def test_from_coverage_dataframe_invalid_demand_id_col2(
self, demand_points_dataframe, facility_service_areas_dataframe):
with pytest.raises(ValueError) as e:
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"test", "ORIG_ID")
assert (e.value.args[0] == f"'test' not in dataframe")
def test_from_coverage_dataframe_invalid_supply_id_col(
self, demand_points_dataframe, facility_service_areas_dataframe):
with pytest.raises(TypeError) as e:
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"GEOID10", None)
assert (
e.value.args[0] ==
"Expected 'str' type for demand_id_col, got '<class 'NoneType'>'")
def test_from_coverage_dataframe_invalid_coverage_type(
self, demand_points_dataframe, facility_service_areas_dataframe):
with pytest.raises(ValueError) as e:
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"GEOID10",
"ORIG_ID",
coverage_type="test")
assert (e.value.args[0] == "Invalid coverage type 'test'")
def test_from_coverage_dataframe_invalid_supply_df(
self, demand_points_dataframe):
with pytest.raises(TypeError) as e:
c = Coverage.from_geodataframes(demand_points_dataframe, None,
"GEOID10", "ORIG_ID")
assert (
e.value.args[0] ==
"Expected 'Dataframe' type for supply_df, got '<class 'NoneType'>'"
)
def test_from_coverage_dataframe_demand_col(
self, demand_points_dataframe, facility_service_areas_dataframe):
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"GEOID10",
"ORIG_ID",
demand_col="Population")
assert (isinstance(c, Coverage))
assert c.demand_col == "Population"
def test_from_coverage_dataframe_supply_name(
self, demand_points_dataframe, facility_service_areas_dataframe):
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"GEOID10",
"ORIG_ID",
supply_name="test")
assert (isinstance(c, Coverage))
assert c.supply_name == "test"
def test_from_coverage_dataframe_partial(self, demand_polygon_dataframe,
facility_service_areas_dataframe):
c = Coverage.from_geodataframes(demand_polygon_dataframe,
facility_service_areas_dataframe,
"GEOID10",
"ORIG_ID",
coverage_type="partial",
demand_col="Population")
assert (isinstance(c, Coverage))
assert (c.coverage_type == "partial")
def test_from_coverage_dataframe_invalid_demand_df(
self, facility_service_areas_dataframe):
with pytest.raises(TypeError) as e:
c = Coverage.from_geodataframes(None,
facility_service_areas_dataframe,
"GEOID10", "ORIG_ID")
assert (
e.value.args[0] ==
"Expected 'Dataframe' type for demand_df, got '<class 'NoneType'>'"
)
def test_from_coverage_dataframe_demand_col_required(
self, demand_points_dataframe, facility_service_areas_dataframe):
with pytest.raises(ValueError) as e:
c = Coverage.from_geodataframes(demand_points_dataframe,
facility_service_areas_dataframe,
"GEOID10",
"ORIG_ID",
coverage_type="partial")
assert (e.value.args[0] ==
"demand_col is required when generating partial coverage")
def test_multiple_supply(self):
demand_id_col = "GEOID10"
supply_id_col = "ORIG_ID"
demand_col = "Population"
d = geopandas.read_file(
os.path.join(self.dir_name, "../test_data/demand_point.shp"))
s = geopandas.read_file(
os.path.join(self.dir_name,
"../test_data/facility_service_areas.shp"))
s2 = geopandas.read_file(
os.path.join(self.dir_name,
"../test_data/facility2_service_areas.shp"))
coverage = Coverage.from_geodataframes(d,
s,
demand_id_col,
supply_id_col,
demand_col=demand_col)
coverage2 = Coverage.from_geodataframes(
d,
s2,
demand_id_col,
supply_id_col,
demand_col=demand_col,
demand_name=coverage.demand_name)
problem = Problem.mclp([coverage, coverage2],
max_supply={
coverage: 5,
coverage2: 10
})
problem.solve(pulp.GLPK())
selected_locations = problem.selected_supply(coverage)
selected_locations2 = problem.selected_supply(coverage2)
covered_demand = d.query(
f"{demand_id_col} in ({[f'{i}' for i in problem.selected_demand(coverage)]})"
)
result = math.ceil(
(covered_demand[demand_col].sum() / d[demand_col].sum()) * 100)
assert (len(selected_locations) == 5)
assert (len(selected_locations2) == 10)
assert result == 96
def test_single_supply(self):
demand_id_col = "GEOID10"
supply_id_col = "ORIG_ID"
d = geopandas.read_file(
os.path.join(self.dir_name, "../test_data/demand_point.shp"))
s = geopandas.read_file(
os.path.join(self.dir_name,
"../test_data/facility_service_areas.shp"))
coverage = Coverage.from_geodataframes(d, s, demand_id_col,
supply_id_col)
problem = Problem.lscp(coverage)
with pytest.raises((InfeasibleException, UndefinedException)) as e:
problem.solve(pulp.GLPK())
def test_single_supply(self):
demand_id_col = "GEOID10"
supply_id_col = "ORIG_ID"
demand_col = "Population"
d = geopandas.read_file(
os.path.join(self.dir_name, "../test_data/demand_point.shp"))
s = geopandas.read_file(
os.path.join(self.dir_name,
"../test_data/facility_service_areas.shp"))
coverage = Coverage.from_geodataframes(d,
s,
demand_id_col,
supply_id_col,
demand_col=demand_col)
problem = Problem.mclp(coverage, max_supply={coverage: 5})
problem.solve(pulp.GLPK())
covered_demand = d.query(
f"{demand_id_col} in ({[f'{i}' for i in problem.selected_demand(coverage)]})"
)
result = math.ceil(
(covered_demand[demand_col].sum() / d[demand_col].sum()) * 100)
assert result == 53