3D CartoPy类似于Matplotlib-Basemap

Question

我是Python的新手,关于Cartopy能够在3D情节中使用的问题.以下是使用的示例matplotlibBasemap.

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.basemap import Basemap

m = Basemap(projection='merc',
            llcrnrlat=52.0,urcrnrlat=58.0,
            llcrnrlon=19.0,urcrnrlon=40.0,
            rsphere=6371200.,resolution='h',area_thresh=10)

fig = plt.figure()
ax = Axes3D(fig)
ax.add_collection3d(m.drawcoastlines(linewidth=0.25))
ax.add_collection3d(m.drawcountries(linewidth=0.35))
ax.add_collection3d(m.drawrivers(color='blue'))

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Height')

fig.show()

这将在3D轴内创建一个贴图,以便您可以在曲面上绘制对象.但随着Cartopy回归matplotlib.axes.GeoAxesSubplot.不清楚如何拍摄并添加到上面的3D图形/轴上matplotlib-basemap.

那么,有人可以提供有关如何使用Cartopy进行类似3D绘图的任何指示吗？

Answer 1

底图mpl3d是一个非常简洁的黑客,但它没有被设计为以所描述的方式运行.因此,除了简单的海岸线之外,您目前无法使用相同的技术.例如,填补的大陆只是不工作AFAICT.

也就是说,使用cartopy时可以使用类似的hack.由于我们可以一般地访问shapefile信息,因此该解决方案适用于任何多线形状文件,例如海岸线.

第一步是获取shapefile和相应的几何:

feature = cartopy.feature.NaturalEarthFeature('physical', 'coastline', '110m')
geoms = feature.geometries()

接下来,我们可以将这些转换为所需的投影:

target_projection = ccrs.PlateCarree()
geoms = [target_projection.project_geometry(geom, feature.crs)
         for geom in geoms]

由于这些是几何形状,我们希望将它们转换为matplotlib路径:

from cartopy.mpl.patch import geos_to_path
import itertools

paths = list(itertools.chain.from_iterable(geos_to_path(geom)
                                             for geom in geoms))

使用路径,我们应该能够在matplotlib中创建一个PathCollection,并将其添加到轴中,但遗憾的是,Axes3D似乎无法处理PathCollection实例,因此我们需要通过构造LineCollection来解决这个问题(如底图一样) ).可悲的是,LineCollections不会采用路径,而是采用我们可以计算的段:

segments = []
for path in paths:
    vertices = [vertex for vertex, _ in path.iter_segments()]
    vertices = np.asarray(vertices)
    segments.append(vertices)

将这些全部拉到一起,我们最终会得到与您的代码生成的底图图类似的结果:

import itertools

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np

import cartopy.feature
from cartopy.mpl.patch import geos_to_path
import cartopy.crs as ccrs


fig = plt.figure()
ax = Axes3D(fig, xlim=[-180, 180], ylim=[-90, 90])
ax.set_zlim(bottom=0)


target_projection = ccrs.PlateCarree()

feature = cartopy.feature.NaturalEarthFeature('physical', 'coastline', '110m')
geoms = feature.geometries()

geoms = [target_projection.project_geometry(geom, feature.crs)
         for geom in geoms]

paths = list(itertools.chain.from_iterable(geos_to_path(geom) for geom in geoms))

# At this point, we start working around mpl3d's slightly broken interfaces.
# So we produce a LineCollection rather than a PathCollection.
segments = []
for path in paths:
    vertices = [vertex for vertex, _ in path.iter_segments()]
    vertices = np.asarray(vertices)
    segments.append(vertices)

lc = LineCollection(segments, color='black')

ax.add_collection3d(lc)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Height')

plt.show()

除此之外,mpl3d似乎很好地处理PolyCollection,这将是我将研究填充几何的路线,例如陆地轮廓(与海岸线相对,严格地说是轮廓).

重要的一步是将路径转换为多边形,并在PolyCollection对象中使用它们:

concat = lambda iterable: list(itertools.chain.from_iterable(iterable))

polys = concat(path.to_polygons() for path in paths)
lc = PolyCollection(polys, edgecolor='black',
                    facecolor='green', closed=False)

这种情况的完整代码如下所示:

import itertools

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection, PolyCollection
import numpy as np

import cartopy.feature
from cartopy.mpl.patch import geos_to_path
import cartopy.crs as ccrs


fig = plt.figure()
ax = Axes3D(fig, xlim=[-180, 180], ylim=[-90, 90])
ax.set_zlim(bottom=0)


concat = lambda iterable: list(itertools.chain.from_iterable(iterable))

target_projection = ccrs.PlateCarree()

feature = cartopy.feature.NaturalEarthFeature('physical', 'land', '110m')
geoms = feature.geometries()

geoms = [target_projection.project_geometry(geom, feature.crs)
         for geom in geoms]

paths = concat(geos_to_path(geom) for geom in geoms)

polys = concat(path.to_polygons() for path in paths)

lc = PolyCollection(polys, edgecolor='black',
                    facecolor='green', closed=False)

ax.add_collection3d(lc)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Height')

plt.show()

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