scipy.sparse.dia_matrix

class scipy.sparse.dia_matrix(arg1, shape=None, dtype=None, copy=False)

Sparse matrix with DIAgonal storage

This can be instantiated in several ways:

dia_matrix(D)

with a dense matrix

dia_matrix(S)

with another sparse matrix S (equivalent to S.todia())

dia_matrix((M, N), [dtype])

to construct an empty matrix with shape (M, N), dtype is optional, defaulting to dtype=’d’.

dia_matrix((data, offsets), shape=(M, N))

where the data[k,:] stores the diagonal entries for diagonal offsets[k] (See example below)

Examples

>>> from scipy.sparse import *
>>> from scipy import *
>>> dia_matrix( (3,4), dtype=int8).todense()
matrix([[0, 0, 0, 0],
        [0, 0, 0, 0],
        [0, 0, 0, 0]], dtype=int8)

>>> data = array([[1,2,3,4]]).repeat(3,axis=0)
>>> offsets = array([0,-1,2])
>>> dia_matrix( (data,offsets), shape=(4,4)).todense()
matrix([[1, 0, 3, 0],
        [1, 2, 0, 4],
        [0, 2, 3, 0],
        [0, 0, 3, 4]])

Methods

asformat
asfptype
astype
conj
conjugate
copy	Generic (shallow and deep) copying operations.
diagonal
dot
getH
get_shape
getcol
getformat
getmaxprint
getnnz
getrow
mean
multiply
nonzero
reshape
set_shape
setdiag
sum
toarray
tobsr
tocoo
tocsc
tocsr
todense
todia
todok
tolil
transpose