def test_geoseries_warning(self):
# Geopandas Issue #305
with pytest.raises(NotImplementedError):
overlay(self.polydf,
self.polydf2.geometry,
how="union",
**self.kwargs)
def test_geometry_not_named_geometry(self):
# Geopandas Issue #306
# Add points and flip names
polydf3 = self.polydf.copy()
polydf3 = polydf3.rename(columns={'geometry': 'polygons'})
polydf3 = polydf3.set_geometry('polygons')
polydf3['geometry'] = self.pointdf.geometry.loc[0:4]
assert polydf3.geometry.name == 'polygons'
df = overlay(polydf3, self.polydf2, how="union", **self.kwargs)
assert type(df) is GeoDataFrame
df2 = overlay(self.polydf, self.polydf2, how="union", **self.kwargs)
assert df.geom_almost_equals(df2).all()
def test_union_no_index(self):
# explicitly ignore indicies
dfB = overlay(self.polydf,
self.polydf2,
how="union",
use_sindex=False,
**self.kwargs)
assert dfB.shape == self.union_shape
# remove indicies from df
self.polydf._sindex = None
self.polydf2._sindex = None
dfC = overlay(self.polydf, self.polydf2, how="union", **self.kwargs)
assert dfC.shape == self.union_shape
def test_symmetric_difference(self):
df = overlay(self.polydf,
self.polydf2,
how="symmetric_difference",
**self.kwargs)
assert df.shape == (15, 9)
def test_intersection(self):
df = overlay(self.polydf,
self.polydf2,
how="intersection",
**self.kwargs)
assert df['BoroName'][0] is not None
assert df.shape == (68, 7)
def test_difference(self):
df = overlay(self.polydf,
self.polydf2,
how="difference",
**self.kwargs)
rows, cols = self.polydf.shape
assert df.shape == (rows, cols + 1) #add one for the index
def test_union_no_index(self):
# explicitly ignore indicies
df = overlay(self.polydf,
self.polydf2,
how="union",
keep_index=False,
**self.kwargs)
assert df.shape[1] == 7
def test_difference(self):
df = overlay(self.polydf,
self.polydf2,
how="difference",
**self.kwargs)
# ALERT: the original difference algorithm creates invalid columns.
# If taking the difference of polydf and polydf2, there should be no
# geometries containing any attributes from polydf2. Yet the original
# algorithm creates the attribute fields for all fields in polydf2 and
# fills them with `None` or `NaN`.
# assert df.shape == (86, 7) #this shape contains 2 invalid columns
# df = geopandas.overlay(polydf, polydf2, how='difference')
# df.dropna().shape
# >>> (86, 5)
assert df.shape == (86, 5)
def test_identity(self):
df = overlay(self.polydf, self.polydf2, how="identity", **self.kwargs)
df['area'] = df.geometry.area
polydf = self.polydf.copy()
polydf['area'] = polydf.geometry.area
ck = polydf.groupby(polydf.index)['area'].sum()
check = df.groupby(['idx1'])['area'].sum()
df_area = df.geometry.area.sum()
polydf_area = self.polydf.geometry.area.sum()
error = (polydf_area - df_area) / polydf_area
assert -self.tol < error < self.tol
assert_series_equal(check,
ck,
check_names=False,
check_index_type=False)
assert df.shape[1] == 9 + 1 # add one for the 'area' field
def test_symmetric_difference(self):
df = overlay(self.polydf,
self.polydf2,
how="symmetric_difference",
**self.kwargs)
# ALERT: the original algorithm creates invalid geometries.
# Symmetric differece geometries should be in either polydf or polydf2.
# Any resulting geometries without attributes from one or the other is
# completely invalid.
# assert df.shape == (122, 7) # this shape contains invalid geometries
# Use 'Shape_Area' as the field to indicate polydf and 'value1' as the
# field for polydf2
# df = geopandas.overlay(polydf, polydf2, how="symmetric_difference")
# len(df.loc[(out['Shape_Area'].isnull()) & (df['value1'].isnull())])
# >>> 10
invalid_sym_diff_geom_len = 10
assert df.shape == (122 - invalid_sym_diff_geom_len, 7)
def test_union(self):
df = overlay(self.polydf, self.polydf2, how="union", **self.kwargs)
df['area'] = df.geometry.area
polydf = self.polydf.copy()
polydf2 = self.polydf2.copy()
polydf['area'] = polydf.geometry.area
ck1 = polydf.groupby(polydf.index)['area'].sum()
polydf2['area'] = polydf2.to_crs(polydf.crs).geometry.area
ck2 = polydf2.groupby(polydf2.index)['area'].sum()
assert type(df) is GeoDataFrame
assert df.crs == self.polydf.crs
assert 'value1' in df.columns and 'Shape_Area' in df.columns
for ix, ck in zip(['idx1', 'idx2'], [ck1, ck2]):
check = df.groupby([ix])['area'].sum()
assert_series_equal(check,
ck,
check_names=False,
check_index_type=False)
def test_union(self):
df = overlay(self.polydf, self.polydf2, how="union", **self.kwargs)
assert type(df) is GeoDataFrame
assert df.shape == self.union_shape
assert 'value1' in df.columns and 'Shape_Area' in df.columns
def test_duplicate_column_name(self):
polydf2r = self.polydf2.rename(columns={'value2': 'Shape_Area'})
df = overlay(self.polydf, polydf2r, how="union", **self.kwargs)
assert 'Shape_Area_2' in df.columns and 'Shape_Area' in df.columns
def test_nonpoly(self):
with pytest.raises(TypeError):
overlay(self.pointdf, self.polydf, how="union", **self.kwargs)
def test_bad_how(self):
with pytest.raises(ValueError):
overlay(self.polydf, self.polydf, how="spandex", **self.kwargs)
def test_identity(self):
df = overlay(self.polydf, self.polydf2, how="identity", **self.kwargs)
assert df.shape == (154, 7)
