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Fonction geomspace - module numpy.matlib

Signature de la fonction geomspace

def geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0) 

Description

geomspace.__doc__

    Return numbers spaced evenly on a log scale (a geometric progression).

    This is similar to `logspace`, but with endpoints specified directly.
    Each output sample is a constant multiple of the previous.

    .. versionchanged:: 1.16.0
        Non-scalar `start` and `stop` are now supported.

    Parameters
    ----------
    start : array_like
        The starting value of the sequence.
    stop : array_like
        The final value of the sequence, unless `endpoint` is False.
        In that case, ``num + 1`` values are spaced over the
        interval in log-space, of which all but the last (a sequence of
        length `num`) are returned.
    num : integer, optional
        Number of samples to generate.  Default is 50.
    endpoint : boolean, optional
        If true, `stop` is the last sample. Otherwise, it is not included.
        Default is True.
    dtype : dtype
        The type of the output array.  If `dtype` is not given, the data type
        is inferred from `start` and `stop`. The inferred dtype will never be
        an integer; `float` is chosen even if the arguments would produce an
        array of integers.
    axis : int, optional
        The axis in the result to store the samples.  Relevant only if start
        or stop are array-like.  By default (0), the samples will be along a
        new axis inserted at the beginning. Use -1 to get an axis at the end.

        .. versionadded:: 1.16.0

    Returns
    -------
    samples : ndarray
        `num` samples, equally spaced on a log scale.

    See Also
    --------
    logspace : Similar to geomspace, but with endpoints specified using log
               and base.
    linspace : Similar to geomspace, but with arithmetic instead of geometric
               progression.
    arange : Similar to linspace, with the step size specified instead of the
             number of samples.

    Notes
    -----
    If the inputs or dtype are complex, the output will follow a logarithmic
    spiral in the complex plane.  (There are an infinite number of spirals
    passing through two points; the output will follow the shortest such path.)

    Examples
    --------
    >>> np.geomspace(1, 1000, num=4)
    array([    1.,    10.,   100.,  1000.])
    >>> np.geomspace(1, 1000, num=3, endpoint=False)
    array([   1.,   10.,  100.])
    >>> np.geomspace(1, 1000, num=4, endpoint=False)
    array([   1.        ,    5.62341325,   31.6227766 ,  177.827941  ])
    >>> np.geomspace(1, 256, num=9)
    array([   1.,    2.,    4.,    8.,   16.,   32.,   64.,  128.,  256.])

    Note that the above may not produce exact integers:

    >>> np.geomspace(1, 256, num=9, dtype=int)
    array([  1,   2,   4,   7,  16,  32,  63, 127, 256])
    >>> np.around(np.geomspace(1, 256, num=9)).astype(int)
    array([  1,   2,   4,   8,  16,  32,  64, 128, 256])

    Negative, decreasing, and complex inputs are allowed:

    >>> np.geomspace(1000, 1, num=4)
    array([1000.,  100.,   10.,    1.])
    >>> np.geomspace(-1000, -1, num=4)
    array([-1000.,  -100.,   -10.,    -1.])
    >>> np.geomspace(1j, 1000j, num=4)  # Straight line
    array([0.   +1.j, 0.  +10.j, 0. +100.j, 0.+1000.j])
    >>> np.geomspace(-1+0j, 1+0j, num=5)  # Circle
    array([-1.00000000e+00+1.22464680e-16j, -7.07106781e-01+7.07106781e-01j,
            6.12323400e-17+1.00000000e+00j,  7.07106781e-01+7.07106781e-01j,
            1.00000000e+00+0.00000000e+00j])

    Graphical illustration of ``endpoint`` parameter:

    >>> import matplotlib.pyplot as plt
    >>> N = 10
    >>> y = np.zeros(N)
    >>> plt.semilogx(np.geomspace(1, 1000, N, endpoint=True), y + 1, 'o')
    [<matplotlib.lines.Line2D object at 0x...>]
    >>> plt.semilogx(np.geomspace(1, 1000, N, endpoint=False), y + 2, 'o')
    [<matplotlib.lines.Line2D object at 0x...>]
    >>> plt.axis([0.5, 2000, 0, 3])
    [0.5, 2000, 0, 3]
    >>> plt.grid(True, color='0.7', linestyle='-', which='both', axis='both')
    >>> plt.show()