Initialise a model experiment instance#
Download cGENIE output from cluster#
The first step starts from getting data from the cluster. If it is in tar.gz format then uncompress it. Otherwise, directly download as a folder.
$ scp -r remote:cgenie_output/experiment_id ~/Downloads
For test, an example output is already attached with the package under directory cgeniepy/src/data/muffin.CBE.worlg4.BASESFeTDTL.SPIN. This is an modern configuration with ecosystem component enabled.
Initialise a model instance#
The next step is to initialise a model experiment instance. Two parameters are needed: (1) the directory path (e.g., muffin.CBE.worlg4.BASESFeTDTL.SPIN); (2) the target sub-model (e.g., biogem or ecogem). The default of sub-model is biogem, but if you want to access more data, you can create of gemflag.
from cgeniepy.model import GenieModel
model = GenieModel('/Users/XX/Downloads/path_a', gemflag=['biogem', 'ecogem'])
The model also support multiple experiment directory. The only change is to use a list of directories as input. This list can be create by yourself, or use Python’s Pathlib module.
# Model ensemble
model_dir = ['/path_a/', '/path_b/']
models = GenieModel(model_dir)
## Alternatively
from pathlib import Path
model_dir = Path("XX/model")
models = GenieModel(model_path)