def main():
getParams()
x = 1
allLog = SortedSet()
errorNo = 0
for line in theOpenFile:
if line.startswith("#"):
continue
if line.startswith("result, logSet"):
continue
if len(line) > 20:
x += 1
if x % 10000 == 0:
print(f'{int(x / 1000):,}')
try:
p: PositionTesterLogItem = PositionTesterLogItem(line, 1)
if not allLog.__contains__(p):
allLog.add(p)
else:
t4 = 1
except Exception as e:
print(f'error {errorNo}:{e}')
errorNo += 1
theOpenFile.close()
agList = []
# remove duplicates
# for each position id,
# remove duplicates
# build a list of (positionId, number of networks that found it, sum of all agrees all nets)
for k in range(1, 200000):
l = list(allLog.irange_key(k, k))
if len(l) > 0:
# if your going to save the entire list or compare other features then do a clean up.
for item in l:
agList.append((k, enu.count(), enu.sum(lambda x: x.agree)))
print(agList[-1])
with open('ur frequencyEasy20k.csv', 'w') as out:
csv_out = csv.writer(out)
csv_out.writerow(['positionID', 'count', 'agree'])
for row in agList:
csv_out.writerow(row)
groups = Enumerable(agList).group_by(key_names=['id', 'count', 'agree'], key=lambda x: x[2])
countList = []
for g in groups:
countList.append((g.count(), g.first()[2]))
with open('countlist.csv', 'w') as out:
csv_out = csv.writer(out)
csv_out.writerow(['howManyPositions', 'AgreeCount'])
for row in countList:
csv_out.writerow(row)
tmp55 = 1
def astar(stare_initiala, stare_finala, euristica, lista_chei):
nod_initial = Nod(stare_initiala, None, None)
deschise = SortedSet([nod_initial])
scor_optim = SortedDict({tuple(stare_initiala): 0})
# [1, 1, 1, 1, 1]
# (1, 1, 1, 1, 1)
while len(deschise) > 0:
# extragem nodul cu f minim
nod = deschise[0]
deschise.pop(0)
# daca am ajuns la starea finala, ne oprim
if nod.stare == stare_finala:
return nod
# generam succesorii si facem verificari
lista_succesori = genereaza_succesori(nod, lista_chei, euristica)
for succesor in lista_succesori:
if scor_optim.__contains__(tuple(succesor.stare)) == False:
# daca starea succesorului nu a mai fost intalnita pana acum, o inseram
scor_optim[tuple(succesor.stare)] = succesor.g
deschise.add(succesor)
elif succesor.g < scor_optim[tuple(succesor.stare)]:
# introducem/editam starea curenta in setul "deschis", dupa caz
succesor_fals = Nod(succesor.stare, None, None)
succesor_fals.f = scor_optim[tuple(
succesor.stare)] + euristica(succesor.stare)
if deschise.__contains__(succesor_fals) is True:
deschise.discard(succesor)
deschise.add(succesor)
# daca starea curenta este intalnita cu un cost mai mic, o reactualizam
scor_optim[tuple(succesor.stare)] = succesor.g
return None
