Emulators¶

Short-term emulator¶

Emulator (Gaussian Process Regressor) of WRFChem.
GitHub repository

Scripts¶

Merge shapefiles into a single multi-polygon (create_merged_shapefile.ipynb).
Crop emissions data to China shapefile training (emis_apply_mask_train.py) and test (emis_apply_mask_test.py) data.
Design of Latin hypercube designs (latin_hypercube.ipynb).
Output of Latin hypercube designs for training (latin_hypercube_inputs_training.csv) and test (latin_hypercube_inputs_test.csv) data.
Automatic machine learning tool (TPOT) using genetic programming to optimise model pipeline on 50 random grid cells (tpot_optimiser.py), with outputs in the tpot_gridcells folder (tpot_emulator_pipeline_PM2_5_DRY_*.py).
Configuration for TPOT based on Gaussian process regresor (config_regressor_gaussian.py).
Emulator cross-validation and sensitivity analysis (emulator.ipynb). Interactively computed on a HPC using Dask and Jupyter Lab following instructions here.
Emulator predictions for custom inputs (emulator_predictions.py). Submitted to HPC (emulator_predictions.bash) using Dask for workers viewing worker status on Jupyter Lab. Can submit in batch mode (emulator_predictions_batch.bash).
Regrid custom outputs to population grid of the world (regrid_to_popgrid.py). Submitted to HPC (regrid_to_popgrid.bash) using Dask for workers viewing worker status on Jupyter Lab. Can submit in batch mode (regrid_to_popgrid_batch.bash).
Crop population-weighted output predictions to region’s shapefile (popweighted_region.py). Submitted to HPC (popweighted_region.bash) using Dask for workers viewing worker status on Jupyter Lab. Uses cropping functions (cutshapefile.py).
Various emulator plots including emulator evaluation, sensitivity maps, prediction maps, and 2D contour pairs, (emulator_plots.ipynb).

Setup Python environment¶

Create a conda environment with the required libraries from the config file (.yml) in the repository:

conda env create --name pangeo --file=pangeo.yml  
pip install salib dask_labextension pyarrow  
jupyter labextension install dask-labextension  
jupyter labextension install @jupyter-widgets/jupyterlab-manager  

License¶

This code is currently licensed under the GPLv3 License, free of charge for non-commercial use.

Long-term Emulator¶

Emulator (Gaussian Process Regressor) of WRFChem.
GitHub repository

Scripts¶

For other scripts designing the emulator see other repository.
Concatenate simulator data for the year (concat_simulation_data.ipynb).
Verification plots of monthly simulation data (check_simulation_data.ipynb).
Create ozone seasonal metric from simulator runs (create_o3_metric.py). Submitted to HPC (create_o3_metric.bash) using Dask for workers viewing worker status on Jupyter Lab.
Create ozone seasonal metric for measurements (create_o3_metric_measurements.py and create_o3_metric_measurements.bash).
Create emulator input dictionaries (create_emulator_inputs_outputs_df_crop).
Emulator cross-validation and sensitivity analysis (emulator_creation.ipynb). Interactively computed on a HPC using Dask and Jupyter Lab following instructions here.
Emulator predictions for custom inputs (emulator_predictions.py). Submitted to HPC (emulator_predictions.bash) using Dask for workers viewing worker status on Jupyter Lab. Can submit in batch mode (emulator_predictions_batch.bash).
Regrid custom outputs to population grid of the world (regrid_to_popgrid.py). Submitted to HPC (regrid_to_popgrid.bash) using Dask for workers viewing worker status on Jupyter Lab. Can submit in batch mode (regrid_to_popgrid_batch.bash).
Crop population-weighted output predictions to region’s shapefile (popweighted_region.py). Submitted to HPC (popweighted_region.bash) using Dask for workers viewing worker status on Jupyter Lab. Uses cropping functions (cutshapefile.py).
Create shapefile clips for the each country, province, and prefecture used in the health impact assessment (create_shapefile_clips.ipynb).
Long-term health impact assessment per configuration (health_impacts_per_emission_configuration.py). Submitted to HPC (health_impacts_per_emission_configuration.bash) using Dask for workers viewing worker status on Jupyter Lab. Can submit in batch mode (health_impacts_per_emission_configuration.bash).
Bottom-up matching of emission configurations that match recent air quality trends (find_emissions_that_caused_air_quality_change.py and find_emissions_that_caused_air_quality_change.bash), splitting by region in (find_emissions_that_caused_air_quality_change.ipynb).
Various emulator plots including emulator evaluation, sensitivity maps, prediction maps, and 2D contour pairs, (emulator_plots.ipynb).

Setup Python environment¶

Create a conda environment with the required libraries from the config file (.yml) in the repository:

conda env create --name pangeo --file=pangeo_latest.yml  
pip install salib dask_labextension pyarrow  
jupyter labextension install dask-labextension  
jupyter labextension install @jupyter-widgets/jupyterlab-manager  