class TestAequilibraeMatrix(TestCase):
def test___init__(self):
os.remove(name_test) if os.path.exists(name_test) else None
args = {'file_name': name_test,
'zones': zones,
'matrix_names': ['mat', 'seed', 'dist'],
'index_names': ['my indices']}
matrix = AequilibraeMatrix()
matrix.create_empty(**args)
matrix.index[:] = np.arange(matrix.zones) + 100
matrix.mat[:, :] = np.random.rand(matrix.zones, matrix.zones)[:, :]
matrix.mat[:, :] = matrix.mat[:, :] * (1000 / np.sum(matrix.mat[:, :]))
matrix.setName('Test matrix - ' + str(random.randint(1, 10)))
matrix.setDescription('Generated at ' + datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
matrix.close(True)
del (matrix)
def test_load(self):
# self.test___init__()
self.new_matrix = AequilibraeMatrix()
self.new_matrix.load(name_test)
def test_computational_view(self):
self.test_load()
self.new_matrix.computational_view(['mat', 'seed'])
self.new_matrix.mat.fill(0)
self.new_matrix.seed.fill(0)
if self.new_matrix.matrix_view.shape[2] != 2:
self.fail('Computational view returns the wrong number of matrices')
self.new_matrix.computational_view(['mat'])
self.new_matrix.matrix_view[:, :] = np.arange(zones ** 2).reshape(zones, zones)
if np.sum(self.new_matrix.mat) != np.sum(self.new_matrix.matrix_view):
self.fail('Assigning to matrix view did not work')
self.new_matrix.setName('Test matrix - ' + str(random.randint(1, 10)))
self.new_matrix.setDescription('Generated at ' + datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
self.new_matrix.close(True)
def test_copy(self):
self.test_load()
# test in-memory matrix_procedures copy
matrix_copy = self.new_matrix.copy(copy_matrix_name, cores=['mat'])
if not np.array_equal(matrix_copy.mat, self.new_matrix.mat):
self.fail('Matrix copy was not perfect')
matrix_copy.close(True)
self.new_matrix.close(True)
def test_export(self):
self.test_load()
self.new_matrix.export(csv_export_name)
self.new_matrix.close(True)
def test_nan_to_num(self):
self.test_load()
s = self.new_matrix.seed.sum() - self.new_matrix.seed[1, 1]
m = self.new_matrix.mat.sum() - self.new_matrix.mat[1, 1]
self.new_matrix.seed[1,1] = np.nan
self.new_matrix.computational_view(['mat', 'seed'])
self.new_matrix.nan_to_num()
self.new_matrix.mat[1,1] = np.nan
self.new_matrix.computational_view(['mat'])
self.new_matrix.nan_to_num()
if s != self.new_matrix.seed.sum():
self.fail('Total for seed matrix not maintained')
if m != self.new_matrix.mat.sum():
self.fail('Total for mat matrix not maintained')
class TestAequilibraeMatrix(TestCase):
matrix = None
def setUp(self) -> None:
self.sf_skims = f"/Aequilibrae_matrix_{uuid.uuid4()}.omx"
copyfile(siouxfalls_skims, self.sf_skims)
temp_folder = gettempdir()
self.name_test = temp_folder + f"/Aequilibrae_matrix_{uuid.uuid4()}.aem"
self.copy_matrix_name = temp_folder + f"/Aequilibrae_matrix_{uuid.uuid4()}.aem"
self.csv_export_name = temp_folder + f"/Aequilibrae_matrix_{uuid.uuid4()}.csv"
self.omx_export_name = temp_folder + f"/Aequilibrae_matrix_{uuid.uuid4()}.omx"
if self.matrix is not None:
return
args = {
"file_name": self.name_test,
"zones": zones,
"matrix_names": ["mat", "seed", "dist"],
"index_names": ["my indices"],
}
self.matrix = AequilibraeMatrix()
self.matrix.create_empty(**args)
self.matrix.index[:] = np.arange(self.matrix.zones) + 100
self.matrix.mat[:, :] = np.random.rand(self.matrix.zones, self.matrix.zones)[:, :]
self.matrix.mat[:, :] = self.matrix.mat[:, :] * (1000 / np.sum(self.matrix.mat[:, :]))
