numpy logspace的用法

numpy.logspace

numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)[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).

Parameters:

start : float

base ** start is the starting value of the sequence.

stop : float

base ** stop is 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.

base : float, optional

The base of the log space. The step size between the elements in ln(samples) / ln(base) (or log_base(samples)) is uniform. Default is 10.0.

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

 

上面是官方的文档，英文说的很明白，但网上尤其是csdn的解释，（其实都是你抄我，我抄你），实在让人看的一头雾水
 
numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)
 
比如 np.logspace(0,10,9)
那么会有结果是：

array([1.00000000e+00, 1.77827941e+01, 3.16227766e+02, 5.62341325e+03,

       1.00000000e+05, 1.77827941e+06, 3.16227766e+07, 5.62341325e+08,

       1.00000000e+10])

第一位是开始值0，第二位是结束值10，然后在这0-10之间产生9个值，这9个值是均匀分布的，默认包括最后一个结束点，就是0到10的9个等产数列，那么根据等差数列的公式，a1+（n-1）*d=an，算出，d=1.25，那么a1=0，接着a2=1.25，a3=2.5，。。。。。a9=10，然后再对这9个值做已10为底的指数运算，也就是10^0, 10^1.25 , 10^2.5 这样的结果