numpy.logspace() function is defined as:
numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)
This function can generate geometric series based on base( such as base = 10.0).
In this tutorial, we will write some examples to show you how to use this function correctly.
Parameters:
start: the start value of the sequence, it is equal to basestart
stop: the end value of the sequence, it is equal to basestop
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.
base: float, optional
The base of the log space. Default is 10.0.
dtype: dtype
The type of the output array.
axis : int, optional
The axis in the result to store the samples.
Returns:
samples : ndarray
Here is an simple example to show how to use this function.
import numpy as np x = np.logspace(3,5,8,base=2) print(x)
The result is:
[ 8. 9.75210923 11.88795431 14.49157863 17.66543222 21.53440308 26.25073139 32. ]
Because endpoint = True, so the mininum value is 23 = 8 and the maximum is 28= 32.
How about is endpoint = False?
x = np.logspace(3,5,8,base=2, endpoint = False) print(x)
The value is:
[ 8. 9.51365692 11.3137085 13.45434264 16. 19.02731384 22.627417 26.90868529]
Why the maximum value is 26.90868529?
We should comfirm the step size between start and end by num.
When endpoint = False, the step size = (end – start) / num.
For example:
As to:
x = np.logspace(3,5,8,base=2, endpoint = False)
The step size is (5-3)/8 = 0.25
np.logspace() function calculate squence based on: [3. 3.25 3.5 3.75 4. 4.25 4.5 4.75]
so the value of sequence is:
[ 8. 9.51365692 11.3137085 13.45434264 16. 19.02731384 22.627417 26.90868529]