Update app.py

app.py

@@ -5,6 +5,7 @@ import tempfile
 from datetime import datetime, timedelta
 from dateutil import tz
 import time
+import logging
 
 import gradio as gr
 import pandas as pd
@@ -22,6 +23,10 @@ from grafanalib.core import (
     Dashboard, Graph, Row, Target, YAxis, YAxes, Time, BarGauge
 )
 
+# 設置日誌
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
 TAIPEI = tz.gettz("Asia/Taipei")
 
 # -----------------------------
@@ -34,36 +39,23 @@ DRIVE_PRESETS = [
 ]
 
 def normalize_drive_url(url: str) -> str:
-    """
-    接受 Google Drive / Google Sheets 各式分享連結，回傳可直接給 pandas 讀取 CSV 的 URL。
-    - Sheets: .../spreadsheets/d/<ID>/edit → .../export?format=csv
-    - Drive File: .../file/d/<ID>/view → https://drive.google.com/uc?export=download&id=<ID>
-    """
     if not isinstance(url, str) or not url.strip():
         raise ValueError("請提供有效的 Google 連結")
-
     url = url.strip()
-
-    # Sheets
     m = re.search(r"https://docs\.google\.com/spreadsheets/d/([a-zA-Z0-9-_]+)", url)
     if m:
         sheet_id = m.group(1)
         return f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv"
-
-    # Drive file
     m = re.search(r"https://drive\.google\.com/file/d/([a-zA-Z0-9-_]+)/", url)
     if m:
         file_id = m.group(1)
         return f"https://drive.google.com/uc?export=download&id={file_id}"
-
     return url
 
-
 # -----------------------------
 # Demo / Data loading with dynamic update
 # -----------------------------
 def make_demo_dataframe(last_time=None) -> tuple[pd.DataFrame, datetime]:
-    """隨機示範資料：含經緯度 + pid，模擬實時更新"""
     if last_time is None:
         last_time = datetime.now(tz=TAIPEI) - timedelta(minutes=60)
     else:
@@ -73,19 +65,12 @@ def make_demo_dataframe(last_time=None) -> tuple[pd.DataFrame, datetime]:
     cnt = np.random.randint(0, 11, size=len(times))
     lats = np.random.uniform(21.8, 25.3, size=len(times))
     lons = np.random.uniform(120.0, 122.0, size=len(times))
-    df = pd.DataFrame({
-        "time": times,
-        "amplitude": amp,
-        "count": cnt,
-        "lat": lats,
-        "lon": lons
-    })
+    df = pd.DataFrame({"time": times, "amplitude": amp, "count": cnt, "lat": lats, "lon": lons})
     df["pid"] = np.arange(len(df))
+    logger.debug(f"Generated new data with last_time: {last_time}")
     return df, last_time
 
-
 def _finalize_time(df: pd.DataFrame) -> pd.DataFrame:
-    """確保 time 欄位有時區、排序"""
     time_col = next((c for c in ["time", "timestamp", "datetime", "date"] if c in df.columns), None)
     if time_col is None:
         raise ValueError("資料需包含時間欄位（time/timestamp/datetime/date 其一）")
@@ -97,83 +82,50 @@ def _finalize_time(df: pd.DataFrame) -> pd.DataFrame:
         df["time"] = df["time"].dt.tz_convert(TAIPEI)
     return df.sort_values("time").reset_index(drop=True)
 
-
 def load_csv(file: gr.File | None) -> pd.DataFrame:
-    """讀上傳 CSV"""
     try:
         df = pd.read_csv(file.name)
-        df = _finalize_time(df)
-        # 若無 lat/lon，補隨機（避免地圖空白）
-        if "lat" not in df.columns or "lon" not in df.columns:
-            n = len(df)
-            df["lat"] = np.random.uniform(21.8, 25.3, size=n)
-            df["lon"] = np.random.uniform(120.0, 122.0, size=n)
-        if "pid" not in df.columns:
-            df["pid"] = np.arange(len(df))
-        return df
+        return _finalize_time(df)
     except Exception as e:
         raise ValueError(f"CSV 載入失敗：{str(e)}")
 
