def test_motion_correction_type():
# Double to double
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan, xy_motion=np.array([0.1, -0.1]))
assert (result.dtype == np.double), 'Motion correction is changing the scan dtype'
#int to double
test_scan = np.arange(16).reshape([4, 4])
result = galvo_corrections.correct_motion(test_scan, xy_motion=np.array([0.1, -0.1]))
assert (result.dtype == np.double), 'Motion correction is not changing the scan ' \
'dtype from int64 to double'
def test_motion_correction_type():
# Double to double
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([0.1, -0.1]))
assert (result.dtype == np.double
), 'Motion correction is changing the scan dtype'
#int to double
test_scan = np.arange(16).reshape([4, 4])
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([0.1, -0.1]))
assert (result.dtype == np.double), 'Motion correction is not changing the scan ' \
'dtype from int64 to double'
def load(self, key):
from pipeline.utils import galvo_corrections
# load
print("Loading scan", flush=True)
reader = scanreader.read_scan(
(experiment.Scan() & key).local_filenames_as_wildcard)
scan = reader[key["field"] - 1, :, :,
key["channel"] - 1].astype(np.float32)
# raster correction
print("Raster correction", flush=True)
pipe = (fuse.MotionCorrection() & key).module
raster_phase = (pipe.RasterCorrection() & key).fetch1("raster_phase")
fill_fraction = (pipe.ScanInfo() & key).fetch1("fill_fraction")
scan = galvo_corrections.correct_raster(scan, raster_phase,
fill_fraction)
# motion correction
print("Motion correction", flush=True)
x_shifts, y_shifts = (pipe.MotionCorrection() & key).fetch1(
"x_shifts", "y_shifts")
scan = galvo_corrections.correct_motion(scan, x_shifts, y_shifts)
return scan, reader.num_scanning_depths
def test_motion_correction_not_in_place():
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan, xy_motion=[0.1, -0.1],
in_place=False)
assert_allclose(test_scan, np.arange(16).reshape([4, 4]),
err_msg='Motion correction is not creating a copy of the scan when '
'asked to (in_place=False)')
def test_motion_correction_nan_xy_motion():
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([np.nan,
0.1]))
assert_allclose(result,
np.arange(16).reshape([4, 4]),
err_msg='Motion correction cannot handle nan in xy_motion')
def test_motion_correction_no_motion():
test_scan = np.double(np.arange(1, 17).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([0, 0]))
assert_allclose(
result,
np.arange(1, 17).reshape([4, 4]),
err_msg='Motion correction with zero xy_motion changes the result')
def test_motion_correction_list_input():
test_scan = np.double(np.arange(36).reshape([6, 6]))
result = galvo_corrections.correct_motion(test_scan, [0.1, -0.1])
desired_result = [[6.5, 7.5, 8.5, 9.5], [12.5, 13.5, 14.5, 15.5],
[18.5, 19.5, 20.5, 21.5], [24.5, 25.5, 26.5, 27.5]]
assert_allclose(result[1:-1, 1:-1], desired_result,
err_msg='Motion correction can not handle xy_motion as a list.')
def test_motion_correction_is_accurate():
test_scan = np.double(np.arange(36).reshape([6, 6]))
result = galvo_corrections.correct_motion(test_scan, xy_motion=np.array([0.1, -0.1]))
desired_result = [[6.5, 7.5, 8.5, 9.5], [12.5, 13.5, 14.5, 15.5],
[18.5, 19.5, 20.5, 21.5], [24.5, 25.5, 26.5, 27.5]]
assert_allclose(result[1:-1,1:-1], desired_result, err_msg='Motion correction is not '
'accurate enough')
def test_motion_correction_not_in_place():
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=[0.1, -0.1],
in_place=False)
assert_allclose(
test_scan,
np.arange(16).reshape([4, 4]),
err_msg='Motion correction is not creating a copy of the scan when '
'asked to (in_place=False)')
def test_motion_correction_list_input():
test_scan = np.double(np.arange(36).reshape([6, 6]))
result = galvo_corrections.correct_motion(test_scan, [0.1, -0.1])
desired_result = [[6.5, 7.5, 8.5, 9.5], [12.5, 13.5, 14.5, 15.5],
[18.5, 19.5, 20.5, 21.5], [24.5, 25.5, 26.5, 27.5]]
assert_allclose(
result[1:-1, 1:-1],
desired_result,
err_msg='Motion correction can not handle xy_motion as a list.')
def test_motion_correction_with_ndimensional_input():
test_scan = np.double(np.arange(128).reshape([4, 4, 2, 2, 2]))
xy_motion = np.reshape(np.arange(16)/10, [2,1,2,2,2])
result = galvo_corrections.correct_motion(test_scan, xy_motion=xy_motion)
desired_first_image = [[25.6, 33.6, 41.6, 49.6], [57.6, 65.6, 73.6, 81.6],
[89.6, 97.6, 105.6, 113.6], [96, 104, 112, 120]]
assert_allclose(result[:, :, 0, 0, 0], desired_first_image,
err_msg='Motion correction is not properly handling n-dimensional '
'scans')
def test_motion_correction_is_accurate():
test_scan = np.double(np.arange(36).reshape([6, 6]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([0.1, -0.1]))
desired_result = [[6.5, 7.5, 8.5, 9.5], [12.5, 13.5, 14.5, 15.5],
[18.5, 19.5, 20.5, 21.5], [24.5, 25.5, 26.5, 27.5]]
assert_allclose(result[1:-1, 1:-1],
desired_result,
err_msg='Motion correction is not '
'accurate enough')
def test_motion_correction_with_ndimensional_input():
test_scan = np.double(np.arange(128).reshape([4, 4, 2, 2, 2]))
xy_motion = np.reshape(np.arange(16) / 10, [2, 1, 2, 2, 2])
result = galvo_corrections.correct_motion(test_scan, xy_motion=xy_motion)
desired_first_image = [[25.6, 33.6, 41.6, 49.6], [57.6, 65.6, 73.6, 81.6],
[89.6, 97.6, 105.6, 113.6], [96, 104, 112, 120]]
assert_allclose(
result[:, :, 0, 0, 0],
desired_first_image,
err_msg='Motion correction is not properly handling n-dimensional '
'scans')
def test_motion_correction_nan_xy_motion():
test_scan = np.double(np.arange(16).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan,
xy_motion=np.array([np.nan, 0.1]))
assert_allclose(result, np.arange(16).reshape([4, 4]),
err_msg='Motion correction cannot handle nan in xy_motion')
def test_motion_correction_no_motion():
test_scan = np.double(np.arange(1, 17).reshape([4, 4]))
result = galvo_corrections.correct_motion(test_scan, xy_motion=np.array([0, 0]))
assert_allclose(result, np.arange(1, 17).reshape([4, 4]),
err_msg='Motion correction with zero xy_motion changes the result')
