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 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 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.