# scipy.sparse.lil_array#

class scipy.sparse.lil_array(arg1, shape=None, dtype=None, copy=False)[source]#

Row-based LIst of Lists sparse array

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

This can be instantiated in several ways:
lil_array(D)

with a dense array or rank-2 ndarray D

lil_array(S)

with another sparse array S (equivalent to S.tolil())

lil_array((M, N), [dtype])

to construct an empty array with shape (M, N) dtype is optional, defaulting to dtype=’d’.

Notes

Sparse arrays can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and array power.

• supports flexible slicing

• changes to the array sparsity structure are efficient

• arithmetic operations LIL + LIL are slow (consider CSR or CSC)

• slow column slicing (consider CSC)

• slow array vector products (consider CSR or CSC)

Intended Usage
• LIL is a convenient format for constructing sparse arrays

• once a array has been constructed, convert to CSR or CSC format for fast arithmetic and array vector operations

• consider using the COO format when constructing large arrays

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:
dtypedtype

Data type of the array

`shape`2-tuple

Get shape of a matrix.

ndimint

Number of dimensions (this is always 2)

`nnz`

Number of stored values, including explicit zeros.

data

LIL format data array of the array

rows

LIL format row index array of the array

Methods

 `__mul__`(*args, **kwargs) `asformat`(format[, copy]) Return this matrix in the passed format. Upcast matrix to a floating point format (if necessary) `astype`(dtype[, casting, copy]) Cast the matrix elements to a specified type. `conj`([copy]) Element-wise complex conjugation. `conjugate`([copy]) Element-wise complex conjugation. Returns a copy of this matrix. Number of non-zero entries, equivalent to `diagonal`([k]) Returns the kth diagonal of the matrix. `dot`(other) Ordinary dot product Return the Hermitian transpose of this matrix. Get shape of a matrix. Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector). Format of a matrix representation as a string. Maximum number of elements to display when printed. `getnnz`([axis]) Number of stored values, including explicit zeros. Returns a copy of the 'i'th row. 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 indices `power`(n[, dtype]) Element-wise power. `reshape`(self, shape[, order, copy]) 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) `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 List of Lists format. `trace`([offset]) Returns the sum along diagonals of the sparse matrix. `transpose`([axes, copy]) Reverses the dimensions of the sparse matrix.
 __getitem__