reworked results chpt

tools/plot_scripts/results_ap_over_latent.py

@@ -143,6 +143,11 @@ def _dynamic_ylim(all_vals: List[float], all_errs: List[float]) -> Tuple[float,
     return (float(y0), float(y1))
 
 
+def _get_dim_mapping(dims: list[int]) -> dict[int, int]:
+    """Map actual dimensions to evenly spaced positions (0, 1, 2, ...)"""
+    return {dim: i for i, dim in enumerate(dims)}
+
+
 def plot_eval(ev: str, agg: Dict[Tuple[str, str, int, int, int], Agg], outdir: Path):
     fig, axes = plt.subplots(
         len(SEMI_LABELING_REGIMES),
@@ -155,6 +160,9 @@ def plot_eval(ev: str, agg: Dict[Tuple[str, str, int, int, int], Agg], outdir: P
     if len(SEMI_LABELING_REGIMES) == 1:
         axes = [axes]
 
+    # Create dimension mapping
+    dim_mapping = _get_dim_mapping(LATENT_DIMS)
+
     for ax, regime in zip(axes, SEMI_LABELING_REGIMES):
         semi_n, semi_a = regime
         data = {}
@@ -163,7 +171,9 @@ def plot_eval(ev: str, agg: Dict[Tuple[str, str, int, int, int], Agg], outdir: P
             for dim in LATENT_DIMS:
                 key = (ev, net, dim, semi_n, semi_a)
                 if key in agg:
-                    xs.append(dim)
+                    xs.append(
+                        dim_mapping[dim]
+                    )  # Use mapped position instead of actual dim
                     ys.append(agg[key].mean)
                     es.append(agg[key].std)
             data[net] = (xs, ys, es)
@@ -172,12 +182,16 @@ def plot_eval(ev: str, agg: Dict[Tuple[str, str, int, int, int], Agg], outdir: P
             xs, ys, es = data[net]
             if not xs:
                 continue
-            ax.set_xticks(LATENT_DIMS)
-            ax.yaxis.set_major_locator(MaxNLocator(nbins=5))  # e.g., always 5 ticks
+
+            # Set evenly spaced ticks with actual dimension labels
+            ax.set_xticks(list(dim_mapping.values()))
+            ax.set_xticklabels(LATENT_DIMS)
+
+            ax.yaxis.set_major_locator(MaxNLocator(nbins=5))
             ax.scatter(
                 xs, ys, s=35, color=color, alpha=SCATTER_ALPHA, label=f"{net} (points)"
             )
-            x_fit, y_fit = _lin_trend(xs, ys)
+            x_fit, y_fit = _lin_trend(xs, ys)  # Now using mapped positions
             ax.plot(
                 x_fit,
                 y_fit,