From f51bb07481d290b8d457914085233e311730d27d Mon Sep 17 00:00:00 2001 From: voigta80 <aiko.voigt@univie.ac.at> Date: Mon, 20 Jun 2022 00:10:35 +0200 Subject: [PATCH] Update README to include alternative imethods and the Levante benchmarks --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 4779a33..b7e1e3a 100644 --- a/README.md +++ b/README.md @@ -7,9 +7,9 @@ TriCCo is distributed under the GNU General Public License v3.0. ## Repository structure The repository is organized as follows: -* **tricco** contains the actual python code. -* **examples** contains two jupyter notebooks that illustrate the use of TriCCo for 2-d data on a single model level and for 3-d data on multiple model levels. The subdirectory data contains the grid and model output from the ICON atmosphere model that is needed to run the notebooks. The plots generated by the notebooks are included as separated pdf files. `find_radius.py` illustrates how the diagnostic output of `tricco.compute_cubulation` can be used to determine the search radius. `find_start.py` can be used to find the triangular cell closest to a given latitude-longitude position. Note that `find_start.py` is written for a grid from the ICON model. -* **benchmarks** contains scripts that were used to characterize the computational performance of TriCCo on the Mistral DKRZ supercomputer. +* **tricco** contains the actual python code. The subdirectory alternatives constains functions for altnernative methods for connected component labeling. +* **examples** contains two jupyter notebooks that illustrate the use of TriCCo for 2-d data on a single model level and for 3-d data on multiple model levels. The subdirectory data contains the grid and model output from the ICON atmosphere model that is needed to run the notebooks. The plots generated by the notebooks are included as separated pdf files. `find_radius.py` illustrates how the diagnostic output of `tricco.compute_cubulation` can be used to determine the search radius. `find_start.py` can be used to find the triangular cell closest to a given latitude-longitude position. Note that `find_start.py` is written for a grid from the ICON model. There are also two jupyter notebooks that illustrated the use of the alternative methods. +* **benchmarks** contains scripts that were used to characterize the computational performance of TriCCo on the Mistral and Levante DKRZ supercomputers. ## Installation @@ -32,6 +32,8 @@ TriCCo has been developed by: The development of TriCCo was supported by funding from a YIN Award of the Young Investigator Network of Karlsruhe Institute of Technology, from the MathSEE Centre of Karlsruhe Institute of Technology, and from the German Ministry of Education and Research (BMBF) and FONA: Research for Sustainable Development under grant 01LK1509A. +We also acknowledge support from the German Climate Computing Center DKRZ in Hamburg, Germany, whose HPC systems Mistral and Levante we have used to develop and benchmark TriCCo. + TriCCo uses a couple of other python libraries, and we are very grateful to the communities of developers and maintainers of these libraries. The libraries are: - numpy, https://numpy.org/ - xarray, http://xarray.pydata.org/ -- GitLab