Deploy weighted clustering presets with 11 physics perspectives

Dockerfile

@@ -9,6 +9,9 @@ COPY app.py .
 COPY scripts/apply_labels_to_map.py scripts/
 COPY search/ search/
 COPY material_universe_cache/plotly_studio_export.csv material_universe_cache/
+COPY material_universe_cache/cluster_labels_*.npy material_universe_cache/
+COPY material_universe_cache/centroid_sim_*.npy material_universe_cache/
+COPY docs/cluster_definitions_presets.json docs/
 
 ENV HOST=0.0.0.0
 ENV PORT=7860

README.md

@@ -1,15 +1,75 @@
----
-title: Material Universe
-emoji: 🔬
-colorFrom: blue
-colorTo: purple
-sdk: docker
-app_port: 7860
-pinned: false
----
+# Crystal-Chroma
 
-# Material Universe — 材料データベースエクスプローラー
+**Physical RAG for Inverse Material Design**
 
-Interactive dashboard for exploring 33,973 materials from the Materials Project, featuring band gap properties, structural clustering, and high-dimensional material embeddings.
+Crystal-Chroma is a Retrieval-Augmented Generation system that retrieves crystal structures based on **physical behavioral similarity** rather than text semantics. It enables "Inverse Design" queries like *"Find a material that behaves like this expensive catalyst but uses cheaper elements."*
 
-Built with Dash 4.0 and Plotly.
+## How It Works
+
+1. **Ingest** ~44,000 stable materials from the [Materials Project](https://materialsproject.org/)
+2. **Featurize** each crystal using MatterVial embeddings (fusing force fields, electronic structure, and composition)
+3. **Store** 3000-dimensional physics vectors in ChromaDB
+4. **Query** by physical similarity to find materials with similar internal forces and electronics
+
+## Quick Start
+
+```bash
+# Install dependencies
+uv sync
+
+# Set your Materials Project API key
+echo 'MP_API_KEY="your_key_here"' > .env
+
+# Build the crystal database (requires VPN - see docs/api_connection_issue.md)
+uv run python build_crystal_db.py
+
+# Search for similar materials
+uv run python tools/physical_search.py samples/test.cif --limit 10
+```
+
+## Project Structure
+
+```
+crystal-chroma/
+├── build_crystal_db.py      # Ingestion pipeline (MP API → MatterVial → ChromaDB)
+├── tools/
+│   └── physical_search.py   # Similarity search tool
+├── mattervial/              # Physics encoder (local package)
+├── crystal_chroma_db/       # Persistent vector store
+├── debug/                   # API connection debug scripts
+├── samples/                 # Sample CIF files
+└── docs/
+    ├── api_connection_issue.md              # VPN/Cloudflare workaround
+    └── proposal_implementation_of_...md     # System design document
+```
+
+## Requirements
+
+- Python 3.12+
+- Materials Project API key ([get one here](https://materialsproject.org/api))
+- VPN with US exit node (see [API Connection Issue](docs/api_connection_issue.md))
+
+## Key Features
+
+| Feature | Description |
+|---------|-------------|
+| **Resume capability** | Ingestion skips already-downloaded materials |
+| **Rate limiting** | 1-second delay between API batches |
+| **Error handling** | Continues on failures, doesn't lose progress |
+| **Physics-based search** | Find materials by behavior, not just composition |
+
+## Dependencies
+
+- `chromadb` - Vector database
+- `mp-api` - Materials Project API client
+- `mattervial` - Physics encoder (local)
+- `numpy`, `tqdm`, `python-dotenv`
+
+## Documentation
+
+- [API Connection Issue & Workaround](docs/api_connection_issue.md)
+- [Implementation Proposal](docs/proposal_implementation_of_physical_rag_crystal_chroma_for_inverse_material_design.md)
+
+## License
+
+MIT

app.py

@@ -1,7 +1,9 @@
 """
 Materials Database Explorer — Dash 4.0
 
-Reproduces the Plotly-Studio-generated dashboard with 6 interactive charts.
+Reproduces the Plotly-Studio-generated dashboard with 7 interactive charts
+plus weighted clustering presets (Centroid Similarity Decomposition).
+
 Supports English and Japanese localization.
 
 Usage:
@@ -11,12 +13,15 @@ Usage:
 """
 
 import argparse
+import json
 import os
 import sys
+from pathlib import Path
 
 from dotenv import load_dotenv
 load_dotenv()
 
