pyprophet/stats.py
def summary_err_table(df, qvalues=[0, 0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5]):
    """ Summary error table for some typical q-values """

    qvalues = to_one_dim_array(qvalues)
    # find best matching fows in df for given qvalues:
    ix = find_nearest_matches(np.float32(df.qvalue.values), qvalues)
    # extract sub table
    df_sub = df.iloc[ix].copy()
    # remove duplicate hits, mark them with None / NAN:
    for i_sub, (i0, i1) in enumerate(zip(ix, ix[1:])):
        if i1 == i0:
            df_sub.iloc[i_sub + 1, :] = None
    # attach q values column
    df_sub.qvalue = qvalues
    # remove old index from original df:
    df_sub.reset_index(inplace=True, drop=True)
    return df_sub[['qvalue','pvalue','svalue','pep','fdr','fnr','fpr','tp','tn','fp','fn','cutoff']]
def summary_err_table(df, qvalues=[0, 0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5]):
    """ Summary error table for some typical q-values """

    qvalues = to_one_dim_array(qvalues)
    # find best matching fows in df for given qvalues:
    ix = find_nearest_matches(np.float32(df.qvalue.values), qvalues)
    # extract sub table
    df_sub = df.iloc[ix].copy()
    # remove duplicate hits, mark them with None / NAN:
    for i_sub, (i0, i1) in enumerate(zip(ix, ix[1:])):
        if i1 == i0:
            df_sub.iloc[i_sub + 1, :] = None
    # attach q values column
    df_sub.qvalue = qvalues
    # remove old index from original df:
    df_sub.reset_index(inplace=True, drop=True)
    return df_sub[['qvalue','pvalue','svalue','pep','fdr','fnr','fpr','tp','tn','fp','fn','cutoff']]
Summary error table for some typical q-values