numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)
[source]
Return numbers spaced evenly on a log scale.
In linear space, the sequence starts at base ** start
(base
to the power of start
) and ends with base ** stop
(see endpoint
below).
Changed in version 1.16.0: Nonscalar start
and stop
are now supported.
Parameters: 


Returns: 

See also
arange
linspace
geomspace
Logspace is equivalent to the code
>>> y = np.linspace(start, stop, num=num, endpoint=endpoint) ... # doctest: +SKIP >>> power(base, y).astype(dtype) ... # doctest: +SKIP
>>> np.logspace(2.0, 3.0, num=4) array([ 100. , 215.443469 , 464.15888336, 1000. ]) >>> np.logspace(2.0, 3.0, num=4, endpoint=False) array([100. , 177.827941 , 316.22776602, 562.34132519]) >>> np.logspace(2.0, 3.0, num=4, base=2.0) array([4. , 5.0396842 , 6.34960421, 8. ])
Graphical illustration:
>>> import matplotlib.pyplot as plt >>> N = 10 >>> x1 = np.logspace(0.1, 1, N, endpoint=True) >>> x2 = np.logspace(0.1, 1, N, endpoint=False) >>> y = np.zeros(N) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([0.5, 1]) (0.5, 1) >>> plt.show()
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.logspace.html