ClImpact merge requestshttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests2024-03-15T18:44:16Zhttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/8Add subregion2024-03-15T18:44:16ZMartin Bergemannbergemann@dkrz.deAdd subregionhttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/7Caps variables2024-03-15T18:27:50ZEtor Lucio EceizaCaps variablespatched [here](https://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/blob/caps_variables/src/climpact/run_directory.py#L424) so it still can handle variable names extracted from the metadata that contain caps:
```python
@cached_pro...patched [here](https://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/blob/caps_variables/src/climpact/run_directory.py#L424) so it still can handle variable names extracted from the metadata that contain caps:
```python
@cached_property
def variables(self) -> list[str]:
"""The variables as they are stored in the dataset."""
return [
var
for var in self._dataset.data_vars
if (var in self._variables) or (var.lower() in self._variables) <---
]
```https://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/6lowercasing from databrowser solved for variables2023-07-03T12:32:57ZEtor Lucio Eceizalowercasing from databrowser solved for variablesthe indexation lowercases everything which is an issue for variables such as `sfcWind`. The dirty patch solves that.
I currently put this branch working on regiklim central repo because a user had a problem, the reason I was tinkering w...the indexation lowercases everything which is an issue for variables such as `sfcWind`. The dirty patch solves that.
I currently put this branch working on regiklim central repo because a user had a problem, the reason I was tinkering with the plugin.https://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/5Fix shape bug2022-09-15T13:47:19ZMartin Bergemannbergemann@dkrz.deFix shape bugMartin Bergemannbergemann@dkrz.deMartin Bergemannbergemann@dkrz.dehttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/4Remove print statements2022-08-22T06:13:55ZMartin Bergemannbergemann@dkrz.deRemove print statementsMartin Bergemannbergemann@dkrz.deMartin Bergemannbergemann@dkrz.dehttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/3Display runtime2022-08-15T15:09:57ZMartin Bergemannbergemann@dkrz.deDisplay runtimeDisplay output summary in results.Display output summary in results.Martin Bergemannbergemann@dkrz.deMartin Bergemannbergemann@dkrz.dehttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/2Fix isses associated with swift2022-06-20T17:38:45ZMartin Bergemannbergemann@dkrz.deFix isses associated with swiftThis fixes some swift issues. It also adds global lon/lat coordinates to the output dataThis fixes some swift issues. It also adds global lon/lat coordinates to the output dataMartin Bergemannbergemann@dkrz.deMartin Bergemannbergemann@dkrz.dehttps://gitlab.dkrz.de/ch1187/plugins4freva/climpact/-/merge_requests/1First attempt to of a plugin that processes climate model input data for impa...2022-03-19T07:05:32ZMartin Bergemannbergemann@dkrz.deFirst attempt to of a plugin that processes climate model input data for impact modelsThis is a first attempt for a plugin that chews through large output of multi-dimensional model output data and creates output files that can be used for processing impact model data.
During the writing of the plugin I realised that th...This is a first attempt for a plugin that chews through large output of multi-dimensional model output data and creates output files that can be used for processing impact model data.
During the writing of the plugin I realised that there are many potential pitfalls I would not be able to anticipate. Like what is the correct unit of each variable - `mm/h`, `mm/day`, `kg/m^2/second` etc. As a possible solution I decided to create a post-processing library that allows users to do such processing by them selves and beyond.
So the plugin does the following:
1. Open all netcdf-files, get the the variables select the desired time-range.
2. Select the region according to the shapefile in the data
3a. If not instructed otherwise create a field average across the time dimension
3b. If instructed other wise, do otherwise instead.
4. Save the output data to the cloud.
5. Prepare a jupyter notebook for post-processing.
The users either download the data from the cloud or use the processed jupyter notebook to make use of the data post-processing library.
@b381718 @b381377 @g300050 if you could try and have a look?
Docs can be found here: https://www-regiklim.dkrz.de/about/climpact/Martin Bergemannbergemann@dkrz.deMartin Bergemannbergemann@dkrz.de