# 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

```>>> 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]])
```

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

Methods

 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 getformat() getmaxprint() getnnz() number of nonzero values getrow(i) Returns a copy of row i of the matrix, as a (1 x n) sparse log1p() Element-wise log1p. mean([axis]) Average the matrix over the given axis. multiply(other) Point-wise multiplication by another matrix nonzero() nonzero indices rad2deg() Element-wise rad2deg. reshape(shape) rint() Element-wise rint. set_shape(shape) setdiag(values[, k]) Fills the diagonal elements {a_ii} with the values from the given sequence. 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.

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