Last Update: 02.05.2017
- Installation
- Global Map with Points & Lines
- Eccentric Ellipsoid
- WMTS (Earth at Night)
- Feature Creation
- Map Tile Acquisition
- Features
To install and begin using Cartopy, run the following commands in your computer's command line interface (Terminal on Mac, Command Prompt on Windows, etc.):
conda install -c scitools cartopy
Then run the following commands in the Julia command line:
using Conda
push!(Conda.CHANNELS, "https://conda.anaconda.org/scitools")
Conda.add("Cartopy")--
When using Python modules (of which Cartopy is an example) in Julia rather than in Python, the syntax generally changes as follows:
Python: ax.stock_img()
Julia: ax[:stock_img]()
As you can see, Julia simply replaces the . syntax with [:] syntax.
using PyPlot, PyCall
@pyimport cartopy.crs as ccrs
ax = axes(projection=ccrs.Robinson())
# make the map global rather than have it zoom in to the extents of any plotted data
ax[:set_global]()
ax[:stock_img]()
ax[:coastlines]()
scatter(-0.08, 51.53, transform=ccrs.PlateCarree(), zorder=4, s=40, linewidth=1.5, edgecolor="k", color="yellow")
scatter(132, 43.17, transform=ccrs.PlateCarree(), zorder=4, s=80, linewidth=2, edgecolor="b", color="c")
scatter(-58.3817, -34.6033, transform=ccrs.PlateCarree(), zorder=4, s=60, linewidth=2, edgecolor="g", color="orange")
plot([-0.08, 132], [51.53, 43.17], transform=ccrs.PlateCarree(), linewidth=3, "r")
plot([-58.3817, 132], [-34.6033, 43.17], transform=ccrs.Geodetic(), linewidth=3, "m")
title("Global Map with Points & Lines")
--
# Eccentric Ellipsoids
# This example demonstrates how the class:cartopy.crs.Globe can be used
# to define a highly eccentric elliptical model of a geoid. This globe
# definition is used in defining a Geostationary projection. The projection
# is then visualised with a Natural Earth image and coastlines, which have both
# been reprojected on the fly.
using PyPlot, PyCall
@pyimport cartopy.crs as ccrs
eccentric_globe = ccrs.Globe(semimajor_axis=1000, semiminor_axis=500, ellipse=nothing)
geostationary = ccrs.Geostationary(globe=eccentric_globe)
ax = axes(projection=geostationary)
ax[:stock_img]()
ax[:coastlines]()
title("Eccentric Ellipse")
--
# Interactive WMTS (Web Map Tile Service)
# This example demonstrates the interactive pan and zoom capability
# supported by an OGC web services Web Map Tile Service (WMTS) aware axes.
# The example WMTS layer is a single composite of data sampled over nine days
# in April 2012 and thirteen days in October 2012 showing the Earth at night.
# It does not vary over time.
# The imagery was collected by the Suomi National Polar-orbiting Partnership
# (Suomi NPP) weather satellite operated by the United States National Oceanic
# and Atmospheric Administration (NOAA).
using PyPlot, PyCall
@pyimport cartopy.crs as ccrs
url = "http://map1c.vis.earthdata.nasa.gov/wmts-geo/wmts.cgi"
layer = "VIIRS_CityLights_2012"
ax = axes(projection=ccrs.PlateCarree())
ax[:add_wmts](url, layer)
ax[:set_extent]([-15, 25, 35, 60])
title("Europe at Night April/October 2012")
--
using PyPlot, PyCall
@pyimport cartopy.crs as ccrs
@pyimport cartopy.feature as cfeature
ax = axes(projection=ccrs.PlateCarree())
ax[:set_extent]([80, 170, -45, 30])
# Put a background image on for nice sea rendering.
ax[:stock_img]()
# Create a feature for States/Admin 1 regions at 1:50m from Natural Earth
states_provinces = cfeature.NaturalEarthFeature(
category="cultural",
name="admin_1_states_provinces_lines",
scale="50m",
facecolor="none")
ax[:add_feature](cfeature.LAND)
ax[:add_feature](cfeature.COASTLINE)
ax[:add_feature](states_provinces, edgecolor="gray")
--
# Demonstrates cartopy's ability to draw map tiles which are downloaded on
# demand from the MapQuest tile server. Internally these tiles are then combined
# into a single image and displayed in the cartopy GeoAxes.
using PyCall
@pyimport cartopy.crs as ccrs
@pyimport cartopy.io.img_tiles as cimgt
matplotlib = pyimport("matplotlib")
matplotlib[:use]("tkagg")
plt = pyimport("matplotlib.pyplot")
transforms = pyimport("matplotlib.transforms")
# Target longitude/latitude coordinates (Eyjafjallajökull volcano).
coords = [-19.613333, 63.62]
# Create a MapQuest open aerial instance.
map_quest_aerial = cimgt.MapQuestOpenAerial()
# Create a GeoAxes in the tile's projection and limit its extent to a small lat/lon range.
ax = plt[:axes](projection=map_quest_aerial[:crs])
ax[:set_extent]([-22, -15, 63, 65])
# Add the MapQuest data at zoom level 8.
ax[:add_image](map_quest_aerial, 8)
# Add a marker at the target coordinates.
plt[:plot](coords[1], coords[2], marker="o", color="yellow", markersize=12,
alpha=0.7, transform=ccrs.Geodetic())
# Use the cartopy interface to create a matplotlib transform object
# for the Geodetic coordinate system. We will use this along with
# matplotlib's offset_copy function to define a coordinate system which
# translates the text by 25 pixels to the left.
geodetic_transform = ccrs.Geodetic()[:_as_mpl_transform](ax)
text_transform = transforms[:offset_copy](geodetic_transform, units="dots", x=-25)
# Add text 25 pixels to the left of the target.
plt[:text](coords[1], coords[2], "Eyjafjallajökull",
verticalalignment="center", horizontalalignment="right",
transform=text_transform,
bbox=Dict("facecolor"=>"wheat", "alpha"=>0.5, "boxstyle"=>"round"))
--
using PyPlot, PyCall
@pyimport cartopy.crs as ccrs
@pyimport cartopy.feature as cfeat
ax = axes(projection=ccrs.PlateCarree())
ax[:add_feature](cfeat.LAND)
ax[:add_feature](cfeat.OCEAN)
ax[:add_feature](cfeat.COASTLINE)
ax[:add_feature](cfeat.BORDERS, linestyle=":")
ax[:add_feature](cfeat.LAKES, alpha=0.5)
ax[:add_feature](cfeat.RIVERS)
ax[:set_extent]([-20, 60, -40, 40])
--