scipy.sparse.load_npz#
- scipy.sparse.load_npz(file)[source]#
Load a sparse matrix from a file using
.npz
format.- Parameters
- filestr or file-like object
Either the file name (string) or an open file (file-like object) where the data will be loaded.
- Returns
- resultcsc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix
A sparse matrix containing the loaded data.
- Raises
- OSError
If the input file does not exist or cannot be read.
See also
scipy.sparse.save_npz
Save a sparse matrix to a file using
.npz
format.numpy.load
Load several arrays from a
.npz
archive.
Examples
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.toarray() array([[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.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64)