self.matrix.setName("Test matrix - " + str(random.randint(1, 10)))
self.matrix.setDescription("Generated at " + datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
self.new_matrix = self.matrix
def tearDown(self) -> None:
try:
del self.matrix
os.remove(self.name_test) if os.path.exists(self.name_test) else None
os.remove(self.csv_export_name) if os.path.exists(self.csv_export_name) else None
os.remove(self.copy_matrix_name) if os.path.exists(self.copy_matrix_name) else None
os.remove(self.omx_export_name) if os.path.exists(self.omx_export_name) else None
except Exception as e:
print(f"Could not delete. {e.args}")
def test_load(self):
self.new_matrix = AequilibraeMatrix()
# Cannot load OMX file with no indices
with self.assertRaises(LookupError):
self.new_matrix.load(no_index_omx)
self.new_matrix = AequilibraeMatrix()
self.new_matrix.load(self.name_test)
del self.new_matrix
def test_computational_view(self):
self.new_matrix.computational_view(["mat", "seed"])
self.new_matrix.mat.fill(0)
self.new_matrix.seed.fill(0)
if self.new_matrix.matrix_view.shape[2] != 2:
self.fail("Computational view returns the wrong number of matrices")
self.new_matrix.computational_view(["mat"])
self.new_matrix.matrix_view[:, :] = np.arange(zones ** 2).reshape(zones, zones)
if np.sum(self.new_matrix.mat) != np.sum(self.new_matrix.matrix_view):
self.fail("Assigning to matrix view did not work")
self.new_matrix.setName("Test matrix - " + str(random.randint(1, 10)))
self.new_matrix.setDescription("Generated at " + datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
del self.new_matrix
def test_computational_view_with_omx(self):
self.new_matrix = AequilibraeMatrix()
self.new_matrix.load(omx_example)
arrays = ["m1", "m2"]
self.new_matrix.computational_view(arrays)
total_mats = np.sum(self.new_matrix.matrix_view)
self.new_matrix.computational_view([arrays[0]])
total_m1 = np.sum(self.new_matrix.matrix_view)
self.new_matrix.close()
omx_file = omx.open_file(omx_example, "r")
m1 = np.array(omx_file["m1"]).sum()
m2 = np.array(omx_file["m2"]).sum()
self.assertEqual(m1 + m2, total_mats)
self.assertEqual(m1, total_m1)
omx_file.close()
del omx_file
def test_copy(self):
# test in-memory matrix_procedures copy
matrix_copy = self.new_matrix.copy(self.copy_matrix_name, cores=["mat"])
if not np.array_equal(matrix_copy.mat, self.new_matrix.mat):
self.fail("Matrix copy was not perfect")
matrix_copy.close()
del matrix_copy
def test_export_to_csv(self):
self.new_matrix.export(self.csv_export_name)
df = pd.read_csv(self.csv_export_name)
df.fillna(0, inplace=True)
self.assertEqual(df.shape[0], 2500, "Exported wrong size")
self.assertEqual(df.shape[1], 5, "Exported wrong size")
self.assertAlmostEqual(df.mat.sum(), np.nansum(self.new_matrix.matrices), 5, "Exported wrong matrix total")
def test_export_to_omx(self):
self.new_matrix.export(self.omx_export_name)
omxfile = omx.open_file(self.omx_export_name, "r")
# Check if matrices values are compatible
for m in self.new_matrix.names:
sm = np.nansum(self.new_matrix.matrix[m])
sm2 = np.nansum(np.array(omxfile[m]))
self.assertEqual(sm, sm2, "Matrix {} was exported with the wrong value".format(m))
del omxfile
def test_nan_to_num(self):
m = self.new_matrix.mat.sum() - self.new_matrix.mat[1, 1]
self.new_matrix.computational_view(["mat", "seed"])
self.new_matrix.nan_to_num()
self.new_matrix.mat[1, 1] = np.nan
self.new_matrix.computational_view(["mat"])
self.new_matrix.nan_to_num()
if abs(m - self.new_matrix.mat.sum()) > 0.000000000001:
