Difference between revisions of "Forecast plotting"

(Created page with "== Creating own forecast visualisations == Both the forecast plotting script and the website creation script is based on python. The plotting script uses dynlib, the webs...")
 
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== Creating own forecast visualisations ==
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Both the forecast plotting script and the website creation script is based on python. The plotting script uses [[dynlib]], the website creating script uses [https://www.djangoproject.com django] the same library that also drives [https://plikt.gfi.uib.no plikt.org].
  
Both the forecast plotting script and the website creation script is based on python. The plotting script uses [[dynlib]], the website creating script uses [https://www.djangoproject.com django] the same library that also drives [https://plikt.gfi.uib.no plikt.org].
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== Preparations ==
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=== Prepare dynlib ===
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To get started, make sure you have followed the procedures to setup dynlib. Use the [[dynlib#Use_the_centrally_installed_dynlib|Guide to use the centrally installed dynlib]]. If you want to start developing own diagnostics, follow also the [[dynlib#Quick_start_to_developing_with_dynlib|Quick start to developing with dynlib]].
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=== Obtain the example scripts ===
  
=== Preparations ===
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Example scripts as well as the actual forecast scripts currently used are available in a tar archive:
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<code>/Data/gfi/users/csp001/forecast_plotting.tar.bz2</code>. In that archive there are three folders called <code>examples</code>, <code>production</code> and <code>website</code>.
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# <code>examples</code> contains a thoroughly documented plot script and the necessary settings file that sets up the right paths and file name structure used for the forecasts.
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# <code>production</code> contains the currently used plot script, and the settings file contains also the colormaps developed by Franziska Menzel.
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# <code>website</code> contains the script and the template file used to create web pages fitting to the plots.
  
To get started, make sure you have followed one of the procedures to setup dynlib. Either use the [[dynlib#Use_the_centrally_installed_dynlib|Guide to use the centrally installed dynlib]], or if you want to start developing own diagnostics, use the [[dynlib#Quick_start_to_developing_with_dynlib|Quick start to developing with dynlib]].
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== Plotconf options ==

Revision as of 22:56, 5 June 2014

Both the forecast plotting script and the website creation script is based on python. The plotting script uses dynlib, the website creating script uses django the same library that also drives plikt.org.

Preparations

Prepare dynlib

To get started, make sure you have followed the procedures to setup dynlib. Use the Guide to use the centrally installed dynlib. If you want to start developing own diagnostics, follow also the Quick start to developing with dynlib.

Obtain the example scripts

Example scripts as well as the actual forecast scripts currently used are available in a tar archive: /Data/gfi/users/csp001/forecast_plotting.tar.bz2. In that archive there are three folders called examples, production and website.

  1. examples contains a thoroughly documented plot script and the necessary settings file that sets up the right paths and file name structure used for the forecasts.
  2. production contains the currently used plot script, and the settings file contains also the colormaps developed by Franziska Menzel.
  3. website contains the script and the template file used to create web pages fitting to the plots.

Plotconf options