, otherwise False.

Parameters
----------
x : array_like
    Input values
out : ndarray, None, or tuple of ndarray and None, optional
    A location into which the result is stored. If provided, it must have
    a shape that the inputs broadcast to. If not provided or None,
    a freshly-allocated array is returned. A tuple (possible only as a
    keyword argument) must have length equal to the number of outputs.
where : array_like, optional
    This condition is broadcast over the input. At locations where the
    condition is True, the `out` array will be set to the ufunc result.
    Elsewhere, the `out` array will retain its original value.
    Note that if an uninitialized `out` array is created via the default
    ``out=None``, locations within it where the condition is False will
    remain uninitialized.
**kwargs
    For other keyword-only arguments, see the
    :ref:`ufunc docs <ufuncs.kwargs>`.

Returns
-------
y : bool (scalar) or boolean ndarray
    True where ``x`` is positive or negative infinity, false otherwise.
    This is a scalar if `x` is a scalar.

See Also
--------
isneginf, isposinf, isnan, isfinite

Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).

Errors result if the second argument is supplied when the first
argument is a scalar, or if the first and second arguments have
different shapes.

Examples
--------
>>> np.isinf(np.inf)
True
>>> np.isinf(np.nan)
False
>>> np.isinf(np.NINF)
True
>>> np.isinf([np.inf, -np.inf, 1.0, np.nan])
array([ True,  True, False, False])

>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isinf(x, y)
array([1, 0, 1])
>>> y
array([1, 0, 1])