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flesh out kn-pmp testing #429

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Dec 10, 2023
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flesh out kn-pmp testing #429

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111 changes: 82 additions & 29 deletions spopt/tests/test_knearest_p_median.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from shapely.geometry import Point

from spopt.locate.p_median import KNearestPMedian
from spopt.locate.base import SpecificationError
import os
import pickle
import platform
Expand All @@ -26,27 +27,26 @@ def setup_method(self) -> None:
"geometry": [Point(1, 1), Point(0, 2), Point(2, 0)],
"capacity": [1, 1, 1],
}
gdf_demand = geopandas.GeoDataFrame(self.demand_data, crs="EPSG:4326")
gdf_fac = geopandas.GeoDataFrame(self.facility_data, crs="EPSG:4326")
self.gdf_demand = geopandas.GeoDataFrame(self.demand_data, crs="EPSG:4326")
self.gdf_fac = geopandas.GeoDataFrame(self.facility_data, crs="EPSG:4326")
self.k_nearest_pmedian = KNearestPMedian.from_geodataframe(
gdf_demand,
gdf_fac,
self.gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=2,
facility_capacity_col="capacity",
k_array=k,
)
self.solver = pulp.PULP_CBC_CMD(msg=False)

def test_knearest_p_median_from_geodataframe(self):
result = self.k_nearest_pmedian.solve(pulp.PULP_CBC_CMD(msg=False))
result = self.k_nearest_pmedian.solve(self.solver)
assert isinstance(result, KNearestPMedian)

def test_knearest_p_median_from_geodataframe_no_results(self):
result = self.k_nearest_pmedian.solve(
pulp.PULP_CBC_CMD(msg=False), results=False
)
result = self.k_nearest_pmedian.solve(self.solver, results=False)
assert isinstance(result, KNearestPMedian)

with pytest.raises(AttributeError):
Expand All @@ -57,8 +57,7 @@ def test_knearest_p_median_from_geodataframe_no_results(self):
result.mean_dist

def test_solve(self):
solver = pulp.PULP_CBC_CMD(msg=False)
self.k_nearest_pmedian.solve(solver)
self.k_nearest_pmedian.solve(self.solver)
assert self.k_nearest_pmedian.problem.status == pulp.LpStatusOptimal

fac2cli_known = [[1], [0], []]
Expand All @@ -68,14 +67,26 @@ def test_solve(self):
assert self.k_nearest_pmedian.cli2fac == cli2fac_known
assert self.k_nearest_pmedian.mean_dist == mean_dist_known

def test_error_overflow_k(self):
k = numpy.array([10, 10])
with pytest.raises(ValueError, match="The value of k should be"):
KNearestPMedian.from_geodataframe(
self.gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=2,
facility_capacity_col="capacity",
k_array=k,
)

def test_error_k_array_non_numpy_array(self):
gdf_demand = geopandas.GeoDataFrame(self.demand_data, crs="EPSG:4326")
gdf_fac = geopandas.GeoDataFrame(self.facility_data, crs="EPSG:4326")
k = [1, 1]
with pytest.raises(TypeError):
with pytest.raises(TypeError, match="k_array should be a numpy array."):
KNearestPMedian.from_geodataframe(
gdf_demand,
gdf_fac,
self.gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
Expand All @@ -85,14 +96,11 @@ def test_error_k_array_non_numpy_array(self):
)

def test_error_k_array_invalid_value(self):
gdf_demand = geopandas.GeoDataFrame(self.demand_data, crs="EPSG:4326")
gdf_fac = geopandas.GeoDataFrame(self.facility_data, crs="EPSG:4326")

k = numpy.array([1, 4])
with pytest.raises(ValueError):
with pytest.raises(ValueError, match="The value of k should be no more"):
KNearestPMedian.from_geodataframe(
gdf_demand,
gdf_fac,
self.gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
Expand All @@ -101,21 +109,66 @@ def test_error_k_array_invalid_value(self):
k_array=k,
)

def test_error_geodataframe_crs_mismatch(self):
gdf_demand = geopandas.GeoDataFrame(self.demand_data, crs="EPSG:4326")
gdf_fac = geopandas.GeoDataFrame(
self.facility_data, crs="EPSG:3857"
) # Different CRS
def test_error_no_crs_demand(self):
_gdf_demand = geopandas.GeoDataFrame(self.demand_data)
k = numpy.array([1, 1])
with pytest.raises(ValueError, match="GeoDataFrame gdf_demand "):
KNearestPMedian.from_geodataframe(
_gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=2,
facility_capacity_col="capacity",
k_array=k,
)

def test_error_no_crs_facility(self):
_gdf_fac = geopandas.GeoDataFrame(self.facility_data)
k = numpy.array([1, 1])
with pytest.raises(ValueError, match="GeoDataFrame gdf_facility "):
KNearestPMedian.from_geodataframe(
self.gdf_demand,
_gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=2,
facility_capacity_col="capacity",
k_array=k,
)

def test_error_geodataframe_crs_mismatch(self):
_gdf_fac = self.gdf_fac.copy().to_crs("EPSG:3857")
k = numpy.array([1, 1])
with pytest.raises(ValueError):
with pytest.raises(ValueError, match="Geodataframes crs are different"):
KNearestPMedian.from_geodataframe(
gdf_demand,
gdf_fac,
self.gdf_demand,
_gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=2,
facility_capacity_col="capacity",
k_array=k,
)

def test_error_high_capacity(self):
_gdf_demand = self.gdf_demand.copy()
_gdf_demand["demand"] = [10, 10]
k = numpy.array([1, 1])
with pytest.raises(
SpecificationError,
match="Problem is infeasible. The highest possible capacity",
):
KNearestPMedian.from_geodataframe(
_gdf_demand,
self.gdf_fac,
"geometry",
"geometry",
"demand",
p_facilities=1,
facility_capacity_col="capacity",
k_array=k,
).solve(self.solver)