Commit 5a02c0fd authored by Evin Dunn's avatar Evin Dunn
Browse files

Added tests for edge.__eq__(), edge. __repr__(), edge.symmetry_check(),... 

Added tests for edge.__eq__(), edge. __repr__(), edge.symmetry_check(), edge.masks, all uncovered control methods
parent 64009b67

autocnet/control/tests/test_control.py

+20 −0
Changes for autocnet/control/tests/test_control.py: 20 added lines, 0 removed lines.
Original line number Diff line number Diff line
@@ -75,3 +75,23 @@ class TestC(unittest.TestCase): 
    def test_to_dataframe(self):

        self.C.to_dataframe()



    def test_point_repr(self):

        expected = 0

        p = control.Point(expected)

        self.assertEqual(str(expected), p.__repr__())



    def test_correspondence_repr(self):

        expected = 0

        c = control.Correspondence(expected, 1, 1)

        self.assertEqual(str(expected), c.__repr__())



    def test_correspondence_eq(self):

        expected = 0

        c = control.Correspondence(expected, 1, 1)

        self.assertTrue(c == expected)



    def test_correspondence_hash(self):

        expected = 200

        c = control.Correspondence(expected, 1, 1)

        self.assertEqual(hash(expected), hash(c))

autocnet/graph/edge.py

+5 −5
Changes for autocnet/graph/edge.py: 5 added lines, 5 removed lines.
Original line number Diff line number Diff line
@@ -118,14 +118,14 @@ class Edge(dict, MutableMapping): 
        pass



    def symmetry_check(self):

        if hasattr(self, 'matches'):

        if self.matches:

            mask = od.mirroring_test(self.matches)

            self.masks = ('symmetry', mask)

        else:

            raise AttributeError('No matches have been computed for this edge.')



    def ratio_check(self, clean_keys=[], **kwargs):

        if hasattr(self, 'matches'):

        if self.matches:

            matches, mask = self.clean(clean_keys)

            distance_mask = od.distance_ratio(matches, **kwargs)

            self.masks = ('ratio', distance_mask)
@@ -152,7 +152,7 @@ class Edge(dict, MutableMapping): 
        autocnet.transformation.transformations.FundamentalMatrix



        """

        if not hasattr(self, 'matches'):

        if not self.matches:

            raise AttributeError('Matches have not been computed for this edge')

            return

        matches, mask = self.clean(clean_keys)
@@ -197,7 +197,7 @@ class Edge(dict, MutableMapping): 
               Boolean array of the outliers

        """



        if hasattr(self, 'matches'):

        if self.matches:

            matches = self.matches

        else:

            raise AttributeError('Matches have not been computed for this edge')
@@ -321,7 +321,7 @@ class Edge(dict, MutableMapping): 
                     of mask keys to be used to reduce the total size

                     of the matches dataframe.

        """

        if not hasattr(self, 'matches'):

        if not self.matches:

            raise AttributeError('This edge does not yet have any matches computed.')



        matches, mask = self.clean(clean_keys)

autocnet/graph/tests/test_edge.py

+76 −0
Changes for autocnet/graph/tests/test_edge.py: 76 added lines, 0 removed lines.
Original line number Diff line number Diff line
@@ -3,6 +3,7 @@ from unittest.mock import Mock 
from unittest.mock import MagicMock



import ogr

import numpy as np

import pandas as pd

from plio.io import io_gdal
@@ -45,6 +46,24 @@ class TestEdge(unittest.TestCase): 
    def test_masks(self):

        self.assertIsInstance(self.edge.masks, pd.DataFrame)



        keypoint_matches = [[0, 0, 1, 4],

                            [0, 1, 1, 3],

                            [0, 2, 1, 2],

                            [0, 3, 1, 1],

                            [0, 4, 1, 0]]



        # Test masks returns properly

        matches_df = pd.DataFrame(data=keypoint_matches, columns=['source_image', 'source_idx',

                                                                  'destination_image', 'destination_idx'])

        e = edge.Edge()

        e.matches = matches_df

        expected = pd.DataFrame(True, columns=['symmetry'],

                                index=matches_df.index)

        self.assertTrue(e.masks.equals(expected))



    def test_masks_setter(self):

        e = edge.Edge()





    def test_compute_fundamental_matrix(self):

        with self.assertRaises(AttributeError):
@@ -321,3 +340,60 @@ class TestEdge(unittest.TestCase): 
        # Check key error thrown when string arg != "source" or "destination"

        with self.assertRaises(KeyError):

            e.get_keypoints("string", clean_keys)



    def test_eq(self):

        edge1 = edge.Edge()

        edge2 = edge.Edge()

        edge3 = edge.Edge()



        # Test edges w/ different keys are not equal, ones with same keys are

        edge1.__dict__["key"] = 1

        edge2.__dict__["key"] = 1

        edge3.__dict__["not_key"] = 1



        self.assertTrue(edge1 == edge2)

        self.assertFalse(edge1 == edge3)



        # Test edges with same keys, but diff df values

        edge1.__dict__["key"] = pd.DataFrame({'x': (0, 1, 2, 3, 4)})

        edge2.__dict__["key"] = pd.DataFrame({'x': (0, 1, 2, 3, 4)})

        edge3.__dict__["key"] = pd.DataFrame({'x': (0, 1, 2, 3, 5)})



        self.assertTrue(edge1 == edge2)

        self.assertFalse(edge1 == edge3)



        # Test edges with same keys, but diff np array vals

        # edge.__eq__ calls ndarray.all(), which checks that

        # all values in an array eval to true

        edge1.__dict__["key"] = np.array([True, True, True], dtype=np.bool)

        edge2.__dict__["key"] = np.array([True, True, True], dtype=np.bool)

        edge3.__dict__["key"] = np.array([True, True, False], dtype=np.bool)



        self.assertTrue(edge1 == edge2)

        self.assertFalse(edge1 == edge3)



    def test_repr(self):

        src = node.Node()

        dst = node.Node()

        masks = pd.DataFrame()



        e = edge.Edge()

        e.source = src

        e.destination = dst



        expected = """

        Source Image Index: {}

        Destination Image Index: {}

        Available Masks: {}

        """.format(src, dst, masks)



        self.assertEqual(expected, e.__repr__())



    def test_symmetry_check(self):

        # Matches is init to None

        e = edge.Edge()

        e.source = node.Node()

        e.destination = node.Node()

        # If there are no matches, should raise attrib err

        with (self.assertRaises(AttributeError)):

            e.symmetry_check()