class CoordinateEncoderTest(unittest.TestCase):
"""Unit tests for CoordinateEncoder class"""
def setUp(self):
self.encoder = CoordinateEncoder(name="coordinate", n=33, w=3)
def testInvalidW(self):
# Even
args = {"name": "coordinate", "n": 45, "w": 4}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# 0
args = {"name": "coordinate", "n": 45, "w": 0}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# Negative
args = {"name": "coordinate", "n": 45, "w": -2}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testInvalidN(self):
# Too small
args = {"name": "coordinate", "n": 11, "w": 3}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testOrderForCoordinate(self):
h1 = self.encoder._orderForCoordinate(np.array([2, 5, 10]))
h2 = self.encoder._orderForCoordinate(np.array([2, 5, 11]))
h3 = self.encoder._orderForCoordinate(np.array([2497477, -923478]))
self.assertTrue(0 <= h1 and h1 < 1)
self.assertTrue(0 <= h2 and h2 < 1)
self.assertTrue(0 <= h3 and h3 < 1)
self.assertTrue(h1 != h2)
self.assertTrue(h2 != h3)
def testBitForCoordinate(self):
n = 1000
b1 = self.encoder._bitForCoordinate(np.array([2, 5, 10]), n)
b2 = self.encoder._bitForCoordinate(np.array([2, 5, 11]), n)
b3 = self.encoder._bitForCoordinate(np.array([2497477, -923478]), n)
self.assertTrue(0 <= b1 and b1 < n)
self.assertTrue(0 <= b2 and b2 < n)
self.assertTrue(0 <= b3 and b3 < n)
self.assertTrue(b1 != b2)
self.assertTrue(b2 != b3)
# Small n
n = 2
b4 = self.encoder._bitForCoordinate(np.array([5, 10]), n)
self.assertTrue(0 <= b4 < n)
@patch.object(CoordinateEncoder, "_orderForCoordinate")
def testTopWCoordinates(self, mockOrderForCoordinate):
# Mock orderForCoordinate
mockFn = lambda coordinate: np.sum(coordinate) / 5.0
mockOrderForCoordinate.side_effect = mockFn
coordinates = np.array([[1], [2], [3], [4], [5]])
top = self.encoder._topWCoordinates(coordinates, 2).tolist()
self.assertEqual(len(top), 2)
self.assertTrue([5] in top)
self.assertTrue([4] in top)
def testNeighbors1D(self):
coordinate = np.array([100])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 11)
self.assertTrue([95] in neighbors)
self.assertTrue([100] in neighbors)
self.assertTrue([105] in neighbors)
def testNeighbors2D(self):
coordinate = np.array([100, 200])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 121)
self.assertTrue([95, 195] in neighbors)
self.assertTrue([95, 205] in neighbors)
self.assertTrue([100, 200] in neighbors)
self.assertTrue([105, 195] in neighbors)
self.assertTrue([105, 205] in neighbors)
def testNeighbors0Radius(self):
coordinate = np.array([100, 200, 300])
radius = 0
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 1)
self.assertTrue([100, 200, 300] in neighbors)
def testEncodeIntoArray(self):
n = 33
w = 3
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
coordinate = np.array([100, 200])
radius = 5
output1 = encode(encoder, coordinate, radius)
self.assertEqual(np.sum(output1), w)
# Test that we get the same output for the same input
output2 = encode(encoder, coordinate, radius)
self.assertTrue(np.array_equal(output2, output1))
def testEncodeSaturateArea(self):
n = 1999
w = 25
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
outputA = encode(encoder, np.array([0, 0]), 2)
outputB = encode(encoder, np.array([0, 1]), 2)
self.assertEqual(overlap(outputA, outputB), 0.8)
def testEncodeRelativePositions(self):
# As you get farther from a coordinate, the overlap should decrease
overlaps = overlapsForRelativeAreas(999,
25,
np.array([100, 200]),
10,
dPosition=np.array([2, 2]),
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativeRadii(self):
# As radius increases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999,
25,
np.array([100, 200]),
5,
dRadius=1,
num=5)
self.assertDecreasingOverlaps(overlaps)
# As radius decreases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999,
25,
