Kernel: Python 3 (system-wide)
Cartopy Examples
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import cartopy cartopy.__version__
'0.18.0'
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import matplotlib.pyplot as plt import numpy as np import cartopy.crs as ccrs import cartopy.feature as cfeature def sample_data(shape=(20, 30)): """ Return ``(x, y, u, v, crs)`` of some vector data computed mathematically. The returned crs will be a rotated pole CRS, meaning that the vectors will be unevenly spaced in regular PlateCarree space. """ crs = ccrs.RotatedPole(pole_longitude=177.5, pole_latitude=37.5) x = np.linspace(311.9, 391.1, shape[1]) y = np.linspace(-23.6, 24.8, shape[0]) x2d, y2d = np.meshgrid(x, y) u = 10 * (2 * np.cos(2 * np.deg2rad(x2d) + 3 * np.deg2rad(y2d + 30))**2) v = 20 * np.cos(6 * np.deg2rad(x2d)) return x, y, u, v, crs fig = plt.figure() ax = fig.add_subplot(1, 1, 1, projection=ccrs.Orthographic(-10, 45)) ax.add_feature(cfeature.OCEAN, zorder=0) ax.add_feature(cfeature.LAND, zorder=0, edgecolor='black') ax.set_global() ax.gridlines() x, y, u, v, vector_crs = sample_data() ax.quiver(x, y, u, v, transform=vector_crs) plt.show()
/usr/local/lib/python3.8/dist-packages/cartopy/io/__init__.py:260: DownloadWarning: Downloading: https://naciscdn.org/naturalearth/110m/physical/ne_110m_ocean.zip
warnings.warn('Downloading: {}'.format(url), DownloadWarning)
/usr/local/lib/python3.8/dist-packages/cartopy/io/__init__.py:260: DownloadWarning: Downloading: https://naciscdn.org/naturalearth/110m/physical/ne_110m_land.zip
warnings.warn('Downloading: {}'.format(url), DownloadWarning)
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import matplotlib.pyplot as plt import cartopy.crs as ccrs from cartopy.examples.arrows import sample_data fig = plt.figure(figsize=(10, 5)) ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree()) ax.set_extent([-90, 75, 10, 85], crs=ccrs.PlateCarree()) ax.coastlines() x, y, u, v, vector_crs = sample_data(shape=(80, 100)) magnitude = (u**2 + v**2)**0.5 ax.streamplot(x, y, u, v, transform=vector_crs, linewidth=2, density=2, color=magnitude) plt.show()
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import matplotlib.patches as mpatches import matplotlib.pyplot as plt import shapely.geometry as sgeom import cartopy.crs as ccrs import cartopy.io.shapereader as shpreader def sample_data(): """ Return a list of latitudes and a list of longitudes (lons, lats) for Hurricane Katrina (2005). The data was originally sourced from the HURDAT2 dataset from AOML/NOAA: https://www.aoml.noaa.gov/hrd/hurdat/newhurdat-all.html on 14th Dec 2012. """ lons = [ -75.1, -75.7, -76.2, -76.5, -76.9, -77.7, -78.4, -79.0, -79.6, -80.1, -80.3, -81.3, -82.0, -82.6, -83.3, -84.0, -84.7, -85.3, -85.9, -86.7, -87.7, -88.6, -89.2, -89.6, -89.6, -89.6, -89.6, -89.6, -89.1, -88.6, -88.0, -87.0, -85.3, -82.9 ] lats = [ 23.1, 23.4, 23.8, 24.5, 25.4, 26.0, 26.1, 26.2, 26.2, 26.0, 25.9, 25.4, 25.1, 24.9, 24.6, 24.4, 24.4, 24.5, 24.8, 25.2, 25.7, 26.3, 27.2, 28.2, 29.3, 29.5, 30.2, 31.1, 32.6, 34.1, 35.6, 37.0, 38.6, 40.1 ] return lons, lats fig = plt.figure() # to get the effect of having just the states without a map "background" # turn off the background patch and axes frame ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.LambertConformal(), frameon=False) ax.patch.set_visible(False) ax.set_extent([-125, -66.5, 20, 50], ccrs.Geodetic()) shapename = 'admin_1_states_provinces_lakes_shp' states_shp = shpreader.natural_earth(resolution='110m', category='cultural', name=shapename) lons, lats = sample_data() ax.set_title('US States which intersect the track of ' 'Hurricane Katrina (2005)') # turn the lons and lats into a shapely LineString track = sgeom.LineString(zip(lons, lats)) # buffer the linestring by two degrees (note: this is a non-physical # distance) track_buffer = track.buffer(2) def colorize_state(geometry): facecolor = (0.9375, 0.9375, 0.859375) if geometry.intersects(track): facecolor = 'red' elif geometry.intersects(track_buffer): facecolor = '#FF7E00' return {'facecolor': facecolor, 'edgecolor': 'black'} ax.add_geometries(shpreader.Reader(states_shp).geometries(), ccrs.PlateCarree(), styler=colorize_state) ax.add_geometries([track_buffer], ccrs.PlateCarree(), facecolor='#C8A2C8', alpha=0.5) ax.add_geometries([track], ccrs.PlateCarree(), facecolor='none', edgecolor='k') # make two proxy artists to add to a legend direct_hit = mpatches.Rectangle((0, 0), 1, 1, facecolor="red") within_2_deg = mpatches.Rectangle((0, 0), 1, 1, facecolor="#FF7E00") labels = [ 'State directly intersects\nwith track', 'State is within \n2 degrees of track' ] ax.legend([direct_hit, within_2_deg], labels, loc='lower left', bbox_to_anchor=(0.025, -0.1), fancybox=True) plt.show()
/usr/local/lib/python3.8/dist-packages/cartopy/io/__init__.py:260: DownloadWarning: Downloading: https://naciscdn.org/naturalearth/110m/cultural/ne_110m_admin_1_states_provinces_lakes_shp.zip
warnings.warn('Downloading: {}'.format(url), DownloadWarning)
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from matplotlib.path import Path import matplotlib.pyplot as plt import numpy as np import cartopy.crs as ccrs from cartopy.io.img_tiles import OSM def tube_locations(): """ Return an (n, 2) array of selected London Tube locations in Ordnance Survey GB coordinates. Source: https://www.doogal.co.uk/london_stations.php """ return np.array([ [531738., 180890.], [532379., 179734.], [531096., 181642.], [530234., 180492.], [531688., 181150.], [530242., 180982.], [531940., 179144.], [530406., 180380.], [529012., 180283.], [530553., 181488.], [531165., 179489.], [529987., 180812.], [532347., 180962.], [529102., 181227.], [529612., 180625.], [531566., 180025.], [529629., 179503.], [532105., 181261.], [530995., 180810.], [529774., 181354.], [528941., 179131.], [531050., 179933.], [530240., 179718.], ]) imagery = OSM() fig = plt.figure() ax = fig.add_subplot(1, 1, 1, projection=imagery.crs) ax.set_extent([-0.14, -0.1, 51.495, 51.515], ccrs.PlateCarree()) # Construct concentric circles and a rectangle, # suitable for a London Underground logo. theta = np.linspace(0, 2 * np.pi, 100) circle_verts = np.vstack([np.sin(theta), np.cos(theta)]).T concentric_circle = Path.make_compound_path(Path(circle_verts[::-1]), Path(circle_verts * 0.6)) rectangle = Path([[-1.1, -0.2], [1, -0.2], [1, 0.3], [-1.1, 0.3]]) # Add the imagery to the map. ax.add_image(imagery, 14) # Plot the locations twice, first with the red concentric circles, # then with the blue rectangle. xs, ys = tube_locations().T ax.plot(xs, ys, transform=ccrs.OSGB(approx=False), marker=concentric_circle, color='red', markersize=9, linestyle='') ax.plot(xs, ys, transform=ccrs.OSGB(approx=False), marker=rectangle, color='blue', markersize=11, linestyle='') ax.set_title('London underground locations') plt.show()
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