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