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:
with a dense matrix
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)


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


>>> 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]])
dtype : dtype

Data type of the matrix

shape : 2-tuple

Get shape of a matrix.

ndim : int

Number of dimensions (this is always 2)


Number of stored values, including explicit zeros.


DIA format data array of the matrix


DIA format offset array of the matrix


__mul__(other) interpret other and call one of the following
arcsin() Element-wise arcsin.
arcsinh() Element-wise arcsinh.
arctan() Element-wise arctan.
arctanh() Element-wise arctanh.
asformat(format[, copy]) Return this matrix in the passed format.
asfptype() Upcast matrix to a floating point format (if necessary)
astype(dtype[, casting, copy]) Cast the matrix 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 matrix.
count_nonzero() Number of non-zero entries, equivalent to
deg2rad() Element-wise deg2rad.
diagonal([k]) Returns the k-th diagonal of the matrix.
dot(other) Ordinary dot product
expm1() Element-wise expm1.
floor() Element-wise floor.
getH() Return the Hermitian transpose of this matrix.
get_shape() Get shape of a matrix.
getcol(j) Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector).
getformat() Format of a matrix representation as a string.
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 matrix, as a (1 x n) sparse matrix (row vector).
log1p() Element-wise log1p.
maximum(other) Element-wise maximum between this and another matrix.
mean([axis, dtype, out]) Compute the arithmetic mean along the specified axis.
minimum(other) Element-wise minimum between this and another matrix.
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(self, shape[, order, copy]) Gives a new shape to a sparse matrix without changing its data.
resize(*shape) Resize the matrix in-place to dimensions given by shape
rint() Element-wise rint.
set_shape(shape) See reshape.
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 matrix elements over a given axis.
tan() Element-wise tan.
tanh() Element-wise tanh.
toarray([order, out]) Return a dense ndarray representation of this matrix.
tobsr([blocksize, copy]) Convert this matrix to Block Sparse Row format.
tocoo([copy]) Convert this matrix to COOrdinate format.
tocsc([copy]) Convert this matrix to Compressed Sparse Column format.
tocsr([copy]) Convert this matrix to Compressed Sparse Row format.
todense([order, out]) Return a dense matrix representation of this matrix.
todia([copy]) Convert this matrix to sparse DIAgonal format.
todok([copy]) Convert this matrix to Dictionary Of Keys format.
tolil([copy]) Convert this matrix to LInked List format.
transpose([axes, copy]) Reverses the dimensions of the sparse matrix.
trunc() Element-wise trunc.

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