Module « scipy.sparse »
Classe « lil_matrix »
Informations générales
Héritage
builtins.object
IndexMixin
builtins.object
spmatrix
lil_matrix
Définition
class lil_matrix(spmatrix, IndexMixin):
Description [extrait de lil_matrix.__doc__]
Row-based list of lists 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 pre-sorted by
index, per row.
This can be instantiated in several ways:
lil_matrix(D)
with a dense matrix or rank-2 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'.
Attributes
----------
dtype : dtype
Data type of the matrix
shape : 2-tuple
Shape of the matrix
ndim : int
Number of dimensions (this is always 2)
nnz
Number of stored values, including explicit zeros
data
LIL format data array of the matrix
rows
LIL format row index array of the matrix
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 non-zero elements.
- The corresponding nonzero values are stored in similar
fashion in ``self.data``.
Constructeur(s)
Liste des attributs statiques
Liste des propriétés
nnz | Number of stored values, including explicit zeros. [extrait de __doc__] |
shape | Get shape of a matrix. [extrait de __doc__] |
Opérateurs hérités de la classe spmatrix
__add__, __eq__, __ge__, __gt__, __le__, __lt__, __matmul__, __mul__, __ne__, __neg__, __pow__, __radd__, __rmul__, __rsub__, __rtruediv__, __sub__
Liste des méthodes
Toutes les méthodes
Méthodes d'instance
Méthodes statiques
Méthodes dépréciées
__str__(self) |
|
copy(self) |
Returns a copy of this matrix. [extrait de copy.__doc__] |
count_nonzero(self) |
Number of non-zero entries, equivalent to [extrait de count_nonzero.__doc__] |
getnnz(self, axis=None) |
Number of stored values, including explicit zeros. [extrait de getnnz.__doc__] |
getrow(self, i) |
Returns a copy of the 'i'th row. [extrait de getrow.__doc__] |
getrowview(self, i) |
Returns a view of the 'i'th row (without copying). [extrait de getrowview.__doc__] |
reshape(self, *args, **kwargs) |
reshape(self, shape, order='C', copy=False) [extrait de reshape.__doc__] |
resize(self, *shape) |
Resize the matrix in-place to dimensions given by ``shape`` [extrait de resize.__doc__] |
toarray(self, order=None, out=None) |
|
tocsr(self, copy=False) |
Convert this matrix to Compressed Sparse Row format. [extrait de tocsr.__doc__] |
tolil(self, copy=False) |
Convert this matrix to List of Lists format. [extrait de tolil.__doc__] |
transpose(self, axes=None, copy=False) |
|
Méthodes héritées de la classe IndexMixin
__init_subclass__, __subclasshook__, getcol
Méthodes héritées de la classe spmatrix
__abs__, __bool__, __div__, __getattr__, __idiv__, __iter__, __len__, __nonzero__, __rdiv__, __repr__, __rmatmul__, __round__, asformat, asfptype, astype, conj, conjugate, diagonal, dot, get_shape, getformat, getH, getmaxprint, maximum, mean, minimum, multiply, nonzero, power, set_shape, setdiag, sum, tobsr, tocoo, tocsc, todense, todia, todok
Méthodes héritées de la classe object
__delattr__,
__dir__,
__format__,
__getattribute__,
__hash__,
__reduce__,
__reduce_ex__,
__setattr__,
__sizeof__
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