Dynlib

Documentation

The steps necessary to obtain dynlib are described below. A more thorough documentation is compiled in the main documentation website.

Quick start to developing with dynlib

• Before you compile you need to set up an environment where you will install the necessary libraries with the required version (e.g., numpy not newer than 1.26.2)

  $ python3 -m venv dyn

  $ pip install numpy==1.26.2

  $ pip install scipy python-dateutil

  $ pip install xarray pandas netcdf4 h5netcdf

  $ pip install python-dateutil

  $ pip install basemap==1.3.8 basemap-data-hires

• Then activate the environment

  $ source dyn/bin/activate

Obtaining dynlib

1. Copying the source code repository

   $ git clone /Data/gfi/users/local/src/dynlib.git

   To clone the repository to your laptop or any machine outside the UiB network, use

   $ git clone <username>@login.uib.no:/Data/gfi/users/local/src/dynlib.git

2. Change into the dynlib folder

   $ cd dynlib

3. Compile the library

   $ ./compile Make sure that the current hostname is recognised, if needed add the following lines to compile

   if [ "${host: -9}" == 'novalocal' ]; then    LIBS="-L$(pwd)/ext/spherepack3.2/lib -lopenblas -lscalapack -lspherepack"     RPATH="" #-Wl,-rpath,/Data/gfi/users/local/lib" and change host=`hostname -f` to host=`hostname`

4. Finally, you need to link external libraries

   export LD_LIBRARY_PATH="/cvmfs/software.eessi.io/versions/2023.06/software/linux/x86_64/generic/software/ScaLAPACK/2.2.0-gompi-2023b-fb/lib:/cvmfs/software.eessi.io/versions/2023.06/software/linux/x86_64/generic/software/OpenBLAS/0.3.24-GCC-13.2.0/lib"

5. To use your personal development version of dynlib, create a symlink in your scripts folder that points to the development version

   <in script folder>$ ln -s <path-to-dynlib>/lib dynlib

Editing the Fortran code

The fortran code lives in lib/fortran directory. At the moment there are 16 source code files

$ ls *.f90
config.f90             detect_lines.f90       ellipse.f90            stat.f90
const.f90              detect_rwb_contour.f90 interpol.f90           tend.f90
derivatives.f90        diag.f90               kind.f90               thermodyn.f90
detect.f90             diag_tend.f90          sphere.f90             utils.f90

The most important are diag.f90 which contains subroutines that calculate various diagnostics, and detect.f90 which contains feature detection algorithms. Changed Fortran sources need to be recompiled, again using

$ ./compile

Version control

The changes you made to the source code files can be listed by

$ git status

or viewed in detailed diff-comparisons by

$ git diff

or for one file only

$ git diff <filename>

In case you want to undo your changes, you can revert any file to the last committed version by

git checkout <filename>

Commit your changes from time to time and give a sensible and brief description of your changes in the editor that is opened (automatically)

$ git commit -a

The commit is then stored in your copy of the source code repository, but not yet available for others, which allows you to also commit work-in-progress.

A more thorough introduction to the version control system is given here or on the official documentation.

Using the Fortran functions

An example python script which calculates deformation using the Fortran function is provided in the documentation.

Dynlib functions

The functions are classified into different categories. All functions and categories listed in the API documentation.