Fixed merge conflicts. (694bc014) · Commits · aflab / astrogeology / Autocnet

autocnet/graph/node.py

+1 −2

Original line number	Diff line number	Diff line
		@@ -7,10 +7,9 @@ import numpy as np
		import pandas as pd
		from plio.io.io_gdal import GeoDataset
		from plio.io.isis_serial_number import generate_serial_number
		from scipy.misc import bytescale
		from scipy.misc import bytescale, imresize
		from shapely.geometry import Polygon


		from autocnet.cg import cg
		from autocnet.control.control import Correspondence, Point

autocnet/graph/tests/test_edge.py

+2 −126

Original line number	Diff line number	Diff line
		@@ -61,11 +61,8 @@ class TestEdge(unittest.TestCase):
		[0, 3, 1, 3],
		[0, 4, 1, 4]]

		<<<<<<< HEAD
		matches_df = pd.DataFrame(data=keypoint_matches, columns=['source_image', 'source_idx', 'destination_image', 'destination_idx'])
		=======
		matches_df = pd.DataFrame(keypoint_matches, columns = ['source_image', 'source_idx', 'destination_image', 'destination_idx'])
		>>>>>>> 1788194d709d73bf22d843752991d8c6dad9f87a

		e = edge.Edge()
		source_node = MagicMock(spec=node.Node())
		destination_node = MagicMock(spec=node.Node())
		@@ -108,7 +105,6 @@ class TestEdge(unittest.TestCase):
		#self.assertRaises(AttributeError, cg.edge[0][1].coverage)
		self.assertEqual(e.coverage(), 0.3)

		<<<<<<< HEAD
		def test_get_keypoints(self):
		src_keypoint_df = pd.DataFrame({'x': (0, 1, 2, 3, 4), 'y': (5, 6, 7, 8, 9),
		'response': (10, 11, 12, 13, 14), 'size': (15, 16, 17, 18, 19),
		@@ -135,33 +131,11 @@ class TestEdge(unittest.TestCase):

		source_node.get_keypoints = MagicMock(return_value=src_keypoint_df)
		destination_node.get_keypoints = MagicMock(return_value=dst_keypoint_df)
		=======
		def test_voronoi_transform(self):
		keypoint_df = pd.DataFrame({'x': (15, 18, 18, 12, 12), 'y': (5, 10, 15, 15, 10)})
		keypoint_matches = [[0, 0, 1, 0],
		[0, 1, 1, 1],
		[0, 2, 1, 2],
		[0, 3, 1, 3],
		[0, 4, 1, 4]]

		matches_df = pd.DataFrame(data=keypoint_matches, columns=['source_image', 'source_idx',
		'destination_image', 'destination_idx'])
		e = edge.Edge()

		e.clean = MagicMock(return_value=(matches_df, None))
		e.matches = matches_df

		source_node = MagicMock(spec=node.Node())
		destination_node = MagicMock(spec=node.Node())

		source_node.get_keypoint_coordinates = MagicMock(return_value=keypoint_df)
		destination_node.get_keypoint_coordinates = MagicMock(return_value=keypoint_df)
		>>>>>>> 1788194d709d73bf22d843752991d8c6dad9f87a

		e.source = source_node
		e.destination = destination_node

		<<<<<<< HEAD

		e.clean = MagicMock(return_value=(matches_df, None))
		e.matches = matches_df

		@@ -203,104 +177,6 @@ class TestEdge(unittest.TestCase):
		# Check key error thrown when string arg != "source" or "destination"
		with self.assertRaises(KeyError):
		e.get_keypoints("string", clean_keys)
		=======
		source_geodata = Mock(spec=io_gdal.GeoDataset)
		destination_geodata = Mock(spec=io_gdal.GeoDataset)

		e.source.geodata = source_geodata
		e.destination.geodata = destination_geodata

		source_corners = [(0, 0),
		(20, 0),
		(20, 20),
		(0, 20)]

		destination_corners = [(10, 5),
		(30, 5),
		(30, 25),
		(10, 25)]

		source_poly = array_to_poly(source_corners)
		destination_poly = array_to_poly(destination_corners)

		def latlon_to_pixel(i, j):
		return vals[(i, j)]

		e.source.geodata.latlon_to_pixel = MagicMock(side_effect=latlon_to_pixel)
		e.destination.geodata.latlon_to_pixel = MagicMock(side_effect=latlon_to_pixel)

		e.source.geodata.footprint = source_poly
		e.source.geodata.xy_corners = source_corners
		e.destination.geodata.footprint = destination_poly
		e.destination.geodata.xy_corners = destination_corners

		vals = {(10, 5): (10, 5), (20, 5): (20, 5), (20, 20): (20, 20), (10, 20): (10, 20)}

		weights = pd.DataFrame({"vor_weights": (19, 28, 37.5, 37.5, 28)})

