rpotter6298
3d7777f010
- Introduced `fused_importance_with_axial.py` to evaluate the importance of Axial_Length in the fused-head model. - Created JSON configurations for various experiments excluding zero-importance clinical features: - `cd_solo_bilateral_dropzero.json`: Bilateral clinical-only evaluation. - `cd_solo_single_dropzero.json`: Single-eye clinical-only evaluation. - `ensemble_refugelike_ckpt_dropzero.json`: Ensemble model with dropped zero-importance features. - `ensemble_single_refugelike_dropzero.json`: Single-eye ensemble model with dropped features.
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
"""F4 (main text) - Bilateral clinical, image, and Hadamard L2 fusion.
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Patient-level analogue of F3: same two-row / three-column layout, same pruned
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clinical panel, but every column is the bilateral (both-eyes) model reading
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from the patient-level 'hb' stage. All three columns share the pruned clinical
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panel: astigmatism, dioptre_1, dioptre_2, and Phakic/Pseudophakic dropped
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(see S8e). The image column has no clinical inputs so is unaffected by the
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prune.
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Columns (left -> right):
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Clinical only (bilateral) (cd_solo_bilateral_dropzero, hb)
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Image only (bilateral) (img_solo_bilateral_refugelike, hb)
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Hadamard L2 fusion (bilateral) (ensemble_refugelike_ckpt_dropzero, hb)
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Rows:
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top: confidence strip - predicted P(Glaucoma) coloured by VF-MD tier
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(severe / moderate / early) with normals in grey. Patients are the
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unit of prediction here (~1 prediction per patient per fold-rep).
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bottom: ROC per severity tier, each tier vs all normals; pooled ROC curve
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with a 95% CI band from patient-level bootstrap; pooled AUC with
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95% CI annotated.
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Glaucoma - VF_MD not recorded is dropped from both rows (n = 0 patients at
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the patient-worst-eye level).
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Re-run:
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python -m v4.figures.F4_bilateral
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"""
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from __future__ import annotations
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import warnings
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warnings.filterwarnings("ignore")
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from pathlib import Path
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import matplotlib
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matplotlib.use("Agg")
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from v4.figures.util.loaders import RESULTS_ROOT
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from v4.figures import F3_hadamard_focus as F3
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OUT = Path(__file__).parent / "output" / "F4_bilateral.png"
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SOURCES = [
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("Clinical only (bilateral)",
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RESULTS_ROOT / "explainability" / "cd_solo_bilateral_dropzero",
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"hb"),
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("Image only (bilateral)",
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RESULTS_ROOT / "refuge_v2m_baseline" / "img_solo_bilateral_refugelike",
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"hb"),
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("Hadamard L2 fusion (bilateral)",
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RESULTS_ROOT / "explainability" / "ensemble_refugelike_ckpt_dropzero",
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"hb"),
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]
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def render() -> None:
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"""Reuse every drawing primitive from F3; only source paths and out-file differ."""
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F3.SOURCES = SOURCES
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F3.OUT = OUT
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F3.render()
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if __name__ == "__main__":
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render()
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