### Navigation

- index
- modules |
- modules |
- SciPy v0.9 Reference Guide (DRAFT) »
- Sparse matrices (`scipy.sparse`) »

# scipy.sparse.lil_matrix

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

  Row-based linked list sparse matrix

  This is an efficient structure for constructing sparse matrices incrementally.

  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.tocsc())
    lil_matrix((M, N), [dtype])
      to construct an empty matrix with shape (M, N) dtype is optional, defaulting to dtype=’d’.

  Notes

  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`.

  Methods

  `asformat` |
  `asfptype` |
  `astype` |
  `conj` |
  `conjugate` |
  `copy` | Generic (shallow and deep) copying operations.
  `diagonal` |
  `dot` |
  `getH` |
  `get_shape` |
  `getcol` |
  `getformat` |
  `getmaxprint` |
  `getnnz` |
  `getrow` |
  `getrowview` |
  `mean` |
  `multiply` |
  `nonzero` |
  `reshape` |
  `set_shape` |
  `setdiag` |
  `sum` |
  `toarray` |
  `tobsr` |
  `tocoo` |
  `tocsc` |
  `tocsr` |
  `todense` |
  `todia` |
  `todok` |
  `tolil` |
  `transpose` |

### Navigation

- index
- modules |
- modules |
- SciPy v0.9 Reference Guide (DRAFT) »
- Sparse matrices (`scipy.sparse`) »