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Fonction absolute - module numpy.matlib

Signature de la fonction absolute

Description

absolute.__doc__

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

Calculate the absolute value element-wise.

``np.abs`` is a shorthand for this function.

Parameters
----------
x : array_like
    Input array.
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
-------
absolute : ndarray
    An ndarray containing the absolute value of
    each element in `x`.  For complex input, ``a + ib``, the
    absolute value is :math:`\sqrt{ a^2 + b^2 }`.
    This is a scalar if `x` is a scalar.

Examples
--------
>>> x = np.array([-1.2, 1.2])
>>> np.absolute(x)
array([ 1.2,  1.2])
>>> np.absolute(1.2 + 1j)
1.5620499351813308

Plot the function over ``[-10, 10]``:

>>> import matplotlib.pyplot as plt

>>> x = np.linspace(start=-10, stop=10, num=101)
>>> plt.plot(x, np.absolute(x))
>>> plt.show()

Plot the function over the complex plane:

>>> xx = x + 1j * x[:, np.newaxis]
>>> plt.imshow(np.abs(xx), extent=[-10, 10, -10, 10], cmap='gray')
>>> plt.show()

The `abs` function can be used as a shorthand for ``np.absolute`` on
ndarrays.

>>> x = np.array([-1.2, 1.2])
>>> abs(x)
array([1.2, 1.2])