Comment out new features (CLIP×φ sort, λ input, brain MEI sidecar) until ready

scripts/explorer/datasets.py

@@ -150,16 +150,16 @@ def _load_dataset(path: str, label: str, *,
         'umap_backup':        umap_backup,
     }
 
-    # Brain MEI sidecar (brain-response-sorted MEI indices)
-    brain_sidecar = stem + '_brain_meis.pt'
-    if os.path.exists(brain_sidecar):
-        print(f"  Loading brain MEI sidecar {os.path.basename(brain_sidecar)} ...")
-        bm = torch.load(brain_sidecar, map_location='cpu', weights_only=False)
-        entry['brain_top_img_idx'] = bm.get('brain_top_img_idx')
-        entry['brain_top_img_act'] = bm.get('brain_top_img_act')
-    else:
-        entry['brain_top_img_idx'] = None
-        entry['brain_top_img_act'] = None
+    # Brain MEI sidecar (disabled — re-enable after running precompute_brain_response_meis.py)
+    # brain_sidecar = stem + '_brain_meis.pt'
+    # if os.path.exists(brain_sidecar):
+    #     print(f"  Loading brain MEI sidecar {os.path.basename(brain_sidecar)} ...")
+    #     bm = torch.load(brain_sidecar, map_location='cpu', weights_only=False)
+    #     entry['brain_top_img_idx'] = bm.get('brain_top_img_idx')
+    #     entry['brain_top_img_act'] = bm.get('brain_top_img_act')
+    # else:
+    #     entry['brain_top_img_idx'] = None
+    #     entry['brain_top_img_act'] = None
 
     # Heatmaps sidecar
     sidecar = stem + '_heatmaps.pt'

scripts/explorer/main.py

@@ -276,7 +276,7 @@ lower_left = column(
     _search_header,
     _clip_row,
     _clip_results,
-    flist_panel.sort_select,
+    # flist_panel.sort_select,   # re-enable for CLIP × φ sort
     flist_panel.gallery_div,
     flist_panel.gallery_bridge_input,
     flist_panel.gallery_page_input,

scripts/explorer/panels/clip_search.py

@@ -55,7 +55,7 @@ else:
             clip_m, clip_p, clip_dev = get_clip()
             from clip_utils import compute_text_embeddings
             q_embed    = compute_text_embeddings([query], clip_m, clip_p, clip_dev)
-            _S.clip_query_embed = q_embed   # store for combined CLIP × φ sort
+            # _S.clip_query_embed = q_embed   # store for combined CLIP × φ sort
             scores_vec = (embeds.float() @ q_embed.T).squeeze(-1)
         except Exception as exc:
             clip_results_div.text = f"<span style='color:#c00'>CLIP error: {exc}</span>"

scripts/explorer/panels/dynadiff.py

@@ -239,24 +239,25 @@ if HAS_DYNADIFF:
                         for k, vals in dd_source.data.items()}
             dd_source.data = new_data
             dd_status.text = ''
-        elif msg.startswith('set_lam:'):
-            parts = msg.split(':', 2)
-            if len(parts) != 3:
-                return
-            try:
-                feat    = int(parts[1])
-                new_val = float(parts[2])
-            except ValueError:
-                return
-            feats = list(dd_source.data['feat'])
-            if feat not in feats:
-                return
-            idx = feats.index(feat)
-            new_lams = list(dd_source.data['lam'])
-            new_lams[idx] = new_val
-            new_data = dict(dd_source.data)
-            new_data['lam'] = new_lams
-            dd_source.data = new_data
+        # set_lam disabled — re-enable with lambda input in rendering.py
+        # elif msg.startswith('set_lam:'):
+        #     parts = msg.split(':', 2)
+        #     if len(parts) != 3:
+        #         return
+        #     try:
+        #         feat    = int(parts[1])
+        #         new_val = float(parts[2])
+        #     except ValueError:
+        #         return
+        #     feats = list(dd_source.data['feat'])
+        #     if feat not in feats:
+        #         return
+        #     idx = feats.index(feat)
+        #     new_lams = list(dd_source.data['lam'])
+        #     new_lams[idx] = new_val
+        #     new_data = dict(dd_source.data)
+        #     new_data['lam'] = new_lams
+        #     dd_source.data = new_data
 
     dd_feat_bridge.on_change('value', _on_feat_bridge)
 

scripts/explorer/panels/feature_list.py

@@ -21,7 +21,8 @@ from bokeh.io import curdoc
 from bokeh.layouts import column, row
 from bokeh.models import (
     Button, ColumnDataSource, DataTable, Div, NumberFormatter,
-    Select, TableColumn, TextInput,
+    # Select,  # re-enable for CLIP × φ sort
+    TableColumn, TextInput,
 )
 
 from ..args import args
@@ -83,28 +84,30 @@ def _schedule_hf_push(file_path: str):
 
