Update app.py

app.py

@@ -8,23 +8,28 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import gradio as gr
 
-# -------- tabulate（可選）偵測，沒裝也不會壞 --------
+# ---- 可選依賴偵測 ----
 try:
     import tabulate as _tabulate  # noqa: F401
     HAS_TABULATE = True
 except Exception:
     HAS_TABULATE = False
 
+try:
+    import numpy as np
+    import pygmt
+    HAS_PYGMT = True
+except Exception:
+    HAS_PYGMT = False
+
 # -----------------------------
 # 台北時區 (UTC+8)
 # -----------------------------
 TAIPEI_TZ = timezone(timedelta(hours=8))
 
-
 def _fmt(dt: datetime) -> str:
     return dt.strftime("%Y-%m-%dT%H:%M:%S")
 
-
 def set_time_range(hours=None, days=None):
     """依台北時間回傳 (timeFrom, timeTo) 字串"""
     now = datetime.now(TAIPEI_TZ)
@@ -36,13 +41,11 @@ def set_time_range(hours=None, days=None):
         t_from = now - timedelta(days=3)
     return _fmt(t_from), _fmt(now)
 
-
 # -----------------------------
 # 取 API 資料
 # -----------------------------
 API_URL = "https://opendata.cwa.gov.tw/api/v1/rest/datastore/E-A0015-001"
 
-
 def fetch_reports(time_from, time_to):
     api_key = os.getenv("CWA_API_KEY", "").strip()
     if not api_key:
@@ -52,7 +55,6 @@ def fetch_reports(time_from, time_to):
     r.raise_for_status()
     return r.json()
 
-
 # -----------------------------
 # 解析 JSON → DataFrame（彈性容錯）
 # -----------------------------
@@ -65,7 +67,6 @@ def _safe_get(d, *keys, default=None):
             return default
     return cur
 
-
 def _to_float(x):
     try:
         if x is None or str(x).strip() == "":
@@ -74,7 +75,6 @@ def _to_float(x):
     except Exception:
         return None
 
-
 def parse_ea0015(obj):
     """
     支援 records/Records、earthquake/Earthquake 等大小寫差異。
@@ -123,16 +123,14 @@ def parse_ea0015(obj):
         df = df.sort_values("OriginTime", ascending=False, na_position="last").reset_index(drop=True)
     return df
 
-
 # -----------------------------
-# 視覺化（回傳「檔案路徑」以相容舊/新 Gradio）
+# 視覺化（回傳檔案路徑；相容舊/新 Gradio）
 # -----------------------------
-def _save_fig_to_tmp(fig, suffix=".png"):
-    buf_path = tempfile.NamedTemporaryFile(delete=False, suffix=suffix).name
-    fig.savefig(buf_path, format="png", dpi=160, bbox_inches="tight")
+def _save_fig_to_tmp(fig, suffix=".png", dpi=180):
+    outpath = tempfile.NamedTemporaryFile(delete=False, suffix=suffix).name
+    fig.savefig(outpath, format="png", dpi=dpi, bbox_inches="tight")
     plt.close(fig)
-    return buf_path
-
+    return outpath
 
 def plot_trend_path(df):
     if df.empty:
@@ -145,24 +143,69 @@ def plot_trend_path(df):
     fig.autofmt_xdate()
     return _save_fig_to_tmp(fig)
 