-
 def load_drive_csv(sheet_or_file_url: str) -> pd.DataFrame:
-    """從 Google Sheets 或 Google Drive File 讀 CSV"""
     try:
         url = normalize_drive_url(sheet_or_file_url)
         df = pd.read_csv(url)
-        df = _finalize_time(df)
-        if "lat" not in df.columns or "lon" not in df.columns:
-            n = len(df)
-            df["lat"] = np.random.uniform(21.8, 25.3, size=n)
-            df["lon"] = np.random.uniform(120.0, 122.0, size=n)
-        if "pid" not in df.columns:
-            df["pid"] = np.arange(len(df))
-        return df
+        return _finalize_time(df)
     except Exception as e:
         raise ValueError(f"Google 連結載入失敗：{str(e)}")
 
-
 def load_data(source: str, file: gr.File | None = None, sheet_url: str = "", last_time=None) -> tuple[pd.DataFrame, datetime]:
-    """依來源載入資料：demo / upload / drive，支援動態更新"""
     if source == "drive":
         if not sheet_url:
             raise ValueError("請選擇 Google 連結")
-        df = load_drive_csv(sheet_url)
-        return df, None
+        return load_drive_csv(sheet_url), None
     elif source == "upload":
         if file is None:
             raise ValueError("請上傳 CSV 檔")
-        df = load_csv(file)
-        return df, None
+        return load_csv(file), None
     else:
         return make_demo_dataframe(last_time)
 
-
 # -----------------------------
 # 新功能：資料過濾
 # -----------------------------
 def filter_data(df: pd.DataFrame, start_time: str, end_time: str) -> pd.DataFrame:
-    """根據時間範圍過濾資料"""
     if start_time:
         df = df[df["time"] >= pd.to_datetime(start_time).tz_localize(TAIPEI)]
     if end_time:
         df = df[df["time"] <= pd.to_datetime(end_time).tz_localize(TAIPEI)]
     return df
 
-
 # -----------------------------
-# grafanalib JSON builder (新增 BarGauge)
+# grafanalib JSON builder
 # -----------------------------
 def build_grafanalib_dashboard(series_columns: list[str], dual_axis: bool, rolling_window: int) -> dict:
-    panels = []
-    panels.append(
-        Graph(
-            title=f"{series_columns[0]}",
-            dataSource="(example)",
-            targets=[Target(expr=f"{series_columns[0]}", legendFormat=series_columns[0])],
-            lines=True, bars=False, points=False,
-            yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short")),
-        )
-    )
+    panels = [
+        Graph(title=f"{series_columns[0]}", dataSource="(example)", targets=[Target(expr=f"{series_columns[0]}", legendFormat=series_columns[0])], lines=True, bars=False, points=False, yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short"))),
+    ]
     if len(series_columns) > 1:
         targets = [Target(expr=f"{series_columns[1]}", legendFormat=series_columns[1])]
         lines, bars, title = False, True, f"{series_columns[1]} (bar)"
@@ -181,40 +133,12 @@ def build_grafanalib_dashboard(series_columns: list[str], dual_axis: bool, rolli
             targets.append(Target(expr=f"{series_columns[0]}", legendFormat=f"{series_columns[0]} (line)"))
             lines, bars = True, True
             title = f"{series_columns[1]} (bar) + {series_columns[0]} (line)"
-        panels.append(
-            Graph(
-                title=title,
-                dataSource="(example)",
-                targets=targets,
-                lines=lines, bars=bars, points=False,
-                yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short")),
-            )
-        )
-    panels.append(
-        Graph(
-            title=f"{series_columns[0]} rolling({rolling_window})",
-            dataSource="(example)",
-            targets=[Target(expr=f"{series_columns[0]}_rolling{rolling_window}",
-                            legendFormat=f"{series_columns[0]}_rolling{rolling_window}")],
-            lines=True, bars=False, points=False,
-            yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short")),
-        )
-    )
-    # 新增 BarGauge 面板，顯示最新值
-    panels.append(
-        BarGauge(
-            title=f"Latest {series_columns[0]}",
-            dataSource="(example)",
-            targets=[Target(expr=f"last({series_columns[0]})", legendFormat=series_columns[0])],
-        )
-    )
-    return Dashboard(
-        title="Grafana-like Demo (grafanalib + Gradio)",
-        rows=[Row(panels=panels)],
-        timezone="browser",
-        time=Time("now-1h", "now"),
-    ).to_json_data()
-
+        panels.append(Graph(title=title, dataSource="(example)", targets=targets, lines=lines, bars=bars, points=False, yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short"))))
+    panels.extend([
+        Graph(title=f"{series_columns[0]} rolling({rolling_window})", dataSource="(example)", targets=[Target(expr=f"{series_columns[0]}_rolling{rolling_window}", legendFormat=f"{series_columns[0]}_rolling{rolling_window}")], lines=True, bars=False, points=False, yAxes=YAxes(left=YAxis(format="short"), right=YAxis(format="short"))),
+        BarGauge(title=f"Latest {series_columns[0]}", dataSource="(example)", targets=[Target(expr=f"last({series_columns[0]})", legendFormat=series_columns[0])]),
+    ])
+    return Dashboard(title="Grafana-like Demo (grafanalib + Gradio)", rows=[Row(panels=panels)], timezone="browser", time=Time("now-1h", "now")).to_json_data()
 
