def test_eval_test_all_loss_functions(self):
eval_t(queue=self.queue,
backend=self.backend,
config=self.configuration,
data=self.data,
seed=1,
num_run=1,
subsample=None,
with_predictions=True,
all_scoring_functions=True,
output_y_test=True,
include=None,
exclude=None,
disable_file_output=False)
info = get_last_result(self.queue)
fixture = {
'f1_metric': 0.0511508951407,
'pac_metric': 0.185257565321,
'acc_metric': 0.06,
'auc_metric': 0.00917546505782,
'bac_metric': 0.0416666666667,
'num_run': -1
}
rval = {
i.split(':')[0]: float(i.split(':')[1])
for i in info[3].split(';')
}
for key, value in fixture.items():
self.assertAlmostEqual(rval[key], fixture[key])
self.assertIn('duration', rval)
self.assertAlmostEqual(info[1], 0.041666666666666852)
self.assertEqual(info[2], 1)
def test_eval_test(self):
eval_t(self.queue, self.configuration, self.data, self.tmp_dir,
1, 1, None, True, False, True)
info = self.queue.get()
self.assertAlmostEqual(info[1], 0.041666666666666852)
self.assertEqual(info[2], 1)
self.assertNotIn('bac_metric', info[3])
def test_eval_test_all_loss_functions(self):
eval_t(self.queue, self.configuration, self.data, self.tmp_dir,
1, 1, None, True, True, True)
info = self.queue.get()
self.assertIn('f1_metric: 0.0511508951407;pac_metric: 0.273385527265;'
'acc_metric: 0.06;auc_metric: 0.00917546505782;'
'bac_metric: 0.0416666666667;duration: ', info[3])
self.assertAlmostEqual(info[1], 0.041666666666666852)
self.assertEqual(info[2], 1)
def test_eval_test(self):
eval_t(queue=self.queue,
backend=self.backend,
config=self.configuration,
data=self.data,
seed=1,
num_run=1,
subsample=None,
with_predictions=True,
all_scoring_functions=False,
output_y_test=True,
include=None,
exclude=None,
disable_file_output=False)
info = get_last_result(self.queue)
self.assertAlmostEqual(info[1], 0.041666666666666852)
self.assertEqual(info[2], 1)
self.assertNotIn('bac_metric', info[3])