02-numpy切片与索引

一、切片与索引基础

import numpy as np
#1.一维数组切片
arr1=np.arange(10)
s=slice(2,7,2)#2到7每次增加2
print(arr1[s])#其等价于-->
print(arr1[2:7:3])
print(arr1[2:-1:1])#2到最后一个但是不包含最后一个
print(arr1[4])#4
print(arr1[0])#0
print(arr1[:])#全部
print(arr1[2:-1],"
---------------")#2开始到最后一个但是不包含最后一个

#2.二维数组切片
arr2=np.arange(20)
arr2.shape=(4,5)
print(arr2)
print(arr2[0])#取出二维数组中的第一个一维数组
print(arr2[2][1:3])#第三个数组从一到三不包括三
print(arr2[::2],"
---------------")#步长为2

print(arr2[1,...])#取出第二行
print(arr2[...,1])#取出第二列
print(arr2[1:3,...])#取出一    到三行
print(arr2[...,1:3])#取出一到二列

　　

二、高级索引

import numpy as np
#1.例子
myarray=np.arange(9)
myarray.shape=(3,3)
mydata=myarray[[0,1,2],[0,1,2]]#[0 4 8] 00 11 22 xy坐标
mydata=myarray[[0,1,2],[2,1,0]]#[2 4 6] 02 11 20 xy坐标

#2.深入
myarray2=np.arange(12)
myarray2.shape=(4,3)
rows=np.array([[0,0],[3,2]])
cols=np.array([[0,2],[2,0]])
print(myarray2,"
-------------")
#[[ 0  1  2]
# [ 3  4  5]
# [ 6  7  8]
# [ 9 10 11]]

print(rows,"
-------------")
#[[0 0]  0
# [3 2]]  11

print(cols,"
-------------")
#[[0 2]  2
# [2 0]]  6

print(myarray2[rows,cols],"
-------------")#矩阵的乘法

#3.联合挖掘
print(myarray2[1:3,1:3],"
-------------")#行1-3，列1-3 不包括3
#[[4 5]
# [7 8]]
print(myarray2[1:3,[1,2]],"
-------------")#行1-3，第一列和第二列

print(myarray2[1:3,[0,1,2]])
#[[3 4 5]
# [6 7 8]]