sparse_utils.py 文件源码

def saveSparseHDF5(matrix, prefix, fname):
    """ matrix: sparse matrix
    prefix: prefix of dataset 
    fname : name of h5py file where matrix will be saved
    """
    assert matrix.__class__==csr_matrix or matrix.__class__==csc_matrix,'Expecting csc/csr'
    with h5py.File(fname,mode='a') as f:
        for info in ['data','indices','indptr','shape']:
            key = '%s_%s'%(prefix,info)
            try:
                data = getattr(matrix, info)
            except:
                assert False,'Expecting attribute '+info+' in matrix'
            """
            For empty arrays, data, indicies and indptr will be []
            To deal w/ this use np.nan in its place
            """
            if len(data)==0:
                f.create_dataset(key,data=np.array([np.nan]))
            else:
                f.create_dataset(key,data= data)
        key = prefix+'_type'
        val = matrix.__class__.__name__
        f.attrs[key] = np.string_(val)