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from collections import Counter | |
import glob | |
def reduce_model_dict(dict): | |
for key, val in dict.items(): | |
used = [] | |
for key2, val2 in val.items(): | |
new = [] | |
for i in val2: | |
if i not in used: | |
new.append(i) | |
used.append(i) | |
val[key2] = new | |
return dict | |
def which_model(position): | |
models_dict = {} | |
x = 1 | |
for i, j in zip(range(1400, 27000, 200), range(1, 27000, 200)): | |
if position <= i and position >= j: | |
models_dict[x] = position | |
x += 1 | |
return models_dict | |
def modelCount(path_to_models): | |
count_list = [] | |
for file in list(path_to_models.glob("*")): | |
protein_id = str(file).split('-')[1] | |
count_list.append(protein_id) | |
count_dict = Counter(count_list) | |
count_dict = {';'.join(sorted(k for k in count_dict.keys() if count_dict[k] == v)): v for v in | |
set(count_dict.values())} | |
return count_dict |