def test_get_parameter_values(self):
current_path = os.path.realpath(__file__)
data_frame = robjects.DataFrame.from_csvfile(current_path[:current_path.rindex('/')] + '/../data/state.df')
prediction_variable = 'Life.Exp'
predictor_variables = ['Population', 'Income', 'Illiteracy', 'Murder', 'HS.Grad', 'Frost', 'Area']
expected_parameter_names_and_values = [
('(Intercept)', 70.94322411112951),
('Population', 5.1800363834827194e-05),
('Income', -2.1804237825318798e-05),
('Illiteracy', 0.033820321355290311),
('Murder', -0.30112317045182957),
('HS.Grad', 0.048929478881717045),
('Frost', -0.0057350011035554654),
('Area', -7.3831661447743889e-08)
]
expected_parameter_names_and_values2 = [
('(Intercept)', 71.027128532085925),
('Population', 5.0139978004722538e-05),
('Murder', -0.30014880033035229),
('HS.Grad', 0.046582246664721869),
('Frost', -0.005943289723506183)
]
model = R_Helper.linear_regression_model(data_frame, prediction_variable, predictor_variables)
parameter_names_and_values = R_Helper.get_parameter_values(model)
self.assertEqual(expected_parameter_names_and_values, parameter_names_and_values)
model = R_Helper.linear_regression_model(
data_frame,
prediction_variable,
predictor_variables,
with_variable_selection=True
)
parameter_names_and_values = R_Helper.get_parameter_values(model)
self.assertEqual(expected_parameter_names_and_values2, parameter_names_and_values)
def test_get_predicted_value(self):
current_path = os.path.realpath(__file__)
data_frame = robjects.DataFrame.from_csvfile(current_path[:current_path.rindex('/')] + '/../data/state.df')
prediction_variable = 'Life.Exp'
predictor_variables = ['Population', 'Income', 'Illiteracy', 'Murder', 'HS.Grad', 'Frost', 'Area']
model = R_Helper.linear_regression_model(data_frame, prediction_variable, predictor_variables)
mf_parameter_names_to_values = dict(R_Helper.get_parameter_values(model))
mf_variable_name_to_value = {'Population': 1.0}
self.assertEqual(
'%0.5f'%70.9432759115,
'%0.5f'%R_Helper.get_predicted_value(mf_parameter_names_to_values, mf_variable_name_to_value)
)
def test_variable_selection_using_backward_elimination(self):
current_path = os.path.realpath(__file__)
data_frame = robjects.DataFrame.from_csvfile(current_path[:current_path.rindex('/')] + '/../data/state.df')
prediction_variable = 'Life.Exp'
predictor_variables = ['Population', 'Income', 'Illiteracy', 'Murder', 'HS.Grad', 'Frost', 'Area']
self.assertEqual(
['Population', 'Murder', 'HS.Grad', 'Frost'],
R_Helper.variable_selection_using_backward_elimination(
data_frame,
prediction_variable,
predictor_variables
)
)
predictor_variables = ['Population', 'Income', 'Illiteracy', 'Murder', 'HS.Grad', 'Frost', 'Area']
self.assertEqual(
['Population', 'Income', 'Murder', 'HS.Grad', 'Frost'],
R_Helper.variable_selection_using_backward_elimination(
data_frame,
prediction_variable,
predictor_variables,
p_to_remove=0.20
)
)
def test_get_data_frame_from_json(self):
returned_data_frame = R_Helper.get_data_frame_from_json(self.data_frame_json)
self.assertEqual(sorted(list(self.data_frame.colnames)), sorted(list(returned_data_frame.colnames)))
def test_get_json_for_data_frame(self):
self.assertEqual(self.data_frame_json, R_Helper.get_json_for_data_frame(self.data_frame))