 # -----------------------------
 # Matplotlib helpers
@@ -229,14 +153,12 @@ def _style_time_axis(ax):
     ax.grid(True, which="major", alpha=0.25)
     plt.margins(x=0.02, y=0.05)
 
-
 def _normalize_times(series: pd.Series) -> pd.Series:
     s = series.copy()
     if getattr(s.dt, "tz", None) is not None:
         s = s.dt.tz_convert("UTC").dt.tz_localize(None)
     return s
 
-
 def render_line(df, col):
     times = _normalize_times(df["time"])
     fig, ax = plt.subplots(figsize=(6, 3))
@@ -248,7 +170,6 @@ def render_line(df, col):
     fig.tight_layout()
     return fig
 
-
 def render_bar_or_dual(df, second_col, first_col, dual_axis):
     times = _normalize_times(df["time"])
     x = mdates.date2num(times.dt.to_pydatetime().tolist())
@@ -270,7 +191,6 @@ def render_bar_or_dual(df, second_col, first_col, dual_axis):
     fig.tight_layout()
     return fig
 
-
 def render_rolling(df, col, window=5):
     times = _normalize_times(df["time"])
     roll_col = f"{col}_rolling{window}"
@@ -285,9 +205,8 @@ def render_rolling(df, col, window=5):
     fig.tight_layout()
     return fig, df
 
-
 # -----------------------------
-# 新增 Gauge 渲染 (使用 Matplotlib patches)
+# 新增 Gauge 渲染
 # -----------------------------
 def degree_range(n):
     start = np.linspace(0, 180, n + 1, endpoint=True)[0:-1]
@@ -295,59 +214,30 @@ def degree_range(n):
     mid_points = start + ((end - start) / 2.)
     return np.c_[start, end], mid_points
 
-
 def rot_text(ang):
     rotation = np.degrees(np.radians(ang) * np.pi / np.pi - np.radians(90))
     return rotation
 
