#### Previous topic

scipy.sparse.dia_matrix.trunc

# scipy.sparse.dok_matrix

class `scipy.sparse.``dok_matrix`(arg1, shape=None, dtype=None, copy=False)

  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

  `shape` | Get shape of a matrix.
  `nnz` | Number of stored values, including explicit zeros.

  dtype | (dtype) Data type of the matrix
  ndim | (int) Number of dimensions (this is always 2)

  Methods

  `asformat`(format) | Return this matrix in a given sparse format
  `asfptype`() | Upcast matrix to a floating point format (if necessary)
  `astype`(t) | Cast the matrix elements to a specified type.
  `clear`(() -> None. Remove all items from D.) |
  `conj`() | Element-wise complex conjugation.
  `conjtransp`() | Return the conjugate transpose
  `conjugate`() | Element-wise complex conjugation.
  `copy`() | Returns a copy of this matrix.
  `count_nonzero`() | Number of non-zero entries, equivalent to
  `diagonal`() | Returns the main diagonal of the matrix
  `dot`(other) | Ordinary dot product
  `fromkeys`(…) | v defaults to None.
  `get`(key[, default]) | This overrides the dict.get method, providing type checking but otherwise equivalent functionality.
  `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 a (m x 1) DOK matrix.
  `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) DOK matrix.
  `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) |
  `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
  `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.
  `power`(n[, dtype]) | Element-wise power.
  `reshape`(shape[, order]) | Gives a new shape to a sparse matrix without changing its data.
  `resize`(shape) | Resize the matrix in-place to dimensions given by ‘shape’.
  `set_shape`(shape) | See `reshape`.
  `setdefault`((k[,d]) -> D.get(k,d), …) |
  `setdiag`(values[, k]) | Set diagonal or off-diagonal elements of the array.
  `sum`([axis, dtype, out]) | Sum the matrix elements over a given axis.
  `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.
  `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`(…) |