self.fail("Total for mat matrix not maintained")
del self.new_matrix
def test_copy_from_omx(self):
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
a.create_from_omx(temp_file, omx_example)
omxfile = omx.open_file(omx_example, "r")
# Check if matrices values are compatible
for m in ["m1", "m2", "m3"]:
sm = a.matrix[m].sum()
sm2 = np.array(omxfile[m]).sum()
if sm != sm2:
self.fail("Matrix {} was copied with the wrong value".format(m))
if np.any(a.index[:] != np.array(list(omxfile.mapping("taz").keys()))):
self.fail("Index was not created properly")
a.close()
del a
del omxfile
def test_copy_from_omx_long_name(self):
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
with self.assertRaises(ValueError):
a.create_from_omx(temp_file, omx_example, robust=False)
del a
def test_copy_omx_wrong_content(self):
# Check if we get a result if we try to copy non-existing cores
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
with self.assertRaises(ValueError):
a.create_from_omx(temp_file, omx_example, cores=["m1", "m2", "m3", "m4"])
with self.assertRaises(ValueError):
a.create_from_omx(temp_file, omx_example, mappings=["wrong index"])
del a
def test_get_matrix(self):
a = AequilibraeMatrix()
a.load(self.sf_skims)
with self.assertRaises(AttributeError):
a.get_matrix("does not exist")
q = a.get_matrix("distance")
self.assertEqual(q.shape[0], 24)
a = AequilibraeMatrix()
a.load(self.name_test)
print(np.array_equal(a.get_matrix("seed"), a.matrix["seed"]))
del a
def test_save(self):
a = AequilibraeMatrix()
a.load(self.sf_skims)
a.computational_view(["distance"])
new_mat = np.random.rand(a.zones, a.zones)
a.matrix_view *= new_mat
res = a.matrix_view.sum()
a.save("new_name_for_matrix")
self.assertEqual(res, a.matrix_view.sum(), "Saved wrong result")
a.save(["new_name_for_matrix2"])
self.assertEqual(a.view_names[0], "new_name_for_matrix2", "Did not update computational view")
self.assertEqual(len(a.view_names), 1, "computational view with the wrong number of matrices")
a.computational_view(["distance", "new_name_for_matrix"])
with self.assertRaises(ValueError):
a.save(["just_one_name"])
a.save(["one_name", "two_names"])
with self.assertRaises(ValueError):
a.save("distance")
b = AequilibraeMatrix()
b.load(self.name_test)
b.computational_view("seed")
b.save()
b.computational_view(["mat", "seed", "dist"])
b.save()
class TestAequilibraeMatrix(TestCase):
def test___init__(self):
os.remove(name_test) if os.path.exists(name_test) else None
args = {
"file_name": name_test,
"zones": zones,
"matrix_names": ["mat", "seed", "dist"],
"index_names": ["my indices"],
}
matrix = AequilibraeMatrix()
matrix.create_empty(**args)
matrix.index[:] = np.arange(matrix.zones) + 100
matrix.mat[:, :] = np.random.rand(matrix.zones, matrix.zones)[:, :]
matrix.mat[:, :] = matrix.mat[:, :] * (1000 / np.sum(matrix.mat[:, :]))
matrix.setName("Test matrix - " + str(random.randint(1, 10)))
matrix.setDescription(
"Generated at " +
datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
matrix.close()
del matrix
def test_load(self):
# self.test___init__()
self.new_matrix = AequilibraeMatrix()
# Cannot load OMX file with no indices
with self.assertRaises(LookupError):
self.new_matrix.load(no_index_omx)
self.new_matrix = AequilibraeMatrix()
self.new_matrix.load(name_test)
def test_computational_view(self):
self.test_load()
self.new_matrix.computational_view(["mat", "seed"])
self.new_matrix.mat.fill(0)
self.new_matrix.seed.fill(0)
if self.new_matrix.matrix_view.shape[2] != 2:
self.fail(
