| 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 | |