欢迎您访问程序员文章站本站旨在为大家提供分享程序员计算机编程知识!
您现在的位置是: 首页  >  后端开发

【Python教程】地理可视化

程序员文章站 2022-03-30 12:30:12
...
Matplotlib是Python常用的数据绘制包,其绘图功能强大;而Basemap则是Matplotlib的一个子包,负责地图绘制。本文简单介绍如何利用该程序包绘制风向图。具体操作如下:

导入命令

1)设置工作环境并导入程序包

%cd "F:\\Dropbox\\python"
import numpy as np
import matplotlib.pyplot as plt
import datetime
from mpl_toolkits.basemap import Basemap, shiftgrid
from netCDF4 import Dataset

3)设定时间并读取数据

yyyy=1993; mm=03; dd=14; hh=00
date = datetime.datetime(yyyy,mm,dd,hh)
URLbase="http://nomads.ncdc.noaa.gov/thredds/dodsC/modeldata/cmd_pgbh/"
URL=URLbase+"%04i/%04i%02i/%04i%02i%02i/pgbh00.gdas.%04i%02i%02i%02i.grb2" %\
(yyyy,yyyy,mm,yyyy,mm,dd,yyyy,mm,dd,hh)
data = Dataset(URL)

4)数据预处理

latitudes = data.variables['lat'][::-1]
longitudes = data.variables['lon'][:].tolist()
slpin = 0.01*data.variables['Pressure_msl'][:].squeeze()
slp[:,0:-1] = slpin[::-1]; slp[:,-1] = slpin[::-1,0]u = np.zeros((uin.shape[0],uin.shape[1]+1),np.float64)
u[:,0:-1] = uin[::-1]; u[:,-1] = uin[::-1,0]v = np.zeros((vin.shape[0],vin.shape[1]+1),np.float64)v[:,0:-1] = vin[::-1]; 
v[:,-1] = vin[::-1,0]longitudes.append(360.); longitudes = np.array(longitudes)lons, lats = np.meshgrid(longitudes,latitudes)

5)设定并绘制图示

m = Basemap(resolution='c',projection='ortho',lat_0=60.,lon_0=-60.)fig1 = plt.figure(figsize=(8,10))
ax = fig1.add_axes([0.1,0.1,0.8,0.8])clevs = np.arange(960,1061,5)x, y = m(lons, lats)parallels = np.arange(-80.,90,20.)
meridians = np.arange(0.,360.,20.)CS1 = m.contour(x,y,slp,clevs,linewidths=0.5,colors='k',animated=True)
CS2 = m.contourf(x,y,slp,clevs,cmap=plt.cm.RdBu_r,animated=True)ugrid,newlons = shiftgrid(180.,u,longitudes,start=False)
vgrid,newlons = shiftgrid(180.,v,longitudes,start=False)
uproj,vproj,xx,yy = \
m.transform_vector(ugrid,vgrid,newlons,latitudes,31,31,returnxy=True,masked=True)
Q = m.quiver(xx,yy,uproj,vproj,scale=700)qk = plt.quiverkey(Q, 0.1, 0.1, 20, '20 m/s', labelpos='W')m.drawcoastlines(linewidth=1.5)
m.drawparallels(parallels)
m.drawmeridians(meridians)
cb = m.colorbar(CS2,"bottom", size="5%", pad="2%")
cb.set_label('hPa')
ax.set_title('SLP and Wind Vectors '+str(date))
plt.show()

输出图像如下

【Python教程】地理可视化


以上就是【Python教程】地理可视化的内容,更多相关内容请关注PHP中文网(www.php.cn)!