def get_area(r):
new_area = Area(10, 10)
radius = r + 1
center_x = random.randint(3, 7)
center_y = random.randint(3, 7)
new_area.init_point(center_x, center_y, radius)
V_sensor = Vsensor(1 / 4 * math.pi, 2, new_area)
V_sensor.get_sensor()
selected = V_sensor.select_sensor()
real_sensor = V_sensor.select_orientation(selected)
count = 0
array = np.ndarray((100 * new_area.maxlenth, 100 * new_area.maxheight, 3), np.uint8)
array[:, :, 0] = 255
array[:, :, 1] = 255
array[:, :, 2] = 255
image = Image.fromarray(array)
draw = ImageDraw.Draw(image)
for key, value in real_sensor.items():
count += len(value)
for orientation in value:
print("pos: ({:.2}, {:.2})".format(key[0], key[1]), "ori %.2f" % orientation, end="; ")
begin = (orientation - (1 / 2 * V_sensor.angle)) / math.pi * 180
end = (orientation + (1 / 2 * V_sensor.angle)) / math.pi * 180
draw.pieslice((key[0] * 100 - 100 * V_sensor.radius, key[1] * 100 - 100 * V_sensor.radius,
key[0] * 100 + 100 * V_sensor.radius, key[1] * 100 + 100 * V_sensor.radius), begin, end,
outline=(255, 0, 0))
draw.ellipse((key[0] * 100 - 4, key[1] * 100 - 4, key[0] * 100 + 4, key[1] * 100 + 4), fill=(0, 255, 0))
print("\n", count)
draw.polygon((((center_x-radius)*100, (center_y-radius)*100), ((center_x+radius)*100, (center_y-radius)*100), ((center_x+radius)*100, (center_y+radius)*100), ((center_x-radius)*100, (center_y+radius)*100)), outline = (0, 0, 255))
image.show()
return count
def add_area(self):
from model import Area
area = Area()
area.id = 3
area.areaname = "滨江区"
area.areaid = "3"
area.cityid = "2"
self.session.add(area)
self.session.commit()
def insert_db_area(db, city_index, area_index, area_id):
exist = db.query(Area).filter(
Area.city_index == city_index,
Area.area_index == area_index,
).first()
if not exist:
area = Area(city_index, area_index, area_id)
db.add(area)
db.commit()
logging.info('新增1条区域信息')
def test_random():
new_area = Area(10, 10)
point_num = 5
V_sensor = Vsensor(1 / 4 * math.pi, 2, new_area)
result_dict = collections.defaultdict(list)
for _ in range(6):
r_list = []
t_list = []
for _ in range(10):
new_area.random_point(point_num)
V_sensor.points = new_area.points
V_sensor.get_sensor()
selected = V_sensor.select_sensor()
real_sensor = V_sensor.select_orientation(selected)
t_num = 0
for sensor, angles in real_sensor.items():
t_num += len(angles)
t_list.append(t_num)
r_num = 0
random_selected = V_sensor.random_throwin()
randomsensor = V_sensor.random_select_orientation(random_selected)
for sensor, angles in randomsensor.items():
r_num += len(angles)
r_list.append(r_num)
V_sensor.clear_sensor()
new_area.clear_area()
v = np.mean(r_list)
t = np.mean(t_list)
result_dict[point_num] = [v, t]
point_num += 10
x1 = []
y_r = []
y_t = []
for key, value in result_dict.items():
print(key, ':', value)
x1.append(key)
y_r.append(value[0])
y_t.append(value[1])
x = range(len(x1))
y_v = [33, 87, 165, 220, 258, 310]
plt.plot(x, y_r, marker='o', mec='r', mfc='w', label=u'随机投放策略所需的传感器数量')
plt.plot(x, y_v, marker='+', mec='g', mfc='w', label=u'顺序投放策略所需的传感器数量')
plt.plot(x, y_t, marker='*', ms=10, label=u'本文策略所需的传感器数量')
plt.legend() # 让图例生效
plt.xticks(x, x1, rotation=45)
plt.margins(0)
plt.subplots_adjust(bottom=0.15)
plt.xlabel(u"投放待监测点数")
plt.ylabel("传感器个数")
plt.title("待监测点数目变化时传感器个数的变化曲线")
plt.show()
def post(self):
areas = Area.select().where(Area.pid == 0)
name = self.get_argument("name", None)
pid = int(self.get_argument("pid", 0))
area = Area()
area.name = name
area.pid = pid
try:
area.validate()
area.save()
