Merge pull request #21 from ni1o1/0.3.5

0.3.5

.github/workflows/tests.yml

@@ -27,7 +27,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.7", "3.8", "3.9"]
+        python-version: ["3.8", "3.9"]
 
     steps:
     - uses: actions/checkout@v2

requirements.txt

@@ -6,3 +6,8 @@ suncalc
 keplergl
 scikit-opt
 transbigdata
+mapbox_vector_tile
+vt2geojson
+requests
+tqdm
+retrying

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="pybdshadow",
-    version="0.3.4",
+    version="0.3.5",
     author="Qing Yu",
     author_email="qingyu0815@foxmail.com",
     description="Python package to generate building shadow geometry",
@@ -17,7 +17,7 @@
         "Bug Tracker": "https://github.com/ni1o1/pybdshadow/issues",
     },
     install_requires=[
-        "numpy", "pandas", "shapely", "geopandas", "matplotlib","suncalc","keplergl","transbigdata"
+        "numpy", "pandas", "shapely", "geopandas", "matplotlib","suncalc","keplergl","transbigdata","mapbox_vector_tile","vt2geojson","requests","tqdm","retrying"
     ],
     classifiers=[
         "Operating System :: OS Independent",
@@ -26,11 +26,10 @@
         "Topic :: Software Development :: Libraries :: Python Modules",
         "License :: OSI Approved :: BSD License",
         "Programming Language :: Python",
-        "Programming Language :: Python :: 3.7",
         "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
     ],
     package_dir={'pybdshadow': 'src/pybdshadow'},
     packages=['pybdshadow'],
-    python_requires=">=3.6",
+    python_requires=">=3.8",
 )

src/pybdshadow/__init__.py

@@ -32,14 +32,18 @@
 OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 """
 
-__version__ = '0.3.4'
+__version__ = '0.3.5'
 __author__ = 'Qing Yu <qingyu0815@foxmail.com>'
 
 # module level doc-string
 __doc__ = """
 `pybdshadow` - Python package to generate building shadow geometry.
 """
 from .pybdshadow import *
+from .get_buildings import (
+    get_buildings_by_polygon,
+    get_buildings_by_bounds,
+)
 from .pybdshadow import (
     bdshadow_sunlight,
     bdshadow_pointlight
@@ -49,6 +53,7 @@
 )
 from .visualization import (
     show_bdshadow,
+    show_sunshine,
 )
 from .analysis import (
     cal_sunshine,
@@ -57,12 +62,25 @@
     get_timetable
 )
 
+from .facade import (
+    cal_sunshine_facade
+)
+
+from .utils import (
+    extrude_poly
+)
+
 __all__ = ['bdshadow_sunlight',
            'bdshadow_pointlight',
            'bd_preprocess',
            'show_bdshadow',
            'cal_sunshine',
            'cal_sunshadows',
            'cal_shadowcoverage',
-           'get_timetable'
+           'get_timetable',
+           'get_buildings_by_polygon',
+           'get_buildings_by_bounds',
+           'cal_sunshine_facade',
+           'show_sunshine',
+           'extrude_poly'
            ]

src/pybdshadow/analysis.py

@@ -1,13 +1,13 @@
 import pandas as pd
 from suncalc import get_times
-from shapely.geometry import MultiPolygon
+from shapely.geometry import MultiPolygon,Polygon
 import transbigdata as tbd
 import geopandas as gpd
 from .pybdshadow import (
     bdshadow_sunlight,
 )
 from .preprocess import bd_preprocess
-
+from .utils import count_overlapping_features
 
 def get_timetable(lon, lat, dates=['2022-01-01'], precision=3600, padding=1800):
     # generate timetable with given interval
@@ -56,6 +56,8 @@ def cal_sunshine(buildings, day='2022-01-01', roof=False, grids=gpd.GeoDataFrame
         grids generated by TransBigData in study area, each grids have a `time` column store the sunshine time
 
