def test_shift_and_crop_static(self):
shift_node = ShiftAugment(sigma=1, shift_axis=0)
shift_node.ndim = 2
upstream_arr = np.arange(16).reshape(4, 4)
sub_shift_array = np.zeros(8, dtype=int).reshape(4, 2)
roi_shape = (4, 4)
voxel_size = Coordinate((1, 1))
downstream_arr = np.arange(16).reshape(4, 4)
result = shift_node.shift_and_crop(upstream_arr, roi_shape,
sub_shift_array, voxel_size)
self.assertTrue(np.array_equal(result, downstream_arr))
def test_shift_and_crop3(self):
shift_node = ShiftAugment(sigma=1, shift_axis=1)
shift_node.ndim = 2
upstream_arr = np.arange(16).reshape(4, 4)
sub_shift_array = np.zeros(8, dtype=int).reshape(4, 2)
sub_shift_array[:, 0] = np.array([0, 1, 0, 2], dtype=int)
roi_shape = (2, 4)
voxel_size = Coordinate((1, 1))
downstream_arr = np.array([[8, 5, 10, 3], [12, 9, 14, 7]], dtype=int)
result = shift_node.shift_and_crop(upstream_arr, roi_shape,
sub_shift_array, voxel_size)
# print(result)
self.assertTrue(np.array_equal(result, downstream_arr))
def test_shift_and_crop2(self):
shift_node = ShiftAugment(sigma=1, shift_axis=0)
shift_node.ndim = 2
upstream_arr = np.arange(16).reshape(4, 4)
sub_shift_array = np.zeros(8, dtype=int).reshape(4, 2)
sub_shift_array[:, 1] = np.array([0, -1, -2, 0], dtype=int)
roi_shape = (4, 2)
voxel_size = Coordinate((1, 1))
downstream_arr = np.array([[0, 1], [5, 6], [10, 11], [12, 13]],
dtype=int)
result = shift_node.shift_and_crop(upstream_arr, roi_shape,
sub_shift_array, voxel_size)
self.assertTrue(np.array_equal(result, downstream_arr))
def test_shift_points5(self):
data = [
Node(id=0, location=np.array([3, 0])),
Node(id=1, location=np.array([3, 2])),
Node(id=2, location=np.array([3, 4])),
Node(id=3, location=np.array([3, 6])),
Node(id=4, location=np.array([3, 8])),
]
spec = GraphSpec(Roi(offset=(0, 0), shape=(15, 10)))
points = Graph(data, [], spec)
request_roi = Roi(offset=(3, 0), shape=(9, 10))
shift_array = np.array([[3, 0], [-3, 0], [0, 0], [-3, 0], [3, 0]],
dtype=int)
lcm_voxel_size = Coordinate((3, 2))
shifted_data = [
Node(id=0, location=np.array([6, 0])),
Node(id=2, location=np.array([3, 4])),
Node(id=4, location=np.array([6, 8])),
]
result = ShiftAugment.shift_points(
points,
request_roi,
shift_array,
shift_axis=1,
lcm_voxel_size=lcm_voxel_size,
)
# print("test 4", result.data, shifted_data)
self.assertTrue(self.points_equal(result.nodes, shifted_data))
self.assertTrue(result.spec == GraphSpec(request_roi))
def test_prepare1(self):
key = ArrayKey("TEST_ARRAY")
spec = ArraySpec(voxel_size=Coordinate((1, 1)), interpolatable=True)
hdf5_source = Hdf5Source(self.fake_data_file, {key: "testdata"},
array_specs={key: spec})
request = BatchRequest()
shape = Coordinate((3, 3))
request.add(key, shape, voxel_size=Coordinate((1, 1)))
shift_node = ShiftAugment(sigma=1, shift_axis=0)
with build((hdf5_source + shift_node)):
shift_node.prepare(request)
self.assertTrue(shift_node.ndim == 2)
self.assertTrue(shift_node.shift_sigmas == tuple([0.0, 1.0]))
def test_compute_upstream_roi2(self):
request_roi = Roi(offset=(0, 0), shape=(5, 10))
sub_shift_array = np.array([[2, 0], [-1, 0], [5, 0], [-2, 0], [0, 0]],
dtype=int)
upstream_roi = Roi(offset=(-5, 0), shape=(12, 10))
result = ShiftAugment.compute_upstream_roi(request_roi,
sub_shift_array)
self.assertTrue(upstream_roi == result)
def test_get_sub_shift_array2(self):
total_roi = Roi(offset=(0, 0), shape=(6, 6))
item_roi = Roi(offset=(1, 2), shape=(3, 3))
shift_array = np.arange(12).reshape(6, 2).astype(int)
shift_axis = 0
lcm_voxel_size = Coordinate((1, 1))