+import numpy as np
 import pandas as pd
 import plotly.express as px
 from dash import Dash, dcc, html, Input, Output, State, callback
@@ -51,7 +56,7 @@ DASH_I18N = {
         "c1_title": "Band gap distribution over material families",
         "c2_title": "Compare band gap distribution of material types",
         "c3_title": "Principal Component Analysis (PCA) for high-dimensional material embeddings",
-        "c3_desc": "Reduces 64-dimensional material embeddings to 2D/3D to reveal clustering patterns.",
+        "c3_desc": "Reduces 32-dimensional material embeddings to 2D/3D to reveal clustering patterns.",
         "c4_title": "Look up materials by chemical family",
         "c5_title": "Band gap by material family and material type",
         "c6_title": "Show the top N material families",
@@ -123,6 +128,23 @@ DASH_I18N = {
         "c7_col_lofm": "OFM",
         "c7_col_esen": "eSEN",
         "c7_col_weighted": "Weighted",
+        # Clustering mode (B5)
+        "lbl_cluster_mode": "Clustering Mode",
+        "mode_preset": "Named Presets",
+        "mode_custom": "Custom Weights",
+        "lbl_perspective": "Clustering Perspective",
+        "lbl_cluster_weights": "Embedding space weights",
+        "preset_balanced": "Balanced (Equal Weights)",
+        "preset_orb_only": "Orb-Only (Force Field)",
+        "preset_mm_only": "MEGNet-Only (Coordination)",
+        "preset_ofm_only": "OFM-Only (Orbital)",
+        "preset_esen_only": "eSEN-Only (Energy)",
+        "preset_stability": "Stability Focus",
+        "preset_electronic": "Electronic Focus",
+        "preset_structural": "Structural Focus",
+        "preset_chemical": "Chemical Focus",
+        "preset_coord_energy": "Coordination Energy",
+        "preset_mechanochem": "Mechanochemical",
     },
     "ja": {
         "app_title": "材料データベースエクスプローラー",
@@ -134,7 +156,7 @@ DASH_I18N = {
         "c1_title": "材料ファミリーごとのバンドギャップ分布",
         "c2_title": "材料タイプ別バンドギャップ分布の比較",
         "c3_title": "高次元材料埋め込みの主成分分析（PCA）",
-        "c3_desc": "64次元の材料埋め込みを2D/3Dに次元削減し、クラスタリングパターンを可視化。",
+        "c3_desc": "32次元の材料埋め込みを2D/3Dに次元削減し、クラスタリングパターンを可視化。",
         "c4_title": "化学ファミリーで材料を検索",
         "c5_title": "材料ファミリーと材料タイプ別バンドギャップ",
         "c6_title": "上位N材料ファミリーを表示",
@@ -205,6 +227,23 @@ DASH_I18N = {
         "c7_col_lofm": "OFM",
         "c7_col_esen": "eSEN",
         "c7_col_weighted": "重み付き",
+        # Clustering mode (B5)
+        "lbl_cluster_mode": "クラスタリングモード",
+        "mode_preset": "名前付きプリセット",
+        "mode_custom": "カスタム重み",
+        "lbl_perspective": "クラスタリング視点",
+        "lbl_cluster_weights": "埋め込み空間の重み",
+        "preset_balanced": "バランス（均等重み）",
+        "preset_orb_only": "Orb単独（力場）",
+        "preset_mm_only": "MEGNet単独（配位）",
+        "preset_ofm_only": "OFM単独（軌道）",
+        "preset_esen_only": "eSEN単独（エネルギー）",
+        "preset_stability": "安定性重視",
+        "preset_electronic": "電子構造重視",
+        "preset_structural": "構造重視",
+        "preset_chemical": "化学重視",
+        "preset_coord_energy": "配位エネルギー",
+        "preset_mechanochem": "力学化学",
     },
 }
 
@@ -217,7 +256,6 @@ TYPE_DISPLAY = {
     "Semiconductor": MT["type_semiconductor"],
     "Insulator": MT["type_insulator"],
 }
-FAMILY_DISPLAY = FAMILY_TRANSLATIONS_JA if LANG == "ja" else {}
 
 # Aggregation display mapping (label shown in chart titles)
 AGG_DISPLAY = {
@@ -235,21 +273,16 @@ METRIC_DISPLAY = {
 }
 
 
-def family_label(en_name):
-    """Translate family name using FAMILY_TRANSLATIONS_JA (verbatim)."""
-    return FAMILY_DISPLAY.get(en_name, en_name)
-
-
 def type_label(en_name):
     """Translate electronic type using MAP_TRANSLATIONS (verbatim)."""
     return TYPE_DISPLAY.get(en_name, en_name)
 
 
 # ── data ──────────────────────────────────────────────────────────────────
-CSV = "material_universe_cache/plotly_studio_export.csv"
+CACHE = Path("material_universe_cache")
+CSV = CACHE / "plotly_studio_export.csv"
 df = pd.read_csv(CSV)
-DIM_COLS = [f"dim_{i}" for i in range(64)]
-ALL_FAMILIES = sorted(df["Family"].unique())
+DIM_COLS = [f"dim_{i}" for i in range(32)]
 ALL_TYPES = ["Metallic", "Semiconductor", "Insulator"]
 
 # Pre-compute PCA (expensive, do once)
@@ -262,8 +295,7 @@ df["PC2"] = pc_all[:, 1]
 df["PC3"] = pc_all[:, 2]
 print("PCA done.")
 
-# Build display columns for charts
-df["FamilyDisplay"] = df["Family_JA"] if LANG == "ja" else df["Family"]
+# Build TypeDisplay column (static, never changes with clustering)
 df["TypeDisplay"] = df["Type"].map(TYPE_DISPLAY)
 
 # C7 material dropdown options (formula + mp_id for display, mp_id as value)
@@ -272,6 +304,121 @@ c7_material_options = sorted([
     for _, row in df[["MP_ID", "Formula"]].drop_duplicates().iterrows()
 ], key=lambda x: x["label"])
 
