def test_bbox_hypervolume_other() -> None:
"""
Test that we get the expected non-trivial area for bboxes of various
dimensions.
"""
# 1D
minp = [4]
maxp = [8]
expected_area = 4
assert AxisAlignedBoundingBox(minp, maxp).hypervolume == expected_area
# 2D
minp = [0, 4]
maxp = [2, 10]
expected_area = 12 # 2 * 6
assert AxisAlignedBoundingBox(minp, maxp).hypervolume == expected_area
# 3D
minp = [0, 4, 3]
maxp = [1, 10, 8]
expected_area = 30 # 1 * 6 * 5
assert AxisAlignedBoundingBox(minp, maxp).hypervolume == expected_area
# 4D
minp = [0, 4, 3, 5]
maxp = [1, 10, 8, 9]
expected_area = 120 # 1 * 6 * 5 * 4
assert AxisAlignedBoundingBox(minp, maxp).hypervolume == expected_area
def test_bbox_construction_incongruous_shape() -> None:
"""
Test that construction fails when one or both input coordinates are not a
single array dimension (i.e. multi-dimensional shape in numpy.array
parlance).
"""
minp_1dim = (0, )
minp_2dim = ((0, ), (1, ))
maxp_1dim = (1, )
maxp_2dim = ((1, ), (2, ))
with pytest.raises(ValueError,
match=r"One or both vertices provided had "
r"more than one array dimension "
r"\(min_vertex\.ndim == 2, "
r"max_vertex\.ndim == 1\)\."):
# noinspection PyTypeChecker
AxisAlignedBoundingBox(minp_2dim, maxp_1dim) # type: ignore
with pytest.raises(ValueError,
match=r"One or both vertices provided had "
r"more than one array dimension "
r"\(min_vertex\.ndim == 1, "
r"max_vertex\.ndim == 2\)\."):
# noinspection PyTypeChecker
AxisAlignedBoundingBox(minp_1dim, maxp_2dim) # type: ignore
with pytest.raises(ValueError,
match=r"One or both vertices provided had "
r"more than one array dimension "
r"\(min_vertex\.ndim == 2, "
r"max_vertex\.ndim == 2\)\."):
# noinspection PyTypeChecker
AxisAlignedBoundingBox(minp_2dim, maxp_2dim) # type: ignore
def test_bbox_equality_other_not_close() -> None:
"""
Test that other bbox is not equal when bbox is sufficiently different.
"""
bb1 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
# Differs in max z bounds.
bb2 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 5])
assert not (bb1 == bb2)
def test_bbox_equality_other_is_copy() -> None:
"""
Test that a bounding box is equal to an equivalent other bounding box
instance.
"""
bb1 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
bb2 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
assert bb1 == bb2
def test_getstate_format() -> None:
"""
Test expected __getstate__ format.
"""
min_v = (4.2, 8.9, 1)
max_v = (9.2, 9.0, 48)
expected_state = ([4.2, 8.9, 1], [9.2, 9.0, 48])
bb1 = AxisAlignedBoundingBox(min_v, max_v)
assert bb1.__getstate__() == expected_state
def test_setstate_format() -> None:
"""
Test expected state format compatible with setstate
"""
state = ([4.2, 8.9, 1], [9.2, 9.0, 48])
expected_min_v = (4.2, 8.9, 1)
expected_max_v = (9.2, 9.0, 48)
bb = AxisAlignedBoundingBox([0], [1])
bb.__setstate__(state)
numpy.testing.assert_allclose(bb.min_vertex, expected_min_v)
numpy.testing.assert_allclose(bb.max_vertex, expected_max_v)
def test_in_bounds_zero_crop_area(self) -> None:
"""
Test that crop is not ``in_bounds`` when it has zero area (undefined).
"""
# noinspection PyArgumentList
bb = AxisAlignedBoundingBox([1, 2], [1, 2])
assert not crop_in_bounds(bb, 4, 6)
def test_in_bounds_completely_outside(self) -> None:
"""
Test that being completely outside the given bounds causes
``in_bounds`` to return False.
"""
bb = AxisAlignedBoundingBox([100, 100], [102, 102])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([-100, -100], [-98, -98])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([-100, 100], [-98, 102])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([100, -100], [102, -98])
assert not crop_in_bounds(bb, 4, 6)
def test_bbox_not_equal(m_bbox_eq: mock.MagicMock) -> None:
"""
Test that non-equality is just calling the __eq__ in
AxisAlignedBoundingBox.
:param mock.MagicMock m_bbox_eq:
"""
bb1 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
bb2 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
m_bbox_eq.assert_not_called()
# noinspection PyStatementEffect
bb1 != bb2
m_bbox_eq.assert_called_once_with(bb2)
def test_bbox_repr() -> None:
"""
Test that __repr__ returns without error.
