update from upstream (b7a8c530) · Commits · aflab / astrogeology / Autocnet

autocnet/matcher/outlier_detector.py

+13 −8

Original line number	Original line	Diff line number	Diff line
	@@ -138,7 +138,7 @@ class SpatialSuppression(Observable):

	"""		"""

	def __init__(self, df, domain, min_radius=1, k=250, error_k=0.1):		def __init__(self, df, domain, min_radius=1.5, k=250, error_k=0.1):
	columns = df.columns		columns = df.columns
	for i in ['x', 'y', 'strength']:		for i in ['x', 'y', 'strength']:
	if i not in columns:		if i not in columns:
	@@ -182,14 +182,13 @@ class SpatialSuppression(Observable):
	self.k = len(self.df)		self.k = len(self.df)
	result = self.df.index		result = self.df.index
	process = False		process = False
	search_space = np.linspace(self.min_radius, self.max_radius / 16, 250)		search_space = np.linspace(self.min_radius, self.max_radius, 100)
	cell_sizes = (search_space / math.sqrt(2)).astype(np.int)		cell_sizes = search_space / math.sqrt(2)
	min_idx = 0		min_idx = 0
	max_idx = len(search_space) - 1		max_idx = len(search_space) - 1

	while process:		while process:
	mid_idx = int((min_idx + max_idx) / 2)		mid_idx = int((min_idx + max_idx) / 2)
	r = search_space[mid_idx]

	cell_size = cell_sizes[mid_idx]		cell_size = cell_sizes[mid_idx]
	n_x_cells = int(self.domain[0] / cell_size)		n_x_cells = int(self.domain[0] / cell_size)
	@@ -222,19 +221,19 @@ class SpatialSuppression(Observable):
	min_idx = mid_idx		min_idx = mid_idx
	break		break

	y_min = y_center - 5		y_min = y_center - int(round(cell_size, 0))
	if y_min < 0:		if y_min < 0:
	y_min = 0		y_min = 0

	x_min = x_center - 5		x_min = x_center - int(round(cell_size, 0))
	if x_min < 0:		if x_min < 0:
	x_min = 0		x_min = 0

	y_max = y_center + 5		y_max = y_center + int(round(cell_size, 0))
	if y_max > grid.shape[0]:		if y_max > grid.shape[0]:
	y_max = grid.shape[0]		y_max = grid.shape[0]

	x_max = x_center + 5		x_max = x_center + int(round(cell_size, 0))
	if x_max > grid.shape[1]:		if x_max > grid.shape[1]:
	x_max = grid.shape[1]		x_max = grid.shape[1]

	@@ -242,18 +241,24 @@ class SpatialSuppression(Observable):
	grid[y_min: y_max,		grid[y_min: y_max,
	x_min: x_max] = True		x_min: x_max] = True


	# Check break conditions		# Check break conditions
	if self.k - self.k * self.error_k <= len(result) <= self.k + self.k * self.error_k:		if self.k - self.k * self.error_k <= len(result) <= self.k + self.k * self.error_k:
	process = False		process = False
	elif len(result) < self.k:		elif len(result) < self.k:
	# The radius is too large		# The radius is too large
	max_idx = mid_idx		max_idx = mid_idx
			if max_idx == 0:
			warnings.warn('Unable to retrieve {} points. Consider reducing the amount of points you request(k)'
			.format(self.k))
			process = False
	if min_idx == max_idx:		if min_idx == max_idx:
	process = False		process = False
	elif min_idx == mid_idx or mid_idx == max_idx:		elif min_idx == mid_idx or mid_idx == max_idx:
	warnings.warn('Unable to optimally solve. Returning with {} points'.format(len(result)))		warnings.warn('Unable to optimally solve. Returning with {} points'.format(len(result)))
	process = False		process = False

			self.mask = pd.Series(False, self.df.index)
	self.mask.loc[list(result)] = True		self.mask.loc[list(result)] = True
	state_package = {'mask': self.mask,		state_package = {'mask': self.mask,
	'k': self.k,		'k': self.k,

autocnet/matcher/tests/test_outlier_detector.py

+37 −3

Original line number	Original line	Diff line number	Diff line
	@@ -6,11 +6,11 @@ import warnings
	import numpy as np		import numpy as np
	import pandas as pd		import pandas as pd

	from .. import outlier_detector		from .. import matcher, outlier_detector
			from autocnet.matcher.outlier_detector import SpatialSuppression

	sys.path.append(os.path.abspath('..'))		sys.path.append(os.path.abspath('..'))


