scipy.sparse.lil_matrix¶

class
scipy.sparse.
lil_matrix
(arg1, shape=None, dtype=None, copy=False)[source]¶ Rowbased 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 presorted by index, per row.
 This can be instantiated in several ways:
 lil_matrix(D)
 with a dense matrix or rank2 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 nonzero elements.  The corresponding nonzero values are stored in similar
fashion in
self.data
.
 An array (
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
(dtype[, casting, copy])Cast the matrix elements to a specified type. conj
()Elementwise complex conjugation. conjugate
()Elementwise complex conjugation. copy
()Returns a copy of this matrix. count_nonzero
()Number of nonzero entries, equivalent to diagonal
([k])Returns the kth 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)Elementwise maximum between this and another matrix. mean
([axis, dtype, out])Compute the arithmetic mean along the specified axis. minimum
(other)Elementwise minimum between this and another matrix. multiply
(other)Pointwise multiplication by another matrix nonzero
()nonzero indices power
(n[, dtype])Elementwise 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 offdiagonal 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.