我正在寻找一种解决方法，将 x 和 y 轴刻度和标签添加到 Lambert 投影中的 Cartopy 地图。
我想出的解决方案只是一个近似值，它会对较大的地图产生更差的结果：它涉及使用 transform_points 方法将所需的刻度位置转换为地图投影。为此，我使用 y 轴（或 x 轴）的中值经度（或纬度）以及所需的纬度（或经度）刻度位置来计算地图投影坐标。请参阅下面的代码。
因此，我假设沿 y 轴的经度恒定（沿 x 轴的纬度），这是不正确的，因此会导致偏差。（请注意所附结果图中的差异：set_extent 中设置的 46° 和结果刻度位置）。
有没有更准确的解决方案？任何提示我如何解决这个问题？
感谢您的任何想法！
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import numpy as np
def main():
#my desired Lambert projection:
myproj = ccrs.LambertConformal(central_longitude=13.3333, central_latitude=47.5,
false_easting=400000, false_northing=400000,
secant_latitudes=(46, 49))
arat = 1.1 #just some factor for the aspect ratio
fig_len = 12
fig_hig = fig_len/arat
fig = plt.figure(figsize=(fig_len,fig_hig), frameon=True)
ax = fig.add_axes([0.08,0.05,0.8,0.94], projection = myproj)
ax.set_extent([10,16,46,49])
#This is what is not (yet) working in Cartopy due to Lambert projection:
#ax.gridlines(draw_labels=True) #TypeError: Cannot label gridlines on a LambertConformal plot. Only PlateCarree and Mercator plots are currently supported.
x_lons = [12,13,14] #want these longitudes as tick positions
y_lats = [46, 47, 48, 49] #want these latitudes as tick positions
tick_fs = 16
#my workaround functions:
cartopy_xlabel(ax,x_lons,myproj,tick_fs)
cartopy_ylabel(ax,y_lats,myproj,tick_fs)
plt.show()
plt.close()
def cartopy_xlabel(ax,x_lons,myproj,tick_fs):
#transform the corner points of my map to lat/lon
xy_bounds = ax.get_extent()
ll_lonlat = ccrs.Geodetic().transform_point(xy_bounds[0],xy_bounds[2], myproj)
lr_lonlat = ccrs.Geodetic().transform_point(xy_bounds[1],xy_bounds[2], myproj)
#take the median value as my fixed latitude for the x-axis
l_lat_median = np.median([ll_lonlat[1],lr_lonlat[1]]) #use this lat for transform on lower x-axis
x_lats_helper = np.ones_like(x_lons)*l_lat_median
x_lons = np.asarray(x_lons)
x_lats_helper = np.asarray(x_lats_helper)
x_lons_xy = myproj.transform_points(ccrs.Geodetic(), x_lons,x_lats_helper)
x_lons_xy = list(x_lons_xy[:,0]) #only lon pos in xy are of interest
x_lons = list(x_lons)
x_lons_labels =[]
for j in xrange(len(x_lons)):
if x_lons[j]>0:
ew=r'$^\circ$E'
else:
ew=r'$^\circ$W'
x_lons_labels.append(str(x_lons[j])+ew)
ax.set_xticks(x_lons_xy)
ax.set_xticklabels(x_lons_labels,fontsize=tick_fs)
def cartopy_ylabel(ax,y_lats,myproj,tick_fs):
xy_bounds = ax.get_extent()
ll_lonlat = ccrs.Geodetic().transform_point(xy_bounds[0],xy_bounds[2], myproj)
ul_lonlat = ccrs.Geodetic().transform_point(xy_bounds[0],xy_bounds[3], myproj)
l_lon_median = np.median([ll_lonlat[0],ul_lonlat[0]]) #use this lon for transform on left y-axis
y_lons_helper = np.ones_like(y_lats)*l_lon_median
y_lats = np.asarray(y_lats)
y_lats_xy = myproj.transform_points(ccrs.Geodetic(), y_lons_helper, y_lats)
y_lats_xy = list(y_lats_xy[:,1]) #only lat pos in xy are of interest
y_lats = list(y_lats)
y_lats_labels =[]
for j in xrange(len(y_lats)):
if y_lats[j]>0:
ew=r'$^\circ$N'
else:
ew=r'$^\circ$S'
y_lats_labels.append(str(y_lats[j])+ew)
ax.set_yticks(y_lats_xy)
ax.set_yticklabels(y_lats_labels,fontsize=tick_fs)
if __name__ == '__main__': main()
