Пример #1
0
def mid_range_f(a, axis=None, masked=False):
    """Return the minimum and maximum of an array or the minimum and
    maximum along an axis.

    ``mid_range_f(a, axis=axis)`` is equivalent to ``(numpy.amin(a,
    axis=axis), numpy.amax(a, axis=axis))``

    :Parameters:

        a: numpy array_like
            Input array

        axis: `int`, optional
            Axis along which to operate. By default, flattened input
            is used.

        kwargs: ignored

    :Returns:

        3-`tuple`
            The sample size, minimum and maximum inside a 3-tuple.

    """
    (N,) = sample_size_f(a, axis=axis, masked=masked)
    amin = numpy_amin(a, axis=axis)
    amax = numpy_amax(a, axis=axis)

    if not numpy_ndim(amin):
        # Make sure that we have a numpy array (as opposed to, e.g. a
        # numpy.float64)
        amin = numpy_asanyarray(amin)
        amax = numpy_asanyarray(amax)

    return asanyarray(N, amin, amax)
Пример #2
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def min_f(a, axis=None, masked=False):
    '''Return the minimum of an array, or the minima of an array along an
    axis.

    :Parameters:

        a: numpy array_like
            Input array

        axis: `int`, optional
            Axis along which to operate. By default, flattened input
            is used.

        masked: `bool`

    :Returns:

        out: 2-tuple of `numpy.ndarray`
            The sample sizes and the minima.

    '''
    N, = sample_size_f(a, axis=axis, masked=masked)
    amin = numpy_amin(a, axis=axis)

    return asanyarray(N, amin)
Пример #3
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def min_f(a, axis=None, masked=False):
    """Return the minimum of an array or minimum along a specified axis.

    :Parameters:

        a: numpy array_like
            Input array

        axis: `int`, optional
            Axis along which to operate. By default, flattened input
            is used.

        masked: `bool`, optional

    :Returns:

        2-`tuple` of `numpy.ndarray`
            The sample size and the minimum.

    """
    (N,) = sample_size_f(a, axis=axis, masked=masked)
    amin = numpy_amin(a, axis=axis)

    return asanyarray(N, amin)