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

异常numpy.linalg.LinAlgError[源代码] ¶

linalg函数引发的通用Python异常派生对象。

通用异常类，它是从Python的exception.Exception类派生的，当与线性代数相关的条件会阻止该函数的进一步正确执行时，在linalg函数中以编程方式引发该异常类。

参量

没有

例子

>>> from numpy import linalg as LA
>>> LA.inv(np.zeros((2,2)))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "...linalg.py", line 350,
    in inv return wrap(solve(a, identity(a.shape[0], dtype=a.dtype)))
  File "...linalg.py", line 249,
    in solve
    raise LinAlgError('Singular matrix')
numpy.linalg.LinAlgError: Singular matrix