np.array([100, 200]),
20,
dRadius=-2,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativePositionsAndRadii(self):
# As radius increases and positions change, the overlap should decrease
overlaps = overlapsForRelativeAreas(999,
25,
np.array([100, 200]),
5,
dPosition=np.array([1, 1]),
dRadius=1,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeUnrelatedAreas(self):
"""
assert unrelated areas don"t share bits
(outside of chance collisions)
"""
avgThreshold = 0.3
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 5)
self.assertTrue(np.max(overlaps) < maxThreshold)
self.assertTrue(np.average(overlaps) < avgThreshold)
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 10)
self.assertTrue(np.max(overlaps) < maxThreshold)
self.assertTrue(np.average(overlaps) < avgThreshold)
maxThreshold = 0.17
overlaps = overlapsForUnrelatedAreas(999, 25, 10)
self.assertTrue(np.max(overlaps) < maxThreshold)
self.assertTrue(np.average(overlaps) < avgThreshold)
maxThreshold = 0.25
overlaps = overlapsForUnrelatedAreas(499, 13, 10)
self.assertTrue(np.max(overlaps) < maxThreshold)
self.assertTrue(np.average(overlaps) < avgThreshold)
def testEncodeAdjacentPositions(self, verbose=False):
repetitions = 100
n = 999
w = 25
radius = 10
minThreshold = 0.75
avgThreshold = 0.90
allOverlaps = np.empty(repetitions)
for i in range(repetitions):
overlaps = overlapsForRelativeAreas(n,
w,
np.array([i * 10, i * 10]),
radius,
dPosition=np.array([0, 1]),
num=1)
allOverlaps[i] = overlaps[0]
self.assertTrue(np.min(allOverlaps) > minThreshold)
self.assertTrue(np.average(allOverlaps) > avgThreshold)
if verbose:
print(
"===== Adjacent positions overlap "
"(n = {0}, w = {1}, radius = {2}) ===").format(n, w, radius)
print "Max: {0}".format(np.max(allOverlaps))
print "Min: {0}".format(np.min(allOverlaps))
print "Average: {0}".format(np.average(allOverlaps))
def assertDecreasingOverlaps(self, overlaps):
self.assertEqual((np.diff(overlaps) >= 0).sum(), 0)
class CoordinateEncoderTest(unittest.TestCase):
"""Unit tests for CoordinateEncoder class"""
def setUp(self):
self.encoder = CoordinateEncoder(name="coordinate", n=33, w=3)
def testInvalidW(self):
# Even
args = {"name": "coordinate",
"n": 45,
"w": 4}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# 0
args = {"name": "coordinate",
"n": 45,
"w": 0}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# Negative
args = {"name": "coordinate",
"n": 45,
"w": -2}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testInvalidN(self):
# Too small
args = {"name": "coordinate",
"n": 11,
"w": 3}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testHashCoordinate(self):
h1 = self.encoder._hashCoordinate(np.array([0]))
self.assertEqual(h1, 7415141576215061722)
h2 = self.encoder._hashCoordinate(np.array([0, 1]))
self.assertEqual(h2, 6909411824118942936)
def testOrderForCoordinate(self):
h1 = self.encoder._orderForCoordinate(np.array([2, 5, 10]))
h2 = self.encoder._orderForCoordinate(np.array([2, 5, 11]))
h3 = self.encoder._orderForCoordinate(np.array([2497477, -923478]))
self.assertTrue(0 <= h1 and h1 < 1)
self.assertTrue(0 <= h2 and h2 < 1)
self.assertTrue(0 <= h3 and h3 < 1)
self.assertTrue(h1 != h2)
self.assertTrue(h2 != h3)
def testBitForCoordinate(self):
n = 1000
b1 = self.encoder._bitForCoordinate(np.array([2, 5, 10]), n)
b2 = self.encoder._bitForCoordinate(np.array([2, 5, 11]), n)
b3 = self.encoder._bitForCoordinate(np.array([2497477, -923478]), n)
self.assertTrue(0 <= b1 and b1 < n)
self.assertTrue(0 <= b2 and b2 < n)
self.assertTrue(0 <= b3 and b3 < n)
self.assertTrue(b1 != b2)
self.assertTrue(b2 != b3)
# Small n
n = 2
b4 = self.encoder._bitForCoordinate(np.array([5, 10]), n)
self.assertTrue(0 <= b4 < n)
@patch.object(CoordinateEncoder, "_orderForCoordinate")
def testTopWCoordinates(self, mockOrderForCoordinate):