-
 def render_gauge(df, col):
     value = df[col].iloc[-1] if not df.empty else 0
     min_val, max_val = df[col].min(), df[col].max()
     normalized = (value - min_val) / (max_val - min_val + 1e-9) if max_val > min_val else 0
-
     labels = ['LOW', 'MEDIUM', 'HIGH']
     N = len(labels)
-    colors = ['#007A00', '#FFCC00', '#ED1C24']  # Green, Yellow, Red
-
-    if normalized < 0.33:
-        arrow = 1
-    elif normalized < 0.66:
-        arrow = 2
-    else:
-        arrow = 3
-
+    colors = ['#007A00', '#FFCC00', '#ED1C24']
+    arrow = 1 if normalized < 0.33 else 2 if normalized < 0.66 else 3
     fig, ax = plt.subplots(figsize=(5, 3.5))
-
     ang_range, mid_points = degree_range(N)
-
     labels = labels[::-1]
-
-    patches = []
-    for ang, c in zip(ang_range, colors):
-        patches.append(Wedge((0., 0.), .4, *ang, facecolor='w', lw=2))
-        patches.append(Wedge((0., 0.), .4, *ang, width=0.10, facecolor=c, lw=2, alpha=0.5))
-
+    patches = [Wedge((0., 0.), .4, *ang, facecolor='w', lw=2) for ang in ang_range] + [Wedge((0., 0.), .4, *ang, width=0.10, facecolor=c, lw=2, alpha=0.5) for ang, c in zip(ang_range, colors)]
     [ax.add_patch(p) for p in patches]
-
     for mid, lab in zip(mid_points, labels):
-        ax.text(0.35 * np.cos(np.radians(mid)), 0.35 * np.sin(np.radians(mid)), lab,
-                horizontalalignment='center', verticalalignment='center', fontsize=12,
-                fontweight='bold', rotation=rot_text(mid))
-
-    r = Rectangle((-0.4, -0.1), 0.8, 0.1, facecolor='w', lw=2)
-    ax.add_patch(r)
-
-    ax.text(0, -0.05, f"Latest {col}: {value:.2f}", horizontalalignment='center',
-            verticalalignment='center', fontsize=12, fontweight='bold')
-
+        ax.text(0.35 * np.cos(np.radians(mid)), 0.35 * np.sin(np.radians(mid)), lab, horizontalalignment='center', verticalalignment='center', fontsize=12, fontweight='bold', rotation=rot_text(mid))
+    ax.add_patch(Rectangle((-0.4, -0.1), 0.8, 0.1, facecolor='w', lw=2))
+    ax.text(0, -0.05, f"Latest {col}: {value:.2f}", horizontalalignment='center', verticalalignment='center', fontsize=12, fontweight='bold')
     pos = mid_points[abs(arrow - N)]
-    ax.arrow(0, 0, 0.225 * np.cos(np.radians(pos)), 0.225 * np.sin(np.radians(pos)),
-             width=0.04, head_width=0.09, head_length=0.1, fc='k', ec='k')
-
-    ax.add_patch(FancyArrowPatch((0, 0), (0.01 * np.cos(np.radians(pos)), 0.01 * np.sin(np.radians(pos))),
-                                 mutation_scale=10, fc='k', ec='k'))
-
+    ax.arrow(0, 0, 0.225 * np.cos(np.radians(pos)), 0.225 * np.sin(np.radians(pos)), width=0.04, head_width=0.09, head_length=0.1, fc='k', ec='k')
+    ax.add_patch(FancyArrowPatch((0, 0), (0.01 * np.cos(np.radians(pos)), 0.01 * np.sin(np.radians(pos))), mutation_scale=10, fc='k', ec='k'))
     ax.set_frame_on(False)
     ax.axes.set_xticks([])
     ax.axes.set_yticks([])
@@ -355,195 +245,113 @@ def render_gauge(df, col):
     plt.tight_layout()
     return fig
 
-
 # -----------------------------
-# Folium helpers (map + legend + heatmap)
+# Folium helpers
 # -----------------------------
 def _to_hex_color(value: float, cmap=cm.viridis) -> str:
     rgba = cmap(value)
     return "#{:02x}{:02x}{:02x}".format(int(rgba[0]*255), int(rgba[1]*255), int(rgba[2]*255))
 
