#acl AdminGroup:read,write,delete,revert  EditorGroup:read,write,delete,revert All:read
#format wiki
#language en
#pragma section-numbers off


<<TableOfContents(3)>>

= Visualisation =

Python does not rely on one standard library for plotting and visualization, you have the choice to from several alternatives:

 * [[http://matplotlib.sourceforge.net/|matplotlib]] is becoming a quasi standard for plotting within the numpy/scipy/ipython environment and easy to use.
 * [[http://www.pyngl.ucar.edu/|PyNGL and PyNIO]] provide interfaces to the functionality existing in the NCAR Command Language (NCL).
 * [[http://code.enthought.com/projects/mayavi/|Mayavi Project - 3D Scientific Data Visualization and Plotting]]
 * [[http://www.pythonware.com/products/pil/|The Python Imaging Library (PIL) supports many file formats, and provides powerful image processing and graphics capabilities.]]
 * Interaction with other (non-Python) tools, e.g. [[http://www.soest.hawaii.edu/GMT/|The Generic Mapping Tools]], Google Earth


== 2 D Plots with Pylab ==

{{attachment:density.png}}

{{{#!python
from pylab import *
# The seawater module is installed only for Python2.6.2:
# module load Python/2.6.2 
import seawater

S=linspace(0,35)
T=linspace(-2,35.0)

rho=zeros((S.size,T.size))

for i,t in enumerate(T):
    rho[i,:]=seawater.dens(S,t)

figure()
CS = contour(S,T,rho,15,colors='k')
clabel(CS, fontsize=8, inline=1)
ylabel('Temperature [$^\circ$C]')
xlabel('Salinity')
title('Sea water density  [kg/m$^3$]')
show()
savefig('density.png',dpi=75)
}}}

== Basemap ==

The [[http://matplotlib.sourceforge.net/basemap/doc/html/| matplotlib basemap toolkit]] is a library for plotting 2D data on maps in Python.

{{attachment:Map1.png}}

{{{#!python
from pylab import *
from mpl_toolkits.basemap import Basemap

m = Basemap(projection='ortho',lon_0=10.0,lat_0=45.0,resolution='l')
m.bluemarble()

lon,lat=10.0,53.5 # Hamburg

x,y=m(lon,lat)
m.plot([x],[y],'r.')
    
show()
savefig('Map1.png',dpi=75)
}}}

Don't forget to set the correct path for using Basemap on ZMAW systems
{{{
module load Python
}}}

== GMT ==

{{attachment:map.png}}

[[http://gmt.soest.hawaii.edu/|GMT]] is an open source collection of ~60 tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing 
publication quality scientific plots.

In particular useful are the [[http://gmt.soest.hawaii.edu/gmt/examples/ex14/gmt_example_14.html|gridding routines]] which can be used for irregular sampled oceanographic as well as for satellite data.

GMT can be easily applied together with Python using the [[http://docs.python.org/library/os.html|os module]].

{{{#!python
import os
os.system('pscoast -R4/12/52/57 -JM6i -P -B1g1 -Ggray -Df > map.ps')
os.system('gv map.ps')
}}}



== Google Earth ==

{{attachment:600px-Google_earth_chlorophyll.png}}

Documentation:

http://code.google.com/apis/kml/documentation/

Chlorophyll data:

http://oceancolor.gsfc.nasa.gov/cgi/climatologies.pl

Download png and make black transparent

{{{
convert -transparent black A20020012007273.L3m_CU_CHLO_4.png A20020012007273.L3m_CU_CHLO_4_trans.png
}}}


Create ''.kml'' file


{{{
<?xml version="1.0"?>
<kml xmlns="http://earth.google.com/kml/2.1"><Document><name>Chlorophyll Climatology</name>
  <Folder>
<Snippet maxLines="0"/>
<name>MODIS</name>
<ScreenOverlay>
  <name>UHH Logo</name>
  <color>ffffffff</color>
  <visibility>1</visibility>
  <Icon>
    <href>http://www.ifm.uni-hamburg.de/logo_uhh_neu.gif</href>
  </Icon>
      <overlayXY x="0" y="1" xunits="fraction" yunits="fraction"/>
      <screenXY x="5" y="5" xunits="pixels" yunits="insetPixels"/>
      <size x="90" y="90" xunits="pixel" yunits="pixel"/>
</ScreenOverlay>
<LookAt>
	<longitude>8</longitude>
	<latitude>53</latitude>
	 <altitude>2000000</altitude>       
  <heading>0</heading>          
</LookAt>
<Folder> <Snippet maxLines="0"/>
<name>Chlorophyll</name><GroundOverlay> <name>2002-2007</name>
<visibility>1</visibility><color>ffffffff</color>
<Icon><href>A20020012007273.L3m_CU_CHLO_4_trans.png</href></Icon>
<LatLonBox><north>90</north><south>-90</south><east>180</east><west>-180</west></LatLonBox>
</GroundOverlay></Folder></Folder></Document></kml>
}}}

== Grads ==

http://opengrads.org/wiki/index.php?title=PyGrADS_Interactive_Shell

= Exercise =

Add to the above Basemap the air temperature from NCEP reanalyis as isolines:

{{{#!python
fid=io.netcdf_file('air.mon.mean.nc','r')
lat=array(fid.variables['lat'])
lon=array(fid.variables['lon'])
air=array(fid.variables['air'])
LON,LAT=meshgrid(lon,lat)
x,y=m(LON,LAT)
m.contour(x,y,air[753,:,:])
}}}