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…n from the monthly averaged data
Addition of connecting to ERA5 monthly averaged data and extracting a bounding box
… delete ENSO_Prediction.ipynb
- Accessing the bounding box - Calculating the mean - Conversion of the pipeline data into an xarray object
…#139) * Update the introduction and added references and a reference section. * Add example of connecting to ERA5 and extracting a bounding box region from the monthly averaged data * Add a script that calculates nino3.4 index to ENSO_Forecast.ipynb and delete ENSO_Prediction.ipynb * Demonstrate the use of the pipeline for: - Accessing the bounding box - Calculating the mean - Conversion of the pipeline data into an xarray object --------- Co-authored-by: Tennessee Leeuwenburg <tennessee.leeuwenburg@bom.gov.au>
- Added a script that prepares a dataframe ready for machine learning, including target variables needed for 1-month lag forecasts with XGBoost and 3-month lag forecasts with MLP - Added a script that encodes 'month' into cyclic features; this is useful if we need to include month as a predictor, using 'month_sin' and 'month_cos' - minor: edited subheadings and cleaned comments Issue: I am using pet/2025.06, and there is no plotly library
…NSO_Forecast and ENSO_Pipeline
…n with the ML model predictions.
Add gridded MLP example (some more commentary and evaluation to be added but well on the way)
…died up, remove the working copies
Adds a tutorial showing: - Extracting and processing data - Training an XGBoost time-series model - Training an MLP time-series model - Training an MLP spatio-temporal model
Pull Request Test Coverage Report for Build 17001704787Details
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This branch supported a feature collaboration developing several notebooks for training a model for ENSO prediction. The work was merged from a fork into this feature branch and I am now merging it into the develop branch. See #145