diff --git a/scripts/analyze_results_directory.py b/scripts/analyze_results_directory.py
index 2107187b9d..da360658ea 100644
--- a/scripts/analyze_results_directory.py
+++ b/scripts/analyze_results_directory.py
@@ -108,8 +108,11 @@ def create_raw_dataframe(
             run_data_defaultdict.update(config)
         else:
             run_data_defaultdict = outdata
-        (env, approach, seed, excluded_predicates, included_options,
-         experiment_id, online_learning_cycle) = filepath[8:-4].split("__")
+        try:
+            (env, approach, seed, excluded_predicates, included_options,
+            experiment_id, online_learning_cycle) = filepath[8:-4].split("__")
+        except ValueError:
+            import ipdb; ipdb.set_trace()
         if not excluded_predicates:
             excluded_predicates = "none"
         run_data = dict(
diff --git a/scripts/plotting/create_active_sampler_learning_plots.py b/scripts/plotting/create_active_sampler_learning_plots.py
index 6d1169dad2..553e7bec60 100644
--- a/scripts/plotting/create_active_sampler_learning_plots.py
+++ b/scripts/plotting/create_active_sampler_learning_plots.py
@@ -160,18 +160,24 @@ def _derive_per_task_average(metric: str,
             lambda v: "grid_row-planning_progress_explore_original" in v)),
         ("No Feature Eng.", "blue", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "grid_row-planning_progress_explore_no_feature_engineering" in v)),
+        ("No Weight Sharing", "red", lambda df: df["EXPERIMENT_ID"].apply(
+            lambda v: "grid_row-planning_progress_explore_no_weight_sharing" in v)),
     ],
     "Ball and Cup Sticky Table": [
         ("Original", "green", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "sticky_table-planning_progress_explore_original" in v)),
         ("No Feature Eng.", "blue", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "sticky_table-planning_progress_explore_no_feature_engineering" in v)),
+        ("No Weight Sharing", "red", lambda df: df["EXPERIMENT_ID"].apply(
+            lambda v: "sticky_table-planning_progress_explore_no_weight_sharing" in v)),
     ],
     "Cleanup Playroom": [
         ("Original", "green", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "spot_sweeping_sim-planning_progress_explore_original" in v)),
         ("No Feature Eng.", "blue", lambda df: df["EXPERIMENT_ID"].apply(
             lambda v: "spot_sweeping_sim-planning_progress_explore_no_feature_engineering" in v)),
+        ("No Weight Sharing", "red", lambda df: df["EXPERIMENT_ID"].apply(
+            lambda v: "spot_sweeping_sim-planning_progress_explore_no_weight_sharing" in v)),
     ],
 }