+# ── Preset label data ──────────────────────────────────────────────────
+PRESET_KEYS = [
+    "balanced", "orb_only", "mm_only", "ofm_only", "esen_only",
+    "stability", "electronic", "structural", "chemical",
+    "coord_energy", "mechanochem",
+]
+
+# Load preset label arrays and family name mappings
+PRESET_LABELS = {}
+PRESET_FAMILIES_EN = {}
+PRESET_FAMILIES_JA = {}
+
+# Load family name definitions
+_families_path = Path("docs/cluster_definitions_presets.json")
+_families_data = {}
+if _families_path.exists():
+    with open(_families_path, "r", encoding="utf-8") as f:
+        _families_data = json.load(f)
+
+for key in PRESET_KEYS:
+    label_path = CACHE / f"cluster_labels_{key}.npy"
+    if label_path.exists():
+        PRESET_LABELS[key] = np.load(label_path)
+        PRESET_FAMILIES_EN[key] = _families_data.get(key, {})
+        PRESET_FAMILIES_JA[key] = _families_data.get(f"{key}_ja", {})
+    else:
+        print(f"  WARNING: {label_path} not found, preset '{key}' unavailable")
+
+# Balanced family maps (used as stable reference for custom mode)
+BALANCED_FAMILY_EN = PRESET_FAMILIES_EN.get("balanced", {})
+BALANCED_FAMILY_JA = PRESET_FAMILIES_JA.get("balanced", {})
+
+# Fall back to static Family/Family_JA from CSV if no presets loaded
+if not PRESET_LABELS:
+    print("  WARNING: No preset labels loaded. Using static CSV clustering.")
+
+# ── Centroid similarity matrices (for custom mode) ─────────────────────
+S_ORB = S_MM = S_OFM = S_ESEN = None
+CLUSTER_IDS = []
+_sim_loaded = False
+
+for name in ["orb", "mm", "ofm", "esen"]:
+    sim_path = CACHE / f"centroid_sim_{name}.npy"
+    if sim_path.exists():
+        arr = np.load(sim_path)
+        if name == "orb":
+            S_ORB = arr
+        elif name == "mm":
+            S_MM = arr
+        elif name == "ofm":
+            S_OFM = arr
+        elif name == "esen":
+            S_ESEN = arr
+
+if S_ORB is not None and S_MM is not None and S_OFM is not None and S_ESEN is not None:
+    _sim_loaded = True
+    # Infer cluster IDs from balanced labels
+    if "balanced" in PRESET_LABELS:
+        CLUSTER_IDS = sorted(set(PRESET_LABELS["balanced"]) - {-1})
+    else:
+        CLUSTER_IDS = list(range(S_ORB.shape[1]))
+    print(f"Centroid similarity loaded: {S_ORB.shape}, {len(CLUSTER_IDS)} clusters")
+else:
+    print("  WARNING: Centroid similarity matrices not loaded. Custom mode unavailable.")
+
+# ── Label resolution ───────────────────────────────────────────────────
+
+def resolve_labels(active_data):
+    """Resolve current clustering labels from the active-labels store data.
+
+    Returns (clusters, families, displays) as pd.Series aligned to df.index.
+    - clusters: integer cluster IDs
+    - families: English family names
+    - displays: display family names (JA if LANG=="ja", else EN)
+    """
+    if active_data is None or not PRESET_LABELS:
+        # Fallback: use CSV columns
+        return df["Cluster"], df["Family"], df.get("FamilyDisplay", df["Family"])
+
+    mode = active_data.get("mode", "preset")
+
+    if mode == "preset":
+        key = active_data.get("key", "balanced")
+        if key not in PRESET_LABELS:
+            key = "balanced"
+        labels = PRESET_LABELS[key]
+        fam_en = PRESET_FAMILIES_EN.get(key, {})
+        fam_ja = PRESET_FAMILIES_JA.get(key, {})
+    else:
+        # Custom: weighted centroid similarity
+        if not _sim_loaded:
+            return df["Cluster"], df["Family"], df.get("FamilyDisplay", df["Family"])
+        w = active_data.get("weights", [0.25, 0.25, 0.25, 0.25])
+        S = w[0] * S_ORB + w[1] * S_MM + w[2] * S_OFM + w[3] * S_ESEN
+        label_indices = S.argmax(axis=1)
+        labels = np.array([CLUSTER_IDS[i] for i in label_indices])
+        fam_en = BALANCED_FAMILY_EN
+        fam_ja = BALANCED_FAMILY_JA
+
+    clusters = pd.Series(labels, index=df.index)
+    families = clusters.astype(str).map(fam_en).fillna("Unclassified")
+    if LANG == "ja":
+        displays = clusters.astype(str).map(fam_ja).fillna(families)
+    else:
+        displays = families
+
+    return clusters, families, displays
+
+
+def get_all_families(active_data):
+    """Get sorted unique family names for the current clustering."""
+    _, families, _ = resolve_labels(active_data)
+    return sorted(families.unique())
+
+
 # ── Lazy Qdrant client (only connected when C7 is used) ─────────────────
 _qdrant_client = None
 _qdrant_error = None
@@ -313,7 +460,7 @@ BODY_FONT = (
     '"Hiragino Sans", "Noto Sans JP", sans-serif'
 )
 
-# ── helpers ───────────────────────────────────────────────────────────────
+# ── helpers ───────────────────────────────────────────────────────────
 AGG_MAP = {
     "Average": "mean", "Median": "median", "Max": "max",
     "Min": "min", "Sum": "sum", "Count": "count",
@@ -338,7 +485,19 @@ def value_to_color(val, vmin, vmax):
 
 
 # ── dropdown option builders ─────────────────────────────────────────────
-family_options = [{"label": family_label(f), "value": f} for f in ALL_FAMILIES]
+
+# Preset dropdown options
+preset_options = [
+    {"label": T[f"preset_{k}"], "value": k}
+    for k in PRESET_KEYS
+    if k in PRESET_LABELS
+]
+if not preset_options:
+    preset_options = [{"label": T["preset_balanced"], "value": "balanced"}]
+
+# Initial family list from balanced preset (will be dynamically updated)
+_init_families = get_all_families({"mode": "preset", "key": "balanced"})
+family_options = [{"label": f, "value": f} for f in _init_families]
 type_options = [{"label": type_label(t), "value": t} for t in ALL_TYPES]
 
 agg_options = [
@@ -417,6 +576,67 @@ app.layout = html.Div(
                style={"color": "#666", "maxWidth": "900px",
                        "marginBottom": "32px"}),
 