"""
assert repr(AxisAlignedBoundingBox([0], [1.2])) == \
"<smqtk_image_io.bbox.AxisAlignedBoundingBox " \
"min_vertex=[0] max_vertex=[1.2]>"
def test_bbox_set_vertices_maintain_type_float() -> None:
"""
Test that ndarray dtypes inherit from input float values explicitly.
"""
# Float input coordinates (1d)
minv = [0.]
maxv = [1.]
# Mock instance so as to not actually hit __init__ method.
m_bb = mock.MagicMock(spec_set=AxisAlignedBoundingBox)
# Invoke private method, which should set attributes onto `m_bb`.
AxisAlignedBoundingBox._set_vertices(m_bb, minv, maxv)
# BOTH vertices should be integer since input coordinates are integers.
assert issubclass(m_bb.min_vertex.dtype.type, numpy.float64)
assert issubclass(m_bb.max_vertex.dtype.type, numpy.float64)
def test_in_bounds_inside_edges(self) -> None:
"""
Test that a crop is "in bounds" when contacting the 4 edges of the
given rectangular bounds.
+--+
| |
## | => (4, 6) image, (2,2) crop
## |
| |
+--+
+##+
|##|
| | => (4, 6) image, (2,2) crop
| |
| |
+--+
+--+
| |
| ## => (4, 6) image, (2,2) crop
| ##
| |
+--+
+--+
| |
| | => (4, 6) image, (2,2) crop
| |
|##|
+##+
"""
# noinspection PyArgumentList
bb = AxisAlignedBoundingBox([0, 2], [2, 4])
assert crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([1, 0], [3, 2])
assert crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([2, 2], [4, 4])
assert crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([1, 4], [3, 6])
assert crop_in_bounds(bb, 4, 6)
def test_bbox_equality_other_is_close() -> None:
"""
Test that a bounding box is equal to an equivalent other bounding box
instance.
"""
e = 1e-8 # default absolute tolerance on ``numpy.allclose`` function.
bb1 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
bb2 = AxisAlignedBoundingBox([1 + e, 2 + e, 3 + e], [2 + e, 3 + e, 4 + e])
# Basic array equality is exact, which should show that these are not
# strictly equal.
# noinspection PyUnresolvedReferences
assert (bb1.min_vertex != bb2.min_vertex).all()
# noinspection PyUnresolvedReferences
assert (bb1.max_vertex != bb2.max_vertex).all()
assert bb1 == bb2
def test_bbox_hash() -> None:
"""
Test expected hashing of bounding box.
"""
p1 = (0, 1, 2)
p2 = (1, 2, 3)
expected_hash = hash((p1, p2))
assert hash(AxisAlignedBoundingBox(p1, p2)) == expected_hash
def test_in_bounds_crossing_edges(self) -> None:
"""
Test that ``in_bounds`` returns False when crop crossed the 4 edges.
+--+
| |
### | => (4, 6) image, (3,2) crop
### |
| |
+--+
+--+
| |
| ### => (4, 6) image, (3,2) crop
| ###
| |
+--+
##
+##+
|##|
| | => (4, 6) image, (2,3) crop
| |
| |
+--+
+--+
| |
| | => (4, 6) image, (2,3) crop
| |
|##|
+##+
##
"""
bb = AxisAlignedBoundingBox([-1, 2], [2, 4])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([2, 2], [5, 4])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([1, -1], [3, 2])
assert not crop_in_bounds(bb, 4, 6)
bb = AxisAlignedBoundingBox([1, 4], [3, 7])
assert not crop_in_bounds(bb, 4, 6)
def test_bbox_hypervolume_1(ndim: int) -> None:
"""
Test that we get the expected 1-area from various 1-area hyper-cubes.
"""
minp = [0] * ndim
maxp = [1] * ndim
expected_area = 1
assert AxisAlignedBoundingBox(minp, maxp).hypervolume == expected_area
def test_bbox_dtype() -> None:
"""
Test getting the representative dtype of the bounding box, including mix
vertex array types
"""
# int
bb = AxisAlignedBoundingBox([0], [1])
assert issubclass(bb.dtype.type, numpy.signedinteger)
bb = AxisAlignedBoundingBox(numpy.array([0], dtype=numpy.uint8),
numpy.array([1], dtype=numpy.uint8))
assert issubclass(bb.dtype.type, numpy.uint8)
bb = AxisAlignedBoundingBox(numpy.array([0], dtype=numpy.uint8),
numpy.array([1], dtype=numpy.uint32))
assert issubclass(bb.dtype.type, numpy.uint32)
# float
bb = AxisAlignedBoundingBox([0.], [1.])
