Commit bbd601f9 authored by Jay's avatar Jay
Browse files

Functional tests updated for nx2 - completes update

parent 4d94c457

autocnet/control/control.py

+0 −1
Original line number Diff line number Diff line
@@ -178,7 +178,6 @@ class ControlNetwork(object): 
        # The node_id is a composite key (image_id, correspondence_id), so just grab the image

        image_id = key[0]

        match_id = key[1]

        print(self.data.columns)

        self.data.loc[self._measure_id] = [point_id, image_id, match_id, edge, match_idx, *fields, 0, 0, np.inf, True]

        self._measure_id += 1

autocnet/graph/edge.py

+0 −3
Original line number Diff line number Diff line
@@ -186,14 +186,11 @@ class Edge(dict, MutableMapping): 
            raise TypeError

        keypts = node.get_keypoint_coordinates(index=index, homogeneous=homogeneous)

        # If we only want keypoints in the overlap

        print('O', overlap)

        if overlap:

            if self.source == node:

                mbr = self['source_mbr']

                print('s', mbr)

            else:

                mbr = self['destin_mbr']

                print('d', mbr)

            # Can't use overlap if we haven't computed MBRs

            if mbr is None:

                return keypts

autocnet/graph/network.py

+0 −3
Original line number Diff line number Diff line
@@ -735,7 +735,6 @@ class CandidateGraph(nx.Graph): 
        """

        filelist = []

        for i, node in self.nodes.data('data'):

            print(type(node), node['image_path'])

            filelist.append(node['image_path'])

        return filelist
@@ -1151,8 +1150,6 @@ class CandidateGraph(nx.Graph): 
        Checks if the graph is a complete graph

        """

        neighbors = nx.degree(self)

        print(neighbors)

        print(self.nodes)

        for edge in neighbors:

            if edge == len(self.neighbors(self.nodes)):

                continue

autocnet/io/network.py

+22 −14
Original line number Diff line number Diff line
@@ -48,8 +48,8 @@ def save(network, projectname): 
        js_str = json.dumps(js, cls=NumpyEncoder, sort_keys=True, indent=4)

        pzip.writestr('graph.json', js_str)



        # Write the array node_attributes to hdf

        for n, data in network.nodes_iter(data=True):

        # Write the array node_attributes

        for n, data in network.nodes.data('data'):

            ndarrays_to_write = {}

            for k, v in data.__dict__.items():

                if isinstance(v, np.ndarray):
@@ -64,7 +64,7 @@ def save(network, projectname): 
            os.remove('{}.npz'.format(data['node_id']))



        # Write the array edge attributes to hdf

        for s, d, data in network.edges_iter(data=True):

        for s, d, data in network.edges.data('data'):

            if s > d:

                s, d = d, s

            ndarrays_to_write = {}
@@ -95,7 +95,6 @@ def load(projectname): 
        # Read the graph object

        with pzip.open('graph.json', 'r') as g:

            data = json.loads(g.read().decode(),object_hook=json_numpy_obj_hook)



        cg = autocnet.graph.network.CandidateGraph()

        Edge = autocnet.graph.edge.Edge

        Node = autocnet.graph.node.Node
@@ -103,6 +102,9 @@ def load(projectname): 
        cg.graph = data['graph']

        # Handle nodes

        for d in data['nodes']:

            # Backwards compatible with nx 1.x proj files (64_apollo in examples)

            if 'data' in d.keys():

                d = d['data']

            n = Node()

            for k, v in d.items():

                if k == 'id':
@@ -117,26 +119,32 @@ def load(projectname): 
                pass  # The node does not have features to load.

            cg.add_node(d['node_id'], data=n)





        for e in data['links']:

            cg.add_edge(e['source'], e['target'])

            edge = Edge()

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

            edge.destination = cg.node[e['target']]



            for k, v in e.items():

            s = e['source']

            d = e['target']

            if s > d:

                s,d = d,s

            source = cg.node[s]['data']

            destination = cg.node[d]['data']

            edge = Edge(source, destination)

            # Backwards compatible with nx 1.x proj files (64_apollo in examples)

            if 'data' in e.keys():

                di = e['data']

            else:

                di = e

            # Read the data and populate edge attrs

            for k, v in di.items():

                if k == 'target' or k == 'source':

                    continue

                edge[k] = v



            try:

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

                nzf = np.load(BytesIO(pzip.read('{}_{}.npz'.format(s,d))))

                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.add_edge(e['source'], e['target'] ,data=edge)

            cg.add_edge(s, d, data=edge)



        cg._order_adjacency

    return cg

tests/conftest.py

+1 −1
Original line number Diff line number Diff line
@@ -30,7 +30,7 @@ def candidategraph(): 
                          [True, False]],

                          columns=['rain', 'maker'])



    for s, d, e in cg.edges_iter(data=True):

    for s, d, e in cg.edges.data('data'):

        e['fundamental_matrix'] = np.random.random(size=(3,3))

        e.matches = matches

        e.masks = masks