def test_missing_in_row_dict_raise_valueerror(self):
database = Database("whoah")
database.register()
dtype = [
(numpy_string('a'), np.uint32),
(numpy_string('b'), np.uint32),
(numpy_string('row'), np.uint32),
(numpy_string('col'), np.uint32),
(numpy_string('values'), np.float32),
]
array = np.array([
(1, 2, MAX_INT_32, MAX_INT_32, 99),
(1, 4, MAX_INT_32, MAX_INT_32, 99),
],
dtype=dtype)
row_dict = {1: 0}
col_dict = {2: 0}
np.save(database.filepath_processed(), array, allow_pickle=False)
with self.assertRaises(ValueError):
MatrixBuilder.build([database.filepath_processed()],
"values",
"a",
"row",
"b",
"col",
row_dict,
col_dict,
drop_missing=False)
def test_database_process_adds_correct_geo(add_biosphere):
database = Database("food")
database.write(food)
package = load_datapackage(ZipFS(database.filepath_processed()))
data = package.get_resource("food_inventory_geomapping_matrix.indices")[0]
assert geomapping["CA"] in data["col"].tolist()
assert geomapping["CH"] in data["col"].tolist()
def test_database_process_adds_default_geo(add_biosphere):
database = Database("food")
new_food = copy.deepcopy(food)
for v in new_food.values():
del v["location"]
database.write(new_food)
package = load_datapackage(ZipFS(database.filepath_processed()))
data = package.get_resource("food_inventory_geomapping_matrix.indices")[0]
assert np.allclose(data["col"], geomapping[config.global_location])
def test_build_one_d_drop_missing(self):
database = Database("ghost")
database.register()
dtype = [
(numpy_string('a'), np.uint32),
(numpy_string('row'), np.uint32),
(numpy_string('values'), np.float32),
]
array = np.array([
(1, MAX_INT_32, 99),
(2, MAX_INT_32, 99),
(3, MAX_INT_32, 99),
],
dtype=dtype)
row_dict = {1: 0, 2: 1}
np.save(database.filepath_processed(), array, allow_pickle=False)
values = MatrixBuilder.build([database.filepath_processed()],
"values",
"a",
"row",
row_dict=row_dict,
one_d=True)[0]
self.assertEqual(values.shape, (2, ))
def test_build_one_d(self):
database = Database("sour")
database.register()
dtype = [
(numpy_string('a'), np.uint32),
(numpy_string('row'), np.uint32),
(numpy_string('values'), np.float32),
]
array = np.array([
(1, MAX_INT_32, 99),
(2, MAX_INT_32, 100),
],
dtype=dtype)
row_dict = {1: 0, 2: 1}
np.save(database.filepath_processed(), array, allow_pickle=False)
matrix = MatrixBuilder.build([database.filepath_processed()],
"values",
"a",
"row",
row_dict=row_dict,
one_d=True)[3]
self.assertTrue(
np.allclose(matrix.toarray(), np.array(((99, 0), (0, 100)))))
def test_build_drop_missing(self):
database = Database("boo")
database.register()
dtype = [
(numpy_string('a'), np.uint32),
(numpy_string('b'), np.uint32),
(numpy_string('row'), np.uint32),
(numpy_string('col'), np.uint32),
(numpy_string('values'), np.float32),
]
array = np.array([
(1, 2, MAX_INT_32, MAX_INT_32, 99),
(3, 4, MAX_INT_32, MAX_INT_32, 99),
(3, 2, MAX_INT_32, MAX_INT_32, 99),
(5, 6, MAX_INT_32, MAX_INT_32, 99),
],
dtype=dtype)
row_dict = {1: 0, 3: 1}
col_dict = {2: 0, 6: 1}
np.save(database.filepath_processed(), array, allow_pickle=False)
values = MatrixBuilder.build([database.filepath_processed()], "values",
"a", "row", "b", "col", row_dict,
col_dict)[0]
self.assertEqual(values.shape, (2, ))