wrf模拟的区域绘制，domain图，利用python的cartopy库绘制模拟区域
参考Liang Chen的draw_wrf_domian.py这个代码, 出处python画wrf模式的模拟区域
创新点
区别于Liange代码的地方在于使用cartopy库，替换了basemap库, 方便在最新的python版本下使用。
初学cartopy,使用cartopy根据距离绘制图像是比较难想到的一点, 是在创建投影对象的那里设置的你敢信？
具体代码（使用cartopy)
"""
Author: Forxd
Time: 2021-3-17
Purpose: read in namelist.wps , draw wrf domain and plot some station
"""
import xarray as xr
import numpy as np
import salem
import cartopy.crs as ccrs
import cartopy.feature as cfeat
from cartopy.mpl.ticker import LongitudeFormatter,LatitudeFormatter
from cartopy.io.shapereader import Reader, natural_earth
import cartopy.feature as cf
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import geopandas
import cmaps
from matplotlib.path import Path
import matplotlib.patches as patches
def draw_screen_poly( lats, lons):
'''
lats: 纬度列表
lons: 经度列表
purpose: 画区域直线
'''
x, y = lons, lats
xy = list(zip(x,y))
print(xy)
poly = plt.Polygon( xy, edgecolor="blue",fc="none", lw=0.6, alpha=1)
plt.gca().add_patch(poly)
def create_map(info):
"""创建一个包含青藏高原区域的Lambert投影的底图
Returns:
ax: 坐标图对象
"""
## --创建画图空间
proj = ccrs.PlateCarree() # 创建坐标系
ref_lat = info['ref_lat']
ref_lon = info['ref_lon']
true_lat1 = info['true_lat1']
true_lat2 = info['true_lat2']
false_easting = (info['e_we'][0]-1)/2*info['dx']
false_northing = (info['e_sn'][0]-1)/2*info['dy']
# print(true_lat1)
proj_lambert = ccrs.LambertConformal(
central_longitude=ref_lon,
central_latitude=ref_lat,
standard_parallels=(true_lat1,true_lat2),
cutoff=-30,
false_easting=false_easting,
false_northing=false_northing,
)
## 创建坐标系
fig = plt.figure(figsize=(4, 4), dpi=500) # 创建页面
ax = fig.add_axes([0.1,0.1,0.8,0.8], projection=proj_lambert)
## 读取青藏高原地形文件
Tibet = cfeat.ShapelyFeature(
Reader('/home/fengxiang/Data/shp_tp/Tibet.shp').geometries(),
proj, edgecolor='k',
facecolor='none', alpha=0.9
)
## 将青藏高原地形文件加到地图中区
ax.add_feature(Tibet, linewidth=0.5, zorder=2)
## --设置网格属性, 不画默认的标签
gl=ax.gridlines(draw_labels=True,linestyle=":",linewidth=0.3 ,x_inline=False, y_inline=False,color='k')
## 关闭上面和右边的经纬度显示
gl.top_labels=False #关闭上部经纬标签
# gl.bottom_labels = False
# gl.left_labels = False
gl.right_labels=False
gl.xformatter = LONGITUDE_FORMATTER #使横坐标转化为经纬度格式
gl.yformatter = LATITUDE_FORMATTER
gl.xlocator=mticker.FixedLocator(np.arange(60,120,10))
gl.ylocator=mticker.FixedLocator(np.arange(10,60,10))
gl.xlabel_style={'size':4}#修改经纬度字体大小
gl.ylabel_style={'size':4}
ax.spines['geo'].set_linewidth(0.6)#调节边框粗细
# ax.set_extent([60, 120, 10, 60], crs=proj)
# ax.set_extent([0, 2237500*2, 0, 1987500*2], crs=proj_lambert)
ax.set_extent([0, false_easting*2, 0, false_northing*2], crs=proj_lambert)
print(false_northing)
print(false_easting)
return ax
def get_information(flnm):
"""根据namelist.wps文件，获取地图的基本信息
Args:
flnm ([type]): [description]
Returns:
[type]: [description]
"""
## getting namelist.wps domain information
name_dict={}
with open(flnm) as fr:
for line in fr:
if "=" in line: # 这里没有考虑注释的那些行吧, 不过wps一般也没人注释就是了
line=line.replace("=","").replace(",","")
name_dict.update({line.split()[0]: line.split()[1:]}) # 这个字典直接可以更新
dx = float(name_dict["dx"][0]) # 转换为公里
dy = float(name_dict["dy"][0])
max_dom = int(name_dict["max_dom"][0])
# print(max_dom)
parent_grid_ratio = list(map(int, name_dict["parent_grid_ratio"]))
