# Visualization Suite (no code changes)

This folder adds **standalone** visualization scripts. It does **not** modify any existing training/inference code.

## Quick start

1. Prepare prediction folders for each method (ours + baselines).  
   Supported formats (per-case):
   - `*_label.nii.gz` (label map, values {0,1,2,4})
   - `*_regions_prob.nii.gz` (probabilities for WT/TC/ET)
   - `*_regions_bin.nii.gz` (binary WT/TC/ET)
   - `{case_id}.nii.gz` (SegMamba 3-channel)

2. Copy and edit the config:
   ```bash
   cp visualizations/vis_config_example.yaml visualizations/vis_config.yaml
   ```

3. Run (full suite):
   ```bash
   python visualizations/vis_suite.py --config visualizations/vis_config.yaml --checkpoint /path/to/ckpt.pt --run all
   ```

4. Run a subset (comma-separated):
   ```bash
   python visualizations/vis_suite.py --config visualizations/vis_config.yaml --checkpoint /path/to/ckpt.pt --run qualitative,et_absent,boundary
   ```

## Notes

- Model-dependent visualizations (`et_absent`, `moe`, `dual_domain`, `ampmix`) require `--checkpoint`.
- Aux outputs (pi_ET, MoE routing, spectral outputs) are cached to `predictions.aux_dir` when provided.
- Output figures are saved to `visualization.output_dir` (default: `visualizations/outputs`).
- If `matplotlib` is missing, install it in your environment.