     '''
+
+
     # calculate day time duration
     lon, lat = buildings['geometry'].iloc[0].bounds[:2]
     date = pd.to_datetime(day+' 12:45:33.959797119')
@@ -73,22 +75,47 @@ def cal_sunshine(buildings, day='2022-01-01', roof=False, grids=gpd.GeoDataFrame
     if accuracy == 'vector':
         if roof:
             shadows = shadows[shadows['type'] == 'roof']
-            shadows = bd_preprocess(shadows)
-            shadows = shadows.groupby(['date', 'type'])['geometry'].apply(
-                lambda df: MultiPolygon(list(df)).buffer(0)).reset_index()
-            shadows = bd_preprocess(shadows)
-            shadows = count_overlapping_features(shadows)
+            if len(shadows)>0:
+                shadows = bd_preprocess(shadows)
+                shadows = shadows.groupby(['date', 'type','height'])['geometry'].apply(
+                    lambda df: MultiPolygon(list(df)).buffer(0)).reset_index()
+                shadows = bd_preprocess(shadows)
+
+            # 额外：增加屋顶面
+            shadows = pd.concat([shadows, buildings])
+            #return shadows
+            shadows = shadows.groupby('height').apply(count_overlapping_features).reset_index()
+            shadows['count'] -= 1
         else:
             shadows = shadows[shadows['type'] == 'ground']
+
             shadows = bd_preprocess(shadows)
             shadows = shadows.groupby(['date', 'type'])['geometry'].apply(
-                lambda df: MultiPolygon(list(df)).buffer(0)).reset_index()
+            lambda df: MultiPolygon(list(df)).buffer(0)).reset_index()
             shadows = bd_preprocess(shadows)
-            shadows = count_overlapping_features(shadows)
+
+            # 额外：增加地面面
+            minpos = shadows.bounds[['minx','miny']].min()
+            maxpos = shadows.bounds[['maxx','maxy']].max()
+
+            ground = gpd.GeoDataFrame(geometry=[
+                Polygon([
+                [minpos['minx'],minpos['miny']],
+                [minpos['minx'],maxpos['maxy']],
+                [maxpos['maxx'],maxpos['maxy']],
+                [maxpos['maxx'],minpos['miny']],
+            ])
+            ])
+            shadows = pd.concat([shadows, 
+                                 ground
+                                 ])
+            shadows = count_overlapping_features(shadows,buffer=False)
+            shadows['count'] -= 1
+
 
         shadows['time'] = shadows['count']*precision
         shadows['Hour'] = sunlighthour-shadows['time']/3600
-        shadows.loc[shadows['Hour'] <= 0, 'Hour'] = 0
+        #shadows.loc[shadows['Hour'] <= 0, 'Hour'] = 0
         return shadows
     else:
         # Grid analysis of shadow cover duration(ground).
@@ -97,7 +124,7 @@ def cal_sunshine(buildings, day='2022-01-01', roof=False, grids=gpd.GeoDataFrame
 
         grids['Hour'] = sunlighthour-grids['time']/3600
         return grids
-
+    
 
 def cal_sunshadows(buildings, cityname='somecity', dates=['2022-01-01'], precision=3600, padding=1800,
                    roof=True, include_building=True, save_shadows=False, printlog=False):
@@ -222,17 +249,3 @@ def cal_shadowcoverage(shadows_input, buildings, grids=gpd.GeoDataFrame(), roof=
 
     return grids
 
-
-def count_overlapping_features(gdf):
-    import shapely
-    bounds = gdf.geometry.exterior.unary_union
-    new_polys = list(shapely.ops.polygonize(bounds))
-    new_gdf = gpd.GeoDataFrame(geometry=new_polys)
-    new_gdf['id'] = range(len(new_gdf))
-    new_gdf_centroid = new_gdf.copy()
-    new_gdf_centroid['geometry'] = new_gdf.centroid
-    overlapcount = gpd.sjoin(new_gdf_centroid, gdf)
-    overlapcount = overlapcount.groupby(
-        ['id'])['index_right'].count().rename('count').reset_index()
-    out_gdf = pd.merge(new_gdf, overlapcount)
-    return out_gdf