【Python教程】地理可视化之二

导入命令

1）设置工作环境并导入程序包

%cd "F:\\Dropbox\\python"
from mpl_toolkits.basemap import Basemap
from netCDF4 import Dataset, date2index
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime

2）设定时间并读取数据

dataset = \
Dataset('http://www.ncdc.noaa.gov/thredds/dodsC/OISST-V2-AVHRR_agg')
timevar = dataset.variables['time']
timeindex = date2index(date,timevar)

3）数据预处理

sst = dataset.variables['sst'][timeindex,:].squeeze()
ice = dataset.variables['ice'][timeindex,:].squeeze()
lats = dataset.variables['lat'][:]
lons = dataset.variables['lon'][:]
lons, lats = np.meshgrid(lons,lats)

4）设定并绘制图示

fig = plt.figure()
ax = fig.add_axes([0.05,0.05,0.9,0.9])
m = Basemap(projection='kav7',lon_0=0,resolution=None)
m.drawmapboundary(fill_color='0.3')im1 = m.pcolormesh(lons,lats,sst,shading='flat',cmap=plt.cm.jet,latlon=True)
im2 = m.pcolormesh(lons,lats,ice,shading='flat',cmap=plt.cm.gist_gray,latlon=True)
m.drawparallels(np.arange(-90.,99.,30.))
m.drawmeridians(np.arange(-180.,180.,60.))cb = m.colorbar(im1,"bottom", size="5%", pad="2%")ax.set_title('SST and ICE analysis for %s'%date)
plt.show()

输出图像如下

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