[1]:
import geopandas
import numpy
import matplotlib.pyplot as plt
import geoplanar
from shapely.geometry import box, Polygon
Planar Enforcement Violation: One polygon overlapping another polygon#
[2]:
p1 = box(0,0,10,10)
p2 = box(8,4, 12,6)
gdf = geopandas.GeoDataFrame(geometry=[p1,p2])
gdf.plot(edgecolor='k')
[2]:
<AxesSubplot:>
[3]:
geoplanar.is_overlapping(gdf)
[3]:
True
[4]:
gdf.geometry[0]
[4]:
[5]:
gdf.geometry[1]
[5]:
[6]:
gdf = geoplanar.trim_overlaps(gdf)
geoplanar.is_overlapping(gdf)
[6]:
False
[7]:
gdf.geometry[0]
[7]:
[8]:
gdf.geometry[1]
[8]:
[9]:
gdf.area
[9]:
0 96.0
1 8.0
dtype: float64
Default trims the largest of the two overlapping polygons#
To have the correction apply the trim to the smaller of the two polygons, set largest=False:
[10]:
p1 = box(0,0,10,10)
p2 = box(8,4, 12,6)
gdf = geopandas.GeoDataFrame(geometry=[p1,p2])
gdf.plot(edgecolor='k')
[10]:
<AxesSubplot:>
[11]:
gdf = geoplanar.trim_overlaps(gdf, largest=False)
gdf.plot(edgecolor='k')
[11]:
<AxesSubplot:>
[12]:
gdf.geometry[0]
[12]:
[13]:
gdf.geometry[1]
[13]:
[14]:
gdf.area
[14]:
0 100.0
1 4.0
dtype: float64
Planar Enforcement Violation: One polygon overlapping two#
As always, care must be taken when carrying out a planar correction, as the result may not be what is desired:
[15]:
p1 = box(0,0,10,10)
p2 = box(10,0, 20,10)
p3 = box(8,4, 12,6)
gdf = geopandas.GeoDataFrame(geometry=[p1,p2,p3])
gdf.plot(edgecolor='k')
[15]:
<AxesSubplot:>
[16]:
gdf1 = geoplanar.trim_overlaps(gdf, largest=False) # trim the smallest feature of an intersecting pair
[17]:
gdf1.area
[17]:
0 100.0
1 100.0
2 0.0
dtype: float64
[18]:
gdf1.plot(edgecolor='k')
[18]:
<AxesSubplot:>
[19]:
p1 = box(0,0,10,10)
p2 = box(10,0, 20,10)
p3 = box(8,4, 12,6)
gdf = geopandas.GeoDataFrame(geometry=[p1,p2,p3])
gdf2 = geoplanar.trim_overlaps(gdf)
[20]:
gdf2.geometry
[20]:
0 POLYGON ((0.00000 0.00000, 0.00000 10.00000, 1...
1 POLYGON ((10.00000 4.00000, 12.00000 4.00000, ...
2 POLYGON ((12.00000 4.00000, 12.00000 6.00000, ...
Name: geometry, dtype: geometry
[21]:
gdf2.area
[21]:
0 96.0
1 96.0
2 8.0
dtype: float64
[22]:
gdf2.plot(edgecolor='k')
[22]:
<AxesSubplot:>
