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_array(D)

with a dense matrix

dia_array(S)

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

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

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

dia_array((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_array
>>> dia_array((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_array((data, offsets), shape=(4, 4)).toarray()
array([[1, 0, 3, 0],
       [1, 2, 0, 4],
       [0, 2, 3, 0],
       [0, 0, 3, 4]])
>>> from scipy.sparse import dia_array
>>> n = 10
>>> ex = np.ones(n)
>>> data = np.array([ex, 2 * ex, ex])
>>> offsets = np.array([-1, 0, 1])
>>> dia_array((data, offsets), shape=(n, n)).toarray()
array([[2., 1., 0., ..., 0., 0., 0.],
       [1., 2., 1., ..., 0., 0., 0.],
       [0., 1., 2., ..., 0., 0., 0.],
       ...,
       [0., 0., 0., ..., 2., 1., 0.],
       [0., 0., 0., ..., 1., 2., 1.],
       [0., 0., 0., ..., 0., 1., 2.]])
Attributes:
dtypedtype

Data type of the matrix

shape2-tuple

Shape of the matrix

ndimint

Number of dimensions (this is always 2)

nnz

Number of stored values, including explicit zeros.

data

DIA format data array of the matrix

offsets

DIA format offset array of the matrix

Methods

__len__()

__mul__(other)

arcsin()

Element-wise arcsin.

arcsinh()

Element-wise arcsinh.

arctan()

Element-wise arctan.

arctanh()

Element-wise arctanh.

asformat(format[, copy])

Return this array in the passed format.

asfptype()

Upcast array to a floating point format (if necessary)

astype(dtype[, casting, copy])

Cast the array elements to a specified type.

ceil()

Element-wise ceil.

conj([copy])

Element-wise complex conjugation.

conjugate([copy])

Element-wise complex conjugation.

copy()

Returns a copy of this array.

count_nonzero()

Number of non-zero entries, equivalent to

deg2rad()

Element-wise deg2rad.

diagonal([k])

Returns the kth diagonal of the array.

dot(other)

Ordinary dot product

expm1()

Element-wise expm1.

floor()

Element-wise floor.

getH()

Return the Hermitian transpose of this array.

get_shape()

Get the shape of the matrix

getcol(j)

Returns a copy of column j of the array, as an (m x 1) sparse array (column vector).

getformat()

Matrix storage format

getmaxprint()

Maximum number of elements to display when printed.

getnnz([axis])

Number of stored values, including explicit zeros.

getrow(i)

Returns a copy of row i of the array, as a (1 x n) sparse array (row vector).

log1p()

Element-wise log1p.

maximum(other)

Element-wise maximum between this and another array.

mean([axis, dtype, out])

Compute the arithmetic mean along the specified axis.

minimum(other)

Element-wise minimum between this and another array.

multiply(other)

Point-wise multiplication by another array

nonzero()

nonzero indices

power(n[, dtype])

This function performs element-wise power.

rad2deg()

Element-wise rad2deg.

reshape(self, shape[, order, copy])

Gives a new shape to a sparse array without changing its data.

resize(*shape)

Resize the array in-place to dimensions given by shape

rint()

Element-wise rint.

set_shape(shape)

Set the shape of the matrix in-place

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, dtype, out])

Sum the array elements over a given axis.

tan()

Element-wise tan.

tanh()

Element-wise tanh.

toarray([order, out])

Return a dense ndarray representation of this sparse array.

tobsr([blocksize, copy])

Convert this array to Block Sparse Row format.

tocoo([copy])

Convert this array to COOrdinate format.

tocsc([copy])

Convert this array to Compressed Sparse Column format.

tocsr([copy])

Convert this array to Compressed Sparse Row format.

todense([order, out])

Return a dense matrix representation of this sparse array.

todia([copy])

Convert this array to sparse DIAgonal format.

todok([copy])

Convert this array to Dictionary Of Keys format.

tolil([copy])

Convert this array to List of Lists format.

trace([offset])

Returns the sum along diagonals of the sparse array.

transpose([axes, copy])

Reverses the dimensions of the sparse array.

trunc()

Element-wise trunc.