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== 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)
}}}
Line 13: Line 41:
[[attachment:Map1.png]] 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}}
Line 30: Line 60:

Set the correct path for using Basemap
{{{
module load R/2.7.0
module load Python/2.6.2
}}}

== 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

Contents

  1. Visualisation
    1. 2 D Plots with Pylab
    2. Basemap
    3. GMT
    4. Google Earth
    5. Grads

Visualisation

2 D Plots with Pylab

density.png 

   1 from pylab import *
   2 # The seawater module is installed only for Python2.6.2:
   3 # module load Python/2.6.2 
   4 import seawater
   5 
   6 S=linspace(0,35)
   7 T=linspace(-2,35.0)
   8 
   9 rho=zeros((S.size,T.size))
  10 
  11 for i,t in enumerate(T):
  12     rho[i,:]=seawater.dens(S,t)
  13 
  14 figure()
  15 CS = contour(S,T,rho,15,colors='k')
  16 clabel(CS, fontsize=8, inline=1)
  17 ylabel('Temperature [$^\circ$C]')
  18 xlabel('Salinity')
  19 title('Sea water density  [kg/m$^3$]')
  20 show()
  21 savefig('density.png',dpi=75)

Basemap

The matplotlib basemap toolkit is a library for plotting 2D data on maps in Python.

Map1.png 

   1 from pylab import *
   2 from mpl_toolkits.basemap import Basemap
   3 
   4 m = Basemap(projection='ortho',lon_0=10.0,lat_0=45.0,resolution='l')
   5 m.bluemarble()
   6 
   7 lon,lat=10.0,53.5 # Hamburg
   8 
   9 x,y=m(lon,lat)
  10 m.plot(x,y,'r.')
  11     
  12 show()
  13 savefig('Map1.png',dpi=75)

Set the correct path for using Basemap 

module load R/2.7.0
module load Python/2.6.2

GMT

map.png

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 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 os module. 

   1 import os
   2 os.system('pscoast -R4/12/52/57 -JM6i -P -B1g1 -Ggray -Df > map.ps')
   3 os.system('gv map.ps')

Google Earth

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

LehreWiki: OpenSource2010/Lesson6 (last edited 2010-11-22 12:55:36 by anonymous)