		e.compute_weights(clean_keys=[])

		k = 0
		for i in e.matches['vor_weights']:
		self.assertAlmostEquals(i, weights['vor_weights'][k])
		k += 1

		def test_voronoi_homography(self):
		source_keypoint_df = pd.DataFrame({'x': (15, 18, 18, 12, 12), 'y': (5, 10, 15, 15, 10)})
		destination_keypoint_df = pd.DataFrame({'x': (5, 8, 8, 2, 2), 'y': (0, 5, 10, 10, 5)})
		keypoint_matches = [[0, 0, 1, 0],
		[0, 1, 1, 1],
		[0, 2, 1, 2],
		[0, 3, 1, 3],
		[0, 4, 1, 4]]

		matches_df = pd.DataFrame(data = keypoint_matches, columns=['source_image', 'source_idx',
		'destination_image', 'destination_idx'])
		e = edge.Edge()

		e.clean = MagicMock(return_value=(matches_df, None))
		e.matches = matches_df

		source_node = MagicMock(spec=node.Node())
		destination_node = MagicMock(spec=node.Node())

		source_node.get_keypoint_coordinates = MagicMock(return_value=source_keypoint_df)
		destination_node.get_keypoint_coordinates = MagicMock(return_value=destination_keypoint_df)

		e.source = source_node
		e.destination = destination_node

		source_geodata = Mock(spec=io_gdal.GeoDataset)
		destination_geodata = Mock(spec=io_gdal.GeoDataset)

		e.source.geodata = source_geodata
		e.destination.geodata = destination_geodata

		source_corners = [(0, 0),
		(20, 0),
		(20, 20),
		(0, 20)]

		destination_corners = [(0, 0),
		(20, 0),
		(20, 20),
		(0, 20)]

		e.source.geodata.coordinate_transformation.this = None
		e.destination.geodata.coordinate_transformation.this = None

		e.source.geodata.xy_corners = source_corners
		e.destination.geodata.xy_corners = destination_corners

		weights = pd.DataFrame({"vor_weights": (19, 28, 37.5, 37.5, 28)})

		e.compute_weights(clean_keys=[])

		k = 0
		for i in e.matches['vor_weights']:
		self.assertAlmostEquals(i, weights['vor_weights'][k])
		k += 1
		>>>>>>> 1788194d709d73bf22d843752991d8c6dad9f87a

		def test_eq(self):
		edge1 = edge.Edge()

autocnet/graph/tests/test_network.py

+3 −21

Original line number	Diff line number	Diff line
		@@ -71,25 +71,7 @@ def test_connected_subgraphs(graph, disconnected_graph):
		subgraph_list = graph.connected_subgraphs()
		assert len(subgraph_list) == 1

		<<<<<<< HEAD

		def test_save_load_features(tmpdir, graph):
		# Create the graph and save the features
		graph = graph.copy()
		graph.extract_features(extractor_parameters={'nfeatures': 10})
		allout = tmpdir.join("all_out.hdf")
		oneout = tmpdir.join("one_out.hdf")

		graph.save_features(allout.strpath, format='hdf')
		graph.save_features(oneout.strpath, nodes=[1], format='hdf')

		graph_no_features = graph.copy()
		graph_no_features.load_features(allout.strpath, nodes=[1], format='hdf')
		assert graph.node[1].get_keypoints().all().all() == graph_no_features.node[1].get_keypoints().all().all()


		=======
		>>>>>>> 1788194d709d73bf22d843752991d8c6dad9f87a
		def test_filter(graph):
		graph = graph.copy()
		test_sub_graph = graph.create_node_subgraph([0, 1])
		@@ -184,7 +166,6 @@ def test_apply_func_to_edges(graph):
		assert not graph[0][2].masks['symmetry'].all()
		assert not graph[0][1].masks['symmetry'].all()

		<<<<<<< HEAD

		def test_intersection():
		# Generate the footprints for the mock nodes
		@@ -248,7 +229,8 @@ def test_intersection():
		assert intersect_gdf.geometry[4].area == 21.25
		# Check if the correct poly was determined to overlap all other images
		assert intersect_gdf.overlaps_all[4] == True
		=======


		def test_set_maxsize(graph):
		maxsizes = network.MAXSIZE
		assert(graph.maxsize == maxsizes[0])
		@@ -264,4 +246,4 @@ def test_update_data(graph):
		graph._update_date()
		ntime = graph.graph['modifieddate']
		assert ctime != ntime
		>>>>>>> 1788194d709d73bf22d843752991d8c6dad9f87a

autocnet/graph/tests/test_node.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -9,6 +9,7 @@ import numpy as np
		import pandas as pd
		import pytest


		from autocnet.examples import get_path
		from plio.io.io_gdal import GeoDataset