assert issubclass(bb.dtype.type, numpy.float64)
bb = AxisAlignedBoundingBox(numpy.array([0], dtype=numpy.float32),
numpy.array([1], dtype=numpy.float16))
assert issubclass(bb.dtype.type, numpy.float32)
# mixed
bb = AxisAlignedBoundingBox([0], [1.0])
assert issubclass(bb.dtype.type, numpy.float64)
bb = AxisAlignedBoundingBox([0.0], [1])
assert issubclass(bb.dtype.type, numpy.float64)
def test_bbox_set_vertices(ndim: int, seq_type: Any) -> None:
"""
Test constructing an AxisAlignedBoundingBox with ``ndim`` coordinates.
"""
minv = [random.randint(0, 9) for _ in range(ndim)]
maxv = [random.randint(10, 19) for _ in range(ndim)]
minv_s = seq_type(minv)
maxv_s = seq_type(maxv)
# Mock instance so as to not actually hit __init__ method.
m_bb = mock.MagicMock(spec_set=AxisAlignedBoundingBox)
# Invoke private method, which should set attributes onto `m_bb`.
AxisAlignedBoundingBox._set_vertices(m_bb, minv_s, maxv_s)
assert isinstance(m_bb.min_vertex, numpy.ndarray)
assert isinstance(m_bb.max_vertex, numpy.ndarray)
numpy.testing.assert_allclose(m_bb.min_vertex, minv)
numpy.testing.assert_allclose(m_bb.max_vertex, maxv)
def test_bbox_deltas_4d() -> None:
"""
Test that `deltas` property returns the correct value for an example 1D
region.
"""
minp = [3] * 4
maxp = [9] * 4
expected = [6] * 4
numpy.testing.assert_allclose(
AxisAlignedBoundingBox(minp, maxp).deltas, expected)
def test_bbox_construction_maxp_not_greater() -> None:
"""
Test the check that the max-coordinate must be >= min-coordinate.
"""
minp = (10, 10)
maxp = (11, 9)
with pytest.raises(ValueError,
match=r"The maximum vertex was not strictly >= the "
r"minimum vertex\."):
AxisAlignedBoundingBox(minp, maxp)
def test_bbox_ndim(ndim: int) -> None:
"""
Test that the ``ndim`` property correctly reflects the dimensionality of
the coordinates stored.
:param ndim: Dimension integer fixture result.
"""
bb = AxisAlignedBoundingBox([1] * ndim, [2] * ndim)
assert bb.ndim == ndim
def test_bbox_deltas_3d() -> None:
"""
Test that `deltas` property returns the correct value for an example 1D
region.
"""
minp = [29, 38, 45]
maxp = [792, 83, 45]
expected = [763, 45, 0]
numpy.testing.assert_allclose(
AxisAlignedBoundingBox(minp, maxp).deltas, expected)
def setUpClass(cls):
cls.gh_image_fp = os.path.join(TEST_DATA_DIR, "grace_hopper.png")
cls.gh_file_element = DataFileElement(cls.gh_image_fp)
assert cls.gh_file_element.content_type() == 'image/png'
cls.gh_cropped_image_fp = \
os.path.join(TEST_DATA_DIR, 'grace_hopper.100x100+100+100.png')
cls.gh_cropped_file_element = DataFileElement(cls.gh_cropped_image_fp)
assert cls.gh_cropped_file_element.content_type() == 'image/png'
cls.gh_cropped_bbox = AxisAlignedBoundingBox([100, 100], [200, 200])
def test_load_as_matrix_with_crop_not_in_bounds(self):
"""
Test that error is raised when crop bbox is not fully within the image
bounds.
"""
inst = PilImageReader()
# Nowhere close
bb = AxisAlignedBoundingBox([5000, 6000], [7000, 8000])
with pytest.raises(RuntimeError,
match=r"Crop provided not within input image\. "
r"Image shape: \(512, 600\), crop: "):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
# Outside left side
bb = AxisAlignedBoundingBox([-1, 1], [2, 2])
with pytest.raises(RuntimeError,
match=r"Crop provided not within input image\. "
r"Image shape: \(512, 600\), crop: "):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
# Outside top side
bb = AxisAlignedBoundingBox([1, -1], [2, 2])
with pytest.raises(RuntimeError,
match=r"Crop provided not within input image\. "
r"Image shape: \(512, 600\), crop: "):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
# Outside right side
bb = AxisAlignedBoundingBox([400, 400], [513, 600])
with pytest.raises(RuntimeError,
match=r"Crop provided not within input image\. "
r"Image shape: \(512, 600\), crop: "):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
# Outside bottom side
bb = AxisAlignedBoundingBox([400, 400], [512, 601])
with pytest.raises(RuntimeError,
match=r"Crop provided not within input image\. "
r"Image shape: \(512, 600\), crop: "):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
def test_bbox_set_vertices_maintain_type_mixed() -> None:
"""
Test that ndarray dtypes inherit from mixed float and integer values
explicitly.
