def score_edges_within_pevents(allevents, historyScores, totalp, prev_error=0.05, ignore_cn=True):
prevalence_error = prev_error
sys.stderr.write("number of events: %d\n" % (len(allevents)))
alledges = []
for event in allevents:
event.unpack()
# if event.segs == []:
# event.make_segs_from_str()
for seg in event.segs:
edge = copy.deepcopy(event)
edge.segs = [seg]
edge.make_segstr()
if ignore_cn:
(mysegstr, sign) = histseg.remove_signs_from_segstr(edge.segstr)
edge.segstr = "+/" + mysegstr
if sign == "-":
edge.cnval = -1 * event.cnval
alledges.append(edge)
# sys.stderr.write("number of edges is: %d\n" % (len(alledges)))
sortededges = sorted(alledges, key=lambda x: (x.segstr, x.cnval))
if ignore_cn:
unique_edges = unique_loc_edges(sortededges)
else:
unique_edges = unique_c_edges(sortededges)
sys.stderr.write("totalp: %s\n" % (str(totalp)))
for edge in unique_edges:
edge.update(historyScores)
edge.likelihood = histseg.compute_likelihood_histories(edge.histories, historyScores, totalp)
edge.trim()
return unique_edges
def __init__(self, edge): self.edge=edge self.isTrue=0 # this will be 0 if edge is FP, 1 if TP, 2 if TN, -1 if FN self.refindex=-1 self.refpreval=-1 self.reforder=-1 self.avecost=-1 self.type=edge.determineEventType() (self.segstr, self.sign)=histseg.remove_signs_from_segstr(edge.segstr) self.cnval=edge.cnval*self.sign
