NumPy NumPy参考

• 数组对象
• 常数
• 通用功能（ufunc）
• 例行程序
•    数组创建例程
•    数组操作例程
•    Binary operations
•    String operations
•    C-Types Foreign Function Interface (numpy.ctypeslib)
•    Datetime Support Functions
•    Data type routines
•    Optionally Scipy-accelerated routines (numpy.dual)
•    Mathematical functions with automatic domain (numpy.emath)
•    Floating point error handling
•    Discrete Fourier Transform (numpy.fft)
•    Financial functions
•    Functional programming
•    NumPy-specific help functions
•    Indexing routines
•    输入输出
•    线性代数（numpy.linalg）
•          numpy.dot
•          numpy.linalg.multi_dot
•          numpy.vdot
•          numpy.inner
•          numpy.outer
•          numpy.matmul
•          numpy.tensordot
•          numpy.einsum
•          numpy.einsum_path
•          numpy.linalg.matrix_power
•          numpy.kron
•          numpy.linalg.holesky
•          numpy.linalg.qr
•          numpy.linalg.svd
•          numpy.linalg.eig
•          numpy.linalg.eigh
•          numpy.linalg.eigvals
•          numpy.linalg.eigvalsh
•          numpy.linalg.norm
•          numpy.linalg.cond
•          numpy.linalg.det
•          numpy.linalg.matrix_rank
•          numpy.linalg.slogdet
•          numpy.trace
•          numpy.linalg.solve
•          numpy.linalg.tensorsolve
•          numpy.linalg.lstsq
•          numpy.linalg.inv
•          numpy.linalg.pinv
•          numpy.linalg.tensorinv
•          numpy.linalg.LinAlgError
•    逻辑功能
•    Mathematical functions
•    Matrix library (numpy.matlib)
•    Miscellaneous routines
•    Padding Arrays
•    Polynomials
•    Random sampling (numpy.random)
•    Set routines
•    Sorting, searching, and counting
•    Statistics
•    Test Support (numpy.testing)
•    Window functions
• Packaging (numpy.distutils)
• NumPy Distutils - Users Guide
• NumPy C-API
• NumPy内部
• NumPy和SWIG

numpy.linalg.tensorinv（a，ind = 2 ）[源代码] ¶

计算N维数组的“逆”。

其结果是逆一个相对于所述tensordot操作 ，即，高达浮点精度， 是用于tensordot操作“同一性”张量。tensordot(a, b, ind)tensordot(tensorinv(a), a, ind)

参量

一个array_like

张量“反转”。其形状必须为“正方形”，即 。prod(a.shape[:ind]) == prod(a.shape[ind:])

ind int，可选

逆和中涉及的第一索引的数量。必须为正整数，默认为2。

退货

b ndarray

一个张量点倒数，形状。a.shape[ind:] + a.shape[:ind]

加薪

LinAlgError

如果a是单数形式或不是'square'形式（在上述意义上）。

也可以看看

numpy.tensordot， tensorsolve

例子

>>> a = np.eye(4*6)
>>> a.shape = (4, 6, 8, 3)
>>> ainv = np.linalg.tensorinv(a, ind=2)
>>> ainv.shape
(8, 3, 4, 6)
>>> b = np.random.randn(4, 6)
>>> np.allclose(np.tensordot(ainv, b), np.linalg.tensorsolve(a, b))
True

>>> a = np.eye(4*6)
>>> a.shape = (24, 8, 3)
>>> ainv = np.linalg.tensorinv(a, ind=1)
>>> ainv.shape
(8, 3, 24)
>>> b = np.random.randn(24)
>>> np.allclose(np.tensordot(ainv, b, 1), np.linalg.tensorsolve(a, b))
True