Article Outline
Python matplotlib example 'find antipode'
Functions in program:
def flip_geom(geom):
Modules used in program:
import shapely
import matplotlib.pyplot
import matplotlib
import cartopy
python find antipode
Python matplotlib example: find antipode
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
# Import modules ...
# NOTE: http://matplotlib.org/faq/howto_faq.html#matplotlib-in-a-web-application-server
import cartopy
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot
import shapely
# Import my module ...
try:
import pyguymer
except:
raise Exception("you need to have the Python module from https://github.com/Guymer/PyGuymer located somewhere in your $PYTHONPATH")
# List countries to find the antipodes of ...
avoids = [
"United Kingdom",
"United States",
]
# List global quadrants ...
quads = [
shapely.geometry.polygon.Polygon(
[
( 0.0, 0.0),
( 0.0, 90.0),
( 180.0, 90.0),
( 180.0, 0.0),
( 0.0, 0.0),
]
),
shapely.geometry.polygon.Polygon(
[
( 0.0, 0.0),
( 0.0, 90.0),
(-180.0, 90.0),
(-180.0, 0.0),
( 0.0, 0.0),
]
),
shapely.geometry.polygon.Polygon(
[
( 0.0, 0.0),
( 0.0, -90.0),
( 180.0, -90.0),
( 180.0, 0.0),
( 0.0, 0.0),
]
),
shapely.geometry.polygon.Polygon(
[
( 0.0, 0.0),
( 0.0, -90.0),
(-180.0, -90.0),
(-180.0, 0.0),
( 0.0, 0.0),
]
),
]
# Define function ...
def flip_geom(geom):
# Find limits of geometry ...
xmin, ymin, xmax, ymax = geom.bounds # [deg], [deg], [deg], [deg]
# Create list to hold its transposed coordinates ...
coords = []
# Loop over coordinates in the external ring, transpose them and add them to the list ...
for coord in geom.exterior.coords:
x, y = coord # [deg], [deg]
if xmin <= 0.0 and xmax <= 0.0:
coords.append((x + 180.0, -y))
elif xmin >= 0.0 and xmax >= 0.0:
coords.append((x - 180.0, -y))
else:
raise Exception("the geom crosses the anti-meridian")
# Check that coordinates were added ...
if len(coords) == 0:
raise Exception("no coords were added")
# Return polygon from the transposed coordinates of the geometry ...
return shapely.geometry.polygon.Polygon(coords)
# Create plot and make it pretty ...
fig = matplotlib.pyplot.figure(
figsize = (9, 6),
dpi = 300
)
ax = matplotlib.pyplot.axes(projection = cartopy.crs.Robinson())
ax.set_global()
pyguymer.add_map_background(ax, resolution = "large4096px")
ax.coastlines(
resolution = "10m",
color = "black",
linewidth = 0.1
)
# Add notable lines of latitude manually ...
y1 = 66.0 + 33.0 / 60.0 + 46.2 / 3600.0 # [deg]
y2 = 23.0 + 26.0 / 60.0 + 13.8 / 3600.0 # [deg]
matplotlib.pyplot.plot(
[-180.0, 180.0],
[ y1, y1],
transform = cartopy.crs.PlateCarree(),
color = "black",
linewidth = 0.1,
linestyle = ":"
)
matplotlib.pyplot.plot(
[-180.0, 180.0],
[ y2, y2],
transform = cartopy.crs.PlateCarree(),
color = "black",
linewidth = 0.1,
linestyle = ":"
)
matplotlib.pyplot.plot(
[-180.0, 180.0],
[0.0, 0.0],
transform = cartopy.crs.PlateCarree(),
color = "black",
linewidth = 0.1,
linestyle = ":"
)
matplotlib.pyplot.plot(
[-180.0, 180.0],
[-y2, -y2],
transform = cartopy.crs.PlateCarree(),
color = "black",
linewidth = 0.1,
linestyle = ":"
)
matplotlib.pyplot.plot(
[-180.0, 180.0],
[-y1, -y1],
transform = cartopy.crs.PlateCarree(),
color = "black",
linewidth = 0.1,
linestyle = ":"
)
# Find file containing all the country shapes ...
shape_file = cartopy.io.shapereader.natural_earth(
resolution = "10m",
category = "cultural",
name = "admin_0_countries"
)
# Loop over records ...
for record in cartopy.io.shapereader.Reader(shape_file).records():
# Set country opacity ...
# HACK: Depending on the resolution of the shape file that is loaded the
# country name is either "name" or "NAME".
alpha = 0.25
if "name" in record.attributes:
if record.attributes["name"] in avoids:
alpha = 0.5
elif "NAME" in record.attributes:
if record.attributes["NAME"] in avoids:
alpha = 0.5
else:
raise Exception("country record doesn't have a name")
# Create list to hold the transposed polygons ...
polys = []
# Loop over geometries ...
for geom in record.geometry.geoms:
# Find bounds ...
xmin, ymin, xmax, ymax = geom.bounds # [deg], [deg], [deg], [deg]
# Check if this geometry needs splitting ...
# NOTE: See https://en.wikipedia.org/wiki/180th_meridian#Software_representation_problems
if not (xmin < 0.0 and xmax < 0.0) and not (xmin > 0.0 and xmax > 0.0):
# Loop over quadrants ...
for quad in quads:
# Find intersection of geometry with quadrant ...
tmp1 = geom.intersection(quad)
# Skip this intersection if it is empty ...
if tmp1.is_empty:
continue
# Check how many polygons describe the intersection ...
if isinstance(tmp1, shapely.geometry.multipolygon.MultiPolygon):
# Loop over sub-intersections ...
for tmp2 in tmp1:
# Add flipped sub-intersection to list ...
polys.append(flip_geom(tmp2))
else:
# Add flipped intersection to list ...
polys.append(flip_geom(tmp1))
else:
# Add flipped geometry to list ...
polys.append(flip_geom(geom))
# Fill the country in ...
if len(polys) > 0:
ax.add_geometries(
polys,
cartopy.crs.PlateCarree(),
alpha = alpha,
edgecolor = "red",
facecolor = "red",
linewidth = 0.5
)
# Save map as PNG and optimise it ...
matplotlib.pyplot.savefig(
"find_antipode.png",
bbox_inches = "tight",
dpi = 300,
pad_inches = 0.1
)
matplotlib.pyplot.close("all")
pyguymer.optipng("find_antipode.png")
Python links
- Learn Python: https://pythonbasics.org/
- Python Tutorial: https://pythonprogramminglanguage.com