Loading autocnet/matcher/tests/test_ciratefi.py +139 −129 Changes for autocnet/matcher/tests/test_ciratefi.py: 139 added lines, 129 removed lines. Original line number Diff line number Diff line Loading @@ -11,154 +11,164 @@ from autocnet.examples import get_path from autocnet.matcher import subpixel as sp from .. import ciratefi import pytest # Can be parameterized for more exhaustive tests upsampling = 10 alpha = math.pi/2 cifi_thresh = 90 rafi_thresh = 90 tefi_thresh = 100 use_percentile = True radii = list(range(1, 3)) @pytest.fixture def img(): return imread(get_path('AS15-M-0298_SML.png'), flatten=True) @pytest.fixture def img_coord(): return (482.09783936, 652.40679932) @pytest.fixture def template(img, img_coord): template = sp.clip_roi(img, img_coord, 5) template = rotate(template, 90) template = imresize(template, 1.) return template @pytest.fixture def search(img, img_coord): search = sp.clip_roi(img, img_coord, 21) search = rotate(search, 0) search = imresize(search, 1.) return search @pytest.fixture def offset_template(img, img_coord): offset = (1, 1) offset_template = sp.clip_roi(img, np.add(img_coord, offset), 5) offset_template = rotate(offset_template, 0) offset_template = imresize(offset_template, 1.) return offset_template def test_cifi_radii_too_large(template, search): # check all warnings with pytest.warns(UserWarning): ciratefi.cifi(template, search, 1.0, radii=[100], use_percentile=False) class TestCiratefi(unittest.TestCase): @classmethod def setUpClass(cls): img = imread(get_path('AS15-M-0298_SML.png'), flatten=True) img_coord = (482.09783936, 652.40679932) cls.template = sp.clip_roi(img, img_coord, 5) cls.template = rotate(cls.template, 90) cls.template = imresize(cls.template, 1.) def test_cifi_bounds_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, -1.1, use_percentile=False) cls.search = sp.clip_roi(img, img_coord, 21) cls.search = rotate(cls.search, 0) cls.search = imresize(cls.search, 1.) def test_cifi_radii_none_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, 90, radii=None) cls.offset = (1, 1) def test_cifi_scales_none_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, 90, scales=None) cls.offset_template = sp.clip_roi(img, np.add(img_coord, cls.offset), 5) cls.offset_template = rotate(cls.offset_template, 0) cls.offset_template = imresize(cls.offset_template, 1.) def test_cifi_template_too_large_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(search,template, 90, scales=None) cls.search_center = [math.floor(cls.search.shape[0]/2), math.floor(cls.search.shape[1]/2)] @pytest.mark.parametrize('cifi_thresh, radii', [(90,list(range(1, 3)))]) def test_cifi(template, search, cifi_thresh, radii): pixels, scales = ciratefi.cifi(template, search, thresh=cifi_thresh, radii=radii, use_percentile=True) cls.upsampling = 10 cls.alpha = math.pi/2 cls.cifi_thresh = 90 cls.rafi_thresh = 90 cls.tefi_thresh = 100 cls.use_percentile = True cls.radii = list(range(1, 3)) assert search.shape == scales.shape assert (np.floor(search.shape[0]/2), np.floor(search.shape[1]/2)) in pixels assert pixels.size in range(0,search.size) cls.cifi_number_of_warnings = 2 cls.rafi_number_of_warnings = 2 def test_cifi(self): # check all warnings with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") ciratefi.cifi(self.template, self.search, 1.0, radii=[100], use_percentile=False) self.assertEqual(len(w), self.cifi_number_of_warnings) # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, -1.1, use_percentile=False) # radii list empty/none error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, radii=None) # scales list empty/none error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, scales=None) # template is bigger than search error self.assertRaises(ValueError, ciratefi.cifi, self.search, self.template, -1.1, use_percentile=False) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") pixels, scales = ciratefi.cifi(self.template, self.search, thresh=self.cifi_thresh, radii=self.radii, use_percentile=True) self.assertEqual(len(w), 0) self.assertEqual(self.search.shape, scales.shape) self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels) self.assertTrue(pixels.size