Getting Started
RASCAL is available to download in PyPi and GitHub. To install RASCAL, it is recommended to create a new environment to avoid possible conflicts with its required dependencies.
(base) $ conda create --name rascal_env python==3.10
(base) $ conda activate rascal_env
Required dependencies
RASCAL runs with Python 3.10.
These are the dependencies of RASCAL:
Warning
Some computers have problems with the cfgrib library and its eccodes dependencies, despite install them, sometimes it raises: “RuntimeError: Cannot find the ecCodes library”. To sove this, install the library ecmwflibs in your virtual environment.
(base) $ conda activate rascal_env
(rascal_env) $ pip install ecmwflibs
Installation via PyPi
RASCAL can be installed via PyPi:
(rascal_env) $ pip install rascal-ties
Installation via GitHub
RASCAL can be used via GitHub:
(rascal_env) $ git clone https://github.com/alvaro-gc95/RASCAL
The GitHub repository also contains the following scripts:
multiple_runs_example.py
to automatize running several configurations of similarity methods and pool sizes for various stations and variables. This can be configured through theconfig.yaml
file
projection_example.py
Mostly the same asmultiple_runs_example.py
, but including a split in training and testing periods for the PCA, and an added year as a projection onto the training period PCs
RASCAL_evaluation.ipynb
a Jupyter Notebook to plot and validate the reconstructions