def test_read_variable_is_value_syntax(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 3)
self.assertEqual(["a", "b", "c"],
list(map(lambda x: x.name, table.domain.variables)))
np.testing.assert_almost_equal(table.X.todense(), np.array([[1, 2,
3]]))
def test_sparse_basket(self):
current_dir = os.path.dirname(__file__)
dataset = os.path.join(current_dir, "iris_basket.basket")
table = BasketReader().read_file(dataset)
test = Orange.data.Table.from_table_rows(table,
range(0, len(table), 2))
train = Orange.data.Table.from_table_rows(table,
range(1, len(table), 2))
learn = DummyMulticlassLearner()
clf = learn(train)
p = clf(test)
self.assertEqual(p.shape, test.Y.shape)
p = clf(test.X)
self.assertEqual(p.shape, test.Y.shape)
def test_handles_quote(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 4)
def test_handles_unicode(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 3)
np.testing.assert_almost_equal(table.X.todense(), np.array([[1, 1,
1]]))
def test_variables_can_be_listed_in_any_order(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 3)
np.testing.assert_almost_equal(table.X.todense(),
np.array([[1, 1, 0], [1, 1, 1]]))
def test_handles_duplicate_variables(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 2)
np.testing.assert_almost_equal(table.X.todense(), np.array([[3, 2]]))
def test_handles_spaces_between_variables(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 3)
self.assertEqual(set(x for x in table[0]), {1, 2, 3})
def test_read_variable_only_syntax(self, fname):
table = BasketReader().read_file(fname)
self.assertEqual(len(table.domain.variables), 5)
np.testing.assert_almost_equal(table.X.todense(),
np.array([[1, 1, 1, 1, 1]]))
def read_basket(filename):
return BasketReader(filename).read()