in range(0, self.search.size)) def test_rafi(self): def test_rafi_warning(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(self.search.shape, dtype=float) # check all warnings with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") ciratefi.rafi(self.template, self.search, rafi_pixels, rafi_scales = np.ones(search.shape, dtype=float) with pytest.warns(UserWarning): ciratefi.rafi(template, search, rafi_pixels, rafi_scales, thresh=1, radii=[100], use_percentile=False) self.assertEqual(len(w), self.rafi_number_of_warnings) # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales, -1.1, use_percentile=False) # Radii list is empty.None error self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, -1.1, radii=None) # candidate pixel list empty/none error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, [], rafi_scales) # scales list empty/none error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, None) # template is bigger than search error self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, rafi_scales) # best scale nd array is not equal image shape self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales[:10]) with warnings.catch_warnings(record=True) as w: pixels, scales = ciratefi.rafi(self.template, self.search, rafi_pixels, rafi_scales, thresh=self.rafi_thresh, radii=self.radii, use_percentile=True, alpha=self.alpha) self.assertEqual(len(w), 0) self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels) self.assertTrue(pixels.size in range(0, self.search.size)) def test_tefi(self): tefi_pixels = [(10, 10)] tefi_scales = np.ones(self.search.shape, dtype=float) tefi_angles = [3.14159265] # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales, tefi_angles, thresh=-1.1, use_percentile=False, alpha=self.alpha) def test_rafi_bounds_error(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales, -1.1, use_percentile=False) # angle list is empty/None error self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, None) # candidate pixel list empty/none error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, None, tefi_scales, tefi_angles) # scales list empty/none error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, None, tefi_angles) # template is bigger than search error self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, -1.1) # best scale nd array is smaller than number of candidate pixels self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales[:10], -1.1) def test_rafi_radii_list_none_error(template, search): rafi_pixels = [(10, 10)] with pytest.raises(ValueError): ciratefi.rafi(search, template, rafi_pixels, -1.1, radii=None) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") pixel = ciratefi.tefi(self.template, self.search, tefi_pixels, tefi_scales, tefi_angles, thresh=self.tefi_thresh, use_percentile=True, alpha=self.alpha, upsampling=self.upsampling) def test_rafi_pixel_list_error(template, search): rafi_pixels = [] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales) for warn in w: print(warn) def test_rafi_scales_list_error(template, search): rafi_pixels = [(10, 10)] with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, None) self.assertEqual(len(w), 0) print(pixel) self.assertTrue(np.equal((.5, .5), (pixel[1], pixel[0])).all()) def test_rafi_template_bigger_error(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(search, template, rafi_pixels,rafi_scales) def test_ciratefi(self): results = ciratefi.ciratefi(self.template, self.search, upsampling=10, cifi_thresh=self.cifi_thresh, rafi_thresh=self.rafi_thresh, tefi_thresh=self.tefi_thresh, use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii) def test_rafi_shape_mismatch(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float)[:10] with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales) self.assertEqual(len(results), 3) self.assertTrue((np.array(results[1], results[0]) < 1).all()) @pytest.mark.parametrize("rafi_thresh, radii, alpha", [(90, list(range(1, 3)),math.pi/2)]) def test_rafi(template, search, rafi_thresh, radii, alpha): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) pixels, scales = ciratefi.rafi(template, search, rafi_pixels, rafi_scales, thresh=rafi_thresh, radii=radii, use_percentile=True, alpha=alpha) assert (np.floor(search.shape[0]/2), np.floor(search.shape[1]/2)) in pixels assert pixels.size in range(0, search.size) # Alternate approach to the more verbose tests above - this tests all combinations @pytest.mark.parametrize("tefi_pixels", [[(10,10)], None]) @pytest.mark.parametrize("tefi_scales", [np.ones(search(img(), img_coord()).shape, dtype=float), None, np.ones(search(img(), img_coord()).shape, dtype=float)[:10]]) @pytest.mark.parametrize("tefi_angles", [[3.14159265], None]) @pytest.mark.parametrize("thresh", [-1.1, 90]) @pytest.mark.parametrize("reverse", [False, True]) def test_tefi_errors(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh, reverse): with pytest.raises(ValueError): if reverse: template, search = search, template ciratefi.tefi(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh=-1.1, use_percentile=False, alpha=math.pi/2) def test_tefi(template, search): tefi_pixels = [(10, 10)] tefi_scales = np.ones(search.shape, dtype=float) tefi_angles = [3.14159265] results = ciratefi.ciratefi(self.offset_template, self.search, upsampling=self.upsampling, cifi_thresh=self.cifi_thresh, rafi_thresh=self.rafi_thresh, tefi_thresh=self.tefi_thresh, use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii) pixel = ciratefi.tefi(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh=tefi_thresh, use_percentile=True, alpha=math.pi/2, upsampling=10) assert np.equal((.5, .5), (pixel[1], pixel[0])).all() @pytest.mark.parametrize("cifi_thresh, rafi_thresh, tefi_thresh, alpha, radii",[(90,90,100,math.pi/2,list(range(1, 3)))]) def test_ciratefi(template, search, cifi_thresh, rafi_thresh, tefi_thresh, alpha, radii): results = ciratefi.ciratefi(template, search, upsampling=10, cifi_thresh=cifi_thresh, rafi_thresh=rafi_thresh, tefi_thresh=tefi_thresh, use_percentile=True, alpha=alpha, radii=radii) def tearDown(self): pass assert len(results) == 3 assert (np.array(results[1], results[0]) < 1).all() autocnet/matcher/tests/test_matcher.py +7 −7 Changes for autocnet/matcher/tests/test_matcher.py: 7 added lines, 7 removed lines. Original line number Diff line number Diff line Loading @@ -52,37 +52,37 @@ class TestMatcher(unittest.TestCase): edges = list() from autocnet.matcher.cpu_matcher import match as match for s, d in cang.edges(): cang[s][d]._match = match cang[s][d]['data']._match = match edges.append(cang[s][d]) # Assert none of the edges have masks yet for edge in edges: self.assertTrue(edge.masks.empty) self.assertTrue(edge['data'].masks.empty) # Match & outlier detect cang.match() cang.symmetry_checks() # Grab the length of a matches df match_len = len(edges[0].matches.index) match_len = len(edges[0]['data'].matches.index) # Assert symmetry check is now in all edge masks for edge in edges: self.assertTrue('symmetry' in edge.masks) self.assertTrue('symmetry' in edge['data'].masks) # Assert matches have been populated for edge in edges: self.assertTrue(not edge.matches.empty) self.assertTrue(not edge['data'].matches.empty) # Re-match cang.match() # Assert that new matches have been added on to old ones self.assertEqual(len(edges[0].matches.index), match_len * 2) self.assertEqual(len(edges[0]['data'].matches.index), match_len * 2) # Assert that the match cleared the masks df for edge in edges: self.assertTrue(edge.masks.empty) self.assertTrue(edge['data'].masks.empty) def tearDown(self): Loading bin/image_match.py +2 −2 Changes for bin/image_match.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -8,8 +8,8 @@ sys.path.insert(0, os.path.abspath('../autocnet')) from autocnet.utils.utils import find_in_dict from autocnet.graph.network import CandidateGraph from autocnet.fileio.io_controlnetwork import to_isis, write_filelist from autocnet.fileio.io_yaml import read_yaml #from autocnet.fileio.io_controlnetwork import to_isis, write_filelist #from autocnet.fileio.io_yaml import read_yaml def parse_arguments(): Loading Loading
