def ewide4(request):
# gauge = Gauge("仪表盘示例")
# gauge.add("业务指标", "完成率", 66.66)
# gauge.show_config()
template = loader.get_template('ewpyecharts.html')
data = [
('北京', 28), ('天津', 29), ('石家庄', 29), ('太原', 34), ('呼和浩特', 27), ('哈尔滨', 31), ('长春', 29), ('沈阳', 30), ('上海', 40),
('合肥', 40), ('南京', 40), ('济南', 35), ('青岛', 33), ('杭州', 40), ('福州', 37), ('厦门', 34), ('南昌', 39), ('武汉', 38),
('长沙', 39),
('郑州', 37), ('南宁', 36), ('广州', 33), ('深圳', 28), ('珠海', 30), ('海口', 30), ('三亚', 31), ('西安', 39), ('兰州', 32),
('乌鲁木齐', 31),
('西宁', 27), ('银川', 30), ('成都', 32), ('重庆', 38), ('贵阳', 29), ('昆明', 22), ('拉萨', 23), ('香港', 30), ('澳门', 30), ]
#
# geo = Geo("7月23日全国主要城市最高气温", "数据源自中国天气网", title_color="#000000", title_pos="center",
# width=1200, height=600, background_color='#FFFFFF')
# attr, value = geo.cast(data)
# geo.add("", attr, value, visual_range=[20, 40], visual_text_color="#000000", symbol_size=15, is_visualmap=True)
# geo.show_config()
geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff",
title_pos="center", width=1200,
height=600, background_color='#404a59')
attr, value = geo.cast(data)
geo.add("", attr, value, type="heatmap", is_visualmap=True, visual_range=[0, 300],
visual_text_color='#fff')
# data = [
# ('汕头市', 50), ('汕尾市', 60), ('揭阳市', 35),
# ('阳江市', 44), ('肇庆市', 72)
# ]
# geo = Geo("广东城市空气质量", "data from pm2.5", title_color="#fff",
# title_pos="center", width=1200,
# height=600, background_color='#404a59')
# attr, value = geo.cast(data)
# geo.add("", attr, value, maptype='广东', type="effectScatter",
# is_random=True, effect_scale=5, is_legend_show=False)
# # geo.show_config()
context = dict(
myechart=geo.render_embed(),
host=REMOTE_HOST,
script_list=geo.get_js_dependencies()
)
return HttpResponse(template.render(context, request))
class PlotGeo:
def __init__(self):
self.data = {{'label': []}, }
self.titles = ['全国销售情势图', 'data from sale']
self.indexes = []
self.geo = Geo()
self.script_list = self.geo.get_js_dependencies()
def plot_geo(self, dat, tit, ind):
self.data = dat
self.titles = tit
self.indexes = ind
self.geo = Geo(self.titles[0], self.titles[1],
title_pos='center', title_color='#fff',
width=1200, height=600, background_color='#404a59')
for label in self.data.keys():
self.geo.add(label, self.indexes, self.data[label],
visual_range=[0, 200], visual_text_color='#fff',
symbol_size=15, is_visualmap=True)
return self.geo.render_embed()
def geo_echarts(request):
if not request.session.get('is_login', None):
# 如果本来就未登录，也就没有登出一说
return redirect("/login/")
if request.method == 'GET':
ptime = request.GET.get('time')
ptype = request.GET.get('type')
phour = request.GET.get('hour')
client = pymongo.MongoClient('localhost', 27017)
db = client['earthquake']
col = db['geo_' + ptime]
lon = []
lat = []
value = []
cities = []
print(col.count())
for item in col.find():
if item['index'] < int(phour):
lon.append(item['lon'])
lat.append(item['lat'])
cities.append(item['city'])
value.append(item['value'])
style = Style(title_color="#fff",
title_pos="center",
width=1000,
height=800,
background_color="#404a59")
df_dic = {'lon': lon, 'lat': lat, 'city': cities, 'value': value}
df = pd.DataFrame(df_dic)
print(df)
attr = list(df['city'])
value = list(df['value'])
geo_coords = {
df.iloc[i]['city']: [df.iloc[i]['lat'], df.iloc[i]['lon']]
for i in range(len(df))
}
if ptype == "0":
# normal
total_geo = Geo(ptime + '地震' + str(phour) + '小时内分布图',
**style.init_style)
total_geo.add("",
attr,
value,
visual_range=[1, 10],
symbol_size=5,
visual_text_color="#fff",
is_visualmap=True,
maptype='china',
visual_split_number=10,
geo_cities_coords=geo_coords)
elif ptype == "1":
# heatmap
total_geo = Geo(ptime + '地震' + str(phour) + '小时内热力分布图',
**style.init_style)
total_geo.add("",
attr,
value,
visual_range=[1, 10],
symbol_size=5,
visual_text_color="#fff",
type="heatmap",
is_visualmap=True,
maptype='china',
visual_split_number=10,
geo_cities_coords=geo_coords)
context = dict(myechart=total_geo.render_embed(),
host=REMOTE_HOST,
script_list=total_geo.get_js_dependencies())
return render(request, "function/echart_base.html", context)
def geographical_distribution(self, time):
dir_name = time[0:4] + time[5:7] + time[8:10]
lon, lat, doc, tag, content, ttime, cities = self.load_doc(time)
