Added tests for CandidateGraph.add_image() (00850ae7) · Commits · aflab / astrogeology / Autocnet

autocnet/graph/edge.py

+6 −0

Original line number	Diff line number	Diff line
		@@ -555,7 +555,13 @@ class Edge(dict, MutableMapping):
		Estimate a source and destination minimum bounding rectangle, in
		pixel space
		"""
		try:
		self.overlap_latlon_coords, self["source_mbr"], self["destin_mbr"] = self.source.geodata.compute_overlap(self.destination.geodata, **kwargs)
		except Exception as e:
		raise Exception("Overlap between {} and {} could not be "
		"computed: {}".format(self.source['image_name'],
		self.destination['image_name'],
		type(e)))

		def get_matches(self): # pragma: no cover
		if self.matches.empty:

autocnet/graph/network.py

+4 −1

Original line number	Diff line number	Diff line
		@@ -32,6 +32,7 @@ MAXSIZE = {0: None,
		8: 12500,
		12: 15310}


		class CandidateGraph(nx.Graph):
		"""
		A NetworkX derived directed graph to store candidate overlap images.
		@@ -355,6 +356,7 @@ class CandidateGraph(nx.Graph):

		# If a json is supplied, load as dict
		if type(adjacency) is not dict:
		adjacency = os.path.join(basepath, adjacency)
		try:
		assert os.path.exists(adjacency)
		except AssertionError:
		@@ -643,6 +645,8 @@ class CandidateGraph(nx.Graph):
		of keys in graph_masks
		"""
		return_lis = []
		if callable(function):
		function = function.__name__

		for s, d, edge in self.edges_iter(data=True):
		try:
		@@ -656,7 +660,6 @@ class CandidateGraph(nx.Graph):
		if any(return_lis):
		return return_lis


		def apply(self, function, on='edge',out=None, args=(), **kwargs):
		"""
		Applys a function to every node or edge, returns collected return

autocnet/graph/tests/test_network.py

+111 −2

Original line number	Diff line number	Diff line
		@@ -57,8 +57,117 @@ def test_size(graph):


		def test_add_image(graph):
		with pytest.raises(NotImplementedError):
		graph.add_image()
		# apply_funcs
		def extract_and_match(edge):
		for n in [edge.source, edge.destination]:
		n.extract_features(n.get_array(band=1),
		extractor_parameters={'nfeatures': 800})
		edge.match()

		basepath = get_path('Apollo15')
		cube_adjacency = {"AS15-M-0297_crop.cub": ["AS15-M-0298_crop.cub"],
		"AS15-M-0298_crop.cub": ["AS15-M-0297_crop.cub"]}
		cang = network.CandidateGraph.from_adjacency(cube_adjacency, basepath=basepath)

		# Test with all optional args
		cub_img = "AS15-M-0299_crop.cub"
		png_img = "AS15-M-0299_SML.png"
		cub_adj = {cub_img: ["AS15-M-0298_crop.cub", "AS15-M-0297_crop.cub"]}
		png_adj = {png_img: ["AS15-M-0298_crop.cub", "AS15-M-0297_crop.cub"]}
		cang.add_image(cub_img, adjacency=cub_adj, basepath=basepath,
		apply_func=extract_and_match)

		# Assert everything worked properly
		assert cub_img in cang.graph['node_name_map'].keys()
		new_node_idx = cang.graph['node_name_map'][cub_img]
		assert new_node_idx in cang.node.keys()
		assert cang.node[new_node_idx]['image_name'] == cub_img
		assert sorted(cang.nodes()) == [0, 1, 2]
		assert sorted(cang.edges()) == [(0, 1), (0, 2), (1, 2)]
		assert cang[0][2].destination['image_name'] == cang.edge[0][2].destination['image_name'] == cub_img
		assert cang[1][2].destination['image_name'] == cang.edge[1][2].destination['image_name'] == cub_img

		# Test for file not found
		with pytest.raises(FileNotFoundError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, basepath=None)

		# Test with auto-detect adjacency
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, basepath=basepath)

		# Test auto-detect when there are nodes w/ invalid geospacial data
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(png_img, adjacency=png_adj, basepath=basepath) # Invalid
		cang.add_image(cub_img, basepath=basepath) # Autodetect

		# Test auto-detect when new node does not intersect
		# TODO: Need a non-intersecting cube file; network.py, lines 324-325

		# Test when img is already in graph
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image("AS15-M-0297_crop.cub", basepath=basepath)

		# Test when adjacency is of wrong type
		with pytest.raises(TypeError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(png_img, adjacency=1, basepath=basepath) # Invalid

		# Test when loading adjacency from json
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency='cube_adjacency.json', basepath=basepath)
		with pytest.raises(FileNotFoundError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency='null.json',
		basepath=basepath)

		# Test when adjacency doesn't contain image as key
		with pytest.raises(KeyError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency='two_image_adjacency.json',
		basepath=basepath)

		# Test when no adjacency supplied, but image doesn't have footprint;
		# This results in a disconnected node added to the graph
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		edges_bf = cang.edges()
		cang.add_image(png_img, basepath=basepath)
		assert cang.edges() == edges_bf # Assert no change in edges

		# Test when adjacency includes a node not already in the graph
		adj = cub_adj
		adj[cub_img].append("AS15-M-0300_crop.cub")
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency=adj, basepath=basepath)

		# Test when adjacency includes a list of something other than image names
		adj[cub_img].append(1)
		with pytest.raises(TypeError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency=adj, basepath=basepath)

		# Test when apply_func is not a function / list of functions
		with pytest.raises(TypeError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency=cub_adj, basepath=basepath,
		apply_func=1)
		with pytest.raises(TypeError):
		cang = network.CandidateGraph.from_adjacency(cube_adjacency,
		basepath=basepath)
		cang.add_image(cub_img, adjacency=cub_adj, basepath=basepath,
		apply_func=[extract_and_match, 1])


		def test_island_nodes(disconnected_graph):