2.5.2.2.4. Coordinate Format (COO)

  • also known as the ‘ijv’ or ‘triplet’ format
    • three NumPy arrays: row, col, data
    • data[i] is value at (row[i], col[i]) position
    • permits duplicate entries
    • subclass of _data_matrix (sparse matrix classes with data attribute)
  • fast format for constructing sparse matrices

  • constructor accepts:
    • dense matrix (array)
    • sparse matrix
    • shape tuple (create empty matrix)
    • (data, ij) tuple
  • very fast conversion to and from CSR/CSC formats

  • fast matrix * vector (sparsetools)

  • fast and easy item-wise operations
    • manipulate data array directly (fast NumPy machinery)
  • no slicing, no arithmetics (directly)

  • use:
    • facilitates fast conversion among sparse formats

    • when converting to other format (usually CSR or CSC), duplicate entries are summed together

      • facilitates efficient construction of finite element matrices

2.5.2.2.4.1. Examples

  • create empty COO matrix:

    >>> mtx = sparse.coo_matrix((3, 4), dtype=np.int8)
    
    >>> mtx.todense()
    matrix([[0, 0, 0, 0],
    [0, 0, 0, 0],
    [0, 0, 0, 0]], dtype=int8)
  • create using (data, ij) tuple:

    >>> row = np.array([0, 3, 1, 0])
    
    >>> col = np.array([0, 3, 1, 2])
    >>> data = np.array([4, 5, 7, 9])
    >>> mtx = sparse.coo_matrix((data, (row, col)), shape=(4, 4))
    >>> mtx
    <4x4 sparse matrix of type '<type 'numpy.int64'>'
    with 4 stored elements in COOrdinate format>
    >>> mtx.todense()
    matrix([[4, 0, 9, 0],
    [0, 7, 0, 0],
    [0, 0, 0, 0],
    [0, 0, 0, 5]])
  • duplicates entries are summed together:

    >>> row = np.array([0, 0, 1, 3, 1, 0, 0])
    
    >>> col = np.array([0, 2, 1, 3, 1, 0, 0])
    >>> data = np.array([1, 1, 1, 1, 1, 1, 1])
    >>> mtx = sparse.coo_matrix((data, (row, col)), shape=(4, 4))
    >>> mtx.todense()
    matrix([[3, 0, 1, 0],
    [0, 2, 0, 0],
    [0, 0, 0, 0],
    [0, 0, 0, 1]])
  • no slicing...:

    >>> mtx[2, 3]   
    
    Traceback (most recent call last):
    ...
    TypeError: 'coo_matrix' object ...