regenerate figures as 650-dpi LZW TIFFs, flattened RGB (publication-ready)

.gitattributes

@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig1_layer_ablation.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig2_cross_modality.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig3_pruning_gain.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig4_floor_ablation.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig5_conformal.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig6_cross_objective.tiff filter=lfs diff=lfs merge=lfs -text
+paper/figures/fig7_rank_law.tiff filter=lfs diff=lfs merge=lfs -text

paper/make_figures.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
-"""Generate paper figures from the locked gate-report numbers. Self-contained (no bucket)."""
+"""Generate paper figures from the locked gate-report numbers. Self-contained (no bucket).
+Output: publication TIFFs at 650 dpi (LZW-compressed)."""
 import matplotlib
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
@@ -8,7 +9,8 @@ from pathlib import Path
 
 OUT = Path(__file__).resolve().parent / "figures"
 OUT.mkdir(exist_ok=True)
-plt.rcParams.update({"figure.dpi": 150, "font.size": 11, "axes.grid": True,
+DPI = 650
+plt.rcParams.update({"figure.dpi": 150, "savefig.dpi": DPI, "font.size": 11, "axes.grid": True,
                      "grid.alpha": 0.3, "axes.axisbelow": True})
 
 
@@ -28,7 +30,7 @@ def fig1_layer():
     ax.set_ylabel("token-level lesion AUROC (LIDC)"); ax.set_ylim(0.55, 0.92)
     ax.set_title("Finding 1: lesion signal peaks mid-layer, erodes with depth")
     ax.legend(loc="lower left", fontsize=8.5)
-    fig.tight_layout(); fig.savefig(OUT / "fig1_layer_ablation.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig1_layer_ablation.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig2_crossmodality():
@@ -51,7 +53,7 @@ def fig2_crossmodality():
                 xytext=(-2, -34), ha="center", fontsize=7.5, color="#1f77b4")
     ax.annotate("attention\n~ chance", (4 + w/2, 0.492), textcoords="offset points",
                 xytext=(2, 4), ha="center", fontsize=7.5, color="#ff7f0e")
-    fig.tight_layout(); fig.savefig(OUT / "fig2_cross_modality.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig2_cross_modality.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig3_pruning_gain():
@@ -70,7 +72,7 @@ def fig3_pruning_gain():
     ax.set_ylabel("small-lesion recall gain (pts)\nmembership vs saliency pruning")
     ax.set_title("Finding 3: membership pruning > saliency pruning")
     ax.legend(loc="upper right", fontsize=9)
-    fig.tight_layout(); fig.savefig(OUT / "fig3_pruning_gain.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig3_pruning_gain.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig4_ablation():
@@ -88,7 +90,7 @@ def fig4_ablation():
     ax.annotate("rank coverage rewards spanning,\nnot lesion concentration",
                 (1 + w, 0.460), textcoords="offset points", xytext=(-6, 18), ha="center",
                 fontsize=7.5, color="#d62728")
-    fig.tight_layout(); fig.savefig(OUT / "fig4_floor_ablation.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig4_floor_ablation.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig5_conformal():
@@ -102,7 +104,7 @@ def fig5_conformal():
     ax.set_xticks(budgets)
     ax.set_title("Conformal retention certificate\n(valid; honest budget tradeoff)")
     ax.legend(loc="center right", fontsize=8)
-    fig.tight_layout(); fig.savefig(OUT / "fig5_conformal.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig5_conformal.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig6_cross_objective():
@@ -122,7 +124,7 @@ def fig6_cross_objective():
     ax.legend(loc="upper right", fontsize=8)
     ax.annotate("MAE flat & low\n(not density-separable)", (9, 0.578),
                 textcoords="offset points", xytext=(0, -28), ha="center", fontsize=7.5, color="#d62728")
-    fig.tight_layout(); fig.savefig(OUT / "fig6_cross_objective.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig6_cross_objective.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 def fig7_law():
@@ -141,10 +143,18 @@ def fig7_law():
     ax.set_ylabel("fraction of rare signal retained"); ax.set_ylim(0, 1.08)
     ax.set_title("The law: rank objectives lose rare/low-rank signal")
     ax.legend(loc="lower right", fontsize=8.5)
-    fig.tight_layout(); fig.savefig(OUT / "fig7_rank_law.png"); plt.close(fig)
+    fig.tight_layout(); fig.savefig(OUT / "fig7_rank_law.tiff", dpi=DPI, pil_kwargs={"compression": "tiff_lzw"}); plt.close(fig)
 
 
 for f in (fig1_layer, fig2_crossmodality, fig3_pruning_gain, fig4_ablation, fig5_conformal,
           fig6_cross_objective, fig7_law):
     f()
-print("figures written:", sorted(p.name for p in OUT.glob("*.png")))
+# flatten RGBA -> RGB on white (journals reject alpha/transparency in TIFFs); keep 650 dpi + LZW
+from PIL import Image
+for p in sorted(OUT.glob("*.tiff")):
+    im = Image.open(p)
+    if im.mode in ("RGBA", "LA", "P"):
+        bg = Image.new("RGB", im.size, "white")
+        bg.paste(im.convert("RGBA"), mask=im.convert("RGBA").split()[-1])
+        bg.save(p, format="TIFF", dpi=(DPI, DPI), compression="tiff_lzw")
+print(f"figures written at {DPI} dpi (TIFF/LZW, RGB):", sorted(p.name for p in OUT.glob("*.tiff")))