def test_get_velocity_diff_for_two_tracks(self):
"""Ensures correct output from _get_velocity_diff_for_two_tracks.
This is an integration test, not a unit test, because it depends on
_theil_sen_fit.
"""
theil_sen_model_for_x_early, theil_sen_model_for_y_early = (
best_tracks._theil_sen_fit(
unix_times_sec=TIMES_EARLY_TRACK_UNIX_SEC,
x_coords_metres=X_COORDS_EARLY_TRACK_METRES,
y_coords_metres=Y_COORDS_EARLY_TRACK_METRES))
theil_sen_model_for_x_late, theil_sen_model_for_y_late = (
best_tracks._theil_sen_fit(
unix_times_sec=TIMES_LATE_TRACK_UNIX_SEC,
x_coords_metres=X_COORDS_LATE_TRACK_METRES,
y_coords_metres=Y_COORDS_LATE_TRACK_METRES))
this_velocity_diff_m_s01 = (
best_tracks._get_velocity_diff_for_two_tracks(
[theil_sen_model_for_x_early, theil_sen_model_for_x_late],
[theil_sen_model_for_y_early, theil_sen_model_for_y_late]))
self.assertTrue(
numpy.isclose(this_velocity_diff_m_s01,
VELOCITY_DIFFERENCE_M_S01,
atol=TOLERANCE))
def test_get_mean_prediction_error_for_two_tracks(self):
"""Ensures correctness of _get_mean_prediction_error_for_two_tracks.
This is an integration test, not a unit test, because it depends on
_theil_sen_fit.
"""
theil_sen_model_for_x_early, theil_sen_model_for_y_early = (
best_tracks._theil_sen_fit(
unix_times_sec=TIMES_EARLY_TRACK_UNIX_SEC,
x_coords_metres=X_COORDS_EARLY_TRACK_METRES,
y_coords_metres=Y_COORDS_EARLY_TRACK_METRES))
this_mean_error_metres = (
best_tracks._get_mean_prediction_error_for_two_tracks(
x_coords_late_metres=X_COORDS_LATE_TRACK_METRES,
y_coords_late_metres=Y_COORDS_LATE_TRACK_METRES,
late_times_unix_sec=TIMES_LATE_TRACK_UNIX_SEC,
theil_sen_model_for_x_early=theil_sen_model_for_x_early,
theil_sen_model_for_y_early=theil_sen_model_for_y_early))
self.assertTrue(
numpy.isclose(this_mean_error_metres,
MEAN_ERROR_LATE_PREDICTED_BY_EARLY_METRES,
atol=TOLERANCE))
def test_theil_sen_fit(self):
"""Ensures correct output from _theil_sen_fit."""
this_ts_model_for_x, this_ts_model_for_y = best_tracks._theil_sen_fit(
unix_times_sec=TIMES_THEIL_SEN_INPUT_UNIX_SEC,
x_coords_metres=X_FOR_THEIL_SEN_INPUT_METRES,
y_coords_metres=Y_FOR_THEIL_SEN_INPUT_METRES)
this_x_coefficient_m_s01 = this_ts_model_for_x.coef_[0]
this_y_coefficient_m_s01 = this_ts_model_for_y.coef_[0]
self.assertTrue(
numpy.absolute(this_x_coefficient_m_s01 -
X_COEFF_THEIL_SEN_M_S01) <= TOLERANCE)
self.assertTrue(
numpy.absolute(this_y_coefficient_m_s01 -
Y_COEFF_THEIL_SEN_M_S01) <= TOLERANCE)
def test_break_ties_one_storm_track(self):
"""Ensures correct output from _break_ties_one_storm_track."""
this_theil_sen_model_for_x, this_theil_sen_model_for_y = (
best_tracks._theil_sen_fit(unix_times_sec=TIMES_IN_TIE_UNIX_SEC,
x_coords_metres=X_COORDS_IN_TIE_METRES,
y_coords_metres=Y_COORDS_IN_TIE_METRES))
these_indices_to_remove = best_tracks._break_ties_one_storm_track(
object_x_coords_metres=X_COORDS_IN_TIE_METRES,
object_y_coords_metres=Y_COORDS_IN_TIE_METRES,
object_times_unix_sec=TIMES_IN_TIE_UNIX_SEC,
theil_sen_model_for_x=this_theil_sen_model_for_x,
theil_sen_model_for_y=this_theil_sen_model_for_y)
self.assertTrue(
numpy.array_equal(these_indices_to_remove,
INDICES_TO_REMOVE_FROM_TIE))
def test_theil_sen_predict(self):
"""Ensures correct output from _theil_sen_predict.
This is an integration test, not a unit test, because it also requires
_theil_sen_fit.
"""
this_ts_model_for_x, this_ts_model_for_y = best_tracks._theil_sen_fit(
unix_times_sec=TIMES_THEIL_SEN_INPUT_UNIX_SEC,
x_coords_metres=X_FOR_THEIL_SEN_INPUT_METRES,
y_coords_metres=Y_FOR_THEIL_SEN_INPUT_METRES)
this_x_predicted_metres, this_y_predicted_metres = (
best_tracks._theil_sen_predict(
theil_sen_model_for_x=this_ts_model_for_x,
theil_sen_model_for_y=this_ts_model_for_y,
query_time_unix_sec=QUERY_TIME_THEIL_SEN_UNIX_SEC))
self.assertTrue(
numpy.absolute(this_x_predicted_metres -
X_PREDICTED_THEIL_SEN_METRES) <= TOLERANCE)
self.assertTrue(
numpy.absolute(this_y_predicted_metres -
Y_PREDICTED_THEIL_SEN_METRES) <= TOLERANCE)