autocnet/matcher/tests/test_ciratefi.py +139 −129 Changes for autocnet/matcher/tests/test_ciratefi.py: 139 added lines, 129 removed lines. Original line number Diff line number Diff line Loading @@ -11,154 +11,164 @@ from autocnet.examples import get_path from autocnet.matcher import subpixel as sp from .. import ciratefi import pytest # Can be parameterized for more exhaustive tests upsampling = 10 alpha = math.pi/2 cifi_thresh = 90 rafi_thresh = 90 tefi_thresh = 100 use_percentile = True radii = list(range(1, 3)) @pytest.fixture def img(): return imread(get_path('AS15-M-0298_SML.png'), flatten=True) @pytest.fixture def img_coord(): return (482.09783936, 652.40679932) @pytest.fixture def template(img, img_coord): template = sp.clip_roi(img, img_coord, 5) template = rotate(template, 90) template = imresize(template, 1.) return template @pytest.fixture def search(img, img_coord): search = sp.clip_roi(img, img_coord, 21) search = rotate(search, 0) search = imresize(search, 1.) return search @pytest.fixture def offset_template(img, img_coord): offset = (1, 1) offset_template = sp.clip_roi(img, np.add(img_coord, offset), 5) offset_template = rotate(offset_template, 0) offset_template = imresize(offset_template, 1.) return offset_template def test_cifi_radii_too_large(template, search): # check all warnings with pytest.warns(UserWarning): ciratefi.cifi(template, search, 1.0, radii=[100], use_percentile=False) class TestCiratefi(unittest.TestCase): @classmethod def setUpClass(cls): img = imread(get_path('AS15-M-0298_SML.png'), flatten=True) img_coord = (482.09783936, 652.40679932) cls.template = sp.clip_roi(img, img_coord, 5) cls.template = rotate(cls.template, 90) cls.template = imresize(cls.template, 1.) def test_cifi_bounds_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, -1.1, use_percentile=False) cls.search = sp.clip_roi(img, img_coord, 21) cls.search = rotate(cls.search, 0) cls.search = imresize(cls.search, 1.) def test_cifi_radii_none_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, 90, radii=None) cls.offset = (1, 1) def test_cifi_scales_none_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(template, search, 90, scales=None) cls.offset_template = sp.clip_roi(img, np.add(img_coord, cls.offset), 5) cls.offset_template = rotate(cls.offset_template, 0) cls.offset_template = imresize(cls.offset_template, 1.) def test_cifi_template_too_large_error(template, search): with pytest.raises(ValueError): ciratefi.cifi(search,template, 90, scales=None) cls.search_center = [math.floor(cls.search.shape[0]/2), math.floor(cls.search.shape[1]/2)] @pytest.mark.parametrize('cifi_thresh, radii', [(90,list(range(1, 3)))]) def test_cifi(template, search, cifi_thresh, radii): pixels, scales = ciratefi.cifi(template, search, thresh=cifi_thresh, radii=radii, use_percentile=True) cls.upsampling = 10 cls.alpha = math.pi/2 cls.cifi_thresh = 90 cls.rafi_thresh = 90 cls.tefi_thresh = 100 cls.use_percentile = True cls.radii = list(range(1, 3)) assert search.shape == scales.shape assert (np.floor(search.shape[0]/2), np.floor(search.shape[1]/2)) in pixels assert pixels.size in range(0,search.size) cls.cifi_number_of_warnings = 2 cls.rafi_number_of_warnings = 2 def test_cifi(self): # check all warnings with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") ciratefi.cifi(self.template, self.search, 1.0, radii=[100], use_percentile=False) self.assertEqual(len(w), self.cifi_number_of_warnings) # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, -1.1, use_percentile=False) # radii list empty/none error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, radii=None) # scales list empty/none error self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, scales=None) # template is bigger than search error self.assertRaises(ValueError, ciratefi.cifi, self.search, self.template, -1.1, use_percentile=False) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") pixels, scales = ciratefi.cifi(self.template, self.search, thresh=self.cifi_thresh, radii=self.radii, use_percentile=True) self.assertEqual(len(w), 0) self.assertEqual(self.search.shape, scales.shape) self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels) self.assertTrue(pixels.size in range(0, self.search.size)) def