Merge remote-tracking branch 'upstream/master' (09aef4a2) · Commits · aflab / astrogeology / Autocnet

autocnet/fileio/io_gdal.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -237,7 +237,7 @@ class GeoDataset(object):
		num_polygon_bytes = find_in_dict(polygon_pvl, 'Bytes')

		# I too dislike the additional open here. Not sure a good option
		with open(self.file_name, 'r+') as f:
		with open(self.file_name, 'r') as f:
		f.seek(start_polygon_byte - 1)
		# Sloppy unicode to string because GDAL pukes on unicode
		stream = str(f.read(num_polygon_bytes))

autocnet/fileio/tests/test_utils.py

0 → 100644

+18 −0

Original line number	Diff line number	Diff line
		import unittest
		import pandas as pd
		import numpy as np

		from .. import utils

		class TestUtils(unittest.TestCase):
		def setUp(self):
		pass

		def test_slopes(self):
		x1 = pd.DataFrame({'x': np.arange(1, 11),
		'y': np.arange(1, 11)})
		x2 = pd.DataFrame({'x': np.arange(6, 16),
		'y': np.arange(11, 21)})

		slope = utils.calculate_slope(x1, x2)
		self.assertEqual(slope.slope[0], 2)

autocnet/fileio/utils.py

+21 −0

Original line number	Diff line number	Diff line
		@@ -3,6 +3,7 @@ import tempfile
		import os
		import fnmatch
		import numpy as np
		import pandas as pd

		def create_dir(basedir=''):
		"""
		@@ -34,3 +35,23 @@ def file_search(searchdir,searchstring):
		filelist.append(os.path.join(root, filename))
		filelist=np.array(filelist)
		return filelist

		def calculate_slope(x1, x2):
		"""
		Calculates the 2-dimensional slope between the points in two dataframes each containing two columns ['x', 'y']
		The slope is calculated from x1 to x2.

		Parameters
		----------
		x1 : dataframe
		Each row is a point with columns ['x', 'y']
		x2 : dataframe
		Each row is a point with columns ['x', 'y']

		Returns
		-------
		: dataframe
		A dataframe with the slope between the points in x1 and x2 for each row.
		"""
		slopes = (x2.y.values - x1.y.values)/(x2.x.values-x1.x.values)
		return pd.DataFrame(slopes, columns=['slope'])

autocnet/graph/network.py

+61 −8

Original line number	Diff line number	Diff line
		@@ -354,13 +354,13 @@ class CandidateGraph(nx.Graph):
		"""
		_, self.clusters = func(self, args, *kwargs)

		def apply_func_to_edges(self, func, args, graph_mask_keys=[], *kwargs):
		def apply_func_to_edges(self, function, args, graph_mask_keys=[], *kwargs):
		"""
		Iterates over edges using an optional mask and and applies the given function.
		If func is not an attribute of Edge, raises AttributeError
		Parameters
		----------
		func : string
		function : obj
		function to be called on every edge
		graph_mask_keys : list
		of keys in graph_masks
		@@ -372,17 +372,17 @@ class CandidateGraph(nx.Graph):
		else:
		edges_to_iter = self.edges()

		if not isinstance(func, str):
		func = func.__name__
		if not isinstance(function, str):
		function = function.__name__

		for s, d in edges_to_iter:
		curr_edge = self.get_edge_data(s, d)
		try:
		function = getattr(curr_edge, func)
		func = getattr(curr_edge, function)
		except:
		raise AttributeError(func, ' is not an attribute of Edge')
		raise AttributeError(function, ' is not an attribute of Edge')
		else:
		function(args, *kwargs)
		func(args, *kwargs)

		def minimum_spanning_tree(self):
		"""
		@@ -698,3 +698,56 @@ class CandidateGraph(nx.Graph):

		H.graph = self.graph
		return H

		def subgraph_from_matches(self):
		"""
		Returns a sub-graph where all edges have matches.
		(i.e. images with no matches are removed)

		Returns
		-------
		: Object
		A networkX graph object
		"""

		# get all edges that have matches
		matches = [(u, v) for u, v, edge in self.edges_iter(data=True)
		if hasattr(edge, 'matches') and
		not edge.matches.empty]

		return self.create_edge_subgraph(matches)

		def filter_nodes(self, func, args, *kwargs):
		"""
		Filters graph and returns a sub-graph from matches. Mimics
		python's filter() function

		Parameters
		----------
		func : function which returns bool used to filter out nodes

		Returns
		-------
		: Object
		A networkX graph object

		"""
		nodes = [n for n, d in self.nodes_iter(data=True) if func(d, args, *kwargs)]
		return self.create_node_subgraph(nodes)

		def filter_edges(self, func, args, *kwargs):
		"""
		Filters graph and returns a sub-graph from matches. Mimics
		python's filter() function

		Parameters
		----------
		func : function which returns bool used to filter out edges

		Returns
		-------
		: Object
		A networkX graph object
		"""
		edges = [(u, v) for u, v, edge in self.edges_iter(data=True) if func(edge, args, *kwargs)]
		return self.create_edge_subgraph(edges)

autocnet/graph/tests/test_network.py

+24 −0

Original line number	Diff line number	Diff line
		@@ -114,6 +114,30 @@ class TestCandidateGraph(unittest.TestCase):
		node_sub = g.create_node_subgraph([0,1])
		self.assertEqual(len(node_sub), 2)

		def test_filter(self):
		def edge_func(edge):
		return hasattr(edge, 'matches') and not edge.matches.empty

		graph = self.graph.copy()
		test_sub_graph = graph.create_node_subgraph([0, 1])
		test_sub_graph.extract_features(extractor_parameters={'nfeatures': 500})
		test_sub_graph.match_features(k=2)

		filtered_nodes = graph.filter_nodes(lambda node: hasattr(node, 'descriptors'))
		filtered_edges = graph.filter_edges(edge_func)

		self.assertEqual(filtered_nodes.number_of_nodes(), test_sub_graph.number_of_nodes())
		self.assertEqual(filtered_edges.number_of_edges(), test_sub_graph.number_of_edges())

		def test_subgraph_from_matches(self):
		test_sub_graph = self.graph.create_node_subgraph([0, 1])
		test_sub_graph.extract_features(extractor_parameters={'nfeatures': 500})
		test_sub_graph.match_features(k=2)

		sub_graph_from_matches = self.graph.subgraph_from_matches()

		self.assertEqual(test_sub_graph.edges(), sub_graph_from_matches.edges())

		def tearDown(self):
		pass