Classe « csc_array »

Informations générales

Héritage

            builtins.object
                sparray
    builtins.object
        IndexMixin
    builtins.object
        _minmax_mixin
builtins.object
    _spbase
        _data_matrix
            _cs_matrix
                _csc_base
                    csc_array

Définition

class csc_array(_csc_base, sparray):

help(csc_array)

Compressed Sparse Column array.

This can be instantiated in several ways:
    csc_array(D)
        where D is a 2-D ndarray

    csc_array(S)
        with another sparse array or matrix S (equivalent to S.tocsc())

    csc_array((M, N), [dtype])
        to construct an empty array with shape (M, N)
        dtype is optional, defaulting to dtype='d'.

    csc_array((data, (row_ind, col_ind)), [shape=(M, N)])
        where ``data``, ``row_ind`` and ``col_ind`` satisfy the
        relationship ``a[row_ind[k], col_ind[k]] = data[k]``.

    csc_array((data, indices, indptr), [shape=(M, N)])
        is the standard CSC representation where the row indices for
        column i are stored in ``indices[indptr[i]:indptr[i+1]]``
        and their corresponding values are stored in
        ``data[indptr[i]:indptr[i+1]]``.  If the shape parameter is
        not supplied, the array dimensions are inferred from
        the index arrays.

Attributes
----------
dtype : dtype
    Data type of the array
shape : 2-tuple
    Shape of the array
ndim : int
    Number of dimensions (this is always 2)
nnz
size
data
    CSC format data array of the array
indices
    CSC format index array of the array
indptr
    CSC format index pointer array of the array
has_sorted_indices
has_canonical_format
T

Notes
-----

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

Advantages of the CSC format
    - efficient arithmetic operations CSC + CSC, CSC * CSC, etc.
    - efficient column slicing
    - fast matrix vector products (CSR, BSR may be faster)

Disadvantages of the CSC format
  - slow row slicing operations (consider CSR)
  - changes to the sparsity structure are expensive (consider LIL or DOK)

Canonical format
  - Within each column, indices are sorted by row.
  - There are no duplicate entries.

Examples
--------

>>> import numpy as np
>>> from scipy.sparse import csc_array
>>> csc_array((3, 4), dtype=np.int8).toarray()
array([[0, 0, 0, 0],
       [0, 0, 0, 0],
       [0, 0, 0, 0]], dtype=int8)

>>> row = np.array([0, 2, 2, 0, 1, 2])
>>> col = np.array([0, 0, 1, 2, 2, 2])
>>> data = np.array([1, 2, 3, 4, 5, 6])
>>> csc_array((data, (row, col)), shape=(3, 3)).toarray()
array([[1, 0, 4],
       [0, 0, 5],
       [2, 3, 6]])

>>> indptr = np.array([0, 2, 3, 6])
>>> indices = np.array([0, 2, 2, 0, 1, 2])
>>> data = np.array([1, 2, 3, 4, 5, 6])
>>> csc_array((data, indices, indptr), shape=(3, 3)).toarray()
array([[1, 0, 4],
       [0, 0, 5],
       [2, 3, 6]])

Constructeur(s)

Signature du constructeur	Description
__init__(self, arg1, shape=None, dtype=None, copy=False, *, maxprint=None)

Liste des propriétés

Nom de la propriété	Description
dtype
format	Format string for matrix. _{[extrait de format.__doc__]}
has_canonical_format	Whether the array/matrix has sorted indices and no duplicates _{[extrait de has_canonical_format.__doc__]}
has_sorted_indices	Whether the indices are sorted _{[extrait de has_sorted_indices.__doc__]}
imag
ndim
nnz	Number of stored values, including explicit zeros. _{[extrait de nnz.__doc__]}
real
shape
size	Number of stored values. _{[extrait de size.__doc__]}
T	Transpose. _{[extrait de T.__doc__]}

Liste des opérateurs

Opérateurs hérités de la classe _cs_matrix

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Liste des opérateurs

Opérateurs hérités de la classe IndexMixin

__getitem__, __setitem__

Liste des opérateurs

Opérateurs hérités de la classe _data_matrix

__imul__, __itruediv__, __neg__

Liste des opérateurs

Opérateurs hérités de la classe _spbase

__add__, __iadd__, __isub__, __matmul__, __mul__, __pow__, __radd__, __rmul__, __rsub__, __rtruediv__, __sub__, __truediv__

Liste des méthodes

Toutes les méthodes Méthodes d'instance Méthodes statiques

Signature de la méthode	Description

Méthodes héritées de la classe sparray

__init_subclass__, __subclasshook__

Méthodes héritées de la classe _csc_base

__iter__, nonzero, tocsc, tocsr, transpose

Méthodes héritées de la classe _cs_matrix

check_format, count_nonzero, diagonal, eliminate_zeros, maximum, minimum, multiply, prune, resize, sort_indices, sorted_indices, sum, sum_duplicates, toarray, tocoo

Méthodes héritées de la classe _minmax_mixin

argmax, argmin, max, min, nanmax, nanmin

Méthodes héritées de la classe _data_matrix

__abs__, __round__, astype, conjugate, copy, power

Méthodes héritées de la classe _spbase

__bool__, __div__, __idiv__, __len__, __nonzero__, __rdiv__, __repr__, __rmatmul__, __str__, asformat, conj, dot, mean, reshape, setdiag, tobsr, todense, todia, todok, tolil, trace