numpy 线性代数

https://docs.scipy.org/doc/numpy/reference/routines.linalg.html

矩阵与向量乘积

方法 描述
dot(a, b[, out]) Dot product of two arrays.
linalg.multi_dot(arrays) Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order.
vdot(a, b) Return the dot product of two vectors.
inner(a, b) Inner product of two arrays.
outer(a, b[, out]) Compute the outer product of two vectors.
matmul(a, b[, out]) Matrix product of two arrays.
tensordot(a, b[, axes]) Compute tensor dot product along specified axes for arrays >= 1-D.
einsum(subscripts, *operands[, out, dtype, …]) Evaluates the Einstein summation convention on the operands.
einsum_path(subscripts, *operands[, optimize]) Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays.
linalg.matrix_power(M, n) Raise a square matrix to the (integer) power n.
kron(a, b) Kronecker product of two arrays.

分解

方法 描述
linalg.cholesky(a) Cholesky decomposition.
linalg.qr(a[, mode]) Compute the qr factorization of a matrix.
linalg.svd(a[, full_matrices, compute_uv]) Singular Value Decomposition.

特征值特征向量

方法 描述
linalg.eig(a) Compute the eigenvalues and right eigenvectors of a square array.
linalg.eigh(a[, UPLO]) Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.
linalg.eigvals(a) Compute the eigenvalues of a general matrix.
linalg.eigvalsh(a[, UPLO]) Compute the eigenvalues of a Hermitian or real symmetric matrix.

Norms and other numbers

方法 描述
linalg.norm(x[, ord, axis, keepdims]) 求范数, 默认是二范数
linalg.cond(x[, p]) Compute the condition number of a matrix.
linalg.det(a) Compute the determinant of an array.
linalg.matrix_rank(M[, tol, hermitian]) Return matrix rank of array using SVD method
linalg.slogdet(a) Compute the sign and (natural) logarithm of the determinant of an array.
trace(a[, offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array.

Solving equations and inverting matrices

方法 描述
linalg.solve(a, b) Solve a linear matrix equation, or system of linear scalar equations.
linalg.tensorsolve(a, b[, axes]) Solve the tensor equation a x = b for x.
linalg.lstsq(a, b[, rcond]) Return the least-squares solution to a linear matrix equation.
linalg.inv(a) Compute the (multiplicative) inverse of a matrix.
linalg.pinv(a[, rcond]) Compute the (Moore-Penrose) pseudo-inverse of a matrix.
linalg.tensorinv(a[, ind]) Compute the ‘inverse’ of an N-dimensional array.

Exceptions

方法 描述
linalg.LinAlgError Generic Python-exception-derived object raised by linalg functions.

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转载自blog.csdn.net/claroja/article/details/80566007