def assign(filename, date, time_l, time_r, m, L, pb, pc, cr, cb):
dat = order_filter.filter_time(filename, date, time_l, time_r)
dest_dat = csvreader.csv_reader_no_headers('../data/destination.csv')
departure_dat = csvreader.csv_reader_no_headers('../data/departure.csv')
coordinates = [[float(departure_dat[0][0]), float(departure_dat[0][1])]]
for line in dest_dat:
coordinates.append([float(line[0]), float(line[1])])
for line in coordinates:
line[0] *= lon_km
line[1] *= lat_km
k = len(coordinates)
dest = []
for line in dat:
departure_longitude = float(line[3]) * lon_km
departure_latitude = float(line[4]) * lat_km
dest_longitude = float(line[5]) * lon_km
dest_latitude = float(line[6]) * lat_km
if (departure_longitude - coordinates[0][0]) ** 2 + (departure_latitude - coordinates[0][1]) ** 2 > departure_radius ** 2:
continue
min_dis, pos = 1e20, 0
for j in range(1, k):
cur_dis = (dest_longitude - coordinates[j][0]) ** 2 + (dest_latitude - coordinates[j][1]) ** 2
if cur_dis < min_dis:
min_dis, pos = cur_dis, j
dest.append(pos)
n = len(dest)
datahelper.dump_json('../data/order_data.json', n, m, k, L, dest, coordinates, pb, pc, cr, cb)
def filter_day(filename):
dat = csvreader.csv_reader_no_headers(filename)
out_dat = []
for line in dat:
s = timestamp_datetime(int(line[1]))
s = s[11:]
if s2 <= s <= s1:
out_dat.append(line)
return out_dat
def filter_time(filename, date, sl, sr):
dat = csvreader.csv_reader_no_headers(filename)
out_dat = []
for line in dat:
s = timestamp_datetime(int(line[1]))
dat = s[:10]
tm = s[11:]
if sl <= tm <= sr and dat == date:
out_dat.append(line)
return out_dat
import csvreader
import json
import numpy as np
import time
from urllib.request import urlopen
if __name__ == '__main__':
dest_dat = csvreader.csv_reader_no_headers('../data/destination.csv')
departure_dat = csvreader.csv_reader_no_headers('../data/departure.csv')
ak = '??????????????????' # Please fill in your AK code
coordinates = [[float(departure_dat[0][0]), float(departure_dat[0][1])]]
for line in dest_dat:
coordinates.append([float(line[0]), float(line[1])])
K = len(coordinates)
new_coordinates = []
dist = np.zeros((K, K))
for i in range(K):
for j in range(K):
print(i, j)
if i == j:
dist[i][j] = 0
else:
uri = 'http://api.map.baidu.com/routematrix/v2/driving?output=json&origins=' + str(coordinates[i][1]) + ',' + \
def selection(re):
dest_cnt = {}
hotel_cnt = {}
dat = order_filter.filter_night(
'../../CS214-CourseData/Projects/data/haikou_order/order_20171011_20171014.csv'
)
departure_dat = csvreader.csv_reader_no_headers('../data/departure.csv')
departure = [float(departure_dat[0][0]), float(departure_dat[0][1])]
hotel_dat = csvreader.csv_reader_no_headers(
'../data/hotel_address_lat_lng.csv')
# Analyze order destination.
for line in dat:
dest_longitude = float(line[5])
dest_latitude = float(line[6])
dest_brick_lon = int(dest_longitude * 500)
dest_brick_lat = int(dest_latitude * 500)
index = str(dest_brick_lon) + '.' + str(dest_brick_lat)
if dest_cnt.get(index) is None:
dest_cnt[index] = 1
else:
dest_cnt[index] += 1
# Analyze hotel data
valid_cnt = 0
for line in hotel_dat:
hotel_lat = float(line[0])
hotel_lon = float(line[1])
if hotel_lon < 109.4 or hotel_lon > 110.82 or hotel_lat < 19.6 or hotel_lat > 20.05:
continue
valid_cnt += 1
hotel_brick_lon = int(hotel_lon * 500)
hotel_brick_lat = int(hotel_lat * 500)
index = str(hotel_brick_lon) + '.' + str(hotel_brick_lat)
if hotel_cnt.get(index) is None:
hotel_cnt[index] = 1
else:
hotel_cnt[index] += 1
# Combine
cnt = {}
for key in dest_cnt.keys():
res = dest_cnt[key]
if res >= 50:
res = 50
cnt[key] = beta_d * res / 50
for key in hotel_cnt.keys():
if cnt.get(key) is None:
cnt[key] = beta_h / (1 + math.exp(-hotel_cnt[key]))
else:
cnt[key] += beta_h / (1 + math.exp(-hotel_cnt[key]))
dest = []
for key in cnt.keys():
brick_lon, brick_lat = key.split('.')
dest.append([cnt[key], int(brick_lon), int(brick_lat)])
dest.sort()
pre_final_list = []
for item in dest:
if re and (lon_km * (departure[0] - item[1] / 500.0))**2 + (
lat_km *
(departure[1] - item[2] / 500.0))**2 <= departure_radius**2:
continue
if item[0] >= 0.6:
pre_final_list.append([item[1], item[2]])
print('longitude =', item[1] / 500.0, 'latitude =',
item[2] / 500.0, 'count =', item[0])
min_arg = [54700, 9800]
max_arg = [55410, 10025]
center, _ = kmeans.kmeans(K, 2, min_arg, max_arg, pre_final_list)
dest_lon = []
dest_lat = []
with open('../data/destination.csv', 'w', newline='') as out:
csv_write = csv.writer(out, dialect='excel')
for item in center:
print(item[0] / 500.0, item[1] / 500.0)
dest_lon.append(item[0] / 500.0)
dest_lat.append(item[1] / 500.0)
csv_write.writerow([item[0] / 500.0, item[1] / 500.0])
print('total', len(dest_lon), 'possible destinations.')
plt.plot(dest_lon, dest_lat, 'o', markersize=2)
plt.savefig('../data/destination.pdf', dpi=300)
plt.show()