def _compute_nfps_uniform(cum_counts, sizes):
nfps = np.zeros((len(sizes), len(sizes)))<EOL>for l in range(len(sizes)):<EOL><INDENT>for u in range(l, len(sizes)):<EOL><INDENT>nfps[l, u] = _compute_nfp_uniform(l, u, cum_counts, sizes)<EOL><DEDENT><DEDENT>return nfps<EOL>
Computes the matrix of expected false positives for all possible
    sub-intervals of the complete domain of set sizes, assuming uniform
    distribution of set_sizes within each sub-intervals.

    Args:
        cum_counts: the complete cummulative distribution of set sizes.
        sizes: the complete domain of set sizes.

    Return (np.array): the 2-D array of expected number of false positives
        for every pair of [l, u] interval, where l is axis-0 and u is
        axis-1.