[python]wgs84转为gcj02坐标

[python]wgs84转为gcj02坐标#!/usr/bin/python
# -*- coding: UTF-8 -*-
import math
import pandas as pd
EE = 0.00669342162296594323
EARTH_RADIUS = 6378.137 #地球近似半径(km)
M_PI = math.pi
def transformLat( x, y) :
ret = -100.0 + 2.0 * x + 3.0 * y + 0.2 * y * y + 0.1 * x * y + 0.2 * math.sqrt(math.fabs(x));
ret += (20.0 * math.sin(6.0 * x * M_PI) + 20.0 * math.sin(2.0 * x * M_PI)) * 2.0 / 3.0;
ret += (20.0 * math.sin(y * M_PI) + 40.0 * math.sin(y / 3.0 * M_PI)) * 2.0 / 3.0;
ret += (160.0 * math.sin(y / 12.0 * M_PI) + 320 * math.sin(y * M_PI / 30.0)) * 2.0 / 3.0;
return ret;
def transformLon( x, y) :
ret = 300.0 + x + 2.0 * y + 0.1 * x * x + 0.1 * x * y + 0.1 * math.sqrt(math.fabs(x));
ret += (20.0 * math.sin(6.0 * x * M_PI) + 20.0 * math.sin(2.0 * x * M_PI)) * 2.0 / 3.0;
ret += (20.0 * math.sin(x * M_PI) + 40.0 * math.sin(x / 3.0 * M_PI)) * 2.0 / 3.0;
ret += (150.0 * math.sin(x / 12.0 * M_PI) + 300.0 * math.sin(x / 30.0 * M_PI)) * 2.0 / 3.0;
return ret;
def Wgs84ToGcj02(lon, lat) :
dLat = transformLat(lon - 105.0, lat - 35.0);
dLon = transformLon(lon - 105.0, lat - 35.0);
radLat = lat / 180.0 * M_PI;
magic = math.sin(radLat);
magic = 1 - magic * magic * EE;
sqrtMagic = math.sqrt(magic);
dLat = (dLat * 180.0) / ((EARTH_RADIUS * 1000 * (1 - EE)) / (magic * sqrtMagic) * M_PI);
dLon = (dLon * 180.0) / (EARTH_RADIUS * 1000 / sqrtMagic * math.cos(radLat) * M_PI);
y02 = lat + dLat;
x02 = lon + dLon;
return x02,y02
def convert_csv(in_csv, use_cols, xy_cols, to_gcj02, time1, time2, check_time, has_header, out_csv):
if len(xy_cols)<2:
print('xy_cols size error', xy_cols)
return
if len(use_cols)<3:
print('use_cols size error, first col must timesatmp', xy_cols)
return
x_col_idx = use_cols.index(xy_cols[0])
y_col_idx = use_cols.index(xy_cols[1])
oth_data = None
if has_header :
oth_data = pd.read_csv(in_csv, index_col=None, usecols=use_cols, encoding='utf8')
else:
oth_data = pd.read_csv(in_csv, index_col=None, usecols=use_cols, header=None, encoding='utf8')
cols = []
for a in oth_data:
cols.append(a)
if not has_header :
cols[x_col_idx]='x'
cols[y_col_idx]='y'
ds = []
for oth in oth_data.itertuples():
ks = list(oth[1:])
# print('1', ks)
if check_time :
if ks[0]>time2 or ks[0]<time1:
continue
if to_gcj02:
x = ks[x_col_idx]
y = ks[y_col_idx]
x02,y02 = Wgs84ToGcj02(x,y)
ks[x_col_idx] = x02
ks[y_col_idx] = y02
# print('2', ks)
ds.append(ks)
df = pd.DataFrame(ds, columns=cols)
print(df)
df.to_csv(out_csv, index = False)
if __name__ == "__main__":
in_file = r'/home/w/temp/20200608/G6/M8P/record/G9DATA.csv'
out_file = r'/home/w/temp/20200608/G6/M8P/record/G9DATA_022.csv'
use_cols = [0,5,6,7]
xy_cols = [5,6]
to_gcj02 = True
time1 = 1
time2 = 2
check_time = False
has_header = True
# convert_csv(in_file, use_cols, xy_cols, to_gcj02, time1, time2, check_time, has_header, out_file) in_file = r'/home/w/temp/20200608/G6/M8P/rtk.txt'
out_file = r'/home/w/temp/20200608/G6/M8P/rtk_02_slim1.txt'
use_cols = [0,1,2,3,4,5,6,7]
xy_cols = [1,2]
to_gcj02 = True
time1 = 1591564304940
time2 = 1591566905740
check_time = True
has_header = False
convert_csv(in_file, use_cols, xy_cols, to_gcj02, time1, time2, check_time, has_header, out_file) in_file = r'/home/w/temp/20200608/G6/M8P/rtk_02.txt'
out_file = r'/home/w/temp/20200608/G6/M8P/rtk_02_slim.txt'
use_cols = [0,1,2,3,4,5,6,7]
xy_cols = [1,2]
to_gcj02 = False
time1 = 1591564304940
time2 = 1591566905740
check_time = True
has_header = False
# convert_csv(in_file, use_cols, xy_cols, to_gcj02, time1, time2, check_time, has_header, out_file)。