最近看了一份人民大学的报告，《中国城市政商关系排行榜2020》，https://new.qq.com/omn/20201230/20201230A0F3MY00.html。
讲的是中国各个城市的政商关系健康指数，决定拿这份报告中的数据，来做一份html的专题图。
效果如下：
一、数据获取
做这份专题图，需要两个数据，一个是各省的边界数据，一个是各省的政商关系健康指数，后者从报告中摘取就行。
前者的参考腾讯地图web api：https://lbs.qq.com/service/webService/webServiceGuide/webServiceDistrict（因为百度没有开放获取省边界数据的接口）。
获取数据python3脚本：
import requests
import time
import shapely
# 获取省code和省name列表
def getAllProvince(key):
url = 'http://apis.map.qq.com/ws/district/v1/list?key='+key
reponse = requests.get(url=url)
reponse.encoding = 'utf-8'
data = reponse.json()
provincelist = []
for r in data['result'][0]:
provincelist.append(r['id']+'\t'+r['name'])
return provincelist
# 获取省围栏
def getProvincePolygon(key,provinceCode):
url = 'https://apis.map.qq.com/ws/district/v1/search?&keyword='+provinceCode+'&key='+key+'&get_polygon=2&max_offset=3000'
print(url)
reponse = requests.get(url=url)
reponse.encoding = 'utf-8'
data = reponse.json()
print(data)
path = data['result'][0][0]['polygon']
polygonlist = []
# 对响应结果进行差分解压，lng lat,lng lat,lng lat|lng lat……格式
for p in path:
print(p)
ringlist = []
pointnum = int(len(p)/2)
for i in range(0,pointnum):
ringlist.append(str(p[i*2])+' '+str(p[i*2+1]))
ringlist.append(ringlist[0])
polygonlist.append('POLYGON(('+','.join(ringlist)+'))')
return polygonlist
key = '你的key'
healthlist = {'北京':86.33,'上海':81.84,'天津':62.73,'海南':51.43,'浙江':49.42,'山东':48.91,
'广东':47.47,'江苏':45,'重庆':44.64,'福建':40.39,'贵州':38.4,'四川':36.74,'安徽':36.52,'广西':34.95,'江西':33.77,
'湖北':31.56,'宁夏':28.82,'湖南':28.03,'辽宁':27.7,'山西':25.73,'内蒙古':25.27,'陕西':23.95,'*':23.94,'甘肃':22.56,'*':21.99,
'青海':21.69,'河北':21.39,'吉林':21.16,'黑龙江':21.08,'河南':20.49,'云南':19.17}
f = open(r'province.txt','a',encoding='utf-8')
f.write('\t'.join(['code','name','health','polygon'])+'\n')
province_list = getAllProvince(key)
for p in province_list:
code,name = p.split('\t')
if healthlist.__contains__(name):
health = healthlist[name]
else:
health = 0.0
time.sleep(1)
polygonlist = getProvincePolygon(key,code)
for pl in polygonlist:
print(pl)
f.write('\t'.join([code,name,str(health),pl])+'\n')
f.close()二、坐标系转换
因为省边界数据是gcj02坐标系的，而百度底图是bd09坐标系的，所以需要将上面获取到的数据转换成bd09坐标系。
坐标系转换脚本CoordinateTransform.py如下：
"""
# wgs84\gcj02\bd09坐标系转换
# wgs84\Pseudo-Mercator投影转换
# bd09\bd09mc投影转换
"""
import math
x_pi = 3.14159265358979324 * 3000.0 / 180.0
pi = 3.1415926535897932384626 # π
a = 6378245.0 # 长半轴
ee = 0.00669342162296594323 # 扁率
#百度墨卡托投影纠正矩阵
LLBAND =[75, 60, 45, 30, 15, 0]
LL2MC = [[-0.0015702102444, 111320.7020616939, 1704480524535203, -10338987376042340, 26112667856603880, -35149669176653700, 26595700718403920, -10725012454188240, 1800819912950474, 82.5],
[0.0008277824516172526, 111320.7020463578, 647795574.6671607, -4082003173.641316, 10774905663.51142, -15171875531.51559, 12053065338.62167, -5124939663.577472, 913311935.9512032, 67.5],
[0.00337398766765, 111320.7020202162, 4481351.045890365, -23393751.19931662, 79682215.47186455, -115964993.2797253, 97236711.15602145, -43661946.33752821, 8477230.501135234, 52.5],
[0.00220636496208, 111320.7020209128, 51751.86112841131, 3796837.749470245, 992013.7397791013, -1221952.21711287, 1340652.697009075, -620943.6990984312, 144416.9293806241, 37.5],
