sparse._matrix_io

Module Contents

Functions

save_npz(file,matrix,compressed=True) Save a sparse matrix to a file using .npz format.
load_npz(file) Load a sparse matrix from a file using .npz format.
save_npz(file, matrix, compressed=True)

Save a sparse matrix to a file using .npz format.

file : str or file-like object
Either the file name (string) or an open file (file-like object) where the data will be saved. If file is a string, the .npz extension will be appended to the file name if it is not already there.
matrix: spmatrix (format: csc, csr, bsr, dia or coo``)
The sparse matrix to save.
compressed : bool, optional
Allow compressing the file. Default: True

scipy.sparse.load_npz: Load a sparse matrix from a file using .npz format. numpy.savez: Save several arrays into a .npz archive. numpy.savez_compressed : Save several arrays into a compressed .npz archive.

Store sparse matrix to disk, and load it again:

>>> import scipy.sparse
>>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
   with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)
>>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
>>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')
>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
   with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)
load_npz(file)

Load a sparse matrix from a file using .npz format.

file : str or file-like object
Either the file name (string) or an open file (file-like object) where the data will be loaded.
result : csc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix
A sparse matrix containing the loaded data.
IOError
If the input file does not exist or cannot be read.

scipy.sparse.save_npz: Save a sparse matrix to a file using .npz format. numpy.load: Load several arrays from a .npz archive.

Store sparse matrix to disk, and load it again:

>>> import scipy.sparse
>>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
   with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)
>>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
>>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')
>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
    with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)