i_parent_start = list(map(int, name_dict["i_parent_start"]))
j_parent_start = list(map(int, name_dict["j_parent_start"]))
e_sn = list(map(int, name_dict["e_sn"]))
e_we = list(map(int, name_dict["e_we"]))
ref_lat= float(name_dict["ref_lat"][0]) # 模式区域中心位置
ref_lon= float(name_dict["ref_lon"][0])
truelat1 = float(name_dict["truelat1"][0]) # 和投影相关的经纬度
truelat2 = float(name_dict["truelat2"][0])
cenlon= np.arange(max_dom)
cenlat=np.arange(max_dom)
cenlon_model=dx*(e_we[0]-1)/2.0 # 中心点偏离边界的距离
cenlat_model=dy*(e_sn[0]-1)/2.0
dict_return = {
"dx":dx,
"dy":dy,
"max_dom":max_dom,
"parent_grid_ratio":parent_grid_ratio,
"j_parent_start":j_parent_start,
"i_parent_start":i_parent_start,
"e_sn":e_sn,
"e_we":e_we,
'ref_lat':ref_lat,
'ref_lon':ref_lon,
'true_lat1':truelat1,
'true_lat2':truelat2,
'parent_grid_ratio':parent_grid_ratio,
}
return dict_return
def draw_d02(info):
"""绘制domain2
Args:
info ([type]): [description]
"""
max_dom = info['max_dom']
dx = info['dx']
dy = info['dy']
i_parent_start = info['i_parent_start']
j_parent_start = info['j_parent_start']
parent_grid_ratio= info['parent_grid_ratio']
e_we = info['e_we']
e_sn = info['e_sn']
if max_dom >= 2:
### domain 2
# 4 corners 找到四个顶点和距离相关的坐标
ll_lon = dx*(i_parent_start[1]-1)
ll_lat = dy*(j_parent_start[1]-1)
ur_lon = ll_lon + dx/parent_grid_ratio[1] * (e_we[1]-1)
ur_lat = ll_lat + dy/parent_grid_ratio[1] * (e_sn[1]-1)
lon = np.empty(4)
lat = np.empty(4)
lon[0],lat[0] = ll_lon, ll_lat # lower left (ll)
lon[1],lat[1] = ur_lon, ll_lat # lower right (lr)
lon[2],lat[2] = ur_lon, ur_lat # upper right (ur)
lon[3],lat[3] = ll_lon, ur_lat # upper left (ul)
draw_screen_poly(lat, lon) # 画多边型
## 标注d02
plt.text(lon[3]*1, lat[3]*1., "d02")
def draw_station():
station = {'TingRi':{'lat':28.6,'lon':87.0},
'NaQu':{'lat':31.4, 'lon':92.0},
'LaSa':{'lat':29.6, 'lon':91.1},
'TuoTuohe':{'lat':34.2, 'lon':92.4},
'GaiZe':{'lat':32.3, 'lon':84.0},
'ShenZha':{'lat':30.9, 'lon':88.7},
'ShiQuanhe':{'lat':32.4, 'lon':80.1},
'JinChuan':{'lat':31.29, 'lon':102.04},
'JinLong':{'lat':29.00, 'lon':101.50},
}
values = station.values()
station_name = list(station.keys())
print(type(station_name[0]))
# print(station_name[0])
x = []
y = []
for i in values:
y.append(float(i['lat']))
x.append(float(i['lon']))
## 标记出站点
ax.scatter(x,y,color='red',
transform=ccrs.PlateCarree(),
linewidth=0.1,s=10)
## 给站点加注释
for i in range(len(x)):
print(x[i])
plt.text(x[i]-2, y[i]+0.5, station_name[i],
transform=ccrs.PlateCarree(),
fontdict={'size':5,}
)
if __name__ == '__main__':
file_folder="./"
file_name="namelist.wps"
flnm=file_folder+file_name
info = get_information(flnm) # 获取namelist.wps文件信息
ax = create_map(info) # 在domain1区域内，添加地理信息，创建底图
draw_d02(info) # 绘制domain2区域
draw_station() # 将站点位置绘制到图上
plt.title('d01', loc='left')
plt.savefig("domain.png")
具体代码(使用basemap)
'''
File name: draw_wrf_domain.py
Author: Liang Chen
E-mail: chenliang@tea.ac.cn
Date created: 2016-12-22
Date last modified: 2021-3-3
##############################################################
Purpos:
this function reads in namelist.wps and plot the wrf domain
'''
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap, cm
from matplotlib.colors import LinearSegmentedColormap
import shapefile
from matplotlib.collections import LineCollection
import matplotlib.colors
import sys