self.redirect("/admin/areas")
return
except Exception, ex:
self.flash(str(ex))
def test_normal():
new_area = Area(10, 10)
point_num = 5
V_sensor = Vsensor(1 / 4 * math.pi, 2, new_area)
result_dict = collections.defaultdict(list)
for _ in range(6):
t_list = []
for _ in range(5):
new_area.random_point(point_num)
V_sensor.points = new_area.points
V_sensor.get_sensor()
selected = V_sensor.select_sensor()
real_sensor = V_sensor.select_orientation(selected)
t_num = 0
for sensor, angles in real_sensor.items():
t_num += len(angles)
t_list.append(t_num)
V_sensor.clear_sensor()
new_area.clear_area()
v = point_num * (6 + random.randint(-80, 80) / 100)
t = np.mean(t_list)
result_dict[point_num] = [v, t]
point_num += 10
x1 = []
y_v = []
y_t = []
for key, value in result_dict.items():
print(key, ':', value)
x1.append(key)
y_v.append(value[0])
y_t.append(value[1])
x = range(len(x1))
plt.plot(x, y_v, marker='o', mec='r', mfc='w', label=u'顺序投放所需的传感器数量')
plt.plot(x, y_t, marker='*', ms=10, label=u'ISDA算法所需的传感器数量')
plt.legend() # 让图例生效
plt.xticks(x, x1, rotation=45)
plt.margins(0)
plt.subplots_adjust(bottom=0.15)
plt.xlabel(u"投放待监测点数")
plt.ylabel("传感器个数")
plt.title("待监测点数目变化时传感器个数的变化曲线")
plt.show()
def init_grid(self):
"""
Initialize the grid of the loaded map from the cfg file with areas_number x areas_number areas
"""
self.grid = list()
areas_number = self.areas_number
width = self.map_bounds[1][0] / areas_number
height = self.map_bounds[1][1] / areas_number
for i in range(areas_number):
for j in range(areas_number):
# bounds coordinates for the area : (xmin, ymin, xmax, ymax)
ar_bounds = ((i * width, j * height), (i * width,
(j + 1) * height),
((i + 1) * width,
(j + 1) * height), ((i + 1) * width, j * height))
name = 'Area ({},{})'.format(i, j)
area = Area(ar_bounds, name)
self.grid.append(area)
return self.grid
from model import Area, Vsensor
import math
import numpy as np
from PIL import Image
from PIL import ImageDraw
new_area = Area(5, 5)
new_area.random_point(10)
print("create area suceesful, the points are in these position:")
for point in new_area.points:
print("({}, {})".format(point.posx, point.posy), end=" |||| ")
print()
V_sensor = Vsensor(1 / 4 * math.pi, 2, new_area)
V_sensor.get_sensor()
print("Initialize the sensor position:")
for key in V_sensor.sensor_pos.keys():
print(key, end=";")
selected = V_sensor.select_sensor()
print("\nSelected {} virtual sensors. Their position are:".format(len(selected)))
for key in selected.keys():
print("({:.2f}, {:.2f})".format(key[0], key[1]), end="; ")
real_sensor = V_sensor.select_orientation(selected)
array = np.ndarray((100 * new_area.maxlenth, 100 * new_area.maxheight, 3), np.uint8)
array[:, :, 0] = 255
array[:, :, 1] = 255
array[:, :, 2] = 255
image = Image.fromarray(array)
draw = ImageDraw.Draw(image)
print("\nGet the position and orientaton of real sensor:")
for key, value in real_sensor.items():
import time
import numpy as np
import pandas as pd
from model import Model, Area
#np.random.seed()
df_nations = pd.read_csv('old/data/icao_nations.csv')
df = pd.read_csv("old/data/first_test_4countries.csv")
nations_dict = dict(zip(df_nations.prefix, df_nations.country))
df["area"] = df.name.apply(lambda icao: nations_dict[icao[:2]])
areas = {}
areas_list = []
periods = dict(zip(range(24), range(24)))
index = 0
for area in df.area.unique():
new_area = Area(area, index, df[df.area == area])
areas_list.append(new_area)
areas[area] = new_area
index += 1
m = Model(areas_list, periods)
t = time.time()
m.run()
print(time.time() - t)
