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scipy.sparse.dok_matrix.viewvalues

# scipy.sparse.lil_matrix

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

  Row-based linked list sparse matrix

  This is a structure for constructing sparse matrices incrementally. Note that inserting a single item can take linear time in the worst case; to construct a matrix efficiently, make sure the items are pre-sorted by index, per row.

  This can be instantiated in several ways:
    lil_matrix(D)
      with a dense matrix or rank-2 ndarray D
    lil_matrix(S)
      with another sparse matrix S (equivalent to S.tolil())
    lil_matrix((M, N), [dtype])
      to construct an empty matrix with 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.

  Advantages of the LIL format
    - supports flexible slicing
    - changes to the matrix sparsity structure are efficient
  Disadvantages of the LIL format
    - arithmetic operations LIL + LIL are slow (consider CSR or CSC)
    - slow column slicing (consider CSC)
    - slow matrix vector products (consider CSR or CSC)
  Intended Usage
    - LIL is a convenient format for constructing sparse matrices
    - once a matrix has been constructed, convert to CSR or CSC format for fast arithmetic and matrix vector operations
    - consider using the COO format when constructing large matrices
  Data Structure
    - An array (`self.rows`) of rows, each of which is a sorted list of column indices of non-zero elements.
    - The corresponding nonzero values are stored in similar fashion in `self.data`.

  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)
  data | LIL format data array of the matrix
  rows | LIL format row index array of the matrix

  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.
  `conj`() | Element-wise complex conjugation.
  `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
  `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 the ‘i’th row.
  `getrowview`(i) | Returns a view of the ‘i’th row (without copying).
  `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]) | Element-wise power.
  `reshape`(shape[, order]) | Gives a new shape to a sparse matrix without changing its data.
  `set_shape`(shape) | See `reshape`.
  `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]) | See the docstring for `spmatrix.toarray`.
  `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.