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| === The basemap way === The first step is the generation of an Basemap object which includes also the definition of the projection. Which projection to choose depends on your application. You might want to have a map with specific properties like e.g. equal area or equal angular and optimized for a specific region like e.g. the polar regions. |
=== The Basemap way === * '''Step 1:''' The first step is the generation of an Basemap object which includes also the definition of the projection. Which projection to choose depends on your application. You might want to have a map with specific properties like e.g. equal area or equal angular and optimized for a specific region like e.g. the polar regions. {{{#!python from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt import numpy as np #/// define a map projection /// map = Basemap(projection='ortho', lat_0 = 50, lon_0 = -100, resolution = 'l', area_thresh = 1000.) #to see a list of potential projections, type help(Basemap) #be aware that each projection has different types of parameters #... you like coastlines? map.drawcoastlines() #... and countries map.drawcountries() #... fill continents map.fillcontinents(color = 'coral') #... draw coordinates map.drawmeridians(np.arange(0, 360, 30)) map.drawparallels(np.arange(-90, 90, 30)) }}} |
Visualising spatial data
High level programming languages like e.g. Python, Matlab, R, IDL allow for the easy generation of maps by using specific modules. Alternatives to produce maps is special commerical or non-commercial software like e.g. ArcGIS, Generic mapping tool (GMT), ...
Map and projection basics
The Earth shape and it's approximation
How to do it in Python
There are different ways to generate maps with geographic information within Python. These are either based on the PyNGL (Gallery) or Basemap packages. PyNGL is very flexible to handle and allows for the generation of high quality maps. However, it takes a while to generate a nice looking map in PyNGL. If you just want to visualise your data, Basemap might be a very good alternative in many cases.
The Basemap way
Step 1: The first step is the generation of an Basemap object which includes also the definition of the projection. Which projection to choose depends on your application. You might want to have a map with specific properties like e.g. equal area or equal angular and optimized for a specific region like e.g. the polar regions.
1 from mpl_toolkits.basemap import Basemap
2 import matplotlib.pyplot as plt
3 import numpy as np
4
5 #/// define a map projection ///
6 map = Basemap(projection='ortho', lat_0 = 50, lon_0 = -100,
7 resolution = 'l', area_thresh = 1000.)
8
9 #to see a list of potential projections, type help(Basemap)
10 #be aware that each projection has different types of parameters
11
12 #... you like coastlines?
13 map.drawcoastlines()
14
15 #... and countries
16 map.drawcountries()
17
18 #... fill continents
19 map.fillcontinents(color = 'coral')
20
21 #... draw coordinates
22 map.drawmeridians(np.arange(0, 360, 30))
23 map.drawparallels(np.arange(-90, 90, 30))
Load some vector data
References:
- Snyder: Map projections - a reference manual