Commit 77c1ad58 authored by Loic Huder's avatar Loic Huder
Browse files

Removed ref to versions in static files

parent c5a6c82c
......@@ -63,7 +63,7 @@ def algorithm(output_path, computation_name, config_file, nb_models, seed=None,
:type logging_level: logging level (https://docs.python.org/3.6/library/logging.html?highlight=logging#levels)
:param inline_save: indicates if the output files should be updated with the result at each step (default: True). Set to False may enhance performance but at the risk at losing data if the computation is aborted.
:type inline_save: bool
:param algo_name: name of the algorithm. As for now (0.7), the only supported algorithm is 'augkf'.
:param algo_name: name of the algorithm. As for now, the only supported algorithm is 'augkf'.
:type algo_name: str
:return: CoreStates containing all the results of the computation, the forecasts and analysis.
:rtype: CoreState, CoreState, CoreState
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......@@ -13,7 +13,7 @@ From Olivier Barrois, Nicolas Gillet, Loïc Huder, Yannick Martin and Franck Tho
### Requirements
The installation of GeDACCMU requires Python 3 (tested under 3.6) to be installed with the following packages:
* _setuptools_ (tested under 40.4.3): to be able to run `setup.py`.
* _setuptools_ (tested against 40.4.3): to be able to run `setup.py`.
* _numpy_ (at least 1.7): to be able to wrap Fortran files with _f2py_.
The other dependencies will be automatically installed by the next step but are listed here for the sake of completeness:
......@@ -64,7 +64,7 @@ The computation is launched by running `run_algo.py`. Several parameters can be
##### Scientific parameters
* `-conf`: the path to the configuration file to use (no default value: must be given)
* `-m`: the number of realisations to consider (default: sets to 2)
* `-algo`: the name of the algorithm to use. As for 0.7, the only supported algorithm is **augkf** (Augmented state Kalman Filter implemented in Python) which is the default value.
* `-algo`: the name of the algorithm to use. As for now, the only supported algorithm is **augkf** (Augmented state Kalman Filter implemented in Python) which is the default value.
* `-seed`: a number used for the generation of random quantities. Set this to get reproducible results (default: generate a new one at each execution).
##### Output files
* `-path`: path where the folder results will be created (default: `~/GeDACCMU_results/`).
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