| seed: 42 | |
| data: | |
| path: data/precip_extremes_gan_fake.npz | |
| format_version: precip_extremes_gan_v1 | |
| samples_per_period: 16 | |
| low_grid: [24, 24] | |
| high_grid: [96, 96] | |
| input_channels: 8 | |
| log_epsilon: 0.001 | |
| model: | |
| filters: [8, 16, 32] | |
| noise_channels: 1 | |
| train: | |
| baseline_epochs: 1 | |
| gan_epochs: 1 | |
| batch_size: 2 | |
| baseline_lr: 0.0007 | |
| gan_lr: 0.0002 | |
| adversarial_weight: 0.01 | |
| intensity_weight: 1.0 | |
| runtime: | |
| device: cpu | |
| paths: | |
| checkpoint: result/checkpoints/precip_extremes_gan.pt | |
| training_metrics: result/training/metrics.json | |
| predictions: result/output/predictions.npz | |
| evaluation: result/evaluation/metrics.json | |
| figure: result/evaluation/comparison.png | |
| evaluation: | |
| ensemble_members: 3 | |
| extreme_percentile: 99.5 | |
| wet_day_threshold: 1.0 | |
| paper_model: | |
| filters: [32, 64, 128] | |
| parameters_baseline: 1500000 | |
| epochs: 250 | |
| batch_size: 32 | |
| adversarial_weight: 0.01 | |
| ensemble_members: 10 | |
| historical_period: 1960-2014 | |
| future_period: 2044-2099 | |
| evaluation_historical: 1985-2014 | |
| evaluation_future: 2070-2099 | |