03-numpy广播和迭代器遍历

一、广播

import numpy as np
a=np.array([1,3,5,7])
b=np.array([2,4,6,8])
print(a+b)
print(a-b)
print(a*b)#不是矩阵乘法而是两两相成
print(a/b)

a=np.array([[1,3,5,7],[2,4,6,8]])
c=np.array([10,20,30,40])#宽度相同就可以进行运算，多的数运算少的数
print(a+c)

　

二、迭代器遍历等

import numpy as np
#1.迭代器遍历
a=np.arange(12)
a=a.reshape(3,4)
for x in np.nditer(a,order="F"):#遍历元素,与矩阵shape无关
    print(x)
print(a.T,"
--------------------")#矩阵转置

#2.copy+C、F风格遍历
b=np.arange(12)
b=b.reshape(2,6)
c=b.copy(order="C")#C风格，从左往右，从上往下遍历
for x in np.nditer(c):
    print(x)

d=b.copy(order="F")#F风格，从上往下，从左往右遍历
for x in np.nditer(d):
    print(x)

#3.权限改为可写入
e=np.arange(12)
e=e.reshape(2,6)
for x in np.nditer(e):
    x=10
    print(x)#这种形式不会改变原来的数组

for x in np.nditer(e,op_flags=["readwrite"]):#权限改为可写入
    x[...]=2*x
    print(e)

#4.flags
f=np.arange(12)
f=f.reshape(2,6)
for x in np.nditer(a,flags=['external_loop']):#把元素当成一维数组打印
    print(x)
for x in np.nditer(a,flags=['c_index']):  print(x)#C风格打印
for x in np.nditer(a, flags=['f_index']):  print(x)  #F风格打印

#5.可广播的，前提列数相同
i=np.arange([0,2,4,6,8,10],[12,14,16,18,20,22])
j=np.arange([1,1,1,1,1,1])
for x,y in np.nditer([a,b]):
    print(x,y)