+        # ── Active labels store ─────────────────────────────────────────
+        dcc.Store(id="active-labels",
+                  data={"mode": "preset", "key": "balanced"}),
+
+        # ── Clustering control panel ────────────────────────────────────
+        html.Div(style={**CARD, "borderLeft": "4px solid #1976d2"}, children=[
+            html.H3(T["lbl_cluster_mode"],
+                     style={"marginTop": "0", "marginBottom": "12px"}),
+            html.Div(style={"display": "flex", "gap": "24px",
+                            "flexWrap": "wrap", "alignItems": "flex-start"},
+                     children=[
+                # Mode selector
+                html.Div([
+                    dcc.RadioItems(
+                        id="cluster-mode",
+                        options=[
+                            {"label": T["mode_preset"], "value": "preset"},
+                            {"label": T["mode_custom"], "value": "custom"},
+                        ],
+                        value="preset",
+                        inline=True,
+                        style={"fontSize": "14px"},
+                        inputStyle={"marginRight": "6px"},
+                        labelStyle={"marginRight": "20px"},
+                    ),
+                ], style={"marginBottom": "8px"}),
+            ]),
+            # Preset dropdown
+            html.Div(id="preset-container", children=[
+                html.Div(T["lbl_perspective"], style=LABEL),
+                dcc.Dropdown(
+                    id="perspective",
+                    options=preset_options,
+                    value="balanced",
+                    clearable=False,
+                    style={"width": "360px"},
+                ),
+            ], style={"marginTop": "8px"}),
+            # Custom weight sliders
+            html.Div(id="custom-container", children=[
+                html.Div(T["lbl_cluster_weights"],
+                         style={**LABEL, "marginTop": "4px"}),
+                html.Div(style={"display": "flex", "gap": "24px",
+                                "flexWrap": "wrap"}, children=[
+                    html.Div([
+                        html.Div(label, style={**LABEL, "fontSize": "12px"}),
+                        dcc.Slider(
+                            id=f"cw-{sid}", min=0, max=1, step=0.05,
+                            value=0.25,
+                            marks={0: "0", 0.5: "0.5", 1: "1"},
+                            tooltip={"placement": "bottom"},
+                        ),
+                    ], style={"width": "180px"})
+                    for sid, label in [
+                        ("orb", "Orb-v3"), ("mm", "l-MM"),
+                        ("ofm", "l-OFM"), ("esen", "eSEN"),
+                    ]
+                ]),
+            ], style={"marginTop": "8px", "display": "none"}),
+        ]),
+
         # ── 1  PCA ───────────────────────────────────────────────────────
         html.Div(style=CARD, children=[
             html.H3(T["c3_title"]),
@@ -490,7 +710,7 @@ app.layout = html.Div(
                 html.Div([
                     html.Div(T["lbl_families"], style=LABEL),
                     dcc.Dropdown(id="c1-families", options=family_options,
-                                 value=ALL_FAMILIES, multi=True,
+                                 value=_init_families, multi=True,
                                  style={"width": "500px"}),
                 ]),
             ]),
@@ -703,20 +923,73 @@ app.layout = html.Div(
 # CALLBACKS
 # ══════════════════════════════════════════════════════════════════════════
 
+# ── Active labels computation ──────────────────────────────────────────
+@callback(
+    Output("active-labels", "data"),
+    Input("cluster-mode", "value"),
+    Input("perspective", "value"),
+    Input("cw-orb", "value"),
+    Input("cw-mm", "value"),
+    Input("cw-ofm", "value"),
+    Input("cw-esen", "value"),
+)
+def compute_labels(mode, preset, w_orb, w_mm, w_ofm, w_esen):
+    if mode == "preset":
+        return {"mode": "preset", "key": preset or "balanced"}
+    # Custom: normalize weights
+    w = [w_orb or 0.25, w_mm or 0.25, w_ofm or 0.25, w_esen or 0.25]
+    total = sum(w)
+    if total > 0:
+        w = [x / total for x in w]
+    else:
+        w = [0.25, 0.25, 0.25, 0.25]
+    return {"mode": "custom", "weights": w}
+
+
+# ── Clustering mode toggle (show/hide preset vs custom controls) ───────
+@callback(
+    Output("preset-container", "style"),
+    Output("custom-container", "style"),
+    Input("cluster-mode", "value"),
+)
+def toggle_cluster_mode(mode):
+    if mode == "preset":
+        return {"marginTop": "8px"}, {"marginTop": "8px", "display": "none"}
+    return {"marginTop": "8px", "display": "none"}, {"marginTop": "8px"}
+
+
+# ── Dynamic family dropdown options (B4) ──────────────────────────────
+@callback(
+    Output("c1-families", "options"),
+    Output("c1-families", "value"),
+    Output("c4-family", "options"),
+    Input("active-labels", "data"),
+)
+def update_family_options(active_data):
+    families = get_all_families(active_data)
+    opts = [{"label": f, "value": f} for f in families]
+    c4_opts = [{"label": T["opt_all"], "value": "All"}] + opts
+    return opts, families, c4_opts
+
+
 # ── 1 Band gap distribution ──────────────────────────────────────────────
 @callback(
     Output("c1-graph", "figure"),
     Input("c1-agg", "value"),
     Input("c1-type", "value"),
     Input("c1-families", "value"),
+    Input("active-labels", "data"),
 )
-def chart1(agg, chart_type, families):
-    sub = df[df["Family"].isin(families)] if families else df
+def chart1(agg, chart_type, families, active_data):
+    _, fam_series, display_series = resolve_labels(active_data)
+    work = df.assign(Family=fam_series, FamilyDisplay=display_series)
+    sub = work[work["Family"].isin(families)] if families else work
     grouped = sub.groupby("Family")["BandGap"].agg(AGG_MAP[agg]).reset_index()
     grouped.columns = ["Family", "BandGap"]
     grouped = grouped.sort_values("BandGap")
-    # Translate family names for display
-    grouped["FamilyDisplay"] = grouped["Family"].map(family_label)
+    # Build display mapping from the current labels
+    fam_to_display = dict(zip(work["Family"], work["FamilyDisplay"]))
+    grouped["FamilyDisplay"] = grouped["Family"].map(fam_to_display)
     fn = px.bar if chart_type == "Bar" else px.line
     agg_display = AGG_DISPLAY.get(agg, agg)
     fig = fn(grouped, x="FamilyDisplay", y="BandGap",
@@ -734,12 +1007,15 @@ def chart1(agg, chart_type, families):
     Input("c2-left-type", "value"),
     Input("c2-right-type", "value"),
     Input("c2-yaxis", "value"),
+    Input("active-labels", "data"),
 )
-def chart2(left_type, right_type, yaxis_mode):
+def chart2(left_type, right_type, yaxis_mode, active_data):
+    clusters, _, _ = resolve_labels(active_data)
+    work = df.assign(Cluster=clusters)
     figs = []
     y_max = 0
     for mat_type in [left_type, right_type]:
-        sub = df[df["Type"] == mat_type]
+        sub = work[work["Type"] == mat_type]
         grouped = (sub.groupby("Cluster")["BandGap"].mean()
                    .reset_index().sort_values("Cluster"))
         type_disp = type_label(mat_type)
@@ -762,9 +1038,12 @@ def chart2(left_type, right_type, yaxis_mode):
     Input("c3-color", "value"),
     Input("c3-filter", "value"),
     Input("c3-topn", "value"),
+    Input("active-labels", "data"),
 )
-def chart3(ndim, color_by, filter_type, topn_str):
-    sub = df if filter_type == "All" else df[df["Type"] == filter_type]
+def chart3(ndim, color_by, filter_type, topn_str, active_data):
+    clusters, families, displays = resolve_labels(active_data)
+    work = df.assign(Cluster=clusters, Family=families, FamilyDisplay=displays)
+    sub = work if filter_type == "All" else work[work["Type"] == filter_type]
 
