def generate_drug_map(date, type='疫苗'):
data = fetch_drug_date(date, type)
points = []
for country, num in data:
poins.append('1', random.sample(random_points[country], num))
count = [1] * len(data)
addresses = []
json_data = {}
for address in test_data:
json_data[address[0]] = [address[1], address[2]]
addresses.append(address[0])
json_str = json.dumps(json_data, ensure_ascii=False, indent=4)
with open('test_data.json', 'w', encoding='utf-8') as json_file:
json_file.write(json_str)
geo = Geo()
geo.add_schema(maptype='world')
geo.add_coordinate_json(json_file='test_data.json')
geo.add('研发中的{}类药物'.format(type), [list(z) for z in zip(addresses, data)], type_=ChartType.EFFECT_SCATTER, color='#1e90ff',
symbol_size=10, symbol='diamond')
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False), effect_opts=opts.EffectOpts(scale=5))
geo.set_global_opts(title_opts=opts.TitleOpts(title="Geo-EffectScatter"),
tooltip_opts=opts.TooltipOpts(is_show=False))
geo.render(path='3.html')
def plot():
# 初始化图表信息
geo = Geo(init_opts=opts.InitOpts(width="96vw",
height="96vh",
page_title="教育网拓扑图",
animation_opts=opts.AnimationOpts(
animation=False)))
# 添加地图
geo.add_schema(maptype="china")
# 添加所有点的地理信息
geo.add_coordinate_json("./data/data.json")
# 画中间节点
geo.add("Route", [(i, "Route") for i in Nodes_Route],
color="Red",
point_size=4,
symbol_size=4,
effect_opts=opts.EffectOpts(is_show=False))
# 画目的节点
geo.add("Dst", [(i, "Dst") for i in Nodes_Dst],
color="SeaGreen",
point_size=4,
symbol_size=4,
effect_opts=opts.EffectOpts(is_show=False))
# 画线 展示拓扑信息
geo.add("",
list(Trace),
type_=ChartType.LINES,
effect_opts=opts.EffectOpts(is_show=False, symbol_size=2),
linestyle_opts=opts.LineStyleOpts(curve=0.1))
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo.set_global_opts(title_opts=opts.TitleOpts(title="教育网拓扑图"))
# 生成图表到指定文件
geo.render("./dist/render.html")
def generate_geo_png(geodata, geomax, geomin, geotitle, display_id,
map_data_title):
from pyecharts import options as opts
from pyecharts.charts import Map, Geo
from pyecharts.render import make_snapshot
# from pyecharts_snapshot.main import make_a_snapshot
from snapshot_selenium import snapshot
geo = Geo()
geo.add_coordinate_json(
'/home/CitizenScience/backend/backend/geoCoordJson.js')
geo.add_schema(maptype="china")
print(geodata)
print(map_data_title)
geo.add(" ", geodata, symbol_size=10)
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo.set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=geomax, min_=geomin))
figure_url = "/home/CitizenScience/file/visualization/" + str(
display_id) + '_geo.png'
# figure_url = str(display_id) + '_geo.png'
make_snapshot(snapshot, geo.render(), figure_url, 2)
# geo.render(path='render.html')
# cmd = "snapshot render.html png"
# try:
# isRun = os.system(cmd)
# print("截图完成")
# except:
# print("截图失败")
# cmd = "mv output.png ../file/visualization/{}".format(figure_url)
# try:
# isRun = os.system(cmd)
# print("移动完成")
# except:
# print("移动失败")
# make_a_snapshot('geo2.html', 'geo3.png')
return figure_url
class NetworkVisualization(object):
"""
class which show the demand heat map and the allocation network
"""
def __init__(self, data_class, json_file=None):
"""
Initialization the class with data_class and json_file parameters, and add the customized city into Geo class
:param data_class: the data_class
:param json_file:
"""
self.geo = Geo()
self.data_class = data_class
self.json_file = json_file
if self.json_file is not None:
self._load_coordinate_json()
else:
if not hasattr(self.data_class, 'city'):
raise ValueError(
'the city and corresponding longitude and latitude should be included in data_class!'
)
else:
self._load_coordinate()
def _load_coordinate(self):
# add the customized city with the corresponding longitude and latitude
if len(self.data_class.city) != len(self.data_class.longitude):
raise ValueError(
'the length of city and longitude and latitude should be same !'
)
for city, longitude, latitude in zip(self.data_class.city,
self.data_class.longitude,
self.data_class.latitude):
self.geo.add_coordinate(city, longitude, latitude)
def _load_coordinate_json(self):
# add the customized city with the longitude and latitude json file to Geo
# json file contents: { 'city name':[120.123,32.345] }
self.geo.add_coordinate_json(self.json_file)
def heat_map(self, city, demand) -> Geo:
c = (Geo().add_schema(maptype="china").add(
"demand heat map ", [list(z) for z in zip(city, demand)],
type_=ChartType.HEATMAP,
symbol_size=8).set_series_opts(label_opts=opts.LabelOpts(
is_show=False)).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=max(demand) * 1.2),
title_opts=opts.TitleOpts(title="demand heat map "),
))
return c
def net_work_map(self, source_list, cost, destination_list, demand, source,
destination) -> Geo:
"""
output the network map based on the source and destination pair.
:param source_list: the unique source list
:param cost: the cost of source list
:param destination_list: the unique destination list
:param demand: the demand of destination
:param source: the all source point
:param destination: the all destination point
:return:
"""
c = (
Geo().add_schema(maptype="china").add(
"", [z for z in zip(source_list, cost)],
type_=ChartType.SCATTER,
color='green',
symbol_size=5,
symbol="image://..\\icon\\warehouse_1.png").add(
"",
[z for z in zip(destination_list, demand)],
type_=ChartType.SCATTER,
color='black',
symbol_size=5,
# symbol="image://..\\icon\\customer.png"
).add(
"Network",
[list(z) for z in zip(source, destination)],
type_=ChartType.LINES,
symbol=[None, 'arrow'],
symbol_size=3,
effect_opts=opts.EffectOpts(
period=20,
scale=1,
symbol="image://..\\icon\\car.png",
symbol_size=15,
color="blue",
trail_length=0),
linestyle_opts=opts.LineStyleOpts(curve=0.1, opacity=0.3),
).set_series_opts(label_opts=opts.LabelOpts(
is_show=False)).set_global_opts(
title_opts=opts.TitleOpts(title="Allocation Network"),
visualmap_opts=opts.VisualMapOpts(is_piecewise=False,
max_=max(demand),
type_='size',
range_size=[10,
20])))
return c
