Commit f9ba2f57 authored by Jay's avatar Jay
Browse files

Updated for markkov testing and to allow loading when some information is missing

parent 6f655e2e

autocnet/examples/Apollo15/sixty_four_apollo.graph

deleted100644 → 0
−47.1 KiB

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autocnet/examples/Apollo15/sixty_four_apollo.proj

0 → 100644
+65.4 KiB

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autocnet/graph/edge.py

+6 −2
Original line number Diff line number Diff line
@@ -55,14 +55,18 @@ class Edge(dict, MutableMapping): 
        d = self.__dict__

        o = other.__dict__

        for k, v in d.items():

            if isinstance(v, pd.DataFrame):

            # If the attribute key is missing they can not be equal

            if not k in o.keys():

                    print(o)

                eq = False

                return eq



            if isinstance(v, pd.DataFrame):

                if not v.equals(o[k]):

                    eq = False

            elif isinstance(v, np.ndarray):

                if not v.all() == o[k].all():

                    eq = False

                    

        return eq



    @property

autocnet/graph/tests/test_markov_cluster.py

+9 −13
Original line number Diff line number Diff line
@@ -7,24 +7,20 @@ from .. import markov_cluster 


from autocnet.examples import get_path

from autocnet.graph.network import CandidateGraph



from autocnet.io.network import load



class TestMarkovCluster(unittest.TestCase):



    def setUp(self):

        pass

        #TODO: These tests need to load a graph from the new zip

        #self.g = CandidateGraph.from_graph(get_path('sixty_four_apollo.graph'))

        self.g = load(get_path('sixty_four_apollo.proj'))



    def test_mcl_from_network(self):

        pass

        #self.g.compute_clusters(inflate_factor=15)

        #self.assertIsInstance(self.g.clusters, dict)

        #self.assertEqual(len(self.g.clusters), 14)

        self.g.compute_clusters(inflate_factor=15)

        self.assertIsInstance(self.g.clusters, dict)

        self.assertEqual(len(self.g.clusters), 14)



    def test_mcl_from_adj_matrix(self):

        pass

        #arr = np.array(nx.adjacency_matrix(self.g).todense())

        #flow, clusters = markov_cluster.mcl(arr)

        #self.assertIsInstance(clusters, dict)

        #self.assertEqual(len(clusters), 3)
 
        arr = np.array(nx.adjacency_matrix(self.g).todense())

        flow, clusters = markov_cluster.mcl(arr)

        self.assertIsInstance(clusters, dict)

        self.assertEqual(len(clusters), 3)

autocnet/io/network.py

+6 −1
Original line number Diff line number Diff line
@@ -102,8 +102,11 @@ def load(projectname): 
        for d in data['nodes']:

            n = Node(image_name=d['image_name'], image_path=d['image_path'], node_id=d['id'])

            n['hash'] = d['hash']

            try:

                # Load the byte stream for the nested npz file into memory and then unpack

                n.load_features(BytesIO(pzip.read('{}.npz'.format(d['id']))))

            except:

                pass  # The node does not have features to load.

            cg.add_node(d['node_id'])

            cg.node[d['node_id']] = n

        for e in data['links']:
@@ -113,10 +116,12 @@ def load(projectname): 
            edge.destination = cg.node[e['target']]

            edge['fundamental_matrix'] = e['fundamental_matrix']

            edge['weights'] = e['weights']

            try:

                nzf = np.load(BytesIO(pzip.read('{}_{}.npz'.format(e['source'], e['target']))))



                edge._masks = pd.DataFrame(nzf['_masks'], index=nzf['_masks_idx'], columns=nzf['_masks_columns'])

                edge.matches = pd.DataFrame(nzf['matches'], index=nzf['matches_idx'], columns=nzf['matches_columns'])

            except:

                pass

            # Add a mock edge

            cg.edge[e['source']][e['target']] = edge