     # Determine color column — use display columns for translated labels
     if color_by == "None":
@@ -843,9 +1122,11 @@ COL_HEADERS = {
     Input("c4-type", "value"),
     Input("c4-sort", "value"),
     Input("c4-limit", "value"),
+    Input("active-labels", "data"),
 )
-def chart4(family, mat_type, sort_col, limit):
-    sub = df.copy()
+def chart4(family, mat_type, sort_col, limit, active_data):
+    clusters, families, displays = resolve_labels(active_data)
+    sub = df.assign(Cluster=clusters, Family=families, FamilyDisplay=displays)
     if family != "All":
         sub = sub[sub["Family"] == family]
     if mat_type != "All":
@@ -869,7 +1150,8 @@ def chart4(family, mat_type, sort_col, limit):
             if c == "BandGap":
                 val = f"{val:.3f}"
             elif c == "Family":
-                val = family_label(str(val))
+                # Use display name from FamilyDisplay
+                val = sub.loc[r.name, "FamilyDisplay"] if r.name in sub.index else str(val)
             elif c == "Type":
                 val = type_label(str(val))
             else:
@@ -892,11 +1174,18 @@ def chart4(family, mat_type, sort_col, limit):
     Input("c5-agg", "value"),
     Input("c5-color", "value"),
     Input("c5-sort", "value"),
+    Input("active-labels", "data"),
 )
-def chart5(row_dim, col_dim, val_col, agg_name, color_mode, sort_mode):
+def chart5(row_dim, col_dim, val_col, agg_name, color_mode, sort_mode, active_data):
+    clusters, families, displays = resolve_labels(active_data)
+    work = df.assign(Cluster=clusters, Family=families, FamilyDisplay=displays)
+
+    # Build display mapping for pivot labels
+    fam_to_display = dict(zip(work["Family"], work["FamilyDisplay"]))
+
     agg_fn = AGG_MAP[agg_name]
-    pivot = df.pivot_table(index=row_dim, columns=col_dim,
-                           values=val_col, aggfunc=agg_fn)
+    pivot = work.pivot_table(index=row_dim, columns=col_dim,
+                             values=val_col, aggfunc=agg_fn)
 
     # Sort
     if "Rows" in sort_mode:
@@ -929,12 +1218,11 @@ def chart5(row_dim, col_dim, val_col, agg_name, color_mode, sort_mode):
             })
         )
 
-    # Translate column headers
+    # Translate pivot labels
     def translate_pivot_label(val, dim):
-        """Translate pivot row/column labels."""
         s = str(val)
         if dim == "Family":
-            return family_label(s)
+            return fam_to_display.get(s, s)
         if dim == "Type":
             return type_label(s)
         return s
@@ -1001,18 +1289,21 @@ def chart5(row_dim, col_dim, val_col, agg_name, color_mode, sort_mode):
     Output("c6-graph", "figure"),
     Input("c6-n", "value"),
     Input("c6-metric", "value"),
+    Input("active-labels", "data"),
 )
-def chart6(n, metric):
+def chart6(n, metric, active_data):
+    _, families, displays = resolve_labels(active_data)
+    work = df.assign(Family=families, FamilyDisplay=displays)
+    fam_to_display = dict(zip(work["Family"], work["FamilyDisplay"]))
     if metric == "Count":
-        grouped = df.groupby("Family").size().reset_index(name="Value")
+        grouped = work.groupby("Family").size().reset_index(name="Value")
     elif metric == "Average BandGap":
-        grouped = df.groupby("Family")["BandGap"].mean().reset_index(name="Value")
+        grouped = work.groupby("Family")["BandGap"].mean().reset_index(name="Value")
     else:
-        grouped = df.groupby("Family")["BandGap"].max().reset_index(name="Value")
+        grouped = work.groupby("Family")["BandGap"].max().reset_index(name="Value")
     grouped = grouped.nlargest(n, "Value")
     grouped = grouped.sort_values("Value")
-    # Translate family names for display
-    grouped["FamilyDisplay"] = grouped["Family"].map(family_label)
+    grouped["FamilyDisplay"] = grouped["Family"].map(fam_to_display)
     metric_display = METRIC_DISPLAY.get(metric, metric)
     fig = px.bar(grouped, y="FamilyDisplay", x="Value", orientation="h",
                  title=T["chart_top_n"].format(n=n, metric=metric_display),