sub_shift_array = np.array([[2, 3], [4, 5], [6, 7]], dtype=int)
result = ShiftAugment.get_sub_shift_array(total_roi, item_roi,
shift_array, shift_axis,
lcm_voxel_size)
self.assertTrue(np.array_equal(result, sub_shift_array))
def test_construct_global_shift_array_static(self):
shift_axis_len = 5
shift_sigmas = (0.0, 1.0)
prob_slip = 0
prob_shift = 0
lcm_voxel_size = Coordinate((1, 1))
shift_array = np.zeros(shape=(shift_axis_len, len(shift_sigmas)),
dtype=int)
result = ShiftAugment.construct_global_shift_array(
shift_axis_len, shift_sigmas, prob_shift, prob_slip,
lcm_voxel_size)
self.assertTrue(np.array_equal(result, shift_array))
def test_pipeline3(self):
array_key = ArrayKey("TEST_ARRAY")
points_key = GraphKey("TEST_POINTS")
voxel_size = Coordinate((1, 1))
spec = ArraySpec(voxel_size=voxel_size, interpolatable=True)
hdf5_source = Hdf5Source(self.fake_data_file, {array_key: "testdata"},
array_specs={array_key: spec})
csv_source = CsvPointsSource(
self.fake_points_file,
points_key,
GraphSpec(roi=Roi(shape=Coordinate((100, 100)), offset=(0, 0))),
)
request = BatchRequest()
shape = Coordinate((60, 60))
request.add(array_key, shape, voxel_size=Coordinate((1, 1)))
request.add(points_key, shape)
shift_node = ShiftAugment(prob_slip=0.2,
prob_shift=0.2,
sigma=5,
shift_axis=0)
pipeline = ((hdf5_source, csv_source) + MergeProvider() +
RandomLocation(ensure_nonempty=points_key) + shift_node)
with build(pipeline) as b:
request = b.request_batch(request)
# print(request[points_key])
target_vals = [
self.fake_data[point[0]][point[1]] for point in self.fake_points
]
result_data = request[array_key].data
result_points = list(request[points_key].nodes)
result_vals = [
result_data[int(point.location[0])][int(point.location[1])]
for point in result_points
]
for result_val in result_vals:
self.assertTrue(
result_val in target_vals,
msg=
"result value {} at points {} not in target values {} at points {}"
.format(
result_val,
list(result_points),
target_vals,
self.fake_points,
),
)
def test_construct_global_shift_array2(self):
shift_axis_len = 5
shift_sigmas = (0.0, 1.0)
prob_slip = 0
prob_shift = 1
lcm_voxel_size = Coordinate((1, 1))
shift_array = np.array([[0, 0], [0, -1], [0, 0], [0, 0], [0, 1]],
dtype=int)
result = ShiftAugment.construct_global_shift_array(
shift_axis_len, shift_sigmas, prob_slip, prob_shift,
lcm_voxel_size)
self.assertTrue(len(result) == shift_axis_len)
for position_shift in result:
self.assertTrue(position_shift[0] == 0)
self.assertTrue(np.array_equal(shift_array, result))
def test_pipeline2(self):
key = ArrayKey("TEST_ARRAY")
spec = ArraySpec(voxel_size=Coordinate((3, 1)), interpolatable=True)
hdf5_source = Hdf5Source(self.fake_data_file, {key: "testdata"},
array_specs={key: spec})
request = BatchRequest()
shape = Coordinate((3, 3))
request.add(key, shape, voxel_size=Coordinate((3, 1)))
shift_node = ShiftAugment(prob_slip=0.2,
prob_shift=0.2,
sigma=1,
shift_axis=0)
with build((hdf5_source + shift_node)) as b:
b.request_batch(request)
def test_shift_points2(self):
data = [Node(id=1, location=np.array([0, 1]))]
spec = GraphSpec(Roi(offset=(0, 0), shape=(5, 5)))
points = Graph(data, [], spec)
request_roi = Roi(offset=(0, 1), shape=(5, 3))
shift_array = np.array([[0, 0], [0, -1], [0, 0], [0, 0], [0, 1]],
dtype=int)
lcm_voxel_size = Coordinate((1, 1))
result = ShiftAugment.shift_points(
points,
request_roi,
shift_array,
shift_axis=0,
lcm_voxel_size=lcm_voxel_size,
)
# print("test 2", result.data, data)
self.assertTrue(self.points_equal(result.nodes, data))
self.assertTrue(result.spec == GraphSpec(request_roi))