代码分析Python地图坐标转换

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我是靠谱客的博主奋斗裙子，最近开发中收集的这篇文章主要介绍代码分析Python地图坐标转换，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

最近做项目正好需要坐标的转换

各地图API坐标系统比较与转换;
WGS84坐标系：即地球坐标系，国际上通用的坐标系。设备一般包含GPS芯片或者北斗芯片获取的经纬度为WGS84地理坐标系,
谷歌地图采用的是WGS84地理坐标系（中国范围除外）;
GCJ02坐标系：即火星坐标系，是由中国国家测绘局制订的地理信息系统的坐标系统。由WGS84坐标系经加密后的坐标系。
谷歌中国地图和搜搜中国地图采用的是GCJ02地理坐标系; BD09坐标系：即百度坐标系，GCJ02坐标系经加密后的坐标系;
搜狗坐标系、图吧坐标系等，估计也是在GCJ02基础上加密而成的.

然后在csv中将其转化。

最后再在百度地图API上进行检验成功

#http://bbs.lbsyun.baidu.com/forum.php?mod=viewthread&tid=10923
#代码原地址
import csv
import string
import time
import math

#系数常量
a = 6378245.0
ee = 0.00669342162296594323
x_pi = 3.14159265358979324 * 3000.0 / 180.0;

#转换经度
def transformLat(lat,lon):
 ret = -100.0 + 2.0 * lat + 3.0 * lon + 0.2 * lon * lon + 0.1 * lat * lon +0.2 * math.sqrt(abs(lat))
 ret += (20.0 * math.sin(6.0 * lat * math.pi) + 20.0 * math.sin(2.0 * lat * math.pi)) * 2.0 / 3.0
 ret += (20.0 * math.sin(lon * math.pi) + 40.0 * math.sin(lon / 3.0 * math.pi)) * 2.0 / 3.0
 ret += (160.0 * math.sin(lon / 12.0 * math.pi) + 320 * math.sin(lon * math.pi / 30.0)) * 2.0 / 3.0
 return ret

#转换纬度
def transformLon(lat,lon):
 ret = 300.0 + lat + 2.0 * lon + 0.1 * lat * lat + 0.1 * lat * lon + 0.1 * math.sqrt(abs(lat))
 ret += (20.0 * math.sin(6.0 * lat * math.pi) + 20.0 * math.sin(2.0 * lat * math.pi)) * 2.0 / 3.0
 ret += (20.0 * math.sin(lat * math.pi) + 40.0 * math.sin(lat / 3.0 * math.pi)) * 2.0 / 3.0
 ret += (150.0 * math.sin(lat / 12.0 * math.pi) + 300.0 * math.sin(lat / 30.0 * math.pi)) * 2.0 / 3.0
 return ret

#Wgs transform to gcj
def wgs2gcj(lat,lon):
 dLat = transformLat(lon - 105.0, lat - 35.0)
 dLon = transformLon(lon - 105.0, lat - 35.0)
 radLat = lat / 180.0 * math.pi
 magic = math.sin(radLat)
 magic = 1 - ee * magic * magic
 sqrtMagic = math.sqrt(magic)
 dLat = (dLat * 180.0) / ((a * (1 - ee)) / (magic * sqrtMagic) * math.pi)
 dLon = (dLon * 180.0) / (a / sqrtMagic * math.cos(radLat) * math.pi)
 mgLat = lat + dLat
 mgLon = lon + dLon
 loc=[mgLat,mgLon]
 return loc

#gcj transform to bd2
def gcj2bd(lat,lon):
 x=lon
 y=lat
 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)
 bd_lon = z * math.cos(theta) + 0.0065
 bd_lat = z * math.sin(theta) + 0.006
 bdpoint = [bd_lon,bd_lat]
 return bdpoint

#wgs transform to bd
def wgs2bd(lat,lon):
 wgs_to_gcj = wgs2gcj(lat,lon)
 gcj_to_bd = gcj2bd(wgs_to_gcj[0], wgs_to_gcj[1])
 return gcj_to_bd;

for i in range (3,4):
 n = str('2017.040'+ str(i)+'.csv')
 m = str('2017040' + str(i)+'.csv')
 csvfile = open(m,'w',encoding='UTF-8',newline='')
 nodes = csv.writer(csvfile)
 nodes.writerow(['md5','content','phone','conntime','recitime','lng','lat'])
 l=[]
 with open(n,newline='',encoding='UTF-8') as f:
  reader = csv.DictReader(f)
  for row in reader:
   if row['md5'] == 'md5':
    continue
   else:
    y=float(row['lng'])
    x=float(row['lat'])
    loc=wgs2bd(x,y)
    l.append([row['md5'],row['content'],row['phone'],row['conntime'],row['recitime'],loc[0],loc[1]])
 nodes.writerows(l)
 csvfile.close()

 print("转换成功")