如何用Python绘制天气图
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#!/bin/env python
#coding=utf-8
import codecs
import numpy as np
import datetime
import re
import pandas as pd
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from metpy.calc import wind_components
from metpy.plots import add_metpy_logo, current_weather, sky_cover, StationPlot, wx_code_map
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from metpy.units import units
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import cartopy.io.shapereader as shpreader
def func_return_self(x):
return x
def split(str_in, sep=None, convert_func=None):
ss = str_in.split(sep)
nn = len(ss)
rst = [None]*nn
if convert_func is None:
cf = [func_return_self] * nn
else:
cf = [_ for _ in convert_func]
# print(nn, len(cf))
for i in range(nn):
xcf = func_return_self if cf[i] is None else cf[i]
rst[i] = xcf(ss[i])
return rst
def d1_parse(filename,encoding="gb2312"):
"""
读micaps第1类数据文件到内存
:return:
"""
with codecs.open(filename, mode='r', encoding=encoding) as fid:
contents = fid.readlines()
dataflag, style, title = split(contents[0],None,None)
nn = len(contents)
nx = int((nn-2)/2)
data = {
"stid":[None]*nx,
"lon":[None]*nx,
"lat":[None]*nx,
"height":[None]*nx,
"stlevel":[None]*nx,
"cloud":[None]*nx,
"wd":[None]*nx,
"ws":[None]*nx,
"psfc":[None]*nx,
"pd3":[None]*nx,
"pw1":[None]*nx,
"pw2":[None]*nx,
"prc6":[None]*nx,
"lc1":[None]*nx,
"lc2":[None]*nx,
"lc3":[None]*nx,
"dp":[None]*nx,
"njd":[None]*nx,
"cw":[None]*nx,
"tc":[None]*nx,
"mc":[None]*nx,
"hc":[None]*nx,
"flag1":[None]*nx,
"flag2":[None]*nx,
"dtc24":[None]*nx,
"dp24":[None]*nx
}
data = pd.DataFrame(data)
j=0
for i in range(2,nn,2):
iline1 = contents[i]
iline2 = contents[i+1]
iline = " ".join([iline1,iline2])
#for iline in contents[2:]:
data.stid[j], data.lon[j], data.lat[j], data.height[j], data.stlevel[j],data.cloud[j],data.wd[j],data.ws[j],data.psfc[j],data.pd3[j], data.pw1[j], data.pw2[j], \
data.prc6[j], data.lc1[j],data.lc2[j],data.lc3[j], data.dp[j], data.njd[j], data.cw[j], data.tc[j], data.mc[j], data.hc[j], data.flag1[j], data.flag2[j], data.dtc24[j],data.dp24[j] \
=split(iline,None,
[int, float,float,float,int,float,float,float,float,float,int,int,\
float,float,float,float,float,float,int, float,float, float,int, int,float,float]
)
j+=1
#data.append([stid, lon, lat, height, stlevel,cloud,wd,ws,psfc,pd3, pw1, pw2,\
#prc6, lc1,lc2,lc3, dp, njd, cw, tc, mc, hc, flag1, flag2, dtc24,dp24])
#print(data)
return dataflag, style, title,data
def d4_parse(filename,encoding="gb2312"):
"""
读micaps第4类数据文件到内存
:return:
"""
try:
file_object = codecs.open(filename, mode='r', encoding=encoding)
all_the_text = file_object.read().strip()
file_object.close()
contents = re.split('[\s]+', all_the_text)
if len(contents) < 23:
return
dataflag = contents[0].strip()
style = contents[1].strip()
title = contents[2].strip()
yy = int(contents[3].strip())
mm = int(contents[4].strip())
dd = int(contents[5].strip())
hh = int(contents[6].strip())
forehh = int(contents[7].strip())
level = contents[8].strip()
deltalon = float(contents[9].strip())
deltalat = float(contents[10].strip())
beginlon = float(contents[11].strip())
endlon = float(contents[12].strip())
beginlat = float(contents[13].strip())
endlat = float(contents[14].strip())
sumlon = int(contents[15].strip())
sumlat = int(contents[16].strip())
distance = float(contents[17].strip())
min = float(contents[18].strip())
max = float(contents[19].strip())
def1 = contents[20].strip()
def2 = contents[21].strip()
x = np.arange(beginlon, endlon + 0.9*deltalon, deltalon)
y = np.arange(beginlat, endlat + 0.9*deltalat, deltalat)
X, Y = np.meshgrid(x, y)
if dataflag == 'diamond' and style == '4':
begin = 22
Z = np.zeros((sumlat, sumlon))
for i in range(sumlon):
for j in range(sumlat):
Z[j, i] = float(contents[begin + j * sumlon + i])
return dataflag, style,title,yy,mm,dd,hh,forehh,level,X,Y,Z,distance,min,max,def1,def2
except Exception as err:
print(u'【{0}】{1}-{2}'.format(filename, err, datetime.datetime.now()))
if __name__ == "__main__":
dataflag, style, title, yy, mm, dd, hh, forehh, level, X, Y, p0_data, distance, dmin, dmax, def1, def2 = d4_parse("/home/hliang/share/share/plotest/20190126/p0/19012602.000")
station_dataflag, staiton_style, station_title, station_data = d1_parse("/home/hliang/share/share/plotest/20190126/plot/19012108.000")
station_data = station_data.replace(9999,np.nan)
station_data = station_data[station_data.stlevel==2]#.dropna()
lat_max=50
lat_min=15
lon_max=130
lon_min=100
proj = ccrs.LambertCylindrical(central_longitude=(lon_max+lon_min)/2.0)#ccrs.LambertConformal(central_longitude=(lon_max+lon_min)/2.0, central_latitude=(lat_max+lat_min)/2.0,standard_parallels=[(lat_max+lat_min)/2.0])
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(1, 1, 1, projection=proj)
ax.set_extent([lon_min,lon_max,lat_min,lat_max],proj)
ax.set_xticks(range(lon_min,lon_max+2,10), crs=proj)
ax.set_yticks(range(lat_min,lat_max+2,10), crs=proj)
shp = shpreader.Reader('/home/hliang/share/share/plotest/shp_resources/CHN_adm/CHN_adm1.shp')
ax.add_geometries(shp.geometries(), crs=proj, facecolor="none", edgecolor="grey", lw=0.8)
contours = ax.contour(X, Y, p0_data,levels=np.arange(dmin,dmax+0.9*distance,distance), colors="black",transform=proj,linewidths=0.5)
plt.clabel(contours, fontsize=8,fmt='%.1f')
stationplot = StationPlot(ax, station_data['lon'].values, station_data['lat'].values, clip_on=True,
transform=proj, fontsize=6)
u,v = wind_components(station_data['ws'].values * units('m/s'),station_data['wd'].values * units.degree)
stationplot.plot_parameter('NW', station_data['tc'], color='red')
stationplot.plot_barb(u, v,sizes=dict(emptybarb=0.15))
cw = station_data.cw.replace(np.nan,0).astype(np.int)
pw1 = station_data.pw1.replace(np.nan,0).astype(np.int)
stationplot.plot_symbol('W', cw, current_weather,color='fuchsia')
stationplot.plot_symbol('SE', pw1, current_weather,color='y')
'''
for record,state in zip(shp.records(), shp.geometries()):
name = record.attributes["NAME_1"]
if name=="Jiangsu":
ax.add_geometries(state,crs=proj,facecolor="none",edgecolor="grey",lw=0.5)
'''
plt.savefig('./fig1.png',dpi=300)
#plt.show()
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