[-0.0003441963504368392, 111320.7020576856, 278.2353980772752, 2485758.690035394, 6070.750963243378, 54821.18345352118, 9540.606633304236, -2710.55326746645, 1405.483844121726, 22.5],
[-0.0003218135878613132, 111320.7020701615, 0.00369383431289, 823725.6402795718, 0.46104986909093, 2351.343141331292, 1.58060784298199, 8.77738589078284, 0.37238884252424, 7.45]]
# 百度墨卡托转回到百度经纬度纠正矩阵
MCBAND = [12890594.86, 8362377.87, 5591021, 3481989.83, 1678043.12, 0]
MC2LL = [[1.410526172116255e-8, 0.00000898305509648872, -1.9939833816331, 200.9824383106796, -187.2403703815547, 91.6087516669843, -23.38765649603339, 2.57121317296198, -0.03801003308653, 17337981.2],
[-7.435856389565537e-9, 0.000008983055097726239, -0.78625201886289, 96.32687599759846, -1.85204757529826, -59.36935905485877, 47.40033549296737, -16.50741931063887, 2.28786674699375, 10260144.86],
[-3.030883460898826e-8, 0.00000898305509983578, 0.30071316287616, 59.74293618442277, 7.357984074871, -25.38371002664745, 13.45380521110908, -3.29883767235584, 0.32710905363475, 6856817.37],
[-1.981981304930552e-8, 0.000008983055099779535, 0.03278182852591, 40.31678527705744, 0.65659298677277, -4.44255534477492, 0.85341911805263, 0.12923347998204, -0.04625736007561, 4482777.06],
[3.09191371068437e-9, 0.000008983055096812155, 0.00006995724062, 23.10934304144901, -0.00023663490511, -0.6321817810242, -0.00663494467273, 0.03430082397953, -0.00466043876332, 2555164.4],
[2.890871144776878e-9, 0.000008983055095805407, -3.068298e-8, 7.47137025468032, -0.00000353937994, -0.02145144861037, -0.00001234426596, 0.00010322952773, -0.00000323890364, 826088.5]]
def gcj02tobd09(lng, lat):
"""
火星坐标系(GCJ02)转百度坐标系(BD09)
:param lng:火星坐标经度
:param lat:火星坐标纬度
:return:
"""
z = math.sqrt(lng * lng + lat * lat) + 0.00002 * math.sin(lat * x_pi)
theta = math.atan2(lat, lng) + 0.000003 * math.cos(lng * x_pi)
bd_lng = z * math.cos(theta) + 0.0065
bd_lat = z * math.sin(theta) + 0.006
return [bd_lng, bd_lat]
def bd09togcj02(bd_lon, bd_lat):
"""
百度坐标系(BD09)转火星坐标系(GCJ02)
:param bd_lat:百度坐标纬度
:param bd_lon:百度坐标经度
:return:转换后的坐标列表形式
"""
x = bd_lon - 0.0065
y = bd_lat - 0.006
z = math.sqrt(x * x + y * y) - 0.00002 * math.sin(y * x_pi)
theta = math.atan2(y, x) - 0.000003 * math.cos(x * x_pi)
gg_lng = z * math.cos(theta)
gg_lat = z * math.sin(theta)
return [gg_lng, gg_lat]
def wgs84togcj02(lng, lat):
"""
WGS84转GCJ02(火星坐标系)
:param lng:WGS84坐标系的经度
:param lat:WGS84坐标系的纬度
:return:
"""
if out_of_china(lng, lat): # 判断是否在国内
return lng, lat
dlat = transformlat(lng - 105.0, lat - 35.0)
dlng = transformlng(lng - 105.0, lat - 35.0)
radlat = lat / 180.0 * pi
magic = math.sin(radlat)
magic = 1 - ee * magic * magic
sqrtmagic = math.sqrt(magic)
dlat = (dlat * 180.0) / ((a * (1 - ee)) / (magic * sqrtmagic) * pi)
dlng = (dlng * 180.0) / (a / sqrtmagic * math.cos(radlat) * pi)
mglat = lat + dlat
mglng = lng + dlng
return [mglng, mglat]
def gcj02towgs84(lng, lat):
"""
GCJ02(火星坐标系)转GPS84
:param lng:火星坐标系的经度
:param lat:火星坐标系纬度
:return:
"""
if out_of_china(lng, lat):
return lng, lat
dlat = transformlat(lng - 105.0, lat - 35.0)
dlng = transformlng(lng - 105.0, lat - 35.0)
radlat = lat / 180.0 * pi
magic = math.sin(radlat)
magic = 1 - ee * magic * magic
sqrtmagic = math.sqrt(magic)
