算法Python numpy作用(numpy.diff、numpy.argwhere)

import numpy as np

函数：numpy.diff

参数:
arr : [array_like] Input array.
n : [int, optional] The number of times values are differenced.
axis : [int, optional] The axis along which the difference is taken, default is the last axis.

返回: [ndarray]The n-th discrete difference. The output is the same as a except along axis where the dimension is smaller by n.

判断一串数据是否有连续性，例如1，2，3，4，5，6，7，8或者a，b，c，d，e，f，g，在或者

0x01，0x02，0x03，0x04，0x05，0x06，再或者A，B，C，D，E，F，G等等

字符串

4001676200000000c40a060000000000101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f

转换ASCII

'@x01gbx00x00x00x00xc4nx06x00x00x00x00x00x10x11x12x13x14x15x16x17x18x19x1ax1bx1cx1dx1ex1f !"#$%&'()*+,-./0123456789:;<=>?'

diff_2 = np.diff(list(payload), n=2)
print(diff_2)


结果：
[ 165 -107  -93   98    0    0  196 -382  182   -2    6    0    0    0
   16  -15    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0]

总结：那些0既表示此数据有很多连续自增数

函数名：numpy.argwhere

参数：
arr :[数组]输入数组。

返回:[ndarray]非零元素的索引。索引按元素分组。

返回数组中，非0的坐标，常用于获取数组中非0的下表，或者非0个数

数组

[ 165 -107  -93   98    0    0  196 -382  182   -2    6    0    0    0
   16  -15    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0    0    0    0    0    0    0    0    0
    0    0    0    0    0    0]

print(np.argwhere(diff_2 != 0))


结果：
[[ 0]
 [ 1]
 [ 2]
 [ 3]
 [ 6]
 [ 7]
 [ 8]
 [ 9]
 [10]
 [14]
 [15]]


print(len(np.argwhere(diff_2 != 0)))


结果：
11