wrf模擬的區域繪製,domain圖,利用python的cartopy庫繪製模擬區域
參考Liang Chen的draw_wrf_domian.py這個程式碼, 出處python畫wrf模式的模擬區域
創新點
區別於Liange程式碼的地方在於使用cartopy庫,替換了basemap庫, 方便在最新的python版本下使用。
初學cartopy,使用cartopy根據距離繪製影像是比較難想到的一點, 是在建立投影物件的那裡設定的你敢信?
具體程式碼(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: 緯度列表
lons: 經度列表
purpose: 畫區域直線
'''
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):
"""建立一個包含青藏高原區域的Lambert投影的底圖
Returns:
ax: 座標圖物件
"""
## --建立畫圖空間
proj = ccrs.PlateCarree() # 建立座標系
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,
)
## 建立座標系
fig = plt.figure(figsize=(4, 4), dpi=500) # 建立頁面
ax = fig.add_axes([0.1,0.1,0.8,0.8], projection=proj_lambert)
## 讀取青藏高原地形檔案
Tibet = cfeat.ShapelyFeature(
Reader('/home/fengxiang/Data/shp_tp/Tibet.shp').geometries(),
proj, edgecolor='k',
facecolor='none', alpha=0.9
)
## 將青藏高原地形檔案加到地圖中區
ax.add_feature(Tibet, linewidth=0.5, zorder=2)
## --設定網格屬性, 不畫預設的標籤
gl=ax.gridlines(draw_labels=True,linestyle=":",linewidth=0.3 ,x_inline=False, y_inline=False,color='k')
## 關閉上面和右邊的經緯度顯示
gl.top_labels=False #關閉上部經緯標籤
# gl.bottom_labels = False
# gl.left_labels = False
gl.right_labels=False
gl.xformatter = LONGITUDE_FORMATTER #使橫座標轉化為經緯度格式
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}#修改經緯度字型大小
gl.ylabel_style={'size':4}
ax.spines['geo'].set_linewidth(0.6)#調節邊框粗細
# 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):
"""根據namelist.wps檔案,獲取地圖的基本資訊
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: # 這裡沒有考慮註釋的那些行吧, 不過wps一般也沒人註釋就是了
line=line.replace("=","").replace(",","")
name_dict.update({line.split()[0]: line.split()[1:]}) # 這個字典直接可以更新
dx = float(name_dict["dx"][0]) # 轉換為公里
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]) # 模式區域中心位置
ref_lon= float(name_dict["ref_lon"][0])
truelat1 = float(name_dict["truelat1"][0]) # 和投影相關的經緯度
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 # 中心點偏離邊界的距離
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):
"""繪製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 找到四個頂點和距離相關的座標
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) # 畫多邊型
## 標註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']))
## 標記出站點
ax.scatter(x,y,color='red',
transform=ccrs.PlateCarree(),
linewidth=0.1,s=10)
## 給站點加註釋
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) # 獲取namelist.wps檔案資訊
ax = create_map(info) # 在domain1區域內,新增地理資訊,建立底圖
draw_d02(info) # 繪製domain2區域
draw_station() # 將站點位置繪製到圖上
plt.title('d01', loc='left')
plt.savefig("domain.png")
具體程式碼(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: 緯度列表
lons: 經度列表
purpose: 畫區域直線
'''
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: # 這裡沒有考慮註釋的那些行吧, 不過wps一般也沒人註釋就是了
line=line.replace("=","").replace(",","")
name_dict.update({line.split()[0]: line.split()[1:]}) # 這個字典直接可以更新
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]) # 模式區域中心位置
ref_lon= float(name_dict["ref_lon"][0])
truelat1 = float(name_dict["truelat1"][0]) # 和投影相關的經緯度
truelat2 = float(name_dict["truelat2"][0])
# # ## draw map
fig = plt.figure(figsize=(7,6)) # 設定畫板大小
#Custom adjust of the subplots
plt.subplots_adjust(left=0.05,right=0.97,top=0.9,bottom=0.1) # 調整畫布大小
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")
### 根據地形檔案,畫底圖
ii=0 # 控制變數
for sr in shape_line:
# print(sr)
r = shapefile.Reader(sShapeFiles+sr) # 讀地形檔案
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
## 畫標籤
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 畫中心點
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)
## 畫區域1的中點和標註
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
#### 區域2
#### 畫多邊形
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) # 畫多邊型
## 標註d02
plt.text(lon[3]*1, lat[3]*1., "d02")
### 區域2畫多邊形中點
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") # 這個畫的是區域2的中點
# 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)
## 標註站點
plt.plot(cenlon_model, cenlat_model,marker="o") # 這個畫的是區域2的中點
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")