.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/plot_13_globe.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_plot_13_globe.py: The world as a globe ==================== An orthographic projection turns the flat world into a sphere seen from space. The trick is to clip the data to the visible hemisphere before projecting (distant points would otherwise fold onto invalid coordinates), then draw on a dark background: * the Natural Earth shaded-relief raster (public domain), warped to the orthographic projection by ``docs/make_rasters.py`` and drawn with :class:`~mappyng.Raster`, plus a soft outer glow for the atmosphere; * a limb-darkening gradient on top, so the raster reads as a sphere; * a graticule from :class:`~mappyng.Graticule`, whose meridians and parallels now bend with the sphere; * great-circle air routes from Paris to African cities, whose width is proportional to the real 2024 passenger traffic on each route. .. GENERATED FROM PYTHON SOURCE LINES 19-119 .. raw:: html .. code-block:: Python import math from pathlib import Path import geopandas as gpd import pandas as pd from pyproj import Geod from shapely.geometry import LineString, Point import mappyng as mp R = 6378137.0 # Earth radius (metres) in the orthographic CRS LON0, LAT0 = 0, 12 # centre of the visible hemisphere ORTHO = f"+proj=ortho +lat_0={LAT0} +lon_0={LON0} +ellps=WGS84 +units=m +no_defs" AEQD = f"+proj=aeqd +lat_0={LAT0} +lon_0={LON0} +ellps=WGS84 +units=m +no_defs" # Visible hemisphere as a polygon in lon/lat: a disc of radius 90 degrees # (just under, to avoid the degenerate limb) built in an azimuthal # equidistant CRS, then expressed in WGS84. cap = gpd.GeoDataFrame( geometry=[Point(0, 0).buffer(R * math.pi / 2 * 0.985, resolution=180)], crs=AEQD).to_crs(4326) cap["geometry"] = cap.make_valid() # Ocean sphere. disc = gpd.GeoDataFrame(geometry=[Point(0, 0).buffer(R, resolution=256)], crs=ORTHO) # Air routes: great circles from Paris to African cities. The line width # encodes the real 2024 passenger traffic (Eurostat). Geod.npts samples the # geodesic, so the densified line bends correctly once projected. PARIS = (2.35, 48.85) traffic = pd.read_csv(Path("data") / "paris_africa_air_traffic.csv") geod = Geod(ellps="WGS84") lines = [LineString([PARIS] + geod.npts(PARIS[0], PARIS[1], lon, lat, 80) + [(lon, lat)]) for lon, lat in zip(traffic["lon"], traffic["lat"])] routes = gpd.GeoDataFrame({"pax": traffic["passengers_2024"]}, geometry=lines, crs=4326) routes = gpd.clip(routes, cap) routes = routes[~routes.is_empty].to_crs(ORTHO) pmin, pmax = routes["pax"].min(), routes["pax"].max() # City markers as small discs (point fills are not drawn, so buffer them). dots = gpd.GeoDataFrame( geometry=[Point(xy) for xy in zip(traffic["lon"], traffic["lat"])], crs=4326).to_crs(ORTHO) dots["geometry"] = dots.buffer(55000) paris = gpd.GeoDataFrame(geometry=[Point(PARIS)], crs=4326).to_crs(ORTHO) paris["geometry"] = paris.buffer(80000) # Limb darkening on top of the raster: transparent at the highlight, dark at # the edge, the focal point sitting up and to the left like a light source. shade = mp.RadialGradient( [(0.0, "#06121f", 0.0), (0.6, "#06121f", 0.0), (1.0, "#06121f", 0.6)], fx=0.36, fy=0.34) # Air routes, drawn above the shading so they stay bright. Line WIDTH is # proportional to 2024 passenger traffic, all in the same red. route_lines = [] for _, route in routes.iterrows(): t = (route["pax"] - pmin) / (pmax - pmin) line = gpd.GeoDataFrame(geometry=[route.geometry], crs=routes.crs) route_lines.append(mp.Vector(line, fill="none", stroke="#e63946", stroke_width=0.6 + 2.6 * t, stroke_linecap="round", position="top")) # Widen the frame beyond the disc so the atmosphere glow is not clipped by # the viewport edge (the bbox is the map's clipping window). margin = 0.18 * R m = ( mp.Map(disc, bbox=[-R - margin, -R - margin, R + margin, R + margin], width=860, height=860, padding=24, style={"base": "classic", "title_color": "#e8edf4"}, background="#070b18") + shade # Atmosphere: a centred, blurred glow of the disc shape. + mp.DropShadow(disc, dx=0, dy=0, blur=22, color="#48cae4", opacity=0.85, fill="#48cae4") # Stacking with explicit z values: atmosphere glow (z=1) < raster (2) < # graticule (3), so the grid shows over the whole sphere. + mp.Raster(paths={"globe": Path("data") / "relief_globe_ortho.tif"}, z=2) + mp.Graticule(step=20, stroke="#ffffff", opacity=0.35, stroke_width=0.6, z=3) + mp.Vector(disc, fill=shade.url, stroke="none", position="top") # A wide, faint red stroke under each route makes it glow. + mp.Vector(routes, fill="none", stroke="#e63946", stroke_width=4.0, stroke_opacity=0.16, stroke_linecap="round", position="top") + route_lines + mp.Vector(dots, fill="#e63946", stroke="#ffffff", stroke_width=0.4, position="top") + mp.Vector(paris, fill="#ffffff", stroke="#e63946", stroke_width=0.8, position="top") + mp.Title("Air routes from Paris", subtitle="Line width: 2024 passenger traffic") + mp.Source("Traffic: Eurostat (avia_par_fr, 2024) | " "Relief: Natural Earth") ) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.686 seconds) .. _sphx_glr_download_gallery_plot_13_globe.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_13_globe.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_13_globe.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_13_globe.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_