argopy.extensions.CanyonMED

class CanyonMED(*args, **kwargs)

Implementation of the CANYON-MED method.

CANYON-MED is a Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea ([1], [2]).

When using this method, please cite the papers.

Examples

Load data, they must contain oxygen measurements:

from argopy import DataFetcher
ArgoSet = DataFetcher(ds='bgc', mode='standard', params='DOXY', measured='DOXY').float(1902605)
ds = ArgoSet.to_xarray()

Once input data are loaded, make all or selected parameters predictions:

ds.argo.canyon_med.predict()
ds.argo.canyon_med.predict('PO4')
ds.argo.canyon_med.predict(['PO4', 'NO3'])

Notes

This Python implementation is largely inspired by work from Marine Fourrier (MarineFou) and Florian Ricour (fricour) from LOV.

First Python implementation was published here: euroargodev/CANYON-MED

References

[1]

Fourrier, M., Coppola, L., Claustre, H., D’Ortenzio, F., Sauzède, R., and Gattuso, J.-P. (2020). A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED. Frontiers in Marine Science 7. doi:10.3389/fmars.2020.00620.

[2]

Fourrier, M., Coppola, L., Claustre, H., D’Ortenzio, F., Sauzède, R., and Gattuso, J.-P. (2021). Corrigendum: A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED. Frontiers in Marine Science 8. doi:10.3389/fmars.2021.650509.

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
ds2df()	Create a CANYON-MED input pd.DataFrame from xr.Dataset
get_param_attrs(param)	Provides attributes to be added to a given predicted parameter
load_normalisation_factors(param[, subset])
load_weights(param, subset, i)
mask_medsea(df)	Mask points not in the Mediterranean Sea
param2suff(param)	File suffix to use for a given parameter to predict
predict([params])	Make predictions using the CANYON-MED neural network

Attributes

decimal_year	Return the decimal year of the xr.Dataset TIME variable
input	CANYON-MED input pd.DataFrame
ne	Number of inputs
output_list	List of parameters that can be predicted with this Neural Network