def test_dataset_init(self):
# From text files
dataset = Dataset(join(tdp(), 'items.txt'), join(tdp(), 'scales.txt'))
self.assertEqual(len(dataset.X), len(dataset.y))
# From pandas DFs
dataset = Dataset(self.X, self.y)
self.assertEqual(len(dataset.X), len(dataset.y))
def test_measure_save(self):
measure = Measure(X=join(tdp(), 'items.txt'), y=join(tdp(), 'scales.txt'), key=join(tdp(), 'key.txt'), missing='drop')
t = tempfile.mkdtemp()
measure.save(key=True, summary=True, pickle=True, path=t)
self.assertTrue(exists(t + '/key.txt'))
self.assertTrue(exists(t + '/data.pkl'))
self.assertTrue(exists(t + '/summary.txt'))
shutil.rmtree(t)
def setUpClass(cls):
measure = Measure(X=join(tdp(), 'items.txt'),
y=join(tdp(), 'scales.txt'),
key=join(tdp(), 'key.txt'),
missing='drop')
abb = abbreviate.TopNAbbreviator(max_items=8, min_r=0.3)
gen = Generator(abbreviator=abb)
gen.run(measure, n_gens=3)
cls.generator = gen
def setUp(self):
self.dataset = Dataset(join(tdp(), 'items.txt'), join(tdp(), 'scales.txt'), missing='drop')
def test_abbreviator(self):
measure = Measure(X=join(tdp(), 'items.txt'), y=join(tdp(), 'scales.txt'), key=join(tdp(), 'key.txt'), missing='drop')
gen = Generator()
am = gen.run(measure, n_gens=3)
def setUp(self):
self.dataset = Dataset(join(tdp(), 'items.txt'),
join(tdp(), 'scales.txt'),
missing='drop')
def setUpClass(cls):
measure = Measure(X=join(tdp(), 'items.txt'), y=join(tdp(), 'scales.txt'), key=join(tdp(), 'key.txt'), missing='drop')
abb = abbreviate.TopNAbbreviator(max_items=8, min_r=0.3)
gen = Generator(abbreviator=abb)
gen.run(measure, n_gens=3)
cls.generator = gen