-
-def render_map_folium(
-    df: pd.DataFrame,
-    value_col: str = "amplitude",
-    size_col: str = "count",
-    cmap_name: str = "viridis",
-    tiles: str = "OpenStreetMap",
-    show_heatmap: bool = False
-) -> str:
+def render_map_folium(df: pd.DataFrame, value_col: str = "amplitude", size_col: str = "count", cmap_name: str = "viridis", tiles: str = "OpenStreetMap", show_heatmap: bool = False) -> str:
     if df.empty:
         return "<p>無資料可顯示地圖</p>"
     center_lat, center_lon = df["lat"].mean(), df["lon"].mean()
     m = folium.Map(location=[center_lat, center_lon], zoom_start=7, tiles=tiles)
-
     vmin, vmax = df[value_col].min(), df[value_col].max()
     cmap = getattr(cm, cmap_name)
-
-    colormap = bcm.LinearColormap(
-        [_to_hex_color(i, cmap) for i in np.linspace(0, 1, 256)],
-        vmin=vmin, vmax=vmax
-    )
+    colormap = bcm.LinearColormap([_to_hex_color(i, cmap) for i in np.linspace(0, 1, 256)], vmin=vmin, vmax=vmax)
     colormap.caption = f"{value_col} (color scale)"
     colormap.add_to(m)
-
     if show_heatmap:
-        # 添加熱圖層
         heat_data = [[row["lat"], row["lon"], row[value_col]] for _, row in df.iterrows()]
         plugins.HeatMap(heat_data, radius=15, blur=10).add_to(m)
     else:
-        # 原有 CircleMarker
         for _, row in df.iterrows():
             norm_val = (row[value_col] - vmin) / (vmax - vmin + 1e-9)
-            popup_html = (
-                f"<b>#ID:</b> {int(row['pid'])}<br>"
-                f"<b>time:</b> {pd.to_datetime(row['time']).strftime('%Y-%m-%d %H:%M:%S')}<br>"
-                f"<b>{value_col}:</b> {row[value_col]:.4f}<br>"
-                f"<b>{size_col}:</b> {row[size_col]}<br>"
-                f"<b>lat/lon:</b> {row['lat']:.5f}, {row['lon']:.5f}"
-            )
-            folium.CircleMarker(
-                location=[row["lat"], row["lon"]],
-                radius=row[size_col] + 3,
-                color="black",
-                weight=1,
-                fill=True,
-                fill_opacity=0.7,
-                fill_color=_to_hex_color(norm_val, cmap),
-                popup=folium.Popup(popup_html, max_width=300),
-            ).add_to(m)
-
+            popup_html = f"<b>#ID:</b> {int(row['pid'])}<br><b>time:</b> {pd.to_datetime(row['time']).strftime('%Y-%m-%d %H:%M:%S')}<br><b>{value_col}:</b> {row[value_col]:.4f}<br><b>{size_col}:</b> {row[size_col]}<br><b>lat/lon:</b> {row['lat']:.5f}, {row['lon']:.5f}"
+            folium.CircleMarker(location=[row["lat"], row["lon"]], radius=row[size_col] + 3, color="black", weight=1, fill=True, fill_opacity=0.7, fill_color=_to_hex_color(norm_val, cmap), popup=folium.Popup(popup_html, max_width=300)).add_to(m)
     return m._repr_html_()
 
-
 # -----------------------------
 # Detail helpers
 # -----------------------------
 def make_point_choices(df: pd.DataFrame) -> list[str]:
-    labels = []
-    for _, r in df.iterrows():
-        t = pd.to_datetime(r["time"]).strftime("%H:%M:%S")
-        labels.append(f"#{int(r['pid'])} | {t} | amp={r.get('amplitude', 0):.3f} cnt={int(r.get('count', 0))}")
-    return labels
-
+    return [f"#{int(r['pid'])} | {pd.to_datetime(r['time']).strftime('%H:%M:%S')} | amp={r.get('amplitude', 0):.3f} cnt={int(r.get('count', 0))}" for _, r in df.iterrows()]
 
 def pick_detail(df: pd.DataFrame, choice: str) -> pd.DataFrame:
     if not choice:
         return pd.DataFrame()
     try:
-        pid_str = choice.split("|")[0].strip().lstrip("#")
-        pid = int(pid_str)
-        row = df[df["pid"] == pid]
-        return row.reset_index(drop=True)
+        pid = int(choice.split("|")[0].strip().lstrip("#"))
+        return df[df["pid"] == pid].reset_index(drop=True)
     except Exception:
         return pd.DataFrame()
 
