Merge pull request #118 from acpaquette/weight (b02632c4) · Commits · aflab / astrogeology / Autocnet

autocnet/cg/cg.py

+56 −0

Original line number	Diff line number	Diff line
		import json
		import ogr
		import pandas as pd

		from scipy.spatial import ConvexHull


		@@ -45,3 +47,57 @@ def overlapping_polygon_area(polys):
		intersection = intersection.Intersection(geom)
		area = intersection.GetArea()
		return area


		def convex_hull(points):

		"""

		Parameters
		----------
		points : ndarray
		(n, 2) array of point coordinates

		Returns
		-------
		hull : 2-D convex hull
		Provides a convex hull that is used
		to determine coverage

		"""

		if isinstance(points, pd.DataFrame) :
		points = pd.DataFrame.as_matrix(points)

		hull = ConvexHull(points)
		return hull


		def two_poly_overlap(poly1, poly2):
		"""

		Parameters
		----------
		poly1 : ogr polygon
		Any polygon that shares some kind of overlap
		with poly2

		poly2 : ogr polygon
		Any polygon that shares some kind of overlap
		with poly1

		Returns
		-------
		overlap_info : list
		Percentage of overlap between the two images
		and the area that is being overlapped

		"""
		a_o = poly2.Intersection(poly1).GetArea()
		area1 = poly1.GetArea()
		area2 = poly2.GetArea()

		overlap_area = a_o
		overlap_percn = (a_o / (area1 + area2 - a_o)) * 100
		overlap_info = [overlap_percn, overlap_area]
		return overlap_info

+13 −0

Original line number	Diff line number	Diff line
		@@ -6,6 +6,7 @@ sys.path.insert(0, os.path.abspath('..'))
		import numpy as np

		from .. import cg
		from osgeo import ogr


		class TestArea(unittest.TestCase):
		@@ -19,3 +20,15 @@ class TestArea(unittest.TestCase):
		ratio = cg.convex_hull_ratio(self.pts, total_area)

		self.assertAlmostEqual(0.7566490, ratio, 5)

		def test_overlap(self):
		wkt1 = "POLYGON ((0 40, 40 40, 40 0, 0 0, 0 40))"
		wkt2 = "POLYGON ((20 60, 60 60, 60 20, 20 20, 20 60))"

		poly1 = ogr.CreateGeometryFromWkt(wkt1)
		poly2 = ogr.CreateGeometryFromWkt(wkt2)

		info = cg.two_poly_overlap(poly1, poly2)

		self.assertEqual(info[1], 400)
		self.assertAlmostEqual(info[0], 14.285714285)
		No newline at end of file

+23 −0

Original line number	Diff line number	Diff line
		@@ -13,6 +13,7 @@ from autocnet.matcher import suppression_funcs as spf
		from autocnet.matcher import subpixel as sp
		from autocnet.transformation.transformations import FundamentalMatrix, Homography
		from autocnet.vis.graph_view import plot_edge
		from autocnet.cg import cg


		class Edge(dict, MutableMapping):
		@@ -31,6 +32,11 @@ class Edge(dict, MutableMapping):
		With key equal to an autoincrementing integer and value
		equal to a dict of parameters used to generate this
		realization.

		weight : dict
		Dictionary with two keys overlap_area, and overlap_percn
		overlap_area returns the area overlaped by both images
		overlap_percn retuns the total percentage of overlap
		"""

		def __init__(self, source=None, destination=None):
		@@ -41,6 +47,8 @@ class Edge(dict, MutableMapping):
		self.fundamental_matrix = None
		self._subpixel_offsets = None

		self.weight = {}

		self._observers = set()

		# Subscribe the heatlh observer
		@@ -410,3 +418,18 @@ class Edge(dict, MutableMapping):
		mask = pd.Series(True, self.matches.index)

		return matches, mask

		def overlap(self):
		"""
		Acts on an edge and returns the overlap area and percentage of overlap
		between the two images on the edge. Data is returned to the
		weight dictionary
		"""
		poly1 = self.source.geodata.footprint
		poly2 = self.destination.geodata.footprint

		overlapinfo = cg.two_poly_overlap(poly1, poly2)

		self.weight['overlap_area'] = overlapinfo[1]
		self.weight['overlap_percn'] = overlapinfo[0]

+10 −2

Original line number	Diff line number	Diff line
		@@ -4,8 +4,6 @@ import warnings

		import dill as pickle
		import networkx as nx
		import numpy as np
		import pandas as pd

		from autocnet.control.control import CorrespondenceNetwork
		from autocnet.fileio import io_hdf
		@@ -476,6 +474,16 @@ class CandidateGraph(nx.Graph):
		'''
		self.apply_func_to_edges('suppress', args, *kwargs)

		def overlap(self):
		'''
		Compute the percentage and area coverage of two images

		See Also
		--------
		autocnet.cg.cg.two_image_overlap
		'''
		self.apply_func_to_edges('overlap')

		def minimum_spanning_tree(self):
		"""
		Calculates the minimum spanning tree of the graph

+29 −0

Original line number	Diff line number	Diff line
		@@ -6,6 +6,7 @@ import numpy as np
		import pandas as pd
		from scipy.misc import bytescale

		from autocnet.cg import cg
		from autocnet.fileio.io_gdal import GeoDataset
		from autocnet.fileio import io_hdf
		from autocnet.matcher import feature_extractor as fe
		@@ -114,6 +115,33 @@ class Node(dict, MutableMapping):
		self._isis_serial = None
		return self._isis_serial

		def coverage(self):
		"""
		Determines the area of keypoint coverage
		using the unprojected image, resulting
		in a rough estimation of the percentage area
		being covered.

		Returns
		-------
		coverage_area : float
		Area covered by the generated
		keypoints
		"""

		points = self.get_keypoint_coordinates()
		hull = cg.convex_hull(points)
		hull_area = hull.volume

		max_x = self.geodata.raster_size[0]
		max_y = self.geodata.raster_size[1]

		total_area = max_x * max_y

		self.coverage_area = (hull_area/total_area)*100

		return self.coverage_area

		def get_array(self, band=1):
		"""
		Get a band as a 32-bit numpy array
		@@ -343,3 +371,4 @@ class Node(dict, MutableMapping):
		mask = panel[clean_keys].all(axis=1)
		matches = self._keypoints[mask]
		return matches, mask