parse_csr_matrix
- pyhelpers.ops.parse_csr_matrix(path_to_csr, verbose=False, **kwargs)
Load in a compressed sparse row (CSR) or compressed row storage (CRS).
- Parameters
path_to_csr (str) – path where a CSR file (e.g. with a file extension “.npz”) is saved
verbose (bool or int) – whether to print relevant information in console as the function runs, defaults to
False
kwargs – [optional] parameters of numpy.load
- Returns
a compressed sparse row
- Return type
scipy.sparse.csr.csr_matrix
Examples:
>>> from pyhelpers.ops import parse_csr_matrix >>> from pyhelpers.dirs import cd >>> from scipy.sparse import csr_matrix, save_npz >>> data_ = [1, 2, 3, 4, 5, 6] >>> indices_ = [0, 2, 2, 0, 1, 2] >>> indptr_ = [0, 2, 3, 6] >>> csr_m = csr_matrix((data_, indices_, indptr_), shape=(3, 3)) >>> csr_m <3x3 sparse matrix of type '<class 'numpy.int32'>' with 6 stored elements in Compressed Sparse Row format> >>> path_to_csr_npz = cd("tests\data", "csr_mat.npz") >>> save_npz(path_to_csr_npz, csr_m) >>> parsed_csr_mat = parse_csr_matrix(path_to_csr_npz, verbose=True) Loading "\tests\data\csr_mat.npz" ... Done. >>> # .nnz gets the count of explicitly-stored values (non-zeros) >>> (parsed_csr_mat != csr_m).count_nonzero() == 0 True >>> (parsed_csr_mat != csr_m).nnz == 0 True