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Fonction amin - module numpy

Signature de la fonction amin

def amin(a, axis=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>) 

Description

amin.__doc__

    Return the minimum of an array or minimum along an axis.

    Parameters
    ----------
    a : array_like
        Input data.
    axis : None or int or tuple of ints, optional
        Axis or axes along which to operate.  By default, flattened input is
        used.

        .. versionadded:: 1.7.0

        If this is a tuple of ints, the minimum is selected over multiple axes,
        instead of a single axis or all the axes as before.
    out : ndarray, optional
        Alternative output array in which to place the result.  Must
        be of the same shape and buffer length as the expected output.
        See :ref:`ufuncs-output-type` for more details.

    keepdims : bool, optional
        If this is set to True, the axes which are reduced are left
        in the result as dimensions with size one. With this option,
        the result will broadcast correctly against the input array.

        If the default value is passed, then `keepdims` will not be
        passed through to the `amin` method of sub-classes of
        `ndarray`, however any non-default value will be.  If the
        sub-class' method does not implement `keepdims` any
        exceptions will be raised.

    initial : scalar, optional
        The maximum value of an output element. Must be present to allow
        computation on empty slice. See `~numpy.ufunc.reduce` for details.

        .. versionadded:: 1.15.0

    where : array_like of bool, optional
        Elements to compare for the minimum. See `~numpy.ufunc.reduce`
        for details.

        .. versionadded:: 1.17.0

    Returns
    -------
    amin : ndarray or scalar
        Minimum of `a`. If `axis` is None, the result is a scalar value.
        If `axis` is given, the result is an array of dimension
        ``a.ndim - 1``.

    See Also
    --------
    amax :
        The maximum value of an array along a given axis, propagating any NaNs.
    nanmin :
        The minimum value of an array along a given axis, ignoring any NaNs.
    minimum :
        Element-wise minimum of two arrays, propagating any NaNs.
    fmin :
        Element-wise minimum of two arrays, ignoring any NaNs.
    argmin :
        Return the indices of the minimum values.

    nanmax, maximum, fmax

    Notes
    -----
    NaN values are propagated, that is if at least one item is NaN, the
    corresponding min value will be NaN as well. To ignore NaN values
    (MATLAB behavior), please use nanmin.

    Don't use `amin` for element-wise comparison of 2 arrays; when
    ``a.shape[0]`` is 2, ``minimum(a[0], a[1])`` is faster than
    ``amin(a, axis=0)``.

    Examples
    --------
    >>> a = np.arange(4).reshape((2,2))
    >>> a
    array([[0, 1],
           [2, 3]])
    >>> np.amin(a)           # Minimum of the flattened array
    0
    >>> np.amin(a, axis=0)   # Minima along the first axis
    array([0, 1])
    >>> np.amin(a, axis=1)   # Minima along the second axis
    array([0, 2])
    >>> np.amin(a, where=[False, True], initial=10, axis=0)
    array([10,  1])

    >>> b = np.arange(5, dtype=float)
    >>> b[2] = np.NaN
    >>> np.amin(b)
    nan
    >>> np.amin(b, where=~np.isnan(b), initial=10)
    0.0
    >>> np.nanmin(b)
    0.0

    >>> np.min([[-50], [10]], axis=-1, initial=0)
    array([-50,   0])

    Notice that the initial value is used as one of the elements for which the
    minimum is determined, unlike for the default argument Python's max
    function, which is only used for empty iterables.

    Notice that this isn't the same as Python's ``default`` argument.

    >>> np.min([6], initial=5)
    5
    >>> min([6], default=5)
    6