5.2.1.1.5. scipy.sparse.dia_matrix

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

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)

Notes

Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power.

Examples

>>> import numpy as np
>>> from scipy.sparse import dia_matrix
>>> dia_matrix((3, 4), dtype=np.int8).toarray()
array([[0, 0, 0, 0],
       [0, 0, 0, 0],
       [0, 0, 0, 0]], dtype=int8)

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

Attributes

nnz number of nonzero values
dtype (dtype) Data type of the matrix
shape (2-tuple) Shape of the matrix
ndim (int) Number of dimensions (this is always 2)
data DIA format data array of the matrix
offsets DIA format offset array of the matrix
__init__(arg1, shape=None, dtype=None, copy=False)[source]

Methods

__init__(arg1[, shape, dtype, copy])
arcsin() Element-wise arcsin.
arcsinh() Element-wise arcsinh.
arctan() Element-wise arctan.
arctanh() Element-wise arctanh.
asformat(format) Return this matrix in a given sparse format
asfptype() Upcast matrix to a floating point format (if necessary)
astype(t)
ceil() Element-wise ceil.
conj()
conjugate()
copy()
deg2rad() Element-wise deg2rad.
diagonal() Returns the main diagonal of the matrix
dot(other) Ordinary dot product
expm1() Element-wise expm1.
floor() Element-wise floor.
getH()
get_shape()
getcol(j) Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector).
getformat()
getmaxprint()
getnnz() number of nonzero values
getrow(i) Returns a copy of row i of the matrix, as a (1 x n) sparse matrix (row vector).
log1p() Element-wise log1p.
maximum(other)
mean([axis]) Average the matrix over the given axis.
minimum(other)
multiply(other) Point-wise multiplication by another matrix
nonzero() nonzero indices
power(n[, dtype]) This function performs element-wise power.
rad2deg() Element-wise rad2deg.
reshape(shape)
rint() Element-wise rint.
set_shape(shape)
setdiag(values[, k]) Set diagonal or off-diagonal elements of the array.
sign() Element-wise sign.
sin() Element-wise sin.
sinh() Element-wise sinh.
sqrt() Element-wise sqrt.
sum([axis]) Sum the matrix over the given axis.
tan() Element-wise tan.
tanh() Element-wise tanh.
toarray([order, out]) Return a dense ndarray representation of this matrix.
tobsr([blocksize])
tocoo()
tocsc()
tocsr()
todense([order, out]) Return a dense matrix representation of this matrix.
todia([copy])
todok()
tolil()
transpose()
trunc() Element-wise trunc.

Attributes

dtype
ndim
nnz number of nonzero values
shape