Fix training and finalize dataset page
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30 changed files with 533 additions and 851 deletions
48
scripts/06static/hex_darts_v1.sh
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48
scripts/06static/hex_darts_v1.sh
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#!/bin/bash
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# Check if running inside the pixi environment
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which train >/dev/null 2>&1
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if [ $? -ne 0 ]; then
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echo "This script must be run inside the pixi environment."
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exit 1
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fi
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# Run some trainings on synopsis datasets for all different tasks + targets + grids + models
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grid="hex"
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target="darts_v1"
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# levels=(3 4 5 6)
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levels=(5 6)
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for level in "${levels[@]}"; do
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# Only apply ERA5 filter for hex-3, hex-4, healpix-6 and healpix-7
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if { [ "$grid" = "hex" ] && { [ "$level" -eq 3 ] || [ "$level" -eq 4 ]; }; } || { [ "$grid" = "healpix" ] && { [ "$level" -eq 6 ] || [ "$level" -eq 7 ]; }; }; then
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era5_dimension_filters="--dimension-filters.ERA5-shoulder.aggregations=median --dimension-filters.ERA5-seasonal.aggregations=median --dimension-filters.ERA5-yearly.aggregations=median"
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else
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era5_dimension_filters=""
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fi
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for task in binary density count; do
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for model in espa xgboost rf knn; do
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# Skip if task is density or count and model is espa because espa only supports binary
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if { [ "$task" = "density" ] || [ "$task" = "count" ]; } && [ "$model" = "espa" ]; then
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continue
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fi
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# Skip if task is count or density and model is rf because rf is super slow for regression tasks
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if { [ "$task" = "density" ] || [ "$task" = "count" ]; } && [ "$model" = "rf" ]; then
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continue
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fi
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# Set number of iterations (use less for slow models)
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if { [ "$model" = "knn" ] || [ "$model" = "rf" ]; }; then
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niter=5
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else
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niter=100
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fi
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echo
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echo "----------------------------------------"
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echo "Running training for grid=$grid, level=$level, target=$target, task=$task, model=$model"
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train --grid "$grid" --level "$level" --target "$target" --task "$task" --model "$model" --n-iter "$niter" --temporal-mode synopsis --experiment "static-variables" --dimension-filters.ArcticDEM.aggregations=median --dimension-filters.AlphaEarth.agg=median $era5_dimension_filters
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echo "----------------------------------------"
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echo
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done
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done
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done
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