dlat = (dlat * 180.0) / ((a * (1 - ee)) / (magic * sqrtmagic) * pi)
dlng = (dlng * 180.0) / (a / sqrtmagic * math.cos(radlat) * pi)
mglat = lat + dlat
mglng = lng + dlng
return [lng * 2 - mglng, lat * 2 - mglat]
def transformlat(lng, lat):
ret = -100.0 + 2.0 * lng + 3.0 * lat + 0.2 * lat * lat + 0.1 * lng * lat + 0.2 * math.sqrt(math.fabs(lng))
ret += (20.0 * math.sin(6.0 * lng * pi) + 20.0 *math.sin(2.0 * lng * pi)) * 2.0 / 3.0
ret += (20.0 * math.sin(lat * pi) + 40.0 *
math.sin(lat / 3.0 * pi)) * 2.0 / 3.0
ret += (160.0 * math.sin(lat / 12.0 * pi) + 320 *
math.sin(lat * pi / 30.0)) * 2.0 / 3.0
return ret
def transformlng(lng, lat):
ret = 300.0 + lng + 2.0 * lat + 0.1 * lng * lng + 0.1 * lng * lat + 0.1 * math.sqrt(math.fabs(lng))
ret += (20.0 * math.sin(6.0 * lng * pi) + 20.0 *math.sin(2.0 * lng * pi)) * 2.0 / 3.0
ret += (20.0 * math.sin(lng * pi) + 40.0 *math.sin(lng / 3.0 * pi)) * 2.0 / 3.0
ret += (150.0 * math.sin(lng / 12.0 * pi) + 300.0 *math.sin(lng / 30.0 * pi)) * 2.0 / 3.0
return ret
def out_of_china(lng, lat):
"""
判断是否在国内，不在国内不做偏移
:param lng:
:param lat:
:return:
"""
if lng < 72.004 or lng > 137.8347:
return True
if lat < 0.8293 or lat > 55.8271:
return True
return False
def wgs84tomercator(lng,lat):
"""
wgs84投影到墨卡托
:param lng:
:param lat:
:return:
"""
x = lng * 20037508.34 / 180
y = math.log(math.tan((90 + lat) * math.pi / 360)) / (math.pi / 180) * 20037508.34 / 180
return x,y
def mercatortowgs84(x,y):
"""
墨卡托投影坐标转回wgs84
:param x:
:param y:
:return:
"""
lng = x / 20037508.34 * 180
lat = 180 / math.pi * (2 * math.atan(math.exp(y / 20037508.34 * 180 * math.pi / 180)) - math.pi / 2)
return lng,lat
def getRange(cC, cB, T):
if (cB != None):
cC = max(cC, cB)
if (T != None):
cC = min(cC, T)
return cC
def getLoop(cC, cB, T):
while (cC > T):
cC -= T - cB
while (cC < cB):
cC += T - cB
return cC
def convertor(cC, cD):
if (cC==None or cD==None):
print('null')
return None
T = cD[0] + cD[1] * abs(cC.x)
cB = abs(cC.y) / cD[9]
cE = cD[2] + cD[3] * cB + cD[4] * cB * cB +cD[5] * cB * cB * cB + cD[6] * cB * cB * cB * cB +cD[7] * cB * cB * cB * cB * cB +cD[8] * cB * cB * cB * cB * cB * cB
if(cC.x<0):
T=T*-1
else:
T=T
if(cC.y<0):
cE=cE*-1
else:
cE=cE
return [T, cE]
def convertLL2MC(T) :
cD=None
T.x = getLoop(T.x, -180, 180)
T.y = getRange(T.y, -74, 74)
cB = T
for cC in range(0,len(LLBAND),1):
if (cB.y >= LLBAND[cC]) :
cD = LL2MC[cC]
break
if (cD!=None) :
for cC in range(len(LLBAND) - 1,-1,-1):
if (cB.y <= -LLBAND[cC]):
cD = LL2MC[cC]
break
cE = convertor(T, cD)
return cE
def convertMC2LL(cB):
cC=LLT(abs(cB.x),abs(cB.y))
cE=None
for cD in range(0,len(MCBAND),1):
if (cC.y >= MCBAND[cD]) :
cE = MC2LL[cD]
break
T = convertor(cB, cE)
return T
def bd09tomercator(lng,lat):
"""
bd09投影到百度墨卡托
:param lng:
:param lat:
:return:
"""
baidut=LLT(lng,lat)
return convertLL2MC(baidut)
def mercatortobd09(x,y):
"""
墨卡托投影坐标转回bd09
:param x:
:param y:
:return:
"""
baidut=LLT(x,y)
return convertMC2LL(baidut)
class LLT:
def __init__(self,x,y):
self.x=x
self.y=y
if __name__ == '__main__':
print(bd09tomercator(123.0,31.0))
print(mercatortobd09(13692446.35077864, 3610540.161433475))
print(wgs84tomercator(123.0,31.0))
文件坐标系转换脚本如下，需要引用shapely和CoordinateTransform中的个cjtobd09方法：
import shapely
from shapely import wkt
