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:
with a dense matrix or rank-2 ndarray D
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’.


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

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