docs/cluster_definitions_presets.json

@@ -0,0 +1,400 @@
+{
+  "balanced": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics",
+    "1": "Alkali Fluorides",
+    "2": "Rare Earth Carbonitrides",
+    "3": "Alkali Hydroxides",
+    "4": "Alkali Chalcogenides",
+    "5": "Alkali Chlorides",
+    "6": "Alkali Heavy Halides",
+    "7": "Alkali Phosphates",
+    "8": "Alkali Chalcogenide Oxysalts",
+    "9": "Transition Metal Pnictides",
+    "10": "Transition Metal Silicides",
+    "11": "Heavy Transition Metal Borides",
+    "12": "p-Block Metal Intermetallics",
+    "13": "Rare Earth Intermetallics",
+    "14": "Heavy Transition Metal Oxides (Ba/Ru)",
+    "15": "Alkali Oxides",
+    "16": "Heavy Transition Metal Oxides (Ta/Ba)"
+  },
+  "balanced_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物",
+    "1": "アルカリ金属フッ化物",
+    "2": "希土類炭窒化物",
+    "3": "アルカリ金属水酸化物",
+    "4": "アルカリ金属カルコゲナイド",
+    "5": "アルカリ金属塩化物",
+    "6": "アルカリ金属重ハロゲン化物",
+    "7": "アルカリ金属リン酸塩",
+    "8": "アルカリ金属カルコゲン酸塩",
+    "9": "遷移金属プニクタイド",
+    "10": "遷移金属ケイ化物",
+    "11": "重遷移金属ホウ化物",
+    "12": "p-ブロック金属金属間化合物",
+    "13": "希土類金属間化合物",
+    "14": "重遷移金属酸化物 (Ba/Ru)",
+    "15": "アルカリ金属酸化物",
+    "16": "重遷移金属酸化物 (Ta/Ba)"
+  },
+  "orb_only": {
+    "-1": "Unclassified / Noise",
+    "0": "Alkali Fluorides",
+    "1": "Alkaline Earth Carbonitrides",
+    "2": "Alkali Chalcogenide Oxysalts",
+    "3": "Rare Earth Intermetallics (Hg/Pm)",
+    "4": "Alkali Chlorides",
+    "5": "Heavy Transition Metal Intermetallics (Pt/Rh)",
+    "6": "p-Block Metal Intermetallics",
+    "7": "Transition Metal Pnictides",
+    "8": "Heavy Transition Metal Borides",
+    "9": "Transition Metal Intermetallics (Si/B)",
+    "10": "Transition Metal Intermetallics (Ga/Zn)",
+    "11": "Rare Earth Intermetallics (Si/Ge)",
+    "12": "Heavy Transition Metal Intermetallics (In/Au)",
+    "13": "Alkaline Earth Pnictides",
+    "14": "Alkali Chalcogenides (Cu/K)",
+    "15": "Rare Earth Chalcogenides (Sb/As)",
+    "16": "Rare Earth Chalcogenides (La/Si)",
+    "17": "Alkali Chalcogenides (P/K)"
+  },
+  "orb_only_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "アルカリ金属フッ化物",
+    "1": "アルカリ土類炭窒化物",
+    "2": "アルカリ金属カルコゲン酸塩",
+    "3": "希土類金属間化合物 (Hg/Pm)",
+    "4": "アルカリ金属塩化物",
+    "5": "重遷移金属金属間化合物 (Pt/Rh)",
+    "6": "p-ブロック金属金属間化合物",
+    "7": "遷移金属プニクタイド",
+    "8": "重遷移金属ホウ化物",
+    "9": "遷移金属金属間化合物 (Si/B)",
+    "10": "遷移金属金属間化合物 (Ga/Zn)",
+    "11": "希土類金属間化合物 (Si/Ge)",
+    "12": "重遷移金属金属間化合物 (In/Au)",
+    "13": "アルカリ土類プニクタイド",
+    "14": "アルカリ金属カルコゲナイド (Cu/K)",
+    "15": "希土類カルコゲナイド (Sb/As)",
+    "16": "希土類カルコゲナイド (La/Si)",
+    "17": "アルカリ金属カルコゲナイド (P/K)"
+  },
+  "mm_only": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics",
+    "1": "Alkali Fluorides",
+    "2": "Alkali Chalcogenide Oxysalts",
+    "3": "Alkaline Earth Nitrides",
+    "4": "Rare Earth Chalcogenides"
+  },
+  "mm_only_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ金属カルコゲン酸塩",
+    "3": "アルカリ土類窒化物",
+    "4": "希土類カルコゲナイド"
+  },
+  "ofm_only": {
+    "-1": "Unclassified / Noise",
+    "0": "Alkali Phosphates",
+    "1": "Transition Metal Nitrides",
+    "2": "Alkali Fluorides",
+    "3": "Rare Earth Intermetallics",
+    "4": "Heavy Transition Metal Intermetallics (Pt/Si)",
+    "5": "Heavy Transition Metal Intermetallics (Si/Ge)",
+    "6": "Transition Metal Chalcogenide Oxysalts (Mo/Mn)",
+    "7": "Transition Metal Chalcogenide Oxysalts (Ti/Zr)",
+    "8": "Transition Metal Chalcogenide Oxysalts (V/Ta)",
+    "9": "p-Block Metal Borates",
+    "10": "Alkali Silicates",
+    "11": "Alkali Chalcogenide Oxysalts",
+    "12": "Rare Earth Chalcogenide Oxysalts",
+    "13": "Heavy Transition Metal Chalcogenide Oxysalts"
+  },
+  "ofm_only_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "アルカリ金属リン酸塩",
+    "1": "遷移金属窒化物",
+    "2": "アルカリ金属フッ化物",
+    "3": "希土類金属間化合物",
+    "4": "重遷移金属金属間化合物 (Pt/Si)",
+    "5": "重遷移金属金属間化合物 (Si/Ge)",
+    "6": "遷移金属カルコゲン酸塩 (Mo/Mn)",
+    "7": "遷移金属カルコゲン酸塩 (Ti/Zr)",
+    "8": "遷移金属カルコゲン酸塩 (V/Ta)",
+    "9": "p-ブロック金属ホウ酸塩",
