|NO.Z.00034|——————————|BigDataEnd|——|Hadoop&Python.v12|——|Arithmetic.v12|NumPy科学计算库：NumPy线性代数|

一、线性代数：矩阵乘积

### --- 矩阵的乘积

A = np.array([[4,2,3],
             [1,3,1]]) # shape(2,3)
B = np.array([[2,7],
             [-5,-7],
             [9,3]]) # shape(3,2)
np.dot(A,B)                                                 # 矩阵运算 A的最后⼀维和B的第⼀维必须⼀致
A @ B                                                       # 符号 @ 表示矩阵乘积运算

### --- 矩阵其他计算
~~~     # 下⾯可以计算矩阵的逆、⾏列式、特征值和特征向量、qr分解值，svd分解值
~~~     # 计算矩阵的逆

from numpy.linalg import inv,det,eig,qr,svd
A = np.array([[1,2,3],
[2,3,4],
[4,5,8]])                                                   # shape(3,3)
inv(t)                                                      # 逆矩阵
det(t)                                                      #计算矩阵⾏列式

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Walter Savage Landor:strove with none,for none was worth my strife.Nature I loved and, next to Nature, Art:I warm'd both hands before the fire of life.It sinks, and I am ready to depart

                                                                                                                                                   ——W.S.Landor

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