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Authors: Harald Schilly, ℏal Snyder
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CartoPy in SageMathCloud

CartoPy in SageMathCloud

AuthorHarald Schilly
Date2017-01-10T00:15:13
Project94169f5c-20cd-43f0-9bfd-8c62c9c56e6c
Locationcartopy.sagews
Original filecartopy.sagews

CartoPy in SageMathCloud

CartoPy

# setting Anaconda python3 to be the default back-end
%auto%default_mode python3
import matplotlib.patches as mpatchesimport matplotlib.pyplot as pltimport shapely.geometry as sgeomimport cartopy.crs as ccrsimport cartopy.io.shapereader as shpreaderdef sample_data():    """    Returns 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:    http://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, latsdef main():    ax = plt.axes([0, 0, 1, 1],                  projection=ccrs.LambertConformal())    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()    # to get the effect of having just the states without a map "background"    # turn off the outline and background patches    ax.background_patch.set_visible(False)    ax.outline_patch.set_visible(False)    plt.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)    for state in shpreader.Reader(states_shp).geometries():        # pick a default color for the land with a black outline,        # this will change if the storm intersects with our track        facecolor = [0.9375, 0.9375, 0.859375]        edgecolor = 'black'        if state.intersects(track):            facecolor = 'red'        elif state.intersects(track_buffer):            facecolor = '#FF7E00'        ax.add_geometries([state], ccrs.PlateCarree(),                          facecolor=facecolor, edgecolor=edgecolor)    ax.add_geometries([track_buffer], ccrs.PlateCarree(),                      facecolor='#C8A2C8', alpha=0.5)    ax.add_geometries([track], ccrs.PlateCarree(),                      facecolor='none')    # 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']    plt.legend([direct_hit, within_2_deg], labels,               loc='lower left', bbox_to_anchor=(0.025, -0.1), fancybox=True)    fig = plt.gcf()    fig.set_figwidth(12)    fig.set_figheight(7)    plt.show()if __name__ == '__main__':    main()