diff --git a/src/pybdshadow/pybdshadow.py b/src/pybdshadow/pybdshadow.py
index c7df5ce..4fa7b55 100644
--- a/src/pybdshadow/pybdshadow.py
+++ b/src/pybdshadow/pybdshadow.py
@@ -152,6 +152,9 @@ def bdshadow_sunlight(buildings, date,  height='height', roof=False,include_buil
     ground_shadow['type'] = 'ground'
 
     if not roof:
+        if not include_building:
+            #从地面阴影裁剪建筑轮廓
+            ground_shadow = gdf_difference(ground_shadow,buildings)
         return ground_shadow
     else:
         def calwall_shadow(walldata, building):
@@ -204,14 +207,17 @@ def calwall_shadow(walldata, building):
             building_roof = building_roof[-building_roof['geometry'].is_empty]
 
             roof_shadows.append(building_roof)
-
-        roof_shadow = pd.concat(roof_shadows)[
-            ['height', 'building_id', 'geometry']]
-        roof_shadow['type'] = 'roof'
-
-        #从地面阴影裁剪建筑轮廓
-        ground_shadow = gdf_difference(ground_shadow,buildings)
-
+        if len(roof_shadows) == 0:
+            roof_shadow = gpd.GeoDataFrame()
+        else:
+            roof_shadow = pd.concat(roof_shadows)[
+                ['height', 'building_id', 'geometry']]
+            roof_shadow['type'] = 'roof'
+
+        if not include_building:
+            #从地面阴影裁剪建筑轮廓
+            ground_shadow = gdf_difference(ground_shadow,buildings)
+        
         shadows = pd.concat([roof_shadow, ground_shadow])
         shadows.crs = None
         shadows['geometry'] = shadows.buffer(0.000001).buffer(-0.000001)
diff --git a/src/pybdshadow/tests/test_pybdshadow.py b/src/pybdshadow/tests/test_pybdshadow.py
index befc4c0..2480a14 100644
--- a/src/pybdshadow/tests/test_pybdshadow.py
+++ b/src/pybdshadow/tests/test_pybdshadow.py
@@ -7,43 +7,49 @@
 
 class Testpybdshadow:
     def test_bdshadow_sunlight(self):
+
         buildings = gpd.GeoDataFrame({
-            'height': [42],
+            'height': [42, 9],
             'geometry': [
                 Polygon([(139.698311, 35.533796),
-                         (139.698311,
-                          35.533642),
-                         (139.699075,
-                          35.533637),
-                         (139.699079,
-                          35.53417),
-                         (139.698891,
-                          35.53417),
-                         (139.698888,
-                          35.533794),
-                         (139.698311, 35.533796)])]})
-        date = pd.to_datetime('2015-01-01 02:45:33.959797119')
+                        (139.698311,
+                            35.533642),
+                        (139.699075,
+                            35.533637),
+                        (139.699079,
+                            35.53417),
+                        (139.698891,
+                            35.53417),
+                        (139.698888,
+                            35.533794),
+                        (139.698311, 35.533796)]),
+                Polygon([(139.69799, 35.534175),
+                        (139.697988, 35.53389),
+                        (139.698814, 35.533885),
+                        (139.698816, 35.534171),
+                        (139.69799, 35.534175)])]})
+        date = pd.to_datetime('2015-01-01 03:45:33.959797119')
 
         buildings = pybdshadow.bd_preprocess(buildings)
 
         buildingshadow = pybdshadow.bdshadow_sunlight(
-            buildings, date)
+            buildings, date, roof=True, include_building=False)
 
         area = buildingshadow['geometry'].iloc[0]
         area = np.array(area.exterior.coords)
-        truth = np.array([[139.698311,  35.533796],
-                          [139.69831102,  35.533796],
-                          [139.69831102,  35.533796],
-                          [139.69831239,  35.53429879],
-                          [139.69888939,  35.53429679],
-                          [139.69889239,  35.53467279],
-                          [139.69908039,  35.53467279],
-                          [139.69907902,  35.53417],
-                          [139.69907502,  35.533637],
-                          [139.699075,  35.533637],
-                          [139.699075,  35.533637],
-                          [139.698311,  35.533642],
-                          [139.698311,  35.533796]])
+        truth = np.array([(139.6983434498457, 35.53388784954066),
+                          (139.698343456533, 35.533887872006716),
+                          (139.6984440527688, 35.53417277873741),
+                          (139.69844406145836, 35.534172800060766),
+                          (139.69844408446318, 35.534172801043766),
+                          (139.69881597541797, 35.534171000119045),
+                          (139.69881599883948, 35.53417099885312),
+                          (139.6988159998281, 35.53417097541834),
+                          (139.69881400017155, 35.533885024533475),
+                          (139.6988139988598, 35.53388500115515),
+                          (139.69881397546646, 35.53388500014851),
+                          (139.69834347324914, 35.53388784822488),
+                          (139.6983434498457, 35.53388784954066)])
         assert np.allclose(area, truth)
 
         pybdshadow.show_bdshadow(buildings=buildings,
diff --git a/src/test.ipynb b/src/test.ipynb
index 6296fd1..e0bb442 100644
--- a/src/test.ipynb
+++ b/src/test.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -65,11 +65,12 @@
     "\n",
     "#地面阴影\n",
     "\n",
-    "shadows.plot(ax = ax,alpha = 0.7,\n",
-    "column = 'type', \n",
-    "categorical=True, \n",
-    "cmap='Set1_r', \n",
-    "legend=True)\n",
+    "shadows.plot(ax = ax,\n",
+    "            alpha = 0.7,\n",
+    "            column = 'type', \n",
+    "            categorical=True, \n",
+    "            cmap='Set1_r', \n",
+    "            legend=True)\n",
     "\n",
     "plt.show()"
    ]