+    "10": "アルカリ金属ケイ酸塩",
+    "11": "アルカリ金属カルコゲン酸塩",
+    "12": "希土類カルコゲン酸塩",
+    "13": "重遷移金属カルコゲン酸塩"
+  },
+  "esen_only": {
+    "-1": "Unclassified / Noise",
+    "0": "Alkali Oxides",
+    "1": "Rare Earth Oxides",
+    "2": "Heavy Transition Metal Intermetallics",
+    "3": "Rare Earth Chalcogenides",
+    "4": "Alkali Pnictides",
+    "5": "Alkali Chalcogenides",
+    "6": "Alkali Chlorides"
+  },
+  "esen_only_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "アルカリ金属酸化物",
+    "1": "希土類酸化物",
+    "2": "重遷移金属金属間化合物",
+    "3": "希土類カルコゲナイド",
+    "4": "アルカリ金属プニクタイド",
+    "5": "アルカリ金属カルコゲナイド",
+    "6": "アルカリ金属塩化物"
+  },
+  "stability": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics (Li/Mg)",
+    "1": "Alkali Fluorides",
+    "2": "Alkali Hydroxides",
+    "3": "Rare Earth Carbonitrides",
+    "4": "Alkali Chalcogenides",
+    "5": "Alkali Phosphates",
+    "6": "Alkali Chalcogenide Oxysalts",
+    "7": "Alkali Chlorides",
+    "8": "Alkali Heavy Halides",
+    "9": "Heavy Transition Metal Oxides (Ba/Ru)",
+    "10": "Heavy Transition Metal Borides",
+    "11": "Transition Metal Pnictides (Ni/P)",
+    "12": "Transition Metal Pnictides (Si/Co)",
+    "13": "Transition Metal Oxides",
+    "14": "Rare Earth Intermetallics (Sn/Ge)",
+    "15": "Heavy Transition Metal Oxides (Ta/Ba)",
+    "16": "Alkali Oxides",
+    "17": "Alkaline Earth Silicates",
+    "18": "p-Block Metal Intermetallics",
+    "19": "Rare Earth Intermetallics (Pd/Ni)",
+    "20": "Heavy Transition Metal Intermetallics (Au/In)"
+  },
+  "stability_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物 (Li/Mg)",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ金属水酸化物",
+    "3": "希土類炭窒化物",
+    "4": "アルカリ金属カルコゲナイド",
+    "5": "アルカリ金属リン酸塩",
+    "6": "アルカリ金属カルコゲン酸塩",
+    "7": "アルカリ金属塩化物",
+    "8": "アルカリ金属重ハロゲン化物",
+    "9": "重遷移金属酸化物 (Ba/Ru)",
+    "10": "重遷移金属ホウ化物",
+    "11": "遷移金属プニクタイド (Ni/P)",
+    "12": "遷移金属プニクタイド (Si/Co)",
+    "13": "遷移金属酸化物",
+    "14": "希土類金属間化合物 (Sn/Ge)",
+    "15": "重遷移金属酸化物 (Ta/Ba)",
+    "16": "アルカリ金属酸化物",
+    "17": "アルカリ土類ケイ酸塩",
+    "18": "p-ブロック金属金属間化合物",
+    "19": "希土類金属間化合物 (Pd/Ni)",
+    "20": "重遷移金属金属間化合物 (Au/In)"
+  },
+  "electronic": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics (Li/Mg)",
+    "1": "Alkali Fluorides",
+    "2": "Alkaline Earth Carbonitrides",
+    "3": "Alkali Hydroxides",
+    "4": "Alkali Chalcogenides",
+    "5": "Heavy Transition Metal Intermetallics (Si/Ni)",
+    "6": "Alkali Phosphates",
+    "7": "Alkali Chlorides",
+    "8": "Alkali Heavy Halides",
+    "9": "Transition Metal Chalcogenide Oxysalts",
+    "10": "Transition Metal Oxides (Mo/V)",
+    "11": "Alkali Oxides",
+    "12": "Heavy Transition Metal Oxides",
+    "13": "Transition Metal Oxides (Mn/Fe)"
+  },
+  "electronic_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物 (Li/Mg)",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ土類炭窒化物",
+    "3": "アルカリ金属水酸化物",
+    "4": "アルカリ金属カルコゲナイド",
+    "5": "重遷移金属金属間化合物 (Si/Ni)",
+    "6": "アルカリ金属リン酸塩",
+    "7": "アルカリ金属塩化物",
+    "8": "アルカリ金属重ハロゲン化物",
+    "9": "遷移金属カルコゲン酸塩",
+    "10": "遷移金属酸化物 (Mo/V)",
+    "11": "アルカリ金属酸化物",
+    "12": "重遷移金属酸化物",
+    "13": "遷移金属酸化物 (Mn/Fe)"
+  },
+  "structural": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics",
+    "1": "Alkali Fluorides",
+    "2": "Rare Earth Carbonitrides",
+    "3": "Alkali Hydroxides",
+    "4": "Alkali Chalcogenides",
+    "5": "Alkali Phosphates",
+    "6": "Alkali Chlorides",
+    "7": "Alkali Heavy Halides",
+    "8": "Heavy Transition Metal Oxides (Ba/Ru)",
+    "9": "Transition Metal Pnictides (Ni/P)",
+    "10": "Alkali Chalcogenide Oxysalts",
+    "11": "Transition Metal Oxides (Mo/V)",
+    "12": "Heavy Transition Metal Borides",
+    "13": "Transition Metal Pnictides (Si/Co)",
+    "14": "p-Block Metal Intermetallics",
+    "15": "Rare Earth Intermetallics",
+    "16": "Alkali Silicates",
+    "17": "Heavy Transition Metal Oxides (Ba/Ta)",
+    "18": "Transition Metal Oxides (Mn/Fe)"
+  },
+  "structural_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物",
+    "1": "アルカリ金属フッ化物",
