seed: 42
data:
  root: data
  format_version: cme_structured_var_seasonal_v1
  samples: 1
  time_steps: 2100
  nodes: 50
  seasons: [DJF, MAM, JJA, SON]
  model_count: 4
  grid_shape: [73, 144]
  years_per_segment: 70
  time_step_days: 3
model:
  max_lag: 10
  alpha: 0.02
  ridge: 1.0e-6
  exclude_self_links: true
paper_model:
  nodes: 50
  time_step_days: 3
  max_lag: 10
  maximum_delay_days: 30
  alpha: 1.0e-4
  method: PCMCI with partial correlation
  engineering_approximation: target-history conditional regression with partial correlation
evaluation:
  lag_tolerance: 2
  reference_f1_for_projection: 0.64
paths:
  dataset: data/cme_fake.npz
  checkpoint: result/checkpoints/causalmodelevaluation.pt
  training_metrics: result/training/metrics.json
  inference: result/output/inference.npz
  evaluation_dir: result/evaluation