def test_update_velocities_group_field_and_indexes_not_None(
self, fixture_update_velocities):
"""
Comparison of the angles of the agents after applying update
velocities through a Kolmogorov-smirnov test. `indexes` and
`group_field` are set not None.
"""
distribution = pytest.distrib
sample_indexes = 500
delta_angles = pytest.delta_angles
df = DataFrame(pytest.data_large_sample)
df["mobility_profile"] = "MG_1"
mobility_group_slice = 300
df.loc[0:mobility_group_slice - 1, "mobility_profile"] = "MG_2"
angles_before = AgentMovement.vector_angles(df, ['vx', 'vy'])
indexes = [i for i in range(sample_indexes + 1)]
df = AgentMovement.update_velocities(df, distribution,
pytest.angle_variance, indexes,
"mobility_profile", "MG_2")
angles_after = AgentMovement.vector_angles(df, ['vx', 'vy'])
angle_variation_1 = angles_after[:mobility_group_slice] - \
angles_before[:mobility_group_slice]
k, p_1 = kstest(angle_variation_1.values, delta_angles)
angle_variation_2 = angles_after[mobility_group_slice:] - \
angles_before[mobility_group_slice:]
k, p_2 = kstest(angle_variation_2.values, delta_angles)
cond_1 = True if p_1 > 0.05 else False
cond_2 = True if p_2 < 0.05 else False
assert cond_1 and cond_2
def test_deviation_angle(self, input_df, expected_angle):
"""Verifies the deviation angle function in three different cases"""
input_df["relative_angle"] = AgentMovement.vector_angles(
input_df, ["x_relative", "y_relative"])
angle = AgentMovement.deviation_angle(input_df)
assert round(angle, 12) == round(expected_angle, 12)
def test_update_velocities_angle_variance_zero_indexes_group_field_None(
self, fixture_update_velocities):
"""
Verifies whether there are no changes in the velocities components when
the standard deviation of the numpy normal distribution is set to zero
`angle_variance=0.0`. `indexes` and `group_field` is se to None.
"""
df = DataFrame(pytest.data_large_sample)
angles_before = AgentMovement.vector_angles(df, ['vx', 'vy'])
df = AgentMovement.update_velocities(df, pytest.distrib, 0.0)
angles_after = AgentMovement.vector_angles(df, ['vx', 'vy'])
not_angle_variation = all(
round(angles_before.head() - angles_after.head(), 7))
assert not_angle_variation == 0
def test_update_velocities_comparison_KS_test(self,
fixture_update_velocities):
"""
Comparison of the angles of the agents after applying update
velocities through a Kolmogorov-smirnov test. `indexes` and
`group_field` are set to None.
"""
df = DataFrame(pytest.data_large_sample)
angles_before = AgentMovement.vector_angles(df, ['vx', 'vy'])
df = AgentMovement.update_velocities(df, pytest.distrib,
pytest.angle_variance)
angles_after = AgentMovement.vector_angles(df, ['vx', 'vy'])
angle_variation = angles_after - angles_before
k, p = kstest(angle_variation.values, pytest.delta_angles)
cond = True if p > 0.05 else False
assert cond
def test_vector_angles(self, input_df, expected_angle):
"""
Calculates the angle position of the agents with components
`x` and `y` of the input DataFrame.
"""
angle = AgentMovement.vector_angles(input_df, ['x', 'y'])
assert round(angle[0], decimals=10) == \
round(expected_angle, decimals=10)
def test_vector_angles_raise_error_correct_list(
self, fixture_vector_angles_raise_error):
"""
Raises an exception when the input DataFrame columns are not in the
list, `vx` and `vy` in this case.
"""
df = DataFrame(pytest.wrong_data)
correct_list = pytest.correct_list
with pytest.raises(ValueError):
assert AgentMovement.vector_angles(df, correct_list)
def test_vector_angles_raise_error_wrong_list(
self, fixture_vector_angles_raise_error):
"""
Raises an exception when the input list does not have correct columns
names, `vx` and `vy` in this case.
"""
df = DataFrame(pytest.data)
wrong_list = pytest.wrong_list
with pytest.raises(ValueError):
assert AgentMovement.vector_angles(df, wrong_list)
def test_update_velocities_group_field_None(self,
fixture_update_velocities):
"""
Comparison of the angles of the agents after applying update
velocities through a Kolmogorov-smirnov test. `group_field` is set
to None.
"""
distribution = pytest.distrib
sample_indexes = 400
df = DataFrame(pytest.data_large_sample)
angles_before = AgentMovement.vector_angles(
df, ['vx', 'vy'])[:sample_indexes]
indexes = [i for i in range(sample_indexes + 1)]
df = AgentMovement.update_velocities(df, distribution,
pytest.angle_variance, indexes,
None, None)
angles_after = AgentMovement.vector_angles(
df, ['vx', 'vy'])[:sample_indexes]
angle_variation = angles_after - angles_before
k, p = kstest(angle_variation.values, pytest.delta_angles)
cond = True if p > 0.05 else False
assert cond