Package linear_operators :: Module operators :: Class TridiagonalOperator

Class TridiagonalOperator

              object --+    
                       |    
interface.LinearOperator --+
                           |
                          TridiagonalOperator

Known Subclasses:

SymmetricTridiagonal


Store a tridiagonal operator in the form of 3 arrays

Attributes
-----------
shape : length 2 tuple.
    The shape of the operator.

diag : ndarray of size shape[0]
    The diagonal of the matrix.

subdiag : ndarray of size shape[0] - 1
    The subdiagonal of the matrix.

superdiag : ndarray of size shape[0] - 1
    The superdiagonal of the matrix.

Instance Methods

[hide private]

__init__(self, shape, diag, subdiag, superdiag, **kwargs)
Parameters ---------- shape : length 2 tuple.

source code

__repr__(self)
repr(x)

source code

todense(self)

source code

__getitem__(self, y)

source code

toband(self)
Convert the TridiagonalOperator into a BandOperator

source code

Inherited from interface.LinearOperator: __add__, __iadd__, __imul__, __isub__, __mul__, __neg__, __pow__, __radd__, __rmul__, __rsub__, __sub__, matmat, matvec

Inherited from interface.LinearOperator (private): _matmat

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

init(self, shape, diag, subdiag, superdiag, **kwargs)
(Constructor)

source code


Parameters
----------
shape : length 2 tuple.
    The shape of the operator.

diag : ndarray of size shape[0]
    The diagonal of the matrix.

subdiag : ndarray of size shape[0] - 1
    The subdiagonal of the matrix.

superdiag : ndarray of size shape[0] - 1
    The superdiagonal of the matrix.

Returns
-------
A Tridiagonal matrix operator instance.

Exemple
-------
>>> import numpy as np
>>> import linear_operators as lo
>>> T = lo.TridiagonalOperator((3, 3), [1, 2, 3], [4, 5], [6, 7])
>>> T.todense()
array([[1, 6, 0],
       [4, 2, 7],
       [0, 5, 3]])