SI_value = []
for item, tag in zip(doc, tag):
SI_value.append(self.SI.SI_content_2(item, tag))
vs = SI_value.copy()
vs.sort()
minSI = vs[0]
vs.sort(reverse=True)
maxSI = vs[0]
print(SI_value)
print('max-', maxSI, 'min- ', minSI)
for i in range(len(SI_value)):
if SI_value[i] > 12:
SI_value[i] = 12
else:
SI_value[i] = 10*(SI_value[i]-minSI)/(12-minSI)
if len(lon) > 7000:
wlon = []
wlat = []
wttime = []
wcities = []
wSI_value = []
for ilon, ilat, ittime, icities, ivalue in zip(lon, lat, ttime, cities, SI_value):
if ivalue > 1.5:
wlon.append(ilon)
wlat.append(ilat)
wttime.append(ittime)
wcities.append(icities)
wSI_value.append(ivalue)
lon = wlon
lat = wlat
ttime = wttime
cities = wcities
SI_value = wSI_value
df_dic = {'lon': lon, 'lat': lat, 'time': ttime, 'city': cities, 'value': SI_value}
df = pd.DataFrame(df_dic)
print(df)
geo_coords = {df.iloc[i]['city']: [df.iloc[i]['lat'], df.iloc[i]['lon']] for i in range(len(df))}
attr = list(df['city'])
value = list(df['value'])
vrange = [0, 0, 0, 0, 0]
for i in range(len(df)):
if df.iloc[i]['value'] > 8:
vrange[0] += 1
elif df.iloc[i]['value'] > 6:
vrange[1] += 1
elif df.iloc[i]['value'] > 4:
vrange[2] += 1
elif df.iloc[i]['value'] > 2:
vrange[3] += 1
else:
vrange[4] += 1
print('percentage:')
for item in vrange:
print(item/len(df)*100, '%')
if self.outputDB.find_one({'name': self.tableName}):
self.outputDB.update_one({'name': self.tableName}, {'$set': {
'time': time,
'SI-V': vrange[0]/len(df),
'SI-IV': vrange[1]/len(df),
'SI-III': vrange[2]/len(df),
'SI-II': vrange[3]/len(df),
'SI-I': vrange[4]/len(df),
}})
else:
self.outputDB.insert_one({'name': self.tableName,
'time': time,
'SI-V': vrange[0]/len(df),
'SI-IV': vrange[1]/len(df),
'SI-III': vrange[2]/len(df),
'SI-II': vrange[3]/len(df),
'SI-I': vrange[4]/len(df),
})
if not os.path.exists(dir_name + '/'):
print("make new dir")
os.makedirs(dir_name + '/')
style = Style(title_color="#fff", title_pos="center",
width=800, height=800, background_color="#404a59")
total_geo = Geo('总体分布图', **style.init_style)
total_geo.add("", attr, value, visual_range=[1, 10], symbol_size=5,
visual_text_color="#fff",
is_visualmap=True, maptype='china', visual_split_number=10,
geo_cities_coords=geo_coords)
total_geo.render(dir_name + '/' + dir_name+'_all.html')
# heatmap
htotal_geo = Geo('总体热力分布图', **style.init_style)
htotal_geo.add("", attr, value, visual_range=[1, 10], symbol_size=5,
visual_text_color="#fff", type="heatmap",
is_visualmap=True, maptype='china', visual_split_number=10,
geo_cities_coords=geo_coords)
arg = htotal_geo.get_js_dependencies()
htotal_geo.render(dir_name + '/' + dir_name + '_allH.html')
start_time = datetime.strptime(time, "%Y-%m-%d %H:%M:%S")
current_time = start_time
timeIndex = []
timeDoc = []
for i in range(7):
current_time = current_time + timedelta(hours=1)
timeIndex.append(current_time)
timeDoc.append([])
for ilon, ilat, ittime, icities, ivalue in zip(lon, lat, ttime, cities, SI_value):
for i in range(7):
if i == 6 or ittime < timeIndex[i+1]:
timeDoc[i].append([ilon, ilat, ittime, icities, ivalue])
for i in range(6):
print("in hour ", i, 'has', len(timeDoc[i]))
tlon = []
tlat = []
tttime = []
tcities = []
tvalue = []
for sdoc in timeDoc[i]:
tlon.append(sdoc[0])
tlat.append(sdoc[1])
tttime.append(sdoc[2])
tcities.append(sdoc[3])
tvalue.append(sdoc[4])
tdf_dic = {'lon': tlon, 'lat': tlat, 'time': tttime, 'city': tcities, 'value': tvalue}
tdf = pd.DataFrame(tdf_dic)
tgeo_coords = {tdf.iloc[i]['city']: [tdf.iloc[i]['lat'], tdf.iloc[i]['lon']] for i in range(len(tdf))}
tattr = list(tdf['city'])
tvalue = list(tdf['value'])
tgeo = Geo(str(i+1) + '小时内分布图', **style.init_style)
tgeo.add("", tattr, tvalue, visual_range=[5, 10], symbol_size=3,
visual_text_color="#fff",
is_visualmap=True, maptype='china', visual_split_number=10,
geo_cities_coords=tgeo_coords)
tgeo.render(dir_name + '/ ' + dir_name + str(i+1) + 'h.html')
# heatmap
htgeo = Geo(str(i + 1) + '小时内热力分布图', **style.init_style)
htgeo.add("", tattr, tvalue, visual_range=[5, 10], symbol_size=3,
visual_text_color="#fff", type='heatmap',
is_visualmap=True, maptype='china', visual_split_number=10,
geo_cities_coords=tgeo_coords)
htgeo.render(dir_name + '/ ' + dir_name + str(i + 1) + 'H.html')
