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 diagonaloffsets[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: Methods
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 sparse 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 shaperint()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.
