Merge pull request #56 from kree/adjacency (3dccfd04) · Commits · aflab / astrogeology / Autocnet

autocnet/examples/Apollo15/fromlist.txt

0 → 100644

+3 −0

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		AS15-M-0297_SML.png
		AS15-M-0298_SML.png
		AS15-M-0299_SML.png

autocnet/fileio/io_gdal.py

+17 −0

Original line number	Diff line number	Diff line
		@@ -6,6 +6,7 @@ import gdal
		import osr

		from autocnet.fileio import extract_metadata
		from pysal import cg

		gdal.UseExceptions()

		@@ -44,6 +45,9 @@ class GeoDataset(object):
		base_name : str
		The base name of the input image, extracted from the full path.

		bounding_box : object
		The bounding box of the image in lat/lon space

		geotransform : object
		Geotransform reference OGR object as an array of size 6 containing the affine
		transformation coefficients for transforming from raw sample/line to projected x/y.
		@@ -207,6 +211,19 @@ class GeoDataset(object):

		return self._xy_extent

		@property
		def bounding_box(self):
		"""
		A bounding box in lat/lon space
		Returns
		-------

		"""
		if not getattr(self, '_bounding_box', None):
		latlons = self.latlon_extent # Will fail without geospatial data
		self._bounding_box = cg.standalone.get_bounding_box([cg.shapes.LineSegment(latlons[0], latlons[1])])
		return self._bounding_box

		@property
		def pixel_polygon(self):
		"""

autocnet/graph/network.py

+42 −2

Original line number	Diff line number	Diff line
		@@ -5,7 +5,9 @@ import networkx as nx
		import numpy as np
		import pandas as pd


		from pysal import cg
		from autocnet.examples import get_path
		from autocnet.fileio.io_gdal import GeoDataset
		from autocnet.control.control import C
		from autocnet.fileio import io_json
		from autocnet.matcher.matcher import FlannMatcher
		@@ -77,6 +79,44 @@ class CandidateGraph(nx.Graph):
		graph = pickle.load(f)
		return graph

		# TODO: Add ability to actually read this out of a file?
		@classmethod
		def from_filelist(cls, filelst):
		"""
		Instantiate the class using a filelist as a python list.
		An adjacency structure is calculated using the lat/lon information in the
		input images. Currently only images with this information are supported.

		Parameters
		----------
		filelst : list
		A list containing the files (with full paths) to construct an adjacency graph from

		Returns
		-------
		: object
		A Network graph object
		"""

		# TODO: Reject unsupported file formats + work with more file formats

		dataset_list = []
		for file in filelst:
		dataset = GeoDataset(file)
		dataset_list.append(dataset)

		adjacency_dict = {}
		for data in dataset_list:
		adjacent_images = []
		other_datasets = dataset_list.copy()
		other_datasets.remove(data)
		for other in other_datasets:
		if(cg.standalone.bbcommon(data.bounding_box, other.bounding_box)):
		adjacent_images.append(other.base_name)
		adjacency_dict[data.base_name] = adjacent_images
		return cls(adjacency_dict)


		@classmethod
		def from_adjacency(cls, input_adjacency, basepath=None):
		"""
		@@ -105,7 +145,7 @@ class CandidateGraph(nx.Graph):
		for k, v in input_adjacency.items():
		input_adjacency[k] = [os.path.join(basepath, i) for i in v]
		input_adjacency[os.path.join(basepath, k)] = input_adjacency.pop(k)

		# print(input_adjacency)
		return cls(input_adjacency)

		def get_name(self, node_index):

autocnet/graph/tests/test_network.py

+11 −1

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		@@ -66,10 +66,20 @@ class TestCandidateGraph(unittest.TestCase):
		pass


		class TestFromList(unittest.TestCase):
		@classmethod
		def setUpClass(cls):
		filelist = [get_path('Mars_MGS_MOLA_ClrShade_MAP2_0.0N0.0_MERC.tif'),
		get_path('Lunar_LRO_LOLA_Shade_MAP2_90.0N20.0_LAMB.tif'),
		get_path('Mars_MGS_MOLA_ClrShade_MAP2_90.0N0.0_POLA.tif')]
		cls.graph = network.CandidateGraph.from_filelist(filelist)

		def test_graph_length(self):
		self.assertEqual(self.graph.__len__(), 3)

		class TestEdge(unittest.TestCase):

		@classmethod
		def setUpClass(cls):
		cls.graph = network.CandidateGraph.from_adjacency(get_path('adjacency.json'))