# Mock orderForCoordinate
mockFn = lambda coordinate: np.sum(coordinate) / 5.0
mockOrderForCoordinate.side_effect = mockFn
coordinates = np.array([[1], [2], [3], [4], [5]])
top = self.encoder._topWCoordinates(coordinates, 2).tolist()
self.assertEqual(len(top), 2)
self.assertIn([5], top)
self.assertIn([4], top)
def testNeighbors1D(self):
coordinate = np.array([100])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 11)
self.assertIn([95], neighbors)
self.assertIn([100], neighbors)
self.assertIn([105], neighbors)
def testNeighbors2D(self):
coordinate = np.array([100, 200])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 121)
self.assertIn([95, 195], neighbors)
self.assertIn([95, 205], neighbors)
self.assertIn([100, 200], neighbors)
self.assertIn([105, 195], neighbors)
self.assertIn([105, 205], neighbors)
def testNeighbors0Radius(self):
coordinate = np.array([100, 200, 300])
radius = 0
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 1)
self.assertIn([100, 200, 300], neighbors)
def testEncodeIntoArray(self):
n = 33
w = 3
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
coordinate = np.array([100, 200])
radius = 5
output1 = encode(encoder, coordinate, radius)
self.assertEqual(np.sum(output1), w)
# Test that we get the same output for the same input
output2 = encode(encoder, coordinate, radius)
self.assertTrue(np.array_equal(output2, output1))
def testEncodeSaturateArea(self):
n = 1999
w = 25
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
outputA = encode(encoder, np.array([0, 0]), 2)
outputB = encode(encoder, np.array([0, 1]), 2)
self.assertEqual(overlap(outputA, outputB), 0.8)
def testEncodeRelativePositions(self):
# As you get farther from a coordinate, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 51, np.array([100, 200]), 10,
dPosition=np.array([2, 2]),
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativeRadii(self):
# As radius increases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 25, np.array([100, 200]), 5,
dRadius=2,
num=5)
self.assertDecreasingOverlaps(overlaps)
# As radius decreases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 51, np.array([100, 200]), 20,
dRadius=-2,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativePositionsAndRadii(self):
# As radius increases and positions change, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 25, np.array([100, 200]), 5,
dPosition=np.array([1, 1]),
dRadius=1,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeUnrelatedAreas(self):
"""
assert unrelated areas don"t share bits
(outside of chance collisions)
"""
avgThreshold = 0.3
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 5)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.17
overlaps = overlapsForUnrelatedAreas(999, 25, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.25
overlaps = overlapsForUnrelatedAreas(499, 13, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
def testEncodeAdjacentPositions(self, verbose=False):
repetitions = 100
n = 999
w = 25
radius = 10
minThreshold = 0.75
avgThreshold = 0.90
allOverlaps = np.empty(repetitions)
for i in range(repetitions):
overlaps = overlapsForRelativeAreas(n, w,
np.array([i * 10, i * 10]), radius,
dPosition=np.array([0, 1]),
num=1)
allOverlaps[i] = overlaps[0]
self.assertGreater(np.min(allOverlaps), minThreshold)
self.assertGreater(np.average(allOverlaps), avgThreshold)
if verbose:
print ("===== Adjacent positions overlap "
"(n = {0}, w = {1}, radius = {2}) ===").format(n, w, radius)
print "Max: {0}".format(np.max(allOverlaps))
print "Min: {0}".format(np.min(allOverlaps))
print "Average: {0}".format(np.average(allOverlaps))
def assertDecreasingOverlaps(self, overlaps):
self.assertEqual((np.diff(overlaps) > 0).sum(), 0)
@unittest.skipUnless(
capnp, "pycapnp is not installed, skipping serialization test.")
