def test_mdpflowmapper():
flow = mdp.nodes.PCANode() + mdp.nodes.SFANode()
fm = MDPFlowMapper(flow)
ds = normal_feature_dataset(perlabel=10, nlabels=2, nfeatures=4)
fm.train(ds)
assert_false(fm.flow[0].is_training())
assert_false(fm.flow[1].is_training())
fds = fm.forward(ds)
assert_true(isinstance(fds, Dataset))
assert_equal(fds.samples.shape, ds.samples.shape)
def test_mdpflow_additional_arguments_nones():
skip_if_no_external('mdp', min_version='2.5')
# we have no IdentityNode yet... is there analog?
ds = normal_feature_dataset(perlabel=10, nlabels=2, nfeatures=4)
flow = mdp.nodes.PCANode() + mdp.nodes.IdentityNode() + mdp.nodes.FDANode()
# this is what it would look like in MDP itself
#flow.train([[ds.samples],
# [[ds.samples, ds.sa.targets]]])
assert_raises(ValueError, MDPFlowMapper, flow, node_arguments=[[],[]])
fm = MDPFlowMapper(flow, node_arguments = (None, None, [ds.sa.targets]))
fm.train(ds)
fds = fm.forward(ds)
assert_equal(ds.samples.shape, fds.samples.shape)
rds = fm.reverse(fds)
assert_array_almost_equal(ds.samples, rds.samples)
