def test_combined_node(self):
ds = datasets['3dsmall']
axis2nodes = dict(h=(mean_feature, mean_feature),
v=(mean_sample, mean_sample))
for i, axis in enumerate('vh'):
nodes = axis2nodes[axis]
combined = CombinedNode([n() for n in nodes], axis, False)
assert_true(combined(ds).shape[i] == 2)
assert_true(combined(ds).shape[1 - i] == ds.shape[1 - i])
def test_compound_node(self):
data = np.asarray([[1, 2, 3, 4]], dtype=np.float_).T
ds = AttrDataset(data, sa=dict(targets=[0, 0, 1, 1]))
add = lambda x: lambda y: x + y
mul = lambda x: lambda y: x * y
add2 = FxNode(add(2))
mul3 = FxNode(mul(3))
assert_array_equal(add2(ds).samples, data + 2)
add2mul3 = ChainNode([add2, mul3])
assert_array_equal(add2mul3(ds), (data + 2) * 3)
add2_mul3v = CombinedNode([add2, mul3], 'v')
add2_mul3h = CombinedNode([add2, mul3], 'h')
assert_array_equal(
add2_mul3v(ds).samples, np.vstack((data + 2, data * 3)))
assert_array_equal(
add2_mul3h(ds).samples, np.hstack((data + 2, data * 3)))
def _call(self, ds):
return CombinedNode._call(self, ds)
def _call(self, ds):
return CombinedNode._call(self, ds)