populating a scipy sparse DOK matrix

scipy_sparse_array_builder.py

def str2num(t):
    return ( int(t[0]), float(t[1]) )
 
 
def parse_line(line):
    '''
    returns:
    (i) score (scalar);
    (ii) adjacency dict (one row in sparse 2D array)
    pass in:
    '''
    S, tx = line.split(maxsplit=1)
    tx = ( line.strip().split(':') for line in tx.split() )
    return S, {k:v for k, v in map(str2num, tx)}
 
 
def file_opener(data_file):
    '''
    returns:
    pass in: data_file as str, relative path from 'User' dir
    '''
    dfile = os.path.expanduser(data_file)
    with open(dfile, 'r', encoding='utf-8') as fh:
    d = (line for line in fh.readlines())
    d = (parse_line(line) for line in d)
    d = list(d)
    return d
 
 
def data2sparse_array(data):
    from scipy.sparse import dok as DOK
    max_key_val = 0
    for i in range(len(data)):
        k = max(data[i][1].keys())
        if k > max_key_val:
        max_key_val = k
    ncols = max_key_val
    nrows = len(data)
    D = DOK((nrows, ncols), dtype=float)
    S = NP.empty((nrows, 1))
    for i in range(nrows):
        s, adict = d[i]
        S[i] = s
    for j in range(ncols):
        D[i,j] = adict.get(j)