`scipy.sparse._lil:lil_array`

source: build-install/usr/lib/python3.14/site-packages/scipy/sparse/_lil.py:539

Signature

def lil_array(arg1, shape = None, dtype = None, copy = False, *, maxprint = None)

Summary

Row-based LIst of Lists sparse array.

Extended Summary

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 the array efficiently, make sure the items are pre-sorted by index, per row.

This can be instantiated in several ways:

lil_array(D): where D is a 2-D ndarray
lil_array(S): with another sparse array or matrix 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'.

Attributes

data : ndarray: LIL format data array of the array
rows : ndarray: LIL format row index array of the array
dtype : dtype: Data type of the array
shape : 2-tuple: Shape of the array
ndim : int: Number of dimensions (this is always 2)
format : str: Three letter code for the format of the array storage, e.g. 'lil'
nnz : int: Number of values stored in the array
size : int: Number of values stored in the array
T : lil_array: The transpose of the array
mT : lil_array: The matrix transpose of the array

Notes

Sparse arrays 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 array 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 arrays
once an array has been constructed, convert to CSR or CSC format for fast arithmetic and matrix 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.

Aliases

scipy.sparse.lil_array