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,"\n--------------------")#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)

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