def test_find_bus_stops_close_to_Politecnico():
print("Checking the find bus stops close to Politecnico, Milan")
x = 9.226182
y = 45.478657
p = Point(x, y)
radius = 0.0015
closest_stops = stops().find_stops_close_to(p, radius)
# Check that there are some stops close to Politecnico
assert len(closest_stops) > 0
print(
f"The number of stops is greater than 0, they are {len(closest_stops)}"
)
# Check that those buses are stopping near Politecnico
bus_lines_to_check = ['19', '33']
print(
f"Looking if the bus lines {bus_lines_to_check} are in the closest stops"
)
bus_lines_in_the_closest_stops = set([stop[0] for stop in closest_stops])
is_the_bus_line_contained = [
bus_line in bus_lines_in_the_closest_stops
for bus_line in bus_lines_to_check
]
print(f"Are they contained? {is_the_bus_line_contained}")
assert all(is_the_bus_line_contained) is True
print("Test passed.\n")
def get_train_routes(initial_point, finishing_point):
"""
Retrieve the all the train routes slices of vehicles that passes near the initial point
and the finishing point
@param initial_point: initial user route Point
@param finishing_point: finishing user route Point
"""
# STEP 2
# Find train stops near I. Do the same for F
stops_object = stops(type_of_dataset='TRAIN')
offset_square = 0.001
Ilist = stops_object.find_stops_close_to(initial_point,
radius=offset_square)
Flist = stops_object.find_stops_close_to(finishing_point,
radius=offset_square)
# STEP 3
# Do the intersection in order to find the bus lines in common
Ilist, Flist = intercept(Ilist, Flist)
print(f'train stops found: {Ilist}')
print(f'train stops found: {Flist}')
# STEP 4
# Create a list of train routes that have a starting point in Ilist and an end in Flist
linestring_selector = LinestringSelector(Ilist,
Flist,
type_of_dataset="TRAIN")
sliced_routes = linestring_selector.get_sliced_routes()
print(f'train routes found: {str(len(sliced_routes))}')
return sliced_routes
def test_loading_dataset():
print("Checking the type of the dataset.")
print("It should be a geopandas.geodataframe.GeoDataFrame .")
geo_dataframe = stops().dataset
# Check that the initialized dataframe is not empty
assert isinstance(geo_dataframe, geopandas.geodataframe.GeoDataFrame)
print("Test passed.\n")
def test_intercept_from_Duomo_to_Politecnico():
print("Intercepting the 'from' dataset with the 'to' dataset")
duomo_x = 9.18951
duomo_y = 45.46427
duomo_coordinate = Point(duomo_x, duomo_y)
politecnico_x = 9.226182
politecnico_y = 45.478657
politecnico_coordinate = Point(politecnico_x, politecnico_y)
radius = 0.0015
duomo_stops = stops().find_stops_close_to(duomo_coordinate, radius)
polimi_stops = stops().find_stops_close_to(politecnico_coordinate, radius)
relevant_duomo_stops, relevant_politecnico_stops = intercept(
duomo_stops, polimi_stops)
# Check the format of the output
assert isinstance(relevant_duomo_stops,
geopandas.geodataframe.GeoDataFrame)
assert isinstance(relevant_politecnico_stops,
geopandas.geodataframe.GeoDataFrame)
print("The returned datasets are both GeoDataframes, Great.")
expected_columns = ['bus_id', 'longitude', 'latitude', 'point']
does_result_contains_the_expected_columns = [
column in relevant_duomo_stops.columns for column in expected_columns
]
assert all(does_result_contains_the_expected_columns) is True
does_result_contains_the_expected_columns = [
column in relevant_politecnico_stops.columns
for column in expected_columns
]
assert all(does_result_contains_the_expected_columns) is True
print(f"The result contains those columns {expected_columns}")
# Check that only the bus line '19' is contained in both dataset
duomo_lines = set(relevant_duomo_stops['bus_id'])
politecnico_lines = set(relevant_politecnico_stops['bus_id'])
assert len(duomo_lines) == 1
assert len(politecnico_lines) == 1
assert '19' in politecnico_lines
assert '19' in duomo_lines
print("Only line '19' connects Duomo to Politecnico")
print("Test passed.\n")