Python Linear algebra
Linear algebra
1.模块文档
NAME numpy.linalg DESCRIPTION Core Linear Algebra Tools ------------------------- Linear algebra basics: - norm Vector or matrix norm - inv Inverse of a square matrix - solve Solve a linear system of equations - det Determinant of a square matrix - lstsq Solve linear least-squares problem - pinv Pseudo-inverse (Moore-Penrose) calculated using a singular value decomposition - matrix_power Integer power of a square matrix Eigenvalues and decompositions: - eig Eigenvalues and vectors of a square matrix - eigh Eigenvalues and eigenvectors of a Hermitian matrix - eigvals Eigenvalues of a square matrix - eigvalsh Eigenvalues of a Hermitian matrix - qr QR decomposition of a matrix - svd Singular value decomposition of a matrix - cholesky Cholesky decomposition of a matrix Tensor operations: - tensorsolve Solve a linear tensor equation - tensorinv Calculate an inverse of a tensor Exceptions: - LinAlgError Indicates a failed linear algebra operation
LA.info? Type: module String form: <module 'numpy.linalg.info' from 'F:\\Anaconda3\\lib\\site-packages\\numpy\\linalg\\info.py'> File: f:\anaconda3\lib\site-packages\numpy\linalg\info.py Docstring: Core Linear Algebra Tools ------------------------- Linear algebra basics: - norm Vector or matrix norm - inv Inverse of a square matrix - solve Solve a linear system of equations - det Determinant of a square matrix - lstsq Solve linear least-squares problem - pinv Pseudo-inverse (Moore-Penrose) calculated using a singular value decomposition - matrix_power Integer power of a square matrix Eigenvalues and decompositions: - eig Eigenvalues and vectors of a square matrix - eigh Eigenvalues and eigenvectors of a Hermitian matrix - eigvals Eigenvalues of a square matrix - eigvalsh Eigenvalues of a Hermitian matrix - qr QR decomposition of a matrix - svd Singular value decomposition of a matrix - cholesky Cholesky decomposition of a matrix Tensor operations: - tensorsolve Solve a linear tensor equation - tensorinv Calculate an inverse of a tensor Exceptions: - LinAlgError Indicates a failed linear algebra operation
2.可用方法
'bench','cholesky','cond','det','division','eig','array','eigh','eigvals','eigvalsh','info','inv','lapack_lite','linalg','lstsq','matrix_power','matrix_rank','multi_dot','norm','pinv','print_function','qr','slogdet','solve','svd','tensorinv','tensorsolve','test' eig : eigenvalues and right eigenvectors of general arrays eigvalsh : eigenvalues of symmetric or Hermitian arrays. eigh : eigenvalues and eigenvectors of symmetric/Hermitian arrays.
3.常用方法
首先导入相关模块
import numpy as np from numpy import linalg as LA
3.1求数组的行列式:det
3.2求方阵的特征值、特征向量:eig
3.3求方阵的逆矩阵::inv
3.4求解线性方程组:solve
Solve the system of equations 3 * x0 + x1 = 9
and x0 + 2 * x1 = 8
:
3.5一个方阵的整数次幂:matrix_power
3.6计算在一个函数调用两个或两个以上的阵列的点积:multi_dot
4.官网文档
https://docs.scipy.org/doc/numpy/reference/routines.linalg.html
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