def testReadWrite(self):
coordinate = np.array([100, 200])
radius = 5
output1 = encode(self.encoder, coordinate, radius)
proto1 = CoordinateEncoderProto.new_message()
self.encoder.write(proto1)
# Write the proto to a temp file and read it back into a new proto
with tempfile.TemporaryFile() as f:
proto1.write(f)
f.seek(0)
proto2 = CoordinateEncoderProto.read(f)
encoder = CoordinateEncoder.read(proto2)
self.assertIsInstance(encoder, CoordinateEncoder)
self.assertEqual(encoder.w, self.encoder.w)
self.assertEqual(encoder.n, self.encoder.n)
self.assertEqual(encoder.name, self.encoder.name)
self.assertEqual(encoder.verbosity, self.encoder.verbosity)
coordinate = np.array([100, 200])
radius = 5
output2 = encode(encoder, coordinate, radius)
self.assertTrue(np.array_equal(output1, output2))
class CoordinateEncoderTest(unittest.TestCase):
"""Unit tests for CoordinateEncoder class"""
def setUp(self):
self.encoder = CoordinateEncoder(name="coordinate", n=33, w=3)
def testInvalidW(self):
# Even
args = {"name": "coordinate",
"n": 45,
"w": 4}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# 0
args = {"name": "coordinate",
"n": 45,
"w": 0}
self.assertRaises(ValueError, CoordinateEncoder, **args)
# Negative
args = {"name": "coordinate",
"n": 45,
"w": -2}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testInvalidN(self):
# Too small
args = {"name": "coordinate",
"n": 11,
"w": 3}
self.assertRaises(ValueError, CoordinateEncoder, **args)
def testHashCoordinate(self):
h1 = self.encoder._hashCoordinate(np.array([0]))
self.assertEqual(h1, 7415141576215061722)
h2 = self.encoder._hashCoordinate(np.array([0, 1]))
self.assertEqual(h2, 6909411824118942936)
def testOrderForCoordinate(self):
h1 = self.encoder._orderForCoordinate(np.array([2, 5, 10]))
h2 = self.encoder._orderForCoordinate(np.array([2, 5, 11]))
h3 = self.encoder._orderForCoordinate(np.array([2497477, -923478]))
self.assertTrue(0 <= h1 and h1 < 1)
self.assertTrue(0 <= h2 and h2 < 1)
self.assertTrue(0 <= h3 and h3 < 1)
self.assertTrue(h1 != h2)
self.assertTrue(h2 != h3)
def testBitForCoordinate(self):
n = 1000
b1 = self.encoder._bitForCoordinate(np.array([2, 5, 10]), n)
b2 = self.encoder._bitForCoordinate(np.array([2, 5, 11]), n)
b3 = self.encoder._bitForCoordinate(np.array([2497477, -923478]), n)
self.assertTrue(0 <= b1 and b1 < n)
self.assertTrue(0 <= b2 and b2 < n)
self.assertTrue(0 <= b3 and b3 < n)
self.assertTrue(b1 != b2)
self.assertTrue(b2 != b3)
# Small n
n = 2
b4 = self.encoder._bitForCoordinate(np.array([5, 10]), n)
self.assertTrue(0 <= b4 < n)
@patch.object(CoordinateEncoder, "_orderForCoordinate")
def testTopWCoordinates(self, mockOrderForCoordinate):
# Mock orderForCoordinate
mockFn = lambda coordinate: np.sum(coordinate) / 5.0
mockOrderForCoordinate.side_effect = mockFn
coordinates = np.array([[1], [2], [3], [4], [5]])
top = self.encoder._topWCoordinates(coordinates, 2).tolist()
self.assertEqual(len(top), 2)
self.assertIn([5], top)
self.assertIn([4], top)
def testNeighbors1D(self):
coordinate = np.array([100])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 11)
self.assertIn([95], neighbors)
self.assertIn([100], neighbors)
self.assertIn([105], neighbors)
def testNeighbors2D(self):
coordinate = np.array([100, 200])
radius = 5
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 121)
self.assertIn([95, 195], neighbors)
self.assertIn([95, 205], neighbors)
self.assertIn([100, 200], neighbors)
self.assertIn([105, 195], neighbors)
self.assertIn([105, 205], neighbors)
def testNeighbors0Radius(self):
coordinate = np.array([100, 200, 300])
radius = 0
neighbors = self.encoder._neighbors(coordinate, radius).tolist()
self.assertEqual(len(neighbors), 1)
self.assertIn([100, 200, 300], neighbors)
def testEncodeIntoArray(self):
n = 33
w = 3
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
