scipy.sparse.dok_matrix¶
-
class
scipy.sparse.
dok_matrix
(arg1, shape=None, dtype=None, copy=False)[source]¶ Dictionary Of Keys based sparse matrix.
This is an efficient structure for constructing sparse matrices incrementally.
- This can be instantiated in several ways:
- dok_matrix(D)
with a dense matrix, D
- dok_matrix(S)
with a sparse matrix, S
- dok_matrix((M,N), [dtype])
create the matrix with initial shape (M,N) dtype is optional, defaulting to dtype=’d’
Notes
Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power.
Allows for efficient O(1) access of individual elements. Duplicates are not allowed. Can be efficiently converted to a coo_matrix once constructed.
Examples
>>> import numpy as np >>> from scipy.sparse import dok_matrix >>> S = dok_matrix((5, 5), dtype=np.float32) >>> for i in range(5): ... for j in range(5): ... S[i, j] = i + j # Update element
- Attributes
Methods
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.
clear
()conj
(self[, copy])Element-wise complex conjugation.
conjtransp
(self)Return the conjugate transpose.
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
diagonal
(self[, k])Returns the k-th diagonal of the matrix.
dot
(self, other)Ordinary dot product
fromkeys
(iterable[, value])Returns a new dict with keys from iterable and values equal to value.
get
(self, key[, default])This overrides the dict.get method, providing type checking but otherwise equivalent functionality.
getH
(self)Return the Hermitian transpose of this matrix.
get_shape
(self)Get shape of a matrix.
getcol
(self, j)Returns the j-th column as a (m x 1) DOK matrix.
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 the i-th row as a (1 x n) DOK matrix.
items
()keys
()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
pop
()If key is not found, d is returned if given, otherwise KeyError is raised
popitem
()2-tuple; but raise KeyError if D is empty.
power
(self, n[, dtype])Element-wise power.
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
shape
set_shape
(self, shape)See
reshape
.setdiag
(self, values[, k])Set diagonal or off-diagonal elements of the array.
sum
(self[, axis, dtype, out])Sum the matrix elements over a given axis.
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.
update
(self, val)If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values
()