numpy.geomspace

numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None)[源代码]

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.

Parameters:
start : scalar

The starting value of the sequence.

stop : scalar

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, infer the data type from the other input arguments.

Returns:
samples : ndarray

num samples, equally spaced on a log scale.

参见

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([-1.00000000+0.j        , -0.70710678+0.70710678j,
        0.00000000+1.j        ,  0.70710678+0.70710678j,
        1.00000000+0.j        ])

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')
>>> plt.semilogx(np.geomspace(1, 1000, N, endpoint=False), y + 2, 'o')
>>> plt.axis([0.5, 2000, 0, 3])
>>> plt.grid(True, color='0.7', linestyle='-', which='both', axis='both')
>>> plt.show()
../../_images/numpy-geomspace-1.png