-
 # -----------------------------
 # Main pipeline with dynamic update
 # -----------------------------
 def pipeline(source, file, sheet_url, series_choice, dual_axis, rolling_window, cmap_choice, tiles_choice, start_time, end_time, show_heatmap, last_time=None):
     try:
         df, new_last_time = load_data(source, file, sheet_url, last_time)
-        df = filter_data(df, start_time, end_time)  # 新增過濾
+        df = filter_data(df, start_time, end_time)
         numeric_cols = [c for c in df.columns if c not in ["time", "lat", "lon", "pid"] and pd.api.types.is_numeric_dtype(df[c])]
-        chosen = [c for c in (series_choice or numeric_cols[:2]) if c in numeric_cols]
-        if not chosen:
-            chosen = numeric_cols[:2]
+        chosen = [c for c in (series_choice or numeric_cols[:2]) if c in numeric_cols] or numeric_cols[:2] or []
         if not chosen:
             raise ValueError("無有效數值欄位可視覺化")
-
         dash_json = build_grafanalib_dashboard(chosen, bool(dual_axis), int(rolling_window))
         dash_json_str = json.dumps(dash_json, ensure_ascii=False, indent=2, default=str)
         with tempfile.NamedTemporaryFile(delete=False, suffix=".json", mode="w", encoding="utf-8") as f:
             f.write(dash_json_str)
             json_path = f.name
-
         fig1 = render_line(df, chosen[0])
         fig2 = render_bar_or_dual(df, chosen[1], chosen[0], bool(dual_axis)) if len(chosen) > 1 else plt.figure()
         fig3, df_with_roll = render_rolling(df.copy(), chosen[0], int(rolling_window))
         fig4 = render_gauge(df, chosen[0])
-
-        map_html = render_map_folium(df, value_col=chosen[0], size_col=chosen[1] if len(chosen) > 1 else "count",
-                                     cmap_name=cmap_choice, tiles=tiles_choice, show_heatmap=bool(show_heatmap))
-
+        map_html = render_map_folium(df, value_col=chosen[0], size_col=chosen[1] if len(chosen) > 1 else "count", cmap_name=cmap_choice, tiles=tiles_choice, show_heatmap=bool(show_heatmap))
         point_choices = [] if show_heatmap else make_point_choices(df)
         default_choice = point_choices[0] if point_choices else ""
         detail_df = pick_detail(df, default_choice)
-
-        demo_df = make_demo_dataframe()[0]  # 只取 DataFrame 部分
+        demo_df = make_demo_dataframe()[0]
         with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode="w", encoding="utf-8") as f:
             demo_df.to_csv(f, index=False)
             demo_csv_path = f.name
-
-        return (
-            fig1, fig2, plot3, plot4, map_out,
-            dash_json_str, json_path, df_with_roll,
-            demo_csv_file,
-            gr.Dropdown(choices=point_choices, value=default_choice),
-            detail_df,
-            "",  # 錯誤訊息清空
-            new_last_time
-        )
+        logger.debug(f"Pipeline executed with new_last_time: {new_last_time}")
+        return fig1, fig2, fig3, fig4, map_html, dash_json_str, json_path, df_with_roll, demo_csv_path, gr.Dropdown(choices=point_choices, value=default_choice), detail_df, "", new_last_time
     except Exception as e:
-        return (
-            None, None, None, None, "<p>錯誤：無資料顯示</p>",
-            "", None, pd.DataFrame(),
-            None,
-            gr.Dropdown(choices=[], value=None),
-            pd.DataFrame(),
-            str(e),
-            last_time
-        )
-
+        logger.error(f"Pipeline error: {str(e)}")
+        return None, None, None, None, "<p>錯誤：無資料顯示</p>", "", None, pd.DataFrame(), None, gr.Dropdown(choices=[], value=None), pd.DataFrame(), str(e), last_time
 
 def regenerate_demo(series_choice, dual_axis, rolling_window, cmap_choice, tiles_choice, current_choice, start_time, end_time, show_heatmap, last_time):
     return pipeline("demo", None, "", series_choice, dual_axis, rolling_window, cmap_choice, tiles_choice, start_time, end_time, show_heatmap, last_time)
 
-
 def update_detail(df: pd.DataFrame, choice: str):
     return pick_detail(df, choice)
 