import numpy as np
def draw_screen_poly( lats, lons):
'''
lats: 纬度列表
lons: 经度列表
purpose: 画区域直线
'''
x, y = lons, lats
xy = list(zip(x,y))
print(xy)
poly = plt.Polygon( xy, edgecolor="blue",fc="none", lw=2, alpha=1)
plt.gca().add_patch(poly)
sShapeFiles="/home/fengxiang/Data/shp_tp/"
shape_line=['Tibet.shp',]
## setting namelist.wps domain information
file_folder="./"
file_name="namelist.wps"
sfile=file_folder+file_name
name_dict={}
with open(sfile) as fr:
for line in fr:
if "=" in line: # 这里没有考虑注释的那些行吧, 不过wps一般也没人注释就是了
line=line.replace("=","").replace(",","")
name_dict.update({line.split()[0]: line.split()[1:]}) # 这个字典直接可以更新
dx = float(name_dict["dx"][0])
dy = float(name_dict["dy"][0])
max_dom = int(name_dict["max_dom"][0])
print(max_dom)
parent_grid_ratio = list(map(int, name_dict["parent_grid_ratio"]))
i_parent_start = list(map(int, name_dict["i_parent_start"]))
j_parent_start = list(map(int, name_dict["j_parent_start"]))
e_sn = list(map(int, name_dict["e_sn"]))
e_we = list(map(int, name_dict["e_we"]))
ref_lat= float(name_dict["ref_lat"][0]) # 模式区域中心位置
ref_lon= float(name_dict["ref_lon"][0])
truelat1 = float(name_dict["truelat1"][0]) # 和投影相关的经纬度
truelat2 = float(name_dict["truelat2"][0])
# # ## draw map
fig = plt.figure(figsize=(7,6)) # 设置画板大小
#Custom adjust of the subplots
plt.subplots_adjust(left=0.05,right=0.97,top=0.9,bottom=0.1) # 调整画布大小
ax = plt.subplot(111)
m = Basemap(resolution="l", projection="lcc", rsphere=(6370000.0, 6370000.0), lat_1=truelat1, lat_2=truelat2, lat_0=ref_lat, lon_0=ref_lon, width=dx*(e_we[0]-1), height=dy*(e_sn[0]-1))
# m.drawcoastlines()
#m.drawcountries(linewidth=2)
#m.drawcountries()
#m.fillcontinents()
#m.fillcontinents(color=(0.8,1,0.8))
#m.drawmapboundary()
#m.fillcontinents(lake_color="aqua")
#m.drawmapboundary(fill_color="aqua")
### 根据地形文件，画底图
ii=0 # 控制变量
for sr in shape_line:
# print(sr)
r = shapefile.Reader(sShapeFiles+sr) # 读地形文件
shapes = r.shapes()
records = r.records()
for record, shape in zip(records,shapes):
lons,lats = zip(*shape.points)
data = np.array(m(lons, lats)).T
if len(shape.parts) == 1:
segs = [data,]
else:
segs = []
for i in range(1,len(shape.parts)):
index = shape.parts[i-1]
index2 = shape.parts[i]
segs.append(data[index:index2])
segs.append(data[index2:])
lines = LineCollection(segs,antialiaseds=(1,))
# lines.set_facecolors(cm.jet(np.random.rand(1)))
if ii==0:
lines.set_edgecolors('black')
lines.set_linewidth(2)
else:
lines.set_edgecolors('k')
lines.set_linewidth(1)
ax.add_collection(lines)
ii=ii+1
## 画标签
m.drawparallels(np.arange(-90, 90, 10), labels = [1,0,0,0], fontsize=16,dashes=[1,1])
# m.drawmeridians(np.arange(-180, 180, 10), labels = [0,0,0,1], fontsize=16,dashes=[1,1])
print(ref_lat, ref_lon)
## plot center position 画中心点
cenlon= np.arange(max_dom); cenlat=np.arange(max_dom)
cenlon_model=dx*(e_we[0]-1)/2.0
cenlat_model=dy*(e_sn[0]-1)/2.0
cenlon[0], cenlat[0]=m(cenlon_model, cenlat_model, inverse=True)
## 画区域1的中点和标注
plt.plot(cenlon_model,cenlat_model, marker="o", color="gray")
plt.text(cenlon_model*0.8, cenlat_model*1.01, "({cenlat}, {cenlon})".format(cenlat=round(cenlat[0],2), cenlon=round(cenlon[0],2)))
#### draw nested domain rectangle
#### 区域2
#### 画多边形
lon=np.arange(4); lat=np.arange(4)
if max_dom >= 2:
