Data type of the array
Shape of the array
Number of dimensions (this is always 2)
Number of stored values, including explicit zeros
LIL format data array of the array
LIL format row index array of the 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'.
Sparse arrays can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and array 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 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
.
Row-based list of lists sparse array
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