Add new scripts and configurations for model comparison and analysis
- Introduced `poster_model_comparison.py` for generating model comparison figures. - Added `plot_poster_roc_comparison.py` for creating ROC comparison figures for PAPILA binary classification. - Created new JSON configuration files for clinical solo models with and without geometry injection. - Implemented batch dispatch updates in `batch_dispatch.py` to utilize run names from configurations. - Added analysis scripts: `compare_grid.py`, `inspect_embeddings.py`, and `summarize_run.py` for evaluating model performance and feature embeddings. - Created experiment configurations for various training scenarios, including warm sweeps and promoting successful runs. - Added binary ROC comparison and model comparison figures to the results directory.
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{
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"_notes": [
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"Diagnostic: cd tower alone, no geometry injection.",
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"Pair to clinical_solo_geom_unet — same architecture but with geom_dim=0",
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"and no img EPC supplier."
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],
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"run_name": "v4/clinical_solo",
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"num_classes": 2,
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"label_filter": [0, 1],
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"split_identity_level": 1,
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"eval_stage": "cd_fuse",
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"save_predictions": true,
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"save_features": true,
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"seed": 1234,
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"folds": 5,
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"fold_seed": 100,
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"output_root": "v4/results",
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"out_dir_tags": ["binary"],
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"data": {
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"module": "v4.classes.profiles.v4papila",
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"args": {
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"image_dir": "Papila/FundusImages",
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"clinical_dir": "Papila/ClinicalData",
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"label_col": "Diagnosis",
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"iop_corr_method": "ratio",
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"iop_drop_raw": true,
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"exclude_cols": ["Axial_Length"],
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"in_memory_cache": false
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}
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},
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"towers": [
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{
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"name": "cd",
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"module": "v4.classes.towers.clinical_tower",
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"class": "ClinicalEncoder",
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"data_source": "matrix",
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"args": {
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"hidden_dim": 128
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}
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}
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],
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"stages": [
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{
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"name": "cd_warm",
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"type": "warm",
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"tower": "cd",
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"head_name": "cd_aux",
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"level": "eye",
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"epochs": 40
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},
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{
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"name": "cd_aux",
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"type": "head",
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"input": "cd",
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"train_with": "cd_fuse"
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},
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{
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"name": "cd_fuse",
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"type": "fusion",
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"module": "v4.classes.bridges.mono_bridge",
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"class": "MonoBridge",
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"inputs": ["cd"],
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"level": "eye",
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"epochs": 36,
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"train_towers": true,
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"args": { "use_ln": false }
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}
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],
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"training": {
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"lr": 1e-4,
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"batch_size": 16,
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"tune_binary_threshold": true
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}
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}
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