Python netcdf cartopy-绘制选定的数据

我有一个netcdf文件（'test.nc'）。netcdf文件的变量如下：

variables(dimensions): float64 lon(lon), float64 lat(lat), int32 crs(), int16 Band1(lat,lon)

我对“Band1”变量感兴趣。 使用cartopy，我可以使用以下代码绘制数据：

import numpy as np
import pandas as pd
import gzip
from netCDF4 import Dataset,num2date
import time
import matplotlib.pyplot as plt
import os 
import matplotlib as mplt
#mplt.use('Agg')
import cartopy.crs as ccrs
import cartopy.feature as cfea
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

projection=ccrs.PlateCarree()
bbox=[-180,180,-60,85];creg='glob'
mplt.rc('xtick', labelsize=9) 
mplt.rc('ytick', labelsize=9)

nc = Dataset('test.nc','r')
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
kopi= (nc.variables['Band1'][:,:])
nc.close()

fig=plt.figure(figsize=(11,5))
ax=fig.add_subplot(1,1,1,projection=projection)
ax.set_extent(bbox,projection)
ax.add_feature(cfea.COASTLINE,lw=.5)
ax.add_feature(cfea.RIVERS,lw=.5)
ax.add_feature(cfea.BORDERS, linewidth=0.6, edgecolor='dimgray')
ax.background_patch.set_facecolor('.9')
levels=[1,4,8,11,14,17,21,25,29]
cmap=plt.cm.BrBG
norm=mplt.colors.BoundaryNorm(levels,cmap.N)
ddlalo=.25
pc=ax.contourf(lon,lat,kopi,levels=levels,transform=projection,cmap=cmap,norm=norm,extend='both')
divider = make_axes_locatable(ax)
ax_cb = divider.new_horizontal(size="3%", pad=0.1, axes_class=plt.Axes)
fig.colorbar(pc,extend='both', cax=ax_cb)
fig.add_axes(ax_cb)
fig.colorbar(pc,extend='both', cax=ax_cb)
ttitle='Jony'
ax.set_title(ttitle,loc='left',fontsize=9)
plt.show()

kopi= (nc.variables['Band1'][:,:])<=3

但是，我只想在变量“Band1”中绘制一组值。我想我可以使用以下代码：

import numpy as np
import pandas as pd
import gzip
from netCDF4 import Dataset,num2date
import time
import matplotlib.pyplot as plt
import os 
import matplotlib as mplt
#mplt.use('Agg')
import cartopy.crs as ccrs
import cartopy.feature as cfea
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

projection=ccrs.PlateCarree()
bbox=[-180,180,-60,85];creg='glob'
mplt.rc('xtick', labelsize=9) 
mplt.rc('ytick', labelsize=9)

nc = Dataset('test.nc','r')
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
kopi= (nc.variables['Band1'][:,:])
nc.close()

fig=plt.figure(figsize=(11,5))
ax=fig.add_subplot(1,1,1,projection=projection)
ax.set_extent(bbox,projection)
ax.add_feature(cfea.COASTLINE,lw=.5)
ax.add_feature(cfea.RIVERS,lw=.5)
ax.add_feature(cfea.BORDERS, linewidth=0.6, edgecolor='dimgray')
ax.background_patch.set_facecolor('.9')
levels=[1,4,8,11,14,17,21,25,29]
cmap=plt.cm.BrBG
norm=mplt.colors.BoundaryNorm(levels,cmap.N)
ddlalo=.25
pc=ax.contourf(lon,lat,kopi,levels=levels,transform=projection,cmap=cmap,norm=norm,extend='both')
divider = make_axes_locatable(ax)
ax_cb = divider.new_horizontal(size="3%", pad=0.1, axes_class=plt.Axes)
fig.colorbar(pc,extend='both', cax=ax_cb)
fig.add_axes(ax_cb)
fig.colorbar(pc,extend='both', cax=ax_cb)
ttitle='Jony'
ax.set_title(ttitle,loc='left',fontsize=9)
plt.show()

kopi= (nc.variables['Band1'][:,:])<=3

---

kopi=（nc.variables['Band1'][：，：]）只需使用
np.nan来屏蔽值

kopi[kopi <=3] = np.nan

kopi[kopi