test_rafi(self): def test_rafi_warning(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(self.search.shape, dtype=float) # check all warnings with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") ciratefi.rafi(self.template, self.search, rafi_pixels, rafi_scales = np.ones(search.shape, dtype=float) with pytest.warns(UserWarning): ciratefi.rafi(template, search, rafi_pixels, rafi_scales, thresh=1, radii=[100], use_percentile=False) self.assertEqual(len(w), self.rafi_number_of_warnings) # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales, -1.1, use_percentile=False) # Radii list is empty.None error self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, -1.1, radii=None) # candidate pixel list empty/none error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, [], rafi_scales) # scales list empty/none error self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, None) # template is bigger than search error self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, rafi_scales) # best scale nd array is not equal image shape self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales[:10]) with warnings.catch_warnings(record=True) as w: pixels, scales = ciratefi.rafi(self.template, self.search, rafi_pixels, rafi_scales, thresh=self.rafi_thresh, radii=self.radii, use_percentile=True, alpha=self.alpha) self.assertEqual(len(w), 0) self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels) self.assertTrue(pixels.size in range(0, self.search.size)) def test_tefi(self): tefi_pixels = [(10, 10)] tefi_scales = np.ones(self.search.shape, dtype=float) tefi_angles = [3.14159265] # Threshold out of bounds error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales, tefi_angles, thresh=-1.1, use_percentile=False, alpha=self.alpha) def test_rafi_bounds_error(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales, -1.1, use_percentile=False) # angle list is empty/None error self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, None) # candidate pixel list empty/none error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, None, tefi_scales, tefi_angles) # scales list empty/none error self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, None, tefi_angles) # template is bigger than search error self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, -1.1) # best scale nd array is smaller than number of candidate pixels self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales[:10], -1.1) def test_rafi_radii_list_none_error(template, search): rafi_pixels = [(10, 10)] with pytest.raises(ValueError): ciratefi.rafi(search, template, rafi_pixels, -1.1, radii=None) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") pixel = ciratefi.tefi(self.template, self.search, tefi_pixels, tefi_scales, tefi_angles, thresh=self.tefi_thresh, use_percentile=True, alpha=self.alpha, upsampling=self.upsampling) def test_rafi_pixel_list_error(template, search): rafi_pixels = [] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales) for warn in w: print(warn) def test_rafi_scales_list_error(template, search): rafi_pixels = [(10, 10)] with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, None) self.assertEqual(len(w), 0) print(pixel) self.assertTrue(np.equal((.5, .5), (pixel[1], pixel[0])).all()) def test_rafi_template_bigger_error(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) with pytest.raises(ValueError): ciratefi.rafi(search, template, rafi_pixels,rafi_scales) def test_ciratefi(self): results = ciratefi.ciratefi(self.template, self.search, upsampling=10, cifi_thresh=self.cifi_thresh, rafi_thresh=self.rafi_thresh, tefi_thresh=self.tefi_thresh, use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii) def test_rafi_shape_mismatch(template, search): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float)[:10] with pytest.raises(ValueError): ciratefi.rafi(template, search, rafi_pixels, rafi_scales) self.assertEqual(len(results), 3) self.assertTrue((np.array(results[1], results[0]) < 1).all()) @pytest.mark.parametrize("rafi_thresh, radii, alpha", [(90, list(range(1, 3)),math.pi/2)]) def test_rafi(template, search, rafi_thresh, radii, alpha): rafi_pixels = [(10, 10)] rafi_scales = np.ones(search.shape, dtype=float) pixels, scales = ciratefi.rafi(template, search, rafi_pixels, rafi_scales, thresh=rafi_thresh, radii=radii, use_percentile=True, alpha=alpha) assert (np.floor(search.shape[0]/2), np.floor(search.shape[1]/2)) in pixels assert pixels.size in range(0, search.size) # Alternate approach to the more verbose tests above - this tests all combinations @pytest.mark.parametrize("tefi_pixels", [[(10,10)], None]) @pytest.mark.parametrize("tefi_scales", [np.ones(search(img(), img_coord()).shape, dtype=float), None, np.ones(search(img(), img_coord()).shape, dtype=float)[:10]]) @pytest.mark.parametrize("tefi_angles", [[3.14159265], None]) @pytest.mark.parametrize("thresh", [-1.1, 90]) @pytest.mark.parametrize("reverse", [False, True]) def test_tefi_errors(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh, reverse): with pytest.raises(ValueError): if reverse: template, search = search, template ciratefi.tefi(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh=-1.1, use_percentile=False, alpha=math.pi/2) def test_tefi(template, search): tefi_pixels = [(10, 10)] tefi_scales = np.ones(search.shape, dtype=float) tefi_angles = [3.14159265] results = ciratefi.ciratefi(self.offset_template, self.search, upsampling=self.upsampling, cifi_thresh=self.cifi_thresh, rafi_thresh=self.rafi_thresh, tefi_thresh=self.tefi_thresh, use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii) pixel = ciratefi.tefi(template, search, tefi_pixels, tefi_scales, tefi_angles, thresh=tefi_thresh, use_percentile=True, alpha=math.pi/2, upsampling=10) assert np.equal((.5, .5), (pixel[1], pixel[0])).all() @pytest.mark.parametrize("cifi_thresh, rafi_thresh, tefi_thresh, alpha, radii",[(90,90,100,math.pi/2,list(range(1, 3)))]) def test_ciratefi(template, search, cifi_thresh, rafi_thresh, tefi_thresh, alpha, radii): results = ciratefi.ciratefi(template, search, upsampling=10, cifi_thresh=cifi_thresh, rafi_thresh=rafi_thresh, tefi_thresh=tefi_thresh, use_percentile=True, alpha=alpha, radii=radii) def tearDown(self): pass assert len(results) == 3 assert (np.array(results[1], results[0]) < 1).all()
autocnet/matcher/tests/test_matcher.py +7 −7 Changes for autocnet/matcher/tests/test_matcher.py: 7 added lines, 7 removed lines. Original line number Diff line number Diff line Loading @@ -52,37 +52,37 @@ class TestMatcher(unittest.TestCase): edges = list() from autocnet.matcher.cpu_matcher import match as match for s, d in cang.edges(): cang[s][d]._match = match cang[s][d]['data']._match = match edges.append(cang[s][d]) # Assert none of the edges have masks yet for edge in edges: self.assertTrue(edge.masks.empty) self.assertTrue(edge['data'].masks.empty) # Match & outlier detect cang.match() cang.symmetry_checks() # Grab the length of a matches df match_len = len(edges[0].matches.index) match_len = len(edges[0]['data'].matches.index) # Assert symmetry check is now in all edge masks for edge in edges: self.assertTrue('symmetry' in edge.masks) self.assertTrue('symmetry' in edge['data'].masks) # Assert matches have been populated for edge in edges: self.assertTrue(not edge.matches.empty) self.assertTrue(not edge['data'].matches.empty) # Re-match cang.match() # Assert that new matches have been added on to old ones self.assertEqual(len(edges[0].matches.index), match_len * 2) self.assertEqual(len(edges[0]['data'].matches.index), match_len * 2) # Assert that the match cleared the masks df for edge in edges: self.assertTrue(edge.masks.empty) self.assertTrue(edge['data'].masks.empty) def tearDown(self): Loading
bin/image_match.py +2 −2 Changes for bin/image_match.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -8,8 +8,8 @@ sys.path.insert(0, os.path.abspath('../autocnet')) from autocnet.utils.utils import find_in_dict from autocnet.graph.network import CandidateGraph from autocnet.fileio.io_controlnetwork import to_isis, write_filelist from autocnet.fileio.io_yaml import read_yaml #from autocnet.fileio.io_controlnetwork import to_isis, write_filelist #from autocnet.fileio.io_yaml import read_yaml def parse_arguments(): Loading