	class TestOutlierDetector(unittest.TestCase):		class TestOutlierDetector(unittest.TestCase):

	def test_distance_ratio(self):		def test_distance_ratio(self):
	@@ -91,7 +91,7 @@ class TestSpatialSuppression(unittest.TestCase):
	def test_suppress(self):		def test_suppress(self):
	self.suppression_obj.k = 30		self.suppression_obj.k = 30
	self.suppression_obj.suppress()		self.suppression_obj.suppress()
	self.assertIn(self.suppression_obj.mask.sum(), list(range(27, 34)))		self.assertIn(self.suppression_obj.mask.sum(), list(range(27, 35)))

	with warnings.catch_warnings(record=True) as w:		with warnings.catch_warnings(record=True) as w:
	self.suppression_obj.k = 101		self.suppression_obj.k = 101
	@@ -99,3 +99,37 @@ class TestSpatialSuppression(unittest.TestCase):
	self.assertEqual(len(w), 1)		self.assertEqual(len(w), 1)
	self.assertTrue(issubclass(w[0].category, UserWarning))		self.assertTrue(issubclass(w[0].category, UserWarning))

			class testSuppressionRanges(unittest.TestCase):

			@classmethod
			def setUpClass(cls):
			cls.r = np.random.RandomState(12345)

			def test_one_by_one(self):
			df = pd.DataFrame(self.r.uniform(0,1,(500, 3)), columns=['x', 'y', 'strength'])
			sup = SpatialSuppression(df, (1,1), k = 1)
			self.assertRaises(ValueError, sup.suppress())

			def test_min_max(self):
			df = pd.DataFrame(self.r.uniform(0,2,(500, 3)), columns=['x', 'y', 'strength'])
			sup = SpatialSuppression(df, (1.5,1.5), k = 1)
			sup.suppress()
			self.assertEqual(len(df[sup.mask]), 1)

			def test_point_overload(self):
			df = pd.DataFrame(self.r.uniform(0,15,(500, 3)), columns=['x', 'y', 'strength'])
			sup = SpatialSuppression(df, (15,15), k = 200)
			sup.suppress()
			self.assertEqual(len(df[sup.mask]), 70)

			def test_small_distribution(self):
			df = pd.DataFrame(self.r.uniform(0,25,(500, 3)), columns=['x', 'y', 'strength'])
			sup = SpatialSuppression(df, (25,25), k = 25)
			sup.suppress()
			self.assertEqual(len(df[sup.mask]), 28)

			def test_normal_distribution(self):
			df = pd.DataFrame(self.r.uniform(0,100,(500, 3)), columns=['x', 'y', 'strength'])
			sup = SpatialSuppression(df, (100,100), k = 15)
			sup.suppress()
			self.assertEqual(len(df[sup.mask]), 17)

autocnet/vis/graph_view.py

+3 −3

Original line number	Original line	Diff line number	Diff line
	@@ -164,8 +164,8 @@ def plot_edge(edge, ax=None, clean_keys=[], image_space=100,
	x = s_shape[1] + d_shape[1] + image_space		x = s_shape[1] + d_shape[1] + image_space
	composite = np.zeros((y, x))		composite = np.zeros((y, x))

	composite[:, :s_shape[1]] = source_array		composite[0: s_shape[0], :s_shape[1]] = source_array
	composite[:, s_shape[1] + image_space:] = destination_array		composite[0: d_shape[0], s_shape[1] + image_space:] = destination_array

	if 'cmap' in image_kwargs:		if 'cmap' in image_kwargs:
	cmap = image_kwargs['cmap']		cmap = image_kwargs['cmap']
	@@ -187,7 +187,7 @@ def plot_edge(edge, ax=None, clean_keys=[], image_space=100,
	# Plot the destination		# Plot the destination
	destination_idx = matches['destination_idx'].values		destination_idx = matches['destination_idx'].values
	d_kps = destination_keypoints.loc[destination_idx]		d_kps = destination_keypoints.loc[destination_idx]
	x_offset = s_shape[0] + image_space		x_offset = s_shape[1] + image_space
	newx = d_kps['x'] + x_offset		newx = d_kps['x'] + x_offset
	ax.scatter(newx, d_kps['y'], **scatter_kwargs)		ax.scatter(newx, d_kps['y'], **scatter_kwargs)

notebooks/Ciratefi.ipynb

0 → 100644

+300 −0

File added.

Preview size limit exceeded, changes collapsed.

autocnet/graph/network.py

+4 −4

File changed.

Contains only whitespace changes.