fixed plots

tools/plot_scripts/ae_elbow_lenet.py

@@ -12,7 +12,7 @@ import numpy as np
 import polars as pl
 
 # CHANGE THIS IMPORT IF YOUR LOADER MODULE IS NAMED DIFFERENTLY
-from plot_scripts.load_results import load_pretraining_results_dataframe
+from load_results import load_pretraining_results_dataframe
 
 # ----------------------------
 # Config
@@ -78,8 +78,8 @@ def build_arch_curves_from_df(
             "overall": (dims, means, stds),
         } }
     """
-    if "split" not in df.columns:
-        raise ValueError("Expected 'split' column in AE dataframe.")
+    # if "split" not in df.columns:
+    #     raise ValueError("Expected 'split' column in AE dataframe.")
     if "scores" not in df.columns:
         raise ValueError("Expected 'scores' column in AE dataframe.")
     if "network" not in df.columns or "latent_dim" not in df.columns:
@@ -88,7 +88,7 @@ def build_arch_curves_from_df(
         raise ValueError(f"Expected '{label_field}' column in AE dataframe.")
 
     # Keep only test split
-    df = df.filter(pl.col("split") == "test")
+    # df = df.filter(pl.col("split") == "test")
 
     groups: dict[tuple[str, int], dict[str, list[float]]] = {}
 
@@ -201,7 +201,7 @@ def plot_multi_loss_curve(arch_results, title, output_path, colors=None):
 
     plt.xlabel("Latent Dimensionality")
     plt.ylabel("Test Loss")
-    plt.title(title)
+    # plt.title(title)
     plt.legend()
     plt.grid(True, alpha=0.3)
     plt.xticks(all_dims)