Python-气象-大气科学-可视化绘图系列（二）——利用basemap叠加地图，并添加白化效果（代码+示例）

本文为原创链接： https:////www.cnblogs.com/zhanling/p/12193031.html

 白化单图代码：
 import numpy as np
 import xarray as xr
 from mpl_toolkits.basemap import Basemap
 import matplotlib.pyplot as plt
 from matplotlib.patches import Polygon
 import matplotlib.patches as mpatches

 ds = xr.open_dataset('2019072300.006.nc')
 t =  ds['value']
 lons = ds.lon.data
 lats = ds.lat.data
 temp = xr.DataArray(t.data.T, coords=[lats,lons], dims=['latitude','longitude'])
 # 创建画图空间
 fig, ax = plt.subplots()
 m = Basemap(projection='cyl',resolution='i',llcrnrlon=lons.min(),llcrnrlat=lats.min(),
         urcrnrlon=lons.max(),urcrnrlat=lats.max(),lon_0=120.,lat_0=90)
 Lon,Lat = np.meshgrid(lons[:],lats[:])
 X,Y = m(Lon,Lat)

 shp_info3 = m.readshapefile("CHN_adm_shp\\CHN_adm3",'states',drawbounds=False,linewidth = 0.4,zorder=10)
 for info, shp in zip(m.states_info, m.states):
     proid = info['NAME_1']  # 可以用notepad打开CHN_adm1.csv文件，可以知道'NAME_1'代表各省的名称
     if proid == 'Hubei':
         poly = Polygon(shp,facecolor='None',edgecolor='b', lw=0.8)
         ax.add_patch(poly)
     else:
         poly = Polygon(shp,facecolor='w',edgecolor='w', lw=0.8)
         ax.add_patch(poly)

 #市一级底图
 shp_info2 = m.readshapefile("CHN_adm_shp\\CHN_adm2",'states',drawbounds=False,linewidth = 0.4,zorder=10)
 for info, shp in zip(m.states_info, m.states):
     proid = info['NAME_1']
     if proid == 'Hubei':
         poly = Polygon(shp,facecolor='None',edgecolor='black', lw=0.8)
         ax.add_patch(poly)
 cs=m.contourf(Lon,Lat,t.data.T,np.arange(0,1.1,0.1),cmap='rainbow')
 legend_elements = [mpatches.Patch(facecolor='#a50026',label='0-0.1'),
                    mpatches.Patch(facecolor='#da362a',label='0.1-0.2'),
                    mpatches.Patch(facecolor='#f67a49',label='0.2-0.3'),
                    mpatches.Patch(facecolor='#fdbf6f',label='0.3-0.4'),
                    mpatches.Patch(facecolor='#feeda1',label='0.4-0.5'),
                    mpatches.Patch(facecolor='#ebf7a3',label='0.5-0.6'),
                    mpatches.Patch(facecolor='#b7e075',label='0.6-0.7'),
                    mpatches.Patch(facecolor='#75c465',label='0.7-0.8'),
                    mpatches.Patch(facecolor='#249d53',label='0.8-0.9'),
                    mpatches.Patch(facecolor='#006837',label='0.9-1')]
 plt.legend(handles=legend_elements, loc='lower right',title='NDVI')
 # cbar = plt.colorbar(cs,orientation='horizontal',label='Potential')

个例效果：

 多图代码：
 import numpy as np
 import xarray as xr
 from mpl_toolkits.basemap import Basemap
 import matplotlib.pyplot as plt
 from matplotlib.patches import Polygon
 import matplotlib.patches as mpatches

 ds = xr.open_dataset('2019072300.006.nc')
 t =  ds['value']
 lons = ds.lon.data
 lats = ds.lat.data
 temp = xr.DataArray(t.data.T, coords=[lats,lons], dims=['latitude','longitude'])
 # 创建画图空间
 fig, ax = plt.subplots(2,2,figsize=(15,15))
 for ii in np.arange(4):
     print('ii:::::',ii)
     plt.sca(ax[np.unravel_index(ii,(2,2))]) # 获取一维索引在二维矩阵中的索引
     m = Basemap(projection='cyl',resolution='i',llcrnrlon=lons.min(),llcrnrlat=lats.min(),
         urcrnrlon=lons.max(),urcrnrlat=lats.max(),lon_0=120.,lat_0=90)
     Lon,Lat = np.meshgrid(lons[:],lats[:])
     X,Y = m(Lon,Lat)

     shp_info3 = m.readshapefile("CHN_adm_shp\\CHN_adm3",'states',drawbounds=False,linewidth = 0.4,zorder=10)
     for info, shp in zip(m.states_info, m.states):
         proid = info['NAME_1']  # 可以用notepad打开CHN_adm1.csv文件，可以知道'NAME_1'代表各省的名称
         if proid == 'Hubei':
             poly = Polygon(shp,facecolor='None',edgecolor='b', lw=0.8)
             ax[np.unravel_index(ii,(2,2))].add_patch(poly)
         else:
             poly = Polygon(shp,facecolor='w',edgecolor='w', lw=0.8)
             ax[np.unravel_index(ii,(2,2))].add_patch(poly)

     #市一级底图
     shp_info2 = m.readshapefile("CHN_adm_shp\\CHN_adm2",'states',drawbounds=False,linewidth = 0.4,zorder=10)
     for info, shp in zip(m.states_info, m.states):
         proid = info['NAME_1']
         if proid == 'Hubei':
             poly = Polygon(shp,facecolor='None',edgecolor='black', lw=0.8)
             ax[np.unravel_index(ii,(2,2))].add_patch(poly)

     cs=m.contourf(Lon,Lat,t.data.T,np.arange(0,1.1,0.1),cmap='rainbow')

 cbar = plt.colorbar(cs, ax=ax.ravel().tolist(), orientation='horizontal')
 plt.savefig('multi_masked.jpg',bbox_inches = 'tight')

效果如下：