"在具有不同 cartopy 投影的两个轴之间绘制多边形"

Question

我正在尝试在两个 cartopy 子图之间创建“缩放”效果（类似于 matplotlib mark_inset函数的想法），其中主图是Orthographic图，放大的子图是PlateCarree 。 到目前为止，我已经弄清楚了如何将它们与patches.ConnectionPatch()函数连接并使用patches.Polygon() () 标记子区域。

我还想绘制一个阴影多边形来覆盖两条连接线和两个子图之间的绘图区域。 但是，我似乎无法让多边形正确覆盖两个轴之间的整个区域（参见链接图）......我怀疑问题可能出在数据坐标和投影坐标之间的转换中？ 有人可以帮我找出我哪里出错了吗？ 谢谢！

添加连接补丁+多边形的功能：

def custom_mark_zoom(axA, axB, direction='right', extent=None, fc=None, ec='k', alpha=1, transform=None):
# starting point:
# https://stackoverflow.com/questions/51268493/drawing-filled-shapes-between-different-axes-in-matplotlib
import matplotlib.patches as patches
import numpy as np
import matplotlib as mpl

xx = [extent[0], extent[1]]
yy = [extent[2], extent[3]]
xy = (xx[0], yy[0])
width = xx[1] - xx[0]
height = yy[1] - yy[0]

xyB1 = (0,1)
xyB2 = (0,0)
xyA1 = transform.transform_point(60,-40,ccrs.PlateCarree())
xyA2 = transform.transform_point(90,-40,ccrs.PlateCarree())

coordsA='data'
coordsB='axes fraction'

# First mark the patch in the main axes
pp = axA.add_patch(patches.Rectangle(xy, width, height, fc=fc, ec=ec, zorder=5, alpha=alpha, transform=ccrs.PlateCarree()))

# now draw an anchor line to the zoomed in axis
p1 = axA.add_patch(patches.ConnectionPatch(
    xyA=xyA1, xyB=xyB1,
    coordsA=coordsA, coordsB=coordsB,
    axesA=axA, axesB=axB))

# draw a 2nd anchor line to the zoomed in axes
p2 = axA.add_patch(patches.ConnectionPatch(
    xyA=xyA2, xyB=xyB2,
    coordsA=coordsA, coordsB=coordsB,
    axesA=axA, axesB=axB))

# create polygon between the lines to add shading (creates a zoomed effect)
verts = np.concatenate([p1.get_path().vertices,np.flipud(p2.get_path().vertices),])
p3 = axA.add_patch(mpl.patches.Polygon(verts, fc=fc, clip_on=False, alpha=alpha))
    
return pp, p1, p2, p3

生成图形的代码：

import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs

# set up figure
fig = plt.figure(figsize=(35,20))
gs = fig.add_gridspec(6, 6)
# Increase resolution of projection - needed to draw polygons accurately
map_proj = ccrs.Orthographic(central_latitude=-90.0, central_longitude=0)
map_proj._threshold /= 100
ax = fig.add_subplot(gs[0:4, 0:2], projection=map_proj)
ax2 = fig.add_subplot(gs[0:3, 2:6], projection=ccrs.PlateCarree())

# define extent
extent = [60, 90, -54, -40]

# format ax1
gl = ax.gridlines(draw_labels=True,
                  lw=3,
                  color="silver",
                  y_inline=True,
                  xlocs=range(-180,180,30),
                  ylocs=range(-80,91,10),
                  zorder=3,
                  )
ax.set_extent([-180,180,-90,-30], crs=ccrs.PlateCarree())

def haversine(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in decimal degrees)
    
    see: https://stackoverflow.com/questions/4913349/haversine-formula-in-python-bearing-and-distance-between-two-gps-points
    """
    from math import radians, cos, sin, asin, sqrt
    # convert decimal degrees to radians 
    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])

    # haversine formula 
    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a)) 
    r = 6371 # Radius of earth in kilometers. Use 3956 for miles
    return c * r

# Create a circular map frame bounded by radius of map extent:
# see https://stackoverflow.com/questions/67877552/how-to-zoom-into-a-specific-latitude-in-cartopy-crs-orthographic
import matplotlib.path as mpath
r_limit = haversine(0,-90,0,-46)*1000 # convert km to m for CartoPy
circle_path = mpath.Path.unit_circle()
circle_path = mpath.Path(circle_path.vertices.copy() * r_limit,
                            circle_path.codes.copy())
# set circle boundary & extent
ax.set_boundary(circle_path)


# format ax2
gl = ax2.gridlines(draw_labels=True)
gl.top_labels = False
gl.right_labels = False
ax2.set_extent(extent)


# add the connection lines and shading
pp, p1, p2, p3 = custom_mark_zoom(ax, ax2, direction='right', extent=[60, 90, -54, -40], fc='lightgray', alpha=0.5, transform=map_proj)

用不正确的多边形生成的图