def test_remove_duplicate_readings():
data = _get_test_data()
velocities = compute_velocities(data)
number_of_duplicates = np.sum(np.isnan(velocities))
fixed_data = remove_duplicate_points(data)
fixed_velocities = compute_velocities(fixed_data)
assert np.sum(np.isnan(fixed_velocities)) == 0
# check that we deleted duplicates only
print(data.shape[0])
print(fixed_data.shape[0])
print(number_of_duplicates)
assert fixed_data.shape[0] == data.shape[0] - number_of_duplicates
print(fixed_data.shape[0], data.shape[0])
fixed_data_processor = apply_filter(data, DuplicateTimeFilter())
assert (fixed_data == fixed_data_processor).all()
def plot_velocity_histogram(data):
delta_time = extract_delta_time(data)
velocities = compute_velocities(data)
plots.plot(delta_time)
plots.show()
plots.hist(velocities*ms_to_mph, 100)
plots.show()
def test_remove_outliers():
np.set_printoptions(suppress=True)
data = remove_stationary_points(remove_duplicate_points(_get_test_data()))
velocity_threshold = 85.0
fixed_data = apply_filter(data, VelocityOutliersFilter(velocity_threshold))
# check that data has outliers in velocity and distance
velocities = compute_velocities(data)
outliers = np.where(velocities * ms_to_mph > 85)[0]
assert len(outliers) > 0
assert np.amax(extract_delta_dist(data)) > 157900
# no large velocities left
velocities = compute_velocities(fixed_data)
assert np.amax(velocities) * ms_to_mph < velocity_threshold
assert np.amax(extract_delta_dist(fixed_data)) < 330
# we expect this number of point to be removed
print(data.shape[0] - fixed_data.shape[0])
assert data.shape[0] - fixed_data.shape[0] == 5