-
 # -----------------------------
-# UI 優化：添加動態更新按鈕和間隔更新
+# UI 優化
 # -----------------------------
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## 動態時間序列 - Grafana-like Demo + Folium Map（支援 Google Drive / Sheets，新增熱圖與 Gauge）")
-
+    gr.Markdown("## 動態時間序列 - Grafana-like Demo + Folium Map")
     with gr.Row():
         with gr.Column(scale=1):
             source_radio = gr.Radio(["upload", "drive", "demo"], label="資料來源", value="demo")
-            file_in = gr.File(label="上傳 CSV（選 upload 時使用）", file_types=[".csv"])
-            preset_dd = gr.Dropdown(
-                label="Google 預設來源（3 個連結）",
-                choices=DRIVE_PRESETS,
-                value=DRIVE_PRESETS[0]
-            )
+            file_in = gr.File(label="上傳 CSV", file_types=[".csv"])
+            preset_dd = gr.Dropdown(label="Google 預設來源", choices=DRIVE_PRESETS, value=DRIVE_PRESETS[0])
             with gr.Row():
-                start_time_in = gr.Textbox(label="開始時間 (YYYY-MM-DD HH:MM:SS)", placeholder="2023-01-01 00:00:00")
-                end_time_in = gr.Textbox(label="結束時間 (YYYY-MM-DD HH:MM:SS)", placeholder="2023-12-31 23:59:59")
-
+                start_time_in = gr.Textbox(label="開始時間", placeholder="2023-01-01 00:00:00")
+                end_time_in = gr.Textbox(label="結束時間", placeholder="2023-12-31 23:59:59")
         with gr.Column(scale=1):
             series_multiselect = gr.CheckboxGroup(label="數值欄位", choices=[])
-            dual_axis_chk = gr.Checkbox(label="第二面板啟用雙軸", value=False)
+            dual_axis_chk = gr.Checkbox(label="第二面板雙軸", value=False)
             rolling_dd = gr.Dropdown(label="Rolling window", choices=["3", "5", "10", "20"], value="5")
-            cmap_dd = gr.Dropdown(label="地圖配色 (colormap)",
-                                  choices=["viridis", "plasma", "inferno", "magma", "cividis", "coolwarm"],
-                                  value="viridis")
-            tiles_dd = gr.Dropdown(label="地圖底圖 (tiles)",
-                                   choices=["OpenStreetMap", "Stamen Terrain", "Stamen Toner",
-                                            "CartoDB positron", "CartoDB dark_matter"],
-                                   value="OpenStreetMap")
-            heatmap_chk = gr.Checkbox(label="顯示熱圖 (Heatmap)", value=False)
-
+            cmap_dd = gr.Dropdown(label="地圖配色", choices=["viridis", "plasma", "inferno", "magma", "cividis", "coolwarm"], value="viridis")
+            tiles_dd = gr.Dropdown(label="地圖底圖", choices=["OpenStreetMap", "Stamen Terrain", "Stamen Toner", "CartoDB positron", "CartoDB dark_matter"], value="OpenStreetMap")
+            heatmap_chk = gr.Checkbox(label="顯示熱圖", value=False)
     with gr.Row():
         run_btn = gr.Button("產生 Dashboard", scale=1)
         update_btn = gr.Button("手動更新數據", scale=1)
         interval = gr.Slider(5, 60, value=10, step=5, label="自動更新間隔 (秒)")
-
     error_msg = gr.Markdown(value="", label="錯誤訊息", visible=True)
-
     with gr.Tabs():
         with gr.Tab("圖表"):
             with gr.Row():
@@ -556,24 +364,19 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                     plot3 = gr.Plot(label="3：Rolling Mean")
                 with gr.Column(scale=1):
                     plot4 = gr.Plot(label="4：Gauge")
-
         with gr.Tab("地圖"):
-            map_out = gr.HTML(label="5：Geo Map (Interactive + Legend + Heatmap)")
-
+            map_out = gr.HTML(label="5：Geo Map")
         with gr.Tab("JSON & 檔案"):
             json_box = gr.Code(label="grafanalib Dashboard JSON", language="json")
             json_file = gr.File(label="下載 dashboard.json")
             demo_csv_file = gr.File(label="下載示範資料 demo.csv")
-
         with gr.Tab("資料預覽"):
-            df_view = gr.Dataframe(label="資料預覽（含 rolling）", wrap=True)
-
+            df_view = gr.Dataframe(label="資料預覽", wrap=True)
         with gr.Tab("點位詳情"):
-            gr.Markdown("### 🔎 點位詳情（對應地圖彈窗中的 #ID，熱圖模式下不可用）")
-            point_selector = gr.Dropdown(label="選擇點位（#ID | 時間 | 值）", choices=[], value=None)
+            gr.Markdown("### 點位詳情")
+            point_selector = gr.Dropdown(label="選擇點位", choices=[], value=None)
             detail_view = gr.Dataframe(label="選取點詳細資料", wrap=True)
 
-    # 探勘欄位並更新 UI
     def probe_columns(source, file, preset_url, start_time, end_time):
         sheet_url = preset_url if source == "drive" else ""
         try:
@@ -584,54 +387,31 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         except Exception as e:
             return gr.CheckboxGroup(choices=[]), pd.DataFrame(), str(e)
 
