Dictionary Of Keys based sparse matrix.
This is an efficient structure for constructing sparse matrices incrementally.
Notes
Allows for efficient O(1) access of individual elements. Duplicates are not allowed. Can be efficiently converted to a coo_matrix once constructed.
Examples
>>> from scipy.sparse import *
>>> from scipy import *
>>> S = dok_matrix((5,5), dtype=float32)
>>> for i in range(5):
>>> for j in range(5):
>>> S[i,j] = i+j # Update element
Methods
asformat(format) | Return this matrix in a given sparse format |
asfptype() | Upcast matrix to a floating point format (if necessary) |
astype(t) | |
clear(() -> None. Remove all items from D.) | |
conj() | |
conjtransp() | Return the conjugate transpose |
conjugate() | |
copy() | |
diagonal() | Returns the main diagonal of the matrix |
dot(other) | |
fromkeys(...) | v defaults to None. |
get(key[, default]) | This overrides the dict.get method, providing type checking |
getH() | |
get_shape() | |
getcol(j) | Returns a copy of column j of the matrix, as an (m x 1) sparse |
getformat() | |
getmaxprint() | |
getnnz() | |
getrow(i) | Returns a copy of row i of the matrix, as a (1 x n) sparse |
has_key((k) -> True if D has a key k, else False) | |
items(() -> list of D’s (key, value) pairs, ...) | |
iteritems(() -> an iterator over the (key, ...) | |
iterkeys(() -> an iterator over the keys of D) | |
itervalues(...) | |
keys(() -> list of D’s keys) | |
mean([axis]) | Average the matrix over the given axis. |
multiply(other) | Point-wise multiplication by another matrix |
nonzero() | nonzero indices |
pop((k[,d]) -> v, ...) | If key is not found, d is returned if given, otherwise KeyError is raised |
popitem(() -> (k, v), ...) | 2-tuple; but raise KeyError if D is empty. |
reshape(shape) | |
resize(shape) | Resize the matrix in-place to dimensions given by ‘shape’. |
set_shape(shape) | |
setdefault((k[,d]) -> D.get(k,d), ...) | |
setdiag(values[, k]) | Fills the diagonal elements {a_ii} with the values from the given sequence. |
split(cols_or_rows[, columns]) | |
sum([axis]) | Sum the matrix over the given axis. |
take(cols_or_rows[, columns]) | |
toarray() | |
tobsr([blocksize]) | |
tocoo() | Return a copy of this matrix in COOrdinate format |
tocsc() | Return a copy of this matrix in Compressed Sparse Column format |
tocsr() | Return a copy of this matrix in Compressed Sparse Row format |
todense() | |
todia() | |
todok([copy]) | |
tolil() | |
transpose() | Return the transpose |
update(([E, ...) | If E present and has a .keys() method, does: for k in E: D[k] = E[k] |
values(() -> list of D’s values) | |
viewitems(...) | |
viewkeys(...) | |
viewvalues(...) |
Return the conjugate transpose
This overrides the dict.get method, providing type checking but otherwise equivalent functionality.
Resize the matrix in-place to dimensions given by ‘shape’.
Any non-zero elements that lie outside the new shape are removed.
Return a copy of this matrix in COOrdinate format
Return a copy of this matrix in Compressed Sparse Column format
Return a copy of this matrix in Compressed Sparse Row format
Return the transpose