-
 def plot_map_path(df):
+    """
+    優先使用 PyGMT 畫台灣區域地圖；若 PyGMT 不可用，退回 Matplotlib 版。
+    範圍：119/123, 21/26；顏色=深度(km)，大小=規模
+    """
+    lon_min, lon_max, lat_min, lat_max = 119, 123, 21, 26
+
+    # ---- PyGMT 版本 ----
+    if HAS_PYGMT and not df.empty:
+        d = df.dropna(subset=["Lon", "Lat"]).copy()
+        if d.empty:
+            return None
+
+        mag = d["Magnitude"].fillna(0).clip(lower=0)
+        size_cm = 0.06 * (mag + 1.5)             # 各點大小（cm）
+        depth = d["Depth_km"].fillna(0)
+
+        vmin = float(max(0, np.nanmin(depth)))
+        vmax = float(max(100, np.nanmax(depth)))
+        cmap = "roma"  # 或試 "turbo", "viridis"
+
+        fig = pygmt.Figure()
+        region = [lon_min, lon_max, lat_min, lat_max]
+
+        fig.coast(
+            region=region, projection="M12c",
+            land="lightgray", water="white",
+            shorelines="0.5p,black", borders="1/0.6p,black",
+            frame=["WSen", "xaf", "yaf"]
+        )
+
+        # 畫震央
+        # 這裡用 per-point size：把每個大小轉字串傳入 style
+        fig.plot(
+            x=d["Lon"].to_list(), y=d["Lat"].to_list(),
+            style=["c{}c".format(s) for s in size_cm.to_list()],
+            color=depth.to_list(), cmap=cmap, pen="0.25p,black"
+        )
+
+        fig.colorbar(frame=["x+lDepth (km)"], cmap=True, position="JMR+w7c/0.4c+o0.6c/0c")
+        fig.basemap(map_scale="jBL+w50k+o0.6c/0.6c+f+lkm")
+
+        outpath = tempfile.NamedTemporaryFile(delete=False, suffix=".png").name
+        fig.savefig(outpath, dpi=220)
+        return outpath
+
+    # ---- 備援：Matplotlib 版本 ----
     if df.empty:
         return None
-    lon_min, lon_max, lat_min, lat_max = 119, 123, 21, 26
     fig, ax = plt.subplots(figsize=(6, 6))
     ax.set_xlim(lon_min, lon_max)
     ax.set_ylim(lat_min, lat_max)
     mags = df["Magnitude"].fillna(0)
     sizes = (mags.clip(lower=0) + 2) ** 3
-    ax.scatter(df["Lon"], df["Lat"], s=sizes, alpha=0.6, edgecolor="black")
-    for m in [3, 4, 5, 6]:
-        ax.scatter([], [], s=((m + 2) ** 3), alpha=0.6, edgecolor="black", label=f"M {m}")
-    ax.legend(title="Magnitude")
+    sc = ax.scatter(df["Lon"], df["Lat"], s=sizes, c=df["Depth_km"], alpha=0.8, edgecolor="black")
+    cb = plt.colorbar(sc, ax=ax, fraction=0.046, pad=0.04)
+    cb.set_label("Depth (km)")
+    ax.set_xlabel("Longitude (°E)")
+    ax.set_ylabel("Latitude (°N)")
+    ax.set_title("Epicenters in Taiwan Region (119–123E, 21–26N)")
     ax.grid(True, linestyle="--", alpha=0.3)
     return _save_fig_to_tmp(fig)
 
-
 # -----------------------------
 # 表格輸出（tabulate 可選）
 # -----------------------------
@@ -176,7 +219,6 @@ def _format_taipei(series):
     except Exception:
         return series.astype(str)
 
-
 def _to_simple_md_table(df: pd.DataFrame) -> str:
     cols = list(df.columns)
     header = "|" + "|".join(cols) + "|\n"
@@ -190,7 +232,6 @@ def _to_simple_md_table(df: pd.DataFrame) -> str:
         rows.append("|" + "|".join(cells) + "|")
     return header + sep + "\n".join(rows)
 
-
 def df_to_markdown(df, top_n=100):
     if df.empty:
         return "（查無資料）"
@@ -206,7 +247,6 @@ def df_to_markdown(df, top_n=100):
         table = _to_simple_md_table(slim.reset_index(drop=True))
     return header + table
 
-
 # -----------------------------
 # 主流程
 # -----------------------------
@@ -233,7 +273,6 @@ def query_and_render(time_from, time_to, sort_order):
     except Exception as e:
         return f"錯誤：{e}", None, None, None
 
-
 # -----------------------------
 # 介面
 # -----------------------------
@@ -261,10 +300,9 @@ with gr.Blocks(fill_height=True) as demo:
         run_btn = gr.Button("查詢", variant="primary")
 
         table_out = gr.Markdown("（尚未查詢）")
-        # 回傳檔案路徑 → Image 用 filepath 模式最穩
         trend_out = gr.Image(label="趨勢圖", type="filepath")
-        map_out = gr.Image(label="台灣範圍圖", type="filepath")
-        dl_btn = gr.DownloadButton(label="下載 CSV")  # 不使用 file_name 參數，傳路徑即可
+        map_out = gr.Image(label="台灣範圍圖（PyGMT）", type="filepath")
+        dl_btn = gr.DownloadButton(label="下載 CSV")  # 傳路徑，不用 file_name 參數
 
     # 快速鍵
     btn_12h.click(lambda: set_time_range(hours=12), outputs=[time_from, time_to])