from CoordinateTransform import gcj02tobd09
f = open(r'province.txt','r',encoding='utf-8')
fpovince = open(r'baiduprovince.txt','a',encoding='utf-8')
flines = f.readlines()
for index,line in enumerate(flines):
if index == 0:
continue
try:
linelist = line.strip('\n').split('\t')
code = linelist[0]
name = linelist[1]
health = linelist[2]
polygon = wkt.loads(linelist[3])
points = list(polygon.exterior.coords)
points_bd09 = []
for p in points:
points_bd09.append(gcj02tobd09(p[0], p[1]))
print(points_bd09)
fpovince.write('\t'.join([code,name,health,str(points_bd09)])+'\n')
except BaseException as e:
print(e)
f.close()
fpovince.close()
三、js文件处理
把上一步骤中的baiduprovince.txt文件，处理成能放在html中的js代码。
import math
from collections import defaultdict
f = open(r'baiduprovince.txt','r',encoding='utf-8')
fnew = open(r'baidudatajs.txt','a',encoding='utf-8')
flines = f.readlines()
colors = ['#000000', '#001133', '#002266', '#003399', '#0044cc', '#0055ff', '#3377ff', '#6699ff', '#99bbff', '#ccddff',
'#ffffff']
polygon_dict = defaultdict(list)
for line in flines:
linelist = line.strip('\n').split('\t')
code = linelist[0]
name = linelist[1]
health = float(linelist[2])
color = colors[10-round(float(health)/10)]
polygon = eval(linelist[3])
polygon_dict[code].append({'name':name,'health':health,'color':color,'polygon':polygon})
overlays = []
for r in polygon_dict:
print(r)
print(polygon_dict[r])
for index,p in enumerate(polygon_dict[r]):
polygon_str = 'var polygon_'+r+'_'+str(index)+'=new BMapGL.Polygon(['
point_str_list = []
for po in p['polygon']:
point_str_list.append('new BMapGL.Point('+str(po[0])+','+str(po[1])+')')
polygon_str = polygon_str+','.join(point_str_list)+'],{strokeWeight:0,fillColor:\''+p['color']+'\',fillOpacity: 0.8,health:'+str(p['health'])+',name:\''+p['name']+'\'});'
fnew.write(polygon_str+'\n')
fnew.write('map.addOverlay(polygon_'+r+'_'+str(index)+');'+'\n')
overlays.append('polygon_'+r+'_'+str(index))
fnew.write('var overlays=['+','.join(overlays)+']'+'\n')
f.close()
fnew.close()
四、前端代码
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="utf-8">
<title>各省/直辖市政商关系健康指数</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<meta name="viewport" content="initial-scale=1.0, user-scalable=no">
<meta http-equiv="X-UA-Compatible" content="IE=Edge">
<style>
body,
html,
#container {
overflow: hidden;
width: 100%;
height: 100%;
margin: 0;
font-family: "微软雅黑";
}
#info{
position: absolute;
left: 20px;
top: 20px;
font-size: 14px;
background: #FFF;
width: 270px;
padding: 10px;
border-radius: 3px;
}
</style>
<script src="http://api.map.baidu.com/api?type=webgl&v=1.0&ak=你的ak"></script>
</head>
<body>
<div id="container"></div>
<div id="info">政商关系健康指数：<span id="position"></span></div>
</body>
</html>
<script>
var map = new BMapGL.Map('container');
var point = new BMapGL.Point(112.273486, 35.719192);
map.centerAndZoom(point, 4);
map.enableScrollWheelZoom(true);
----------------------------
baidudatajs.txt里的全部内容
----------------------------
for (let j = 0; j < overlays.length; j++) {
const overlay = overlays[j];
overlay.addEventListener('click', e => {
position.innerHTML = e.target['_config']['name']+'为'+e.target['_config']['health'];
});
}
</script>
五、总结
百度最大的问题在于坐标系不具有通用性。