Update app.py

app.py

@@ -1,5 +1,4 @@
 import os
-import io
 import tempfile
 from datetime import datetime, timedelta, timezone
 
@@ -56,17 +55,8 @@ def fetch_reports(time_from, time_to):
     return r.json()
 
 # -----------------------------
-# JSON 解析（修正為讀 EarthquakeInfo）
+# JSON 解析（讀 EarthquakeInfo）
 # -----------------------------
-def _safe_get(d, *keys, default=None):
-    cur = d
-    for k in keys:
-        if isinstance(cur, dict) and k in cur:
-            cur = cur[k]
-        else:
-            return default
-    return cur
-
 def _to_float(x):
     try:
         if x is None or str(x).strip() == "":
@@ -134,8 +124,10 @@ def _save_fig_to_tmp(fig, suffix=".png", dpi=180):
 def plot_trend_path(df):
     if df.empty:
         return None
+    # 顯式轉數值更穩
+    m = pd.to_numeric(df["Magnitude"], errors="coerce")
     fig, ax = plt.subplots(figsize=(6, 4))
-    ax.scatter(df["OriginTime"], df["Magnitude"])
+    ax.scatter(df["OriginTime"], m)
     ax.set_xlabel("Origin Time (Taipei)")
     ax.set_ylabel("Magnitude")
     ax.grid(True, linestyle="--", alpha=0.4)
@@ -153,9 +145,9 @@ def plot_map_path(df):
     if HAS_PYGMT and not df.empty:
         d = df.dropna(subset=["Lon", "Lat"]).copy()
         if not d.empty:
-            mag = d["Magnitude"].fillna(0).clip(lower=0)
+            mag = pd.to_numeric(d["Magnitude"], errors="coerce").fillna(0).clip(lower=0)
             size_cm = 0.06 * (mag + 1.5)          # 每點大小（cm）
-            depth = d["Depth_km"].fillna(0)
+            depth = pd.to_numeric(d["Depth_km"], errors="coerce").fillna(0)
 
             vmin = float(max(0, float(depth.min()) if len(depth) else 0))
             vmax = float(max(100, float(depth.max()) if len(depth) else 100))
@@ -182,17 +174,18 @@ def plot_map_path(df):
             fig.savefig(outpath, dpi=220)
             return outpath
 
-    # --- Matplotlib 備援 ---
+    # --- Matplotlib 備援（顯式轉數值，避免 FutureWarning） ---
     if df.empty:
         return None
     fig, ax = plt.subplots(figsize=(6, 6))
     ax.set_xlim(lon_min, lon_max)
     ax.set_ylim(lat_min, lat_max)
-    sc = ax.scatter(
-        df["Lon"], df["Lat"],
-        s=(df["Magnitude"].fillna(0).clip(lower=0) + 2) ** 3,
-        c=df["Depth_km"], edgecolor="black", alpha=0.85
-    )
+
+    m = pd.to_numeric(df["Magnitude"], errors="coerce").fillna(0).clip(lower=0)
+    s = (m + 2) ** 3
+    depth = pd.to_numeric(df["Depth_km"], errors="coerce")
+
+    sc = ax.scatter(df["Lon"], df["Lat"], s=s, c=depth, alpha=0.85, 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)")