Skip to content
Snippets Groups Projects
Commit 49c26e0e authored by leufen1's avatar leufen1
Browse files

update in changelog, instructions and dist

parent 49238b68
No related branches found
No related tags found
2 merge requests!436Master,!431Resolve "release v2.1.0"
Pipeline #102142 passed
# Changelog # Changelog
All notable changes to this project will be documented in this file. All notable changes to this project will be documented in this file.
## v2.1.0 - 2022-06-07 - new evaluation metrics and improved training
### general:
* new evaluation metrics, IOA and MNMB
* advanced train options for early stopping
* reduced execution time by refactoring
### new features:
* uncertainty estimation of MSE is now applied for each season separately (#374)
* added different configurations of early stopping to use either last trained or best epoch (#378)
* train monitoring plots now add a star for best epoch when using early stopping (#367)
* new evaluation metric index of agreement, IOA (#376)
* new evaluation metric modified normalised mean bias, MNMB (#380)
* new plot available that shows temporal evolution of MSE for each station (#381)
### technical:
* reduced loading of forecast path from data store (#328)
* bug fix for not catched error during transformation (#385)
* bug fix for data handler with climate and fir filter leading to calculate transformation always with fir filter (#387)
* improved duration for latex report creation at end of preprocessing (#388)
* enhanced speed for make prediction in postprocessing (#389)
* fix to always create version badge from version and not from tag name (#382)
## v2.0.0 - 2022-04-08 - tf2 usage, new model classes, and improved uncertainty estimate ## v2.0.0 - 2022-04-08 - tf2 usage, new model classes, and improved uncertainty estimate
### general: ### general:
......
...@@ -34,7 +34,7 @@ HPC systems, see [here](#special-instructions-for-installation-on-jülich-hpc-sy ...@@ -34,7 +34,7 @@ HPC systems, see [here](#special-instructions-for-installation-on-jülich-hpc-sy
* Installation of **MLAir**: * Installation of **MLAir**:
* Either clone MLAir from the [gitlab repository](https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair.git) * Either clone MLAir from the [gitlab repository](https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair.git)
and use it without installation (beside the requirements) and use it without installation (beside the requirements)
* or download the distribution file ([current version](https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/dist/mlair-2.0.0-py3-none-any.whl)) * or download the distribution file ([current version](https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/dist/mlair-2.1.0-py3-none-any.whl))
and install it via `pip install <dist_file>.whl`. In this case, you can simply import MLAir in any python script and install it via `pip install <dist_file>.whl`. In this case, you can simply import MLAir in any python script
inside your virtual environment using `import mlair`. inside your virtual environment using `import mlair`.
......
File added
...@@ -27,7 +27,7 @@ Installation of MLAir ...@@ -27,7 +27,7 @@ Installation of MLAir
* Install all requirements from `requirements.txt <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/requirements.txt>`_ * Install all requirements from `requirements.txt <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/requirements.txt>`_
preferably in a virtual environment preferably in a virtual environment
* Either clone MLAir from the `gitlab repository <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair.git>`_ * Either clone MLAir from the `gitlab repository <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair.git>`_
* or download the distribution file (`current version <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/dist/mlair-2.0.0-py3-none-any.whl>`_) * or download the distribution file (`current version <https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/blob/master/dist/mlair-2.1.0-py3-none-any.whl>`_)
and install it via :py:`pip install <dist_file>.whl`. In this case, you can simply and install it via :py:`pip install <dist_file>.whl`. In this case, you can simply
import MLAir in any python script inside your virtual environment using :py:`import mlair`. import MLAir in any python script inside your virtual environment using :py:`import mlair`.
......
__version_info__ = { __version_info__ = {
'major': 2, 'major': 2,
'minor': 0, 'minor': 1,
'micro': 0, 'micro': 0,
} }
......
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment