def label_sets_for_nodes(cursor):
"""
Returns <sets_for_nodes> id --> ncRNA family (can be None)
"""
c2.CONN_FUNC = CONN_FUNC
nodes_label = {}
cursor.execute("SELECT i FROM sets_for_nodes")
for r in cursor.fetchall():
print >> sys.stderr, "labeling for node....", r[0]
ncRNA_id, ncRNA_fam = c2.check_hit(r[0])
nodes_label[r[0]] = ncRNA_fam
return nodes_label
def graph_ncRNA_connectivity(clique_pickle=None):
"""
Looks at table:parsed, and for each ncRNA of family F,
calculate the ratio of connected F members/Nones,
and do this for both immediately connected nodes
and path-2 nodes.
"""
c2.CONN_FUNC = CONN_FUNC
ncRNA_map = defaultdict(lambda: []) # fam --> list of <i>s
dum = 0
with CONN_FUNC() as cursor:
cursor.execute("SELECT i FROM sets_for_nodes")
for r in cursor.fetchall():
print >> sys.stderr, "i is....", r[0]
id,fam = c2.check_hit(r[0])
if id is not None:
ncRNA_map[fam].append(id)
dum += 1
if dum > 100: break
for fam,list_of_i in ncRNA_map.iteritems():
get_connectivity(list_of_i, cursor)
clique_stats = defaultdict(lambda: {'sizes':[],'precisions':[]})
ncRNA_id_to_family = {}
hitQ_sizes = []
conn = get_conn_Actino()
cursor = get_dict_cursor(conn)
with open(clique_filename) as f:
QQQ = load(f)
for Q in QQQ:
if 75 in Q or 163 in Q: continue
if len(Q) < 5:
continue
tally_by_family = defaultdict(lambda: 0)
for i in Q:
# if it's not a hit, will return (None,None)
(ncRNA_id, ncRNA_family) = c2.check_hit(i, cursor)
tally_by_family[ncRNA_family] += 1
ncRNA_ids_seen[ncRNA_id] += 1
ncRNA_id_to_family[ncRNA_id] = ncRNA_family
# decide the dominant family of this cluster
tally_by_family = tally_by_family.items()
tally_by_family.sort(key=itemgetter(1))
fam,count = tally_by_family[-1]
if fam is not None:
print("{0}\t{1}/{2}".format(fam,count,len(Q)))
hitQ_sizes.append(len(Q))
clique_stats[fam]['sizes'].append(len(Q))
clique_stats[fam]['precisions'].append(count*1./len(Q))
# now print the stats
print('####################### stats #########################')
