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)
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)