"Computational view returns the wrong number of matrices")
self.new_matrix.computational_view(["mat"])
self.new_matrix.matrix_view[:, :] = np.arange(zones**2).reshape(
zones, zones)
if np.sum(self.new_matrix.mat) != np.sum(self.new_matrix.matrix_view):
self.fail("Assigning to matrix view did not work")
self.new_matrix.setName("Test matrix - " + str(random.randint(1, 10)))
self.new_matrix.setDescription(
"Generated at " +
datetime.datetime.now().strftime("%I:%M%p on %B %d, %Y"))
self.new_matrix.close()
def test_computational_view_with_omx(self):
self.new_matrix = AequilibraeMatrix()
self.new_matrix.load(omx_example)
arrays = ["m1", "m2"]
self.new_matrix.computational_view(arrays)
total_mats = np.sum(self.new_matrix.matrix_view)
self.new_matrix.computational_view([arrays[0]])
total_m1 = np.sum(self.new_matrix.matrix_view)
self.new_matrix.close()
omx_file = omx.open_file(omx_example, "r")
m1 = np.array(omx_file["m1"]).sum()
m2 = np.array(omx_file["m2"]).sum()
self.assertEqual(m1 + m2, total_mats)
self.assertEqual(m1, total_m1)
omx_file.close()
def test_copy(self):
self.test_load()
# test in-memory matrix_procedures copy
matrix_copy = self.new_matrix.copy(copy_matrix_name, cores=["mat"])
if not np.array_equal(matrix_copy.mat, self.new_matrix.mat):
self.fail("Matrix copy was not perfect")
matrix_copy.close()
self.new_matrix.close()
def test_export_to_csv(self):
self.test_load()
self.new_matrix.export(csv_export_name)
self.new_matrix.close()
def test_export_to_omx(self):
self.test_load()
self.new_matrix.export(omx_export_name)
omxfile = omx.open_file(omx_export_name, "r")
# Check if matrices values are compatible
for m in self.new_matrix.names:
sm = np.nansum(self.new_matrix.matrix[m])
sm2 = np.nansum(np.array(omxfile[m]))
self.assertEqual(
sm, sm2,
"Matrix {} was exported with the wrong value".format(m))
self.new_matrix.close()
def test_nan_to_num(self):
self.test_load()
s = self.new_matrix.seed.sum() - self.new_matrix.seed[1, 1]
m = self.new_matrix.mat.sum() - self.new_matrix.mat[1, 1]
self.new_matrix.seed[1, 1] = np.nan
self.new_matrix.computational_view(["mat", "seed"])
self.new_matrix.nan_to_num()
self.new_matrix.mat[1, 1] = np.nan
self.new_matrix.computational_view(["mat"])
self.new_matrix.nan_to_num()
if s != self.new_matrix.seed.sum():
self.fail("Total for seed matrix not maintained")
if m != self.new_matrix.mat.sum():
self.fail("Total for mat matrix not maintained")
def test_copy_from_omx(self):
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
a.create_from_omx(temp_file, omx_example)
omxfile = omx.open_file(omx_example, "r")
# Check if matrices values are compatible
for m in ["m1", "m2", "m3"]:
sm = a.matrix[m].sum()
sm2 = np.array(omxfile[m]).sum()
if sm != sm2:
self.fail(
"Matrix {} was copied with the wrong value".format(m))
if np.any(a.index[:] != np.array(list(omxfile.mapping("taz").keys()))):
self.fail("Index was not created properly")
a.close()
def test_copy_from_omx_long_name(self):
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
with self.assertRaises(ValueError):
a.create_from_omx(temp_file, omx_example, robust=False)
def test_copy_omx_wrong_content(self):
# Check if we get a result if we try to copy non-existing cores
temp_file = AequilibraeMatrix().random_name()
a = AequilibraeMatrix()
with self.assertRaises(ValueError):
a.create_from_omx(temp_file,
omx_example,
cores=["m1", "m2", "m3", "m4"])
with self.assertRaises(ValueError):
a.create_from_omx(temp_file, omx_example, mappings=["wrong index"])
