This repository contains the source files (LaTeX) and the figures necessary to generate the User Guide of the Diva (Data Interpolating Variational Analysis) tool.
Directly download the main documentation in pdf format.
The source files (.tex) in the source directory and the figures necessary to build the pdf.
.
├── DivaWorkshop
│ ├── figures
│ ├── SlidesDivaLecce2016
│ └── SlidesDivaWorkshop2015
├── src
│ ├── figures
│ │ ├── advection
│ │ ├── analysis
│ │ ├── divaonweb
│ │ ├── errors
│ │ ├── examples
│ │ ├── gallery
│ │ ├── GUI
│ │ ├── icones
│ │ ├── images
│ │ ├── papers
│ │ ├── postprocessing
│ │ ├── preprocessing
│ │ └── test_cases
│ └── old
└── tags
└── DivaUserGuide_March2013
└── figures
If you plan to edit the User Guide, here are some instructions.
The manual requires several LaTeX packages to be compiled; the header file contains the list package to be installed along with the commands for the layout.
You need to have LaTeX and BibTex installed on your machine in order to compile the sources.
cd src/
latex DivaUserGuide.tex
bibtex bibtex DivaUserGuide.aux
mkindex DivaUserGuide.tex
latex DivaUserGuide.tex
latex DivaUserGuide.tex- The 3rd line creates a list of references for the bibliography.
- The 4th line prepares the index.
- The last 2 lines are identical but necessary to obtain the correct references to the bibliography.
- Try to use the commands
\file{}
\command{}
\directory{}
in order to evidence the file, command and directory names.
Example:
"Execute \command{divafit}, and you get file \file{param.par.fit} in \directory{output}"-
Progressively add commands such as
\index{key-word}to build a consistent index. -
English: try to stick to British English.
DIVAndnd.jl performs n-dimensional variational analysis of arbitrarily located observations.
divand.py is the Python interface to the previous code (not maintained anymore).
DivaPythonTools is a set of utilies to read, write and plot the content of input or output files used in DIVA.