 # ---------- Feature list table ----------
 
-sort_select = Select(
-    title="Sort by", value="Frequency",
-    options=["Frequency", "CLIP × Brain φ"],
-    width=160,
-)
+# sort_select = Select(                           # re-enable for CLIP × φ sort
+#     title="Sort by", value="Frequency",
+#     options=["Frequency", "CLIP × Brain φ"],
+#     width=160,
+# )
+sort_select = None
 
 
 def _get_sorted_order():
-    ds = active_ds()
-    if (sort_select.value == "CLIP × Brain φ"
-            and _S.clip_query_embed is not None):
-        embeds = ds.get('nsd_clip_embeds') if ds.get('nsd_clip_embeds') is not None else ds.get('clip_embeds')
-        if embeds is not None:
-            clip_sims = (embeds.float() @ _S.clip_query_embed.T).squeeze(-1).cpu().numpy()
-            phi_vals  = np.array(phi_c_vals(list(range(len(clip_sims)))))
-            c = clip_sims - clip_sims.min(); c = c / (c.max() + 1e-8)
-            p = phi_vals / (phi_vals.max() + 1e-8)
-            order = np.argsort(-(c * p))
-        else:
-            order = np.argsort(-ds['freq'])
-    else:
-        order = np.argsort(-ds['freq'])
+    ds    = active_ds()
+    # CLIP × φ sort (disabled):
+    # if (sort_select is not None and sort_select.value == "CLIP × Brain φ"
+    #         and _S.clip_query_embed is not None):
+    #     embeds = ds.get('nsd_clip_embeds') if ds.get('nsd_clip_embeds') is not None else ds.get('clip_embeds')
+    #     if embeds is not None:
+    #         clip_sims = (embeds.float() @ _S.clip_query_embed.T).squeeze(-1).cpu().numpy()
+    #         phi_vals  = np.array(phi_c_vals(list(range(len(clip_sims)))))
+    #         c = clip_sims - clip_sims.min(); c = c / (c.max() + 1e-8)
+    #         p = phi_vals / (phi_vals.max() + 1e-8)
+    #         order = np.argsort(-(c * p))
+    #     else:
+    #         order = np.argsort(-ds['freq'])
+    # else:
+    order = np.argsort(-ds['freq'])
     if _S.search_filter is not None:
         mask  = np.isin(order, list(_S.search_filter))
         order = order[mask]
@@ -123,11 +126,10 @@ def _build_list_data(order) -> dict:
     )
 
 
-def _on_sort_change(attr, old, new):
-    apply_order(_get_sorted_order())
-    rebuild_gallery()
-
-sort_select.on_change('value', _on_sort_change)
+# def _on_sort_change(attr, old, new):            # re-enable for CLIP × φ sort
+#     apply_order(_get_sorted_order())
+#     rebuild_gallery()
+# sort_select.on_change('value', _on_sort_change)
 
 feature_list_source = ColumnDataSource(data=_build_list_data(_get_sorted_order()))
 

scripts/explorer/rendering.py

@@ -480,19 +480,20 @@ def make_active_features_tile_html(feats: list, ds: dict, mei_size: int = 72,
                       f'margin-top:2px;text-align:center;overflow:hidden;'
                       f'text-overflow:ellipsis;white-space:nowrap">{label}</div>') if label else ''
 
-        # Lambda number input (only when removable/editable)
-        if removable:
-            lam_val = lam_map.get(feat, 3.0)
-            lam_html = (
-                f'<input type="number" value="{lam_val:.2g}" step="0.5" '
-                f'style="width:54px;font-size:10px;text-align:center;'
-                f'border:1px solid #ccc;border-radius:3px;margin-top:2px" '
-                f'onclick="event.stopPropagation()" '
-                f'onchange="window._dd_feat_action(\'set_lam:{feat}:\'+this.value)" '
-                f'title="Steering strength λ"/>'
-            )
-        else:
-            lam_html = ''
+        # Lambda number input (disabled — re-enable when set_lam handler is active)
+        # if removable:
+        #     lam_val = lam_map.get(feat, 3.0)
+        #     lam_html = (
+        #         f'<input type="number" value="{lam_val:.2g}" step="0.5" '
+        #         f'style="width:54px;font-size:10px;text-align:center;'
+        #         f'border:1px solid #ccc;border-radius:3px;margin-top:2px" '
+        #         f'onclick="event.stopPropagation()" '
+        #         f'onchange="window._dd_feat_action(\'set_lam:{feat}:\'+this.value)" '
+        #         f'title="Steering strength λ"/>'
+        #     )
+        # else:
+        #     lam_html = ''
+        lam_html = ''
 
         cards.append(
             f'<div onclick="window._sae_select_feature({feat})" '

scripts/explorer/state.py

@@ -23,7 +23,7 @@ class _S:
     patch_img = None         # image index currently loaded in patch explorer
     patch_z = None           # (n_patches, d_sae) float32 for the loaded patch image
     gallery_page: int = 0    # current page in the MEI thumbnail gallery
-    clip_query_embed = None  # last CLIP text query embedding (1, d_clip) tensor for combined sort
+    # clip_query_embed = None  # last CLIP text query embedding (1, d_clip) tensor for combined sort
 
 
 _all_datasets: list[dict] = []