NumPy 从数值范围创建数组

numpy.arange(start, stop, step, dtype)

import numpy as np
x = np.arange(5)  
print (x)

[0  1  2  3  4]

import numpy as np
# 设置了 dtype
x = np.arange(5, dtype=float)  
print (x)

[0.  1.  2.  3.  4.]

import numpy as np
x = np.arange(10,20,2)  
print (x)

[10  12  14  16  18]

np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)

import numpy as np
a = np.linspace(1,10,10)
print(a)

[ 1.  2.  3.  4.  5.  6.  7.  8.  9. 10.]

import numpy as np
a = np.linspace(1,1,10)
print(a)

[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]

import numpy as np
a = np.linspace(10, 20,  5, endpoint =  False)
print(a)

[10. 12. 14. 16. 18.]

import numpy as np
a =np.linspace(1,10,10,retstep=True)
print(a)
# 拓展例子
b =np.linspace(1,10,10).reshape([10,1])
print(b)

(array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10.]), 1.0)
[[ 1.]
 [ 2.]
 [ 3.]
 [ 4.]
 [ 5.]
 [ 6.]
 [ 7.]
 [ 8.]
 [ 9.]
 [10.]]

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

import numpy as np
# 默认底数是 10
a = np.logspace(1.0,  2.0, num =  10)  
print (a)

[ 10.           12.91549665     16.68100537      21.5443469  27.82559402      
  35.93813664   46.41588834     59.94842503      77.42636827    100.    ]

import numpy as np
a = np.logspace(0,9,10,base=2)
print (a)

[  1.   2.   4.   8.  16.  32.  64. 128. 256. 512.]