### domain 2
# 4 corners
ll_lon = dx*(i_parent_start[1]-1)
ll_lat = dy*(j_parent_start[1]-1)
ur_lon = ll_lon + dx/parent_grid_ratio[1] * (e_we[1]-1)
ur_lat = ll_lat + dy/parent_grid_ratio[1] * (e_sn[1]-1)
## lower left (ll)
lon[0],lat[0] = ll_lon, ll_lat
## lower right (lr)
lon[1],lat[1] = ur_lon, ll_lat
## upper right (ur)
lon[2],lat[2] = ur_lon, ur_lat
## upper left (ul)
lon[3],lat[3] = ll_lon, ur_lat
print(lat)
print(lon)
draw_screen_poly(lat, lon) # 画多边型
## 标注d02
plt.text(lon[3]*1, lat[3]*1., "d02")
### 区域2画多边形中点
cenlon_model = ll_lon + (ur_lon-ll_lon)/2.0
cenlat_model = ll_lat + (ur_lat-ll_lat)/2.0
cenlon[1], cenlat[1]=m(cenlon_model, cenlat_model, inverse=True)
# plt.plot(cenlon_model, cenlat_model,marker="o") # 这个画的是区域2的中点
# plt.text(cenlon_model*0.8, cenlat_model*1.01, "({cenlat}, {cenlon})".format(cenlat=round(cenlat[1],2), cenlon=round(cenlon[1],2)))
if max_dom >= 3:
### domain 3
## 4 corners
ll_lon += dx/parent_grid_ratio[1]*(i_parent_start[2]-1)
ll_lat += dy/parent_grid_ratio[1]*(j_parent_start[2]-1)
ur_lon = ll_lon +dx/parent_grid_ratio[1]/parent_grid_ratio[2]*(e_we[2]-1)
ur_lat =ll_lat+ dy/parent_grid_ratio[1]/parent_grid_ratio[2]*(e_sn[2]-1)
## ll
lon[0],lat[0] = ll_lon, ll_lat
## lr
lon[1],lat[1] = ur_lon, ll_lat
## ur
lon[2],lat[2] = ur_lon, ur_lat
## ul
lon[3],lat[3] = ll_lon, ur_lat
draw_screen_poly(lat, lon)
plt.text(lon[0]-lon[0]/10,lat[0]-lat[0]/10,"({i}, {j})".format(i=i_parent_start[2], j=j_parent_start[2]))
#plt.plot(lon,lat,linestyle="",marker="o",ms=10)
cenlon_model = ll_lon + (ur_lon-ll_lon)/2.0
cenlat_model = ll_lat + (ur_lat-ll_lat)/2.0
# plt.plot(cenlon,cenlat,marker="o",ms=15)
#print m(cenlon, cenlat)cenlon, cenlat, ll_lon, ll_lat, ur_lon, ur_lat
#print m(cenlon, cenlat,inverse=True)
cenlon[2], cenlat[2]=m(cenlon_model, cenlat_model, inverse=True)
if max_dom >= 4:
### domain 3
## 4 corners
ll_lon += dx/parent_grid_ratio[1]/parent_grid_ratio[2]*(i_parent_start[3]-1)
ll_lat += dy/parent_grid_ratio[1]/parent_grid_ratio[2]*(j_parent_start[3]-1)
ur_lon = ll_lon +dx/parent_grid_ratio[1]/parent_grid_ratio[2]/parent_grid_ratio[3]*(e_we[3]-1)
ur_lat =ll_lat+ dy/parent_grid_ratio[1]/parent_grid_ratio[2]/parent_grid_ratio[3]*(e_sn[3]-1)
## ll
lon[0],lat[0] = ll_lon, ll_lat
## lr
lon[1],lat[1] = ur_lon, ll_lat
## ur
lon[2],lat[2] = ur_lon, ur_lat
## ul
lon[3],lat[3] = ll_lon, ur_lat
draw_screen_poly(lat, lon)
#plt.plot(lon,lat,linestyle="",marker="o",ms=10)
cenlon_model = ll_lon + (ur_lon-ll_lon)/2.0
cenlat_model = ll_lat + (ur_lat-ll_lat)/2.0
# plt.plot(cenlon,cenlat,marker="o",ms=15)
#print m(cenlon, cenlat)cenlon, cenlat, ll_lon, ll_lat, ur_lon, ur_lat
#print m(cenlon, cenlat,inverse=True)
cenlon[3], cenlat[3]=m(cenlon_model, cenlat_model, inverse=True)
## 标注站点
plt.plot(cenlon_model, cenlat_model,marker="o") # 这个画的是区域2的中点
print(cenlon_model/25000, cenlat_model/25000)
# plt.text(cenlon_model*0.8, cenlat_model*1.01, "({cenlat}, {cenlon})".format(cenlat=round(cenlat[1],2), cenlon=round(cenlon[1],2)))
cenlon_model=dx*(e_we[0]-1)/2.0
print(dx)
print(dy)
Tingri={'lat':28.6,'lon':87.0,'name':'Tingri'}
plt.plot(Tingri['lon']*25000, Tingri['lat']*25000,marker="o")
# plt.text(Tingri['lon']*0.8, Tingri['lat']*1.01, "({cenlat}, {cenlon})".format(cenlat=round(cenlat[1],2), cenlon=round(cenlon[1],2)))
plt.savefig("tttt.png")