Cartopy Coastlines Hidden By Inset_axes Use Of Axes.pie

I am producing a map of the world with pie charts in individual model grid boxes. I make the map and coastlines using cartopy. The pie charts I produce using inset_axes. Unfortunat

Solution 1:

The problem is that each axes either lies on top or below another axes. So changing the zorder of artists within axes, does not help here. In principle, one could set the zorder of the axes themselves, putting the inset axes behind the main axes.

ax_sub.set_zorder(axis_main.get_zorder()-1)

Cartopy's GeoAxes uses its own background patch. This would then need to be set to invisble.

ax_main.background_patch.set_visible(False)

Complete example:

import cartopy.crs as ccrs
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

defplot_pie_inset(dataframe_pie,ilat_pie,ilon_pie,axis_main,width_local,alpha_local):
    ax_sub= inset_axes(axis_main, width=width_local, height=width_local, loc=3, 
                       bbox_to_anchor=(ilat_pie, ilon_pie),
                       bbox_transform=axis_main.transAxes, 
                       borderpad=0.0)
    wedges,texts= ax_sub.pie(dataframe_pie,colors=colors_dual)
    for w in wedges:
        w.set_linewidth(0.02)
        w.set_alpha(alpha_local)
        w.set_zorder(1)
    plt.axis('equal')
    # Put insets behind main axes
    ax_sub.set_zorder(axis_main.get_zorder()-1)

colors_dual=['RosyBrown','LightBlue']
lat_list= np.arange(0.2,0.7,0.05)

fig= plt.figure()
ax_main= plt.subplot(1,1,1,projection=ccrs.PlateCarree())
ax_main.coastlines()

# set background patch invisible, such that axes becomes transparent# since the GeoAxes from cartopy uses a different patch as background# the following does not work# ax_main.patch.set_visible(False)# so we need to set the GeoAxes' background_patch invisible
ax_main.background_patch.set_visible(False)

for ilat in np.arange(len(lat_list)):
    plot_pie_inset([75,25],lat_list[ilat],0.72,ax_main,0.2,0.9)

plt.show()

Solution 2:

An alternative solution suggest by a colleague neglects to use the inset_axes but achieves a similar result. The main difference is that the coordinate system in this solution is in the original latitude/longitude coordinates rather than figure coordinates.

def plot_pie_direct(dataframe_pie,ilat_pie,ilon_pie,axis_main,width_local,alpha_local):
    wedges,texts= ax_main.pie(dataframe_pie,colors=colors_aer_atm,radius=width_local)
    for w in wedges:
        w.set_linewidth(0.02)  ## Reduce linewidth to near-zero
        w.set_center((ilat_pie,ilon_pie))
        w.set_zorder(0)

fig= plt.figure()
ax_main= plt.axes(projection=ccrs.PlateCarree())
ax_main.coastlines(zorder=3)
ax_main.set_global()
lim_x= ax_main.get_xlim()
lim_y= ax_main.get_ylim()
for ilat in np.arange(len(lat_list_trim)):
    plot_pie_direct(frac_aer_atm_reshape_trim[:,ilat,ilon],x_val_pies[ilon],y_val_pies[ilat],ax_main,lat_list_diff_trim,0.9)

ax_main.coastlines(zorder=3)
ax_main.set_xlim(lim_x)
ax_main.set_ylim(lim_y)
plt.show()