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(self)Element-wise arcsin. arcsinh(self)Element-wise arcsinh. arctan(self)Element-wise arctan. arctanh(self)Element-wise arctanh. asformat(self, format[, copy])Return this matrix in the passed format. asfptype(self)Upcast matrix to a floating point format (if necessary) astype(self, dtype[, casting, copy])Cast the matrix elements to a specified type. ceil(self)Element-wise ceil. conj(self[, copy])Element-wise complex conjugation. conjugate(self[, copy])Element-wise complex conjugation. copy(self)Returns a copy of this matrix. count_nonzero(self)Number of non-zero entries, equivalent to deg2rad(self)Element-wise deg2rad. diagonal(self[, k])Returns the k-th diagonal of the matrix. dot(self, other)Ordinary dot product expm1(self)Element-wise expm1. floor(self)Element-wise floor. getH(self)Return the Hermitian transpose of this matrix. get_shape(self)Get shape of a matrix. getcol(self, j)Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector). getformat(self)Format of a matrix representation as a string. getmaxprint(self)Maximum number of elements to display when printed. getnnz(self[, axis])Number of stored values, including explicit zeros. getrow(self, i)Returns a copy of row i of the matrix, as a (1 x n) sparse matrix (row vector). log1p(self)Element-wise log1p. maximum(self, other)Element-wise maximum between this and another matrix. mean(self[, axis, dtype, out])Compute the arithmetic mean along the specified axis. minimum(self, other)Element-wise minimum between this and another matrix. multiply(self, other)Point-wise multiplication by another matrix nonzero(self)nonzero indices power(self, n[, dtype])This function performs element-wise power. rad2deg(self)Element-wise rad2deg. reshape(self, shape[, order, copy])Gives a new shape to a sparse matrix without changing its data. resize(self, \*shape)Resize the matrix in-place to dimensions given by shaperint(self)Element-wise rint. set_shape(self, shape)See reshape.setdiag(self, values[, k])Set diagonal or off-diagonal elements of the array. sign(self)Element-wise sign. sin(self)Element-wise sin. sinh(self)Element-wise sinh. sqrt(self)Element-wise sqrt. sum(self[, axis, dtype, out])Sum the matrix elements over a given axis. tan(self)Element-wise tan. tanh(self)Element-wise tanh. toarray(self[, order, out])Return a dense ndarray representation of this matrix. tobsr(self[, blocksize, copy])Convert this matrix to Block Sparse Row format. tocoo(self[, copy])Convert this matrix to COOrdinate format. tocsc(self[, copy])Convert this matrix to Compressed Sparse Column format. tocsr(self[, copy])Convert this matrix to Compressed Sparse Row format. todense(self[, order, out])Return a dense matrix representation of this matrix. todia(self[, copy])Convert this matrix to sparse DIAgonal format. todok(self[, copy])Convert this matrix to Dictionary Of Keys format. tolil(self[, copy])Convert this matrix to LInked List format. transpose(self[, axes, copy])Reverses the dimensions of the sparse matrix. trunc(self)Element-wise trunc.