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Diffstat (limited to 'Code')
| -rw-r--r-- | Code/merge_edges.py | 34 |
1 files changed, 0 insertions, 34 deletions
diff --git a/Code/merge_edges.py b/Code/merge_edges.py index be74ee6..ddd60d4 100644 --- a/Code/merge_edges.py +++ b/Code/merge_edges.py @@ -118,40 +118,6 @@ def compute_time_difference_in_days(t1, t2): return (t1 - t2).days -def make_new_edge(lst_tuple): - lst = sorted(lst_tuple, reverse=True, key = lambda x: abs(float(x[2]))) # sort tuples according to absolute value of score - best_edge = list( lst[0] ) # use the first tuple as a basis edge - - # see section 'Ranking edges using frecency' in the brain documentation - F = len(lst_tuple) - - RN_lst = [] - r_lst = [] - most_recent_edge_date = '00000000' - method_or_tissue = [] - cids = '' - for t in lst: - r_lst.append( abs(float(t[2])) ) - rids = t[4] - if t[5] > cids: - cids = t[5] - RN_lst.append( get_number_of_RNAseq_ids(rids) ) - date = t[7] - if date > most_recent_edge_date: - most_recent_edge_date = date - method_or_tissue.append(t[9]) - S = 365 * 10 - curr_date = datetime.datetime.now().strftime('%Y%m%d') - time_diff = compute_time_difference_in_days(most_recent_edge_date, curr_date) - strength = sum(r_lst)/len(r_lst) * math.log(sum(RN_lst)/len(RN_lst)+1, 10) * math.log(F+1, 2) * math.exp(time_diff/S) - best_edge[4] = '%d' % max(RN_lst) - best_edge[5] = cids - best_edge[7] = most_recent_edge_date - best_edge[8] = '%.2f' % strength - best_edge[9] = ','.join(sorted(list(set(method_or_tissue)))) # unique methods or tissues, in string format - return best_edge - - def get_unique_cids(lst): ''' Return a list of unique, sorted ChIP-seq IDs. ''' cids = [] |