"""
# Mock instance so as to not actually hit __init__ method.
m_bb = mock.MagicMock(spec_set=AxisAlignedBoundingBox)
# Integer/Float coordinates (3d)
minv = [0, 1, 2] # integer
maxv = [1, 2.0, 3] # float
AxisAlignedBoundingBox._set_vertices(m_bb, minv, maxv)
assert issubclass(m_bb.min_vertex.dtype.type, numpy.integer)
assert issubclass(m_bb.max_vertex.dtype.type, numpy.float64)
# Float/Integer coordinates (3d)
minv = [0, 1, 2.0] # type: ignore # float
maxv = [1, 2, 3] # type: ignore # integer
AxisAlignedBoundingBox._set_vertices(m_bb, minv, maxv)
assert issubclass(m_bb.min_vertex.dtype.type, numpy.float64)
assert issubclass(m_bb.max_vertex.dtype.type, numpy.integer)
def test_bbox_equality_other_not_close_enough(m_bbox_rtol: int,
m_bbox_atol: int) -> None:
"""
Test modifying tolerance values
:return:
"""
e = 1e-8 # default absolute tolerance on ``numpy.allclose`` function.
bb1 = AxisAlignedBoundingBox([1, 2, 3], [2, 3, 4])
bb2 = AxisAlignedBoundingBox([1 + e, 2 + e, 3 + e], [2 + e, 3 + e, 4 + e])
# Basic array equality is exact, which should show that these are not
# strictly equal.
# noinspection PyUnresolvedReferences
assert (bb1.min_vertex != bb2.min_vertex).all()
# noinspection PyUnresolvedReferences
assert (bb1.max_vertex != bb2.max_vertex).all()
# If we reduce the tolerances, the 1e-8 difference will become intolerable.
m_bbox_rtol.return_value = 1.e-10 # type: ignore
m_bbox_atol.return_value = 1.e-16 # type: ignore
assert not (bb1 == bb2)
def test_load_as_matrix_with_crop_not_integer(self):
"""
Test passing a bounding box that is not integer aligned, which should
raise an error in the super call.
"""
inst = PilImageReader()
bb = AxisAlignedBoundingBox([100, 100.6], [200, 200.2])
with pytest.raises(ValueError,
match=r"Crop bounding box must be "
r"composed of integer "
r"coordinates\."):
inst.load_as_matrix(self.gh_file_element, pixel_crop=bb)
def test_serialize_deserialize_pickle() -> None:
"""
Test expected state representation.
"""
min_v = (4.2, 8.9, 1)
max_v = (9.2, 9.0, 48)
bb1 = AxisAlignedBoundingBox(min_v, max_v)
#: :type: AxisAlignedBoundingBox
bb2 = pickle.loads(pickle.dumps(bb1))
numpy.testing.assert_allclose(bb2.min_vertex, min_v)
numpy.testing.assert_allclose(bb2.max_vertex, max_v)
def test_load_as_matrix_crop_zero_volume() -> None:
"""
Test that a ValueError is raised when a crop bbox is passed with zero
volume.
"""
m_reader = mock.MagicMock(spec=ImageReader)
m_data = mock.MagicMock(spec_set=DataElement)
crop_bb = AxisAlignedBoundingBox([0, 0], [0, 0])
with pytest.raises(ValueError,
match=r"Volume of crop bounding box must be "
r"greater than 0\."):
ImageReader.load_as_matrix(m_reader, m_data, pixel_crop=crop_bb)
def setUpClass(cls) -> None:
# Initialize test image paths/elements/associated crop boxes.
cls.gh_image_fp = os.path.join(TEST_DATA_DIR, "grace_hopper.png")
cls.gh_file_element = DataFileElement(cls.gh_image_fp, readonly=True)
assert cls.gh_file_element.content_type() == 'image/png'
cls.gh_cropped_image_fp = \
os.path.join(TEST_DATA_DIR, 'grace_hopper.100x100+100+100.png')
cls.gh_cropped_file_element = \
DataFileElement(cls.gh_cropped_image_fp, readonly=True)
assert cls.gh_cropped_file_element.content_type() == 'image/png'
cls.gh_cropped_bbox = AxisAlignedBoundingBox([100, 100], [200, 200])
