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).
Parameters: | start : float
stop : float
num : integer, optional
endpoint : boolean, optional
base : float, optional
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Returns: | samples : ndarray
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See also
Notes
Logspace is equivalent to the code
>>> y = linspace(start, stop, num=num, endpoint=endpoint)
>>> power(base, y)
Examples
>>> 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')
>>> plt.plot(x2, y + 0.5, 'o')
>>> plt.ylim([-0.5, 1])
>>> plt.show()
Output