-    source_radio.change(probe_columns, inputs=[source_radio, file_in, preset_dd, start_time_in, end_time_in], outputs=[series_multiselect, df_view, error_msg])
-    file_in.change(probe_columns, inputs=[source_radio, file_in, preset_dd, start_time_in, end_time_in], outputs=[series_multiselect, df_view, error_msg])
-    preset_dd.change(probe_columns, inputs=[source_radio, file_in, preset_dd, start_time_in, end_time_in], outputs=[series_multiselect, df_view, error_msg])
-    start_time_in.change(probe_columns, inputs=[source_radio, file_in, preset_dd, start_time_in, end_time_in], outputs=[series_multiselect, df_view, error_msg])
-    end_time_in.change(probe_columns, inputs=[source_radio, file_in, preset_dd, start_time_in, end_time_in], outputs=[series_multiselect, df_view, error_msg])
+    source_radio.change(probe_columns, [source_radio, file_in, preset_dd, start_time_in, end_time_in], [series_multiselect, df_view, error_msg])
+    file_in.change(probe_columns, [source_radio, file_in, preset_dd, start_time_in, end_time_in], [series_multiselect, df_view, error_msg])
+    preset_dd.change(probe_columns, [source_radio, file_in, preset_dd, start_time_in, end_time_in], [series_multiselect, df_view, error_msg])
+    start_time_in.change(probe_columns, [source_radio, file_in, preset_dd, start_time_in, end_time_in], [series_multiselect, df_view, error_msg])
+    end_time_in.change(probe_columns, [source_radio, file_in, preset_dd, start_time_in, end_time_in], [series_multiselect, df_view, error_msg])
 
-    # 初次載入
     demo.load(
         fn=lambda: pipeline("drive", None, DRIVE_PRESETS[0], [], False, "5", "viridis", "OpenStreetMap", "", "", False),
-        outputs=[
-            plot1, plot2, plot3, plot4, map_out,
-            json_box, json_file, df_view,
-            demo_csv_file,
-            point_selector, detail_view,
-            error_msg,
-            gr.State(value=None)
-        ]
+        outputs=[plot1, plot2, plot3, plot4, map_out, json_box, json_file, df_view, demo_csv_file, point_selector, detail_view, error_msg, gr.State(value=None)]
     )
 
-    # 產生 / 重新產生 / 動態更新
     run_btn.click(
         fn=pipeline,
         inputs=[source_radio, file_in, preset_dd, series_multiselect, dual_axis_chk, rolling_dd, cmap_dd, tiles_dd, start_time_in, end_time_in, heatmap_chk, gr.State(value=None)],
-        outputs=[
-            plot1, plot2, plot3, plot4, map_out,
-            json_box, json_file, df_view,
-            demo_csv_file,
-            point_selector, detail_view,
-            error_msg,
-            gr.State()
-        ]
+        outputs=[plot1, plot2, plot3, plot4, map_out, json_box, json_file, df_view, demo_csv_file, point_selector, detail_view, error_msg, gr.State()]
     )
 
     update_btn.click(
         fn=pipeline,
         inputs=[source_radio, file_in, preset_dd, series_multiselect, dual_axis_chk, rolling_dd, cmap_dd, tiles_dd, start_time_in, end_time_in, heatmap_chk, gr.State()],
-        outputs=[
-            plot1, plot2, plot3, plot4, map_out,
-            json_box, json_file, df_view,
-            demo_csv_file,
-            point_selector, detail_view,
-            error_msg,
-            gr.State()
-        ]
+        outputs=[plot1, plot2, plot3, plot4, map_out, json_box, json_file, df_view, demo_csv_file, point_selector, detail_view, error_msg, gr.State()]
     )
 
-    # 自動更新邏輯
     def start_auto_update(interval):
+        logger.debug(f"Setting auto update interval to {interval} seconds")
         return gr.update(value=interval)
 
     interval.change(
@@ -650,13 +430,13 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             }, intervalValue);
         }
         update();
+        document.querySelector('input[type="range"]').addEventListener('input', function() {
+            intervalValue = parseInt(this.value) * 1000;
+            clearTimeout(window.updateTimeout);
+            update();
+        });
     }
     startAutoUpdate();
-    document.querySelector('input[type="range"]').addEventListener('input', function() {
-        let newInterval = parseInt(this.value) * 1000;
-        clearTimeout(window.updateTimeout);
-        startAutoUpdate();
-    });
     """
 
     point_selector.change(
@@ -666,4 +446,4 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)  # 方便部署，綁定所有 IP
+    demo.launch(server_name="0.0.0.0", server_port=7860)