+    "2": "希土類炭窒化物",
+    "3": "アルカリ金属水酸化物",
+    "4": "アルカリ金属カルコゲナイド",
+    "5": "アルカリ金属リン酸塩",
+    "6": "アルカリ金属塩化物",
+    "7": "アルカリ金属重ハロゲン化物",
+    "8": "重遷移金属酸化物 (Ba/Ru)",
+    "9": "遷移金属プニクタイド (Ni/P)",
+    "10": "アルカリ金属カルコゲン酸塩",
+    "11": "遷移金属酸化物 (Mo/V)",
+    "12": "重遷移金属ホウ化物",
+    "13": "遷移金属プニクタイド (Si/Co)",
+    "14": "p-ブロック金属金属間化合物",
+    "15": "希土類金属間化合物",
+    "16": "アルカリ金属ケイ酸塩",
+    "17": "重遷移金属酸化物 (Ba/Ta)",
+    "18": "遷移金属酸化物 (Mn/Fe)"
+  },
+  "chemical": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics (Li/Mg)",
+    "1": "Alkali Fluorides",
+    "2": "Alkaline Earth Carbonitrides",
+    "3": "Alkali Hydroxides",
+    "4": "Alkali Phosphates",
+    "5": "Alkali Chalcogenides",
+    "6": "Alkali Heavy Halides",
+    "7": "Alkali Chlorides",
+    "8": "Transition Metal Pnictides",
+    "9": "Heavy Transition Metal Oxides (Ba/Ru)",
+    "10": "Heavy Transition Metal Borides",
+    "11": "Transition Metal Oxides (Mo/V)",
+    "12": "Alkali Chalcogenide Oxysalts",
+    "13": "Transition Metal Silicides",
+    "14": "Heavy Transition Metal Oxides (Ta/Ba)",
+    "15": "Transition Metal Oxides (Mn/Fe)",
+    "16": "Alkali Oxides",
+    "17": "Alkali Silicates",
+    "18": "Heavy Transition Metal Intermetallics (Pd/Ni)",
+    "19": "Heavy Transition Metal Intermetallics (Au/In)",
+    "20": "p-Block Metal Intermetallics"
+  },
+  "chemical_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物 (Li/Mg)",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ土類炭窒化物",
+    "3": "アルカリ金属水酸化物",
+    "4": "アルカリ金属リン酸塩",
+    "5": "アルカリ金属カルコゲナイド",
+    "6": "アルカリ金属重ハロゲン化物",
+    "7": "アルカリ金属塩化物",
+    "8": "遷移金属プニクタイド",
+    "9": "重遷移金属酸化物 (Ba/Ru)",
+    "10": "重遷移金属ホウ化物",
+    "11": "遷移金属酸化物 (Mo/V)",
+    "12": "アルカリ金属カルコゲン酸塩",
+    "13": "遷移金属ケイ化物",
+    "14": "重遷移金属酸化物 (Ta/Ba)",
+    "15": "遷移金属酸化物 (Mn/Fe)",
+    "16": "アルカリ金属酸化物",
+    "17": "アルカリ金属ケイ酸塩",
+    "18": "重遷移金属金属間化合物 (Pd/Ni)",
+    "19": "重遷移金属金属間化合物 (Au/In)",
+    "20": "p-ブロック金属金属間化合物"
+  },
+  "coord_energy": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics",
+    "1": "Alkali Fluorides",
+    "2": "Alkali Hydroxides",
+    "3": "Alkali Oxides",
+    "4": "Alkali Heavy Halides",
+    "5": "Alkaline Earth Carbonitrides",
+    "6": "Alkali Chalcogenides",
+    "7": "p-Block Metal Intermetallics",
+    "8": "Rare Earth Intermetallics",
+    "9": "Transition Metal Pnictides",
+    "10": "Transition Metal Silicides",
+    "11": "Heavy Transition Metal Borides"
+  },
+  "coord_energy_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ金属水酸化物",
+    "3": "アルカリ金属酸化物",
+    "4": "アルカリ金属重ハロゲン化物",
+    "5": "アルカリ土類炭窒化物",
+    "6": "アルカリ金属カルコゲナイド",
+    "7": "p-ブロック金属金属間化合物",
+    "8": "希土類金属間化合物",
+    "9": "遷移金属プニクタイド",
+    "10": "遷移金属ケイ化物",
+    "11": "重遷移金属ホウ化物"
+  },
+  "mechanochem": {
+    "-1": "Unclassified / Noise",
+    "0": "Heavy Transition Metal Intermetallics",
+    "1": "Alkali Fluorides",
+    "2": "Alkaline Earth Carbonitrides",
+    "3": "Alkali Hydroxides",
+    "4": "Alkali Chlorides",
+    "5": "Alkali Heavy Halides",
+    "6": "Alkali Chalcogenides",
+    "7": "Alkali Phosphates",
+    "8": "Rare Earth Intermetallics",
+    "9": "Transition Metal Pnictides",
+    "10": "Transition Metal Silicides",
+    "11": "Heavy Transition Metal Borides",
+    "12": "Alkali Chalcogenide Oxysalts",
+    "13": "Transition Metal Chalcogenide Oxysalts",
+    "14": "Heavy Transition Metal Oxides",
+    "15": "Alkali Oxides",
+    "16": "Transition Metal Oxides",
+    "17": "Rare Earth Oxides"
+  },
+  "mechanochem_ja": {
+    "-1": "未分類 / ノイズ",
+    "0": "重遷移金属金属間化合物",
+    "1": "アルカリ金属フッ化物",
+    "2": "アルカリ土類炭窒化物",
+    "3": "アルカリ金属水酸化物",
+    "4": "アルカリ金属塩化物",
+    "5": "アルカリ金属重ハロゲン化物",
+    "6": "アルカリ金属カルコゲナイド",
+    "7": "アルカリ金属リン酸塩",
+    "8": "希土類金属間化合物",
+    "9": "遷移金属プニクタイド",
+    "10": "遷移金属ケイ化物",
+    "11": "重遷移金属ホウ化物",
+    "12": "アルカリ金属カルコゲン酸塩",
+    "13": "遷移金属カルコゲン酸塩",
+    "14": "重遷移金属酸化物",
+    "15": "アルカリ金属酸化物",
+    "16": "遷移金属酸化物",
+    "17": "希土類酸化物"
+  }
+}

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