def get_events_for_view(self, top_right, bottom_left):
self.cur.execute("SELECT DISTINCT * FROM Venues WHERE VenueLatitude < ? AND VenueLongitude < ? AND VenueLatitude > ? "
"AND VenueLongitude > ?", (top_right["latitude"], top_right["longitude"],
bottom_left["latitude"], bottom_left["longitude"]))
venues_in_sight = self.cur.fetchall()
events_instance = Event()
for venue in venues_in_sight:
self.cur.execute("SELECT * FROM Events WHERE VenueId = ?", (venue[0],))
events = self.cur.fetchall()
events = events[0]
#for event in events:
self.cur.execute("SELECT * FROM Categories WHERE CategoryId = ?", (events[1],))
category = self.cur.fetchall()
events_instance.add_event(events, venue, category)
return events_instance
def run(self):
self.event_instance = self.data_manager.get_events_for_view(self.top_right, self.bottom_left)
train_and_test = self.divide_events_into_train_test()
training_data_array = np.array(self.event_instance.get_train_list(train_and_test["training_labels"]))
training_target_array = np.array(self.event_instance.get_target_list(train_and_test["training_labels"]))
testing_array = np.array(self.event_instance.get_test_list(train_and_test["testing_labels"]))
testing_target = np.array(self.event_instance.get_target_list(train_and_test["testing_labels"]))
#knn = neighbors.KNeighborsClassifier(10)
#knn.fit(training_data_array, training_target_array)
#testing_target = knn.predict(testing_array)
data_points = np.concatenate((training_data_array, testing_array))
targets = np.concatenate((training_target_array, testing_target))
knn = neighbors.KNeighborsClassifier(12)
knn.fit(data_points, targets)
targets = knn.predict(data_points)
targets_map = list()
target_index = 0
for target in np.unique(targets):
targets_map.append((target, target_index, Event.get_category_color(target)))
target_index += 1
result = []
result.append([[t, c] for (t, i, c) in targets_map])
dp = list()
#df = file("datapoints.csv", "w")
for i in range(len(data_points)):
# df.write(str(data_points[i][0])+","+str(data_points[i][1])+","+str(targets_map[targets[i]][0])+"\n")
index = [index for (t, index, c) in targets_map if t == targets[i]]
dp.append([data_points[i][0], data_points[i][1], index[0]])
result.append(dp)
return result
def setUp(self):
self.event = Event(
id=249792023,
name="January Event",
time=1527344911000,
status="upcoming",
rsvp_limit=40,
waitlist_count=10,
yes_rsvp_count=40,
announced=True,
event_url=
"https://www.example.com/Stockholm-Roleplaying-Guild/events/249792023/",
venue={"name": "STORG Clubhouse"})
self.member = Member(name="Dave", meetup_id=100001, slack_id="u19292")
self.table = GameTable(number=1,
title="Awesome Game",
blurb="Long text goes here",
max_players=4,
players=["Dave", "John", "Jane"],
gm="Doe",
system="D&D")
self.rsvp = Rsvp(venue="STORG Clubhouse",
response="yes",
answers=["My email is [email protected]"],
member={
"member_id": 100001,
"name": "Dave"
})
def check_circle_event(self, i):
if (i.e is not None) and (i.e.x != self.x0):
i.e.valid = False
i.e = None
if (i.pprev is None) or (i.pnext is None): return
flag, x, o = self.circle(i.pprev.p, i.p, i.pnext.p)
if flag and (x > self.x0):
i.e = Event(x, o, i)
self.event.push(i.e)
