From 6ff8c7d6aee4ccb01dc0647b1565dbf7ec8034a2 Mon Sep 17 00:00:00 2001 From: voigta80 <aiko.voigt@univie.ac.at> Date: Mon, 20 Jun 2022 00:15:26 +0200 Subject: [PATCH] Corrected typo in README --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index b7e1e3a..7c7223e 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ TriCCo is distributed under the GNU General Public License v3.0. The repository is organized as follows: * **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. +* **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 illustrate 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 -- GitLab