coordinate = np.array([100, 200])
radius = 5
output1 = encode(encoder, coordinate, radius)
self.assertEqual(np.sum(output1), w)
# Test that we get the same output for the same input
output2 = encode(encoder, coordinate, radius)
self.assertTrue(np.array_equal(output2, output1))
# Test that a float radius raises an assertion error
with self.assertRaises(AssertionError):
encoder.encode((coordinate, float(radius)))
def testEncodeSaturateArea(self):
n = 1999
w = 25
encoder = CoordinateEncoder(name="coordinate", n=n, w=w)
outputA = encode(encoder, np.array([0, 0]), 2)
outputB = encode(encoder, np.array([0, 1]), 2)
self.assertEqual(overlap(outputA, outputB), 0.8)
def testEncodeRelativePositions(self):
# As you get farther from a coordinate, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 51, np.array([100, 200]), 10,
dPosition=np.array([2, 2]),
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativeRadii(self):
# As radius increases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 25, np.array([100, 200]), 5,
dRadius=2,
num=5)
self.assertDecreasingOverlaps(overlaps)
# As radius decreases, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 51, np.array([100, 200]), 20,
dRadius=-2,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeRelativePositionsAndRadii(self):
# As radius increases and positions change, the overlap should decrease
overlaps = overlapsForRelativeAreas(999, 25, np.array([100, 200]), 5,
dPosition=np.array([1, 1]),
dRadius=1,
num=5)
self.assertDecreasingOverlaps(overlaps)
def testEncodeUnrelatedAreas(self):
"""
assert unrelated areas don"t share bits
(outside of chance collisions)
"""
avgThreshold = 0.3
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 5)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.12
overlaps = overlapsForUnrelatedAreas(1499, 37, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.17
overlaps = overlapsForUnrelatedAreas(999, 25, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
maxThreshold = 0.25
overlaps = overlapsForUnrelatedAreas(499, 13, 10)
self.assertLess(np.max(overlaps), maxThreshold)
self.assertLess(np.average(overlaps), avgThreshold)
def testEncodeAdjacentPositions(self, verbose=False):
repetitions = 100
n = 999
w = 25
radius = 10
minThreshold = 0.75
avgThreshold = 0.90
allOverlaps = np.empty(repetitions)
for i in range(repetitions):
overlaps = overlapsForRelativeAreas(n, w,
np.array([i * 10, i * 10]), radius,
dPosition=np.array([0, 1]),
num=1)
allOverlaps[i] = overlaps[0]
self.assertGreater(np.min(allOverlaps), minThreshold)
self.assertGreater(np.average(allOverlaps), avgThreshold)
if verbose:
print(("===== Adjacent positions overlap "
"(n = {0}, w = {1}, radius = {2}) ===").format(n, w, radius))
print("Max: {0}".format(np.max(allOverlaps)))
print("Min: {0}".format(np.min(allOverlaps)))
print("Average: {0}".format(np.average(allOverlaps)))
def assertDecreasingOverlaps(self, overlaps):
self.assertEqual((np.diff(overlaps) > 0).sum(), 0)
@unittest.skipUnless(
capnp, "pycapnp is not installed, skipping serialization test.")
def testReadWrite(self):
coordinate = np.array([100, 200])
radius = 5
output1 = encode(self.encoder, coordinate, radius)
proto1 = CoordinateEncoderProto.new_message()
self.encoder.write(proto1)
# Write the proto to a temp file and read it back into a new proto
with tempfile.TemporaryFile() as f:
proto1.write(f)
f.seek(0)
proto2 = CoordinateEncoderProto.read(f)
encoder = CoordinateEncoder.read(proto2)
self.assertIsInstance(encoder, CoordinateEncoder)
self.assertEqual(encoder.w, self.encoder.w)
self.assertEqual(encoder.n, self.encoder.n)
self.assertEqual(encoder.name, self.encoder.name)
self.assertEqual(encoder.verbosity, self.encoder.verbosity)
coordinate = np.array([100, 200])
radius = 5
output2 = encode(encoder, coordinate, radius)
self.assertTrue(np.array_equal(output1, output2))
