def test_static(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertTrue(ds.is_static())
self.assertEqual(3, len(ds))
self.assertEqual({'value': 1}, dict(ds[0].num_values))
self.assertEqual({'value': 2}, dict(ds[1].num_values))
self.assertEqual({'value': 3}, dict(ds[2].num_values))
self.assertEqual({'v': 1}, dict(ds.get(0)))
self.assertEqual({'v': 2}, dict(ds.get(1)))
self.assertEqual({'v': 3}, dict(ds.get(2)))
ds2 = ds[(1, 2)]
self.assertEqual(2, len(ds2))
self.assertEqual({'value': 2}, dict(ds2[0].num_values))
self.assertEqual({'value': 3}, dict(ds2[1].num_values))
self.assertEqual({'v': 2}, dict(ds2.get(0)))
self.assertEqual({'v': 3}, dict(ds2.get(1)))
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx + 1}, dict(row.num_values))
expected_idx += 1
def test_static(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertTrue(ds.is_static())
self.assertEqual(3, len(ds))
self.assertEqual({'value': 1}, dict(ds[0].num_values))
self.assertEqual({'value': 2}, dict(ds[1].num_values))
self.assertEqual({'value': 3}, dict(ds[2].num_values))
self.assertEqual({'v': 1}, dict(ds.get(0)))
self.assertEqual({'v': 2}, dict(ds.get(1)))
self.assertEqual({'v': 3}, dict(ds.get(2)))
ds2 = ds[(1,2)]
self.assertEqual(2, len(ds2))
self.assertEqual({'value': 2}, dict(ds2[0].num_values))
self.assertEqual({'value': 3}, dict(ds2[1].num_values))
self.assertEqual({'v': 2}, dict(ds2.get(0)))
self.assertEqual({'v': 3}, dict(ds2.get(1)))
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx+1}, dict(row.num_values))
expected_idx += 1
def test_convert_empty(self):
loader = StubLoader()
ds1 = BaseDataset(loader, self.SCHEMA)
ds2 = ds1.convert(lambda data: [None
for d in data]) # ds2 should be empty
for d in ds2:
self.fail()
def test_convert(self):
loader = StubLoader()
ds1 = BaseDataset(loader, self.SCHEMA)
def f(d):
new_d = {}
for (k, v) in d.items():
new_d[k] = d[k] + 1
return new_d
ds2 = ds1.convert(lambda data: [f(d) for d in data])
self.assertEqual(1, ds1[0].num_values[0][1])
self.assertEqual(2, ds2[0].num_values[0][1])
def test_convert(self):
loader = StubLoader()
ds1 = BaseDataset(loader, self.SCHEMA)
def f(d):
new_d = {}
for (k, v) in d.items():
new_d[k] = d[k] + 1
return new_d
ds2 = ds1.convert(lambda data: [f(d) for d in data])
self.assertEqual(1, ds1[0].num_values[0][1])
self.assertEqual(2, ds2[0].num_values[0][1])
def test_infinite(self):
loader = StubInfiniteLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertFalse(ds.is_static())
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx+1}, dict(row.num_values))
expected_idx += 1
if 10 < expected_idx:
break
def test_nonstatic(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA, False)
self.assertFalse(ds.is_static())
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx+1}, dict(row.num_values))
self.assertEqual(row.num_values, ds[idx].num_values)
self.assertEqual({'v': idx+1}, ds.get(idx))
expected_idx += 1
def test_infinite(self):
loader = StubInfiniteLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertFalse(ds.is_static())
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx + 1}, dict(row.num_values))
expected_idx += 1
if 10 < expected_idx:
break
def test_nonstatic(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA, False)
self.assertFalse(ds.is_static())
expected_idx = 0
for (idx, row) in ds:
self.assertEqual(expected_idx, idx)
self.assertEqual({'value': idx + 1}, dict(row.num_values))
self.assertEqual(row.num_values, ds[idx].num_values)
self.assertEqual({'v': idx + 1}, ds.get(idx))
expected_idx += 1
def test_nonstatic_ops(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA, False)
self.assertRaises(RuntimeError, ds.shuffle, 0)
self.assertRaises(RuntimeError, ds.convert, lambda x: x)
self.assertRaises(RuntimeError, ds.get, 0)
self.assertRaises(RuntimeError, len, ds)
self.assertRaises(RuntimeError, lambda: ds[0])
def test_shuffle(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA).shuffle(0)
rows = []
for (_, row) in ds:
rows.append(row)
row_values = [x.num_values[0][1] for x in rows]
self.assertEqual([1, 2, 3], sorted(row_values))
def test_convert_empty(self):
loader = StubLoader()
ds1 = BaseDataset(loader, self.SCHEMA)
ds2 = ds1.convert(lambda data: [None for d in data]) # ds2 should be empty
for d in ds2:
self.fail()
def test_predict(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertRaises(NotImplementedError, ds._predict, {})
def test_get_schema(self): loader = StubLoader() ds = BaseDataset(loader, self.SCHEMA) self.assertEqual(self.SCHEMA, ds.get_schema())
def test_get_schema(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertEqual(self.SCHEMA, ds.get_schema())
def test_index_access(self):
loader = StubLoader()
ds = BaseDataset(loader, self.SCHEMA)
self.assertTrue(isinstance(ds[0], jubatus.common.Datum))
self.assertTrue(isinstance(ds[0:1], BaseDataset))
def test_invalid_convert(self):
loader = StubLoader()
ds1 = BaseDataset(loader, self.SCHEMA)
self.assertRaises(RuntimeError, ds1.convert, lambda x: None)