def CreatePlaneSegmentation():
w, h = 5, 5
img_mask = [[[1.0 for x in range(w)] for y in range(h)],
[[2.0 for x in range(w)] for y in range(h)]]
pix_mask = [[1, 2, 1.0], [3, 4, 1.0], [5, 6, 1.0], [7, 8, 2.0],
[9, 10, 2.0]]
iSS = ImageSeries(name='test_iS',
data=np.ones((2, 2, 2)),
unit='unit',
external_file=['external_file'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=[1., 2.])
oc = OpticalChannel('test_optical_channel', 'description', 500.)
device = Device(name='device_name')
ip = ImagingPlane('test_imaging_plane', oc, 'description', device, 600.,
300., 'indicator', 'location', (1, 2, 1, 2, 3), 4.0,
'unit', 'reference_frame')
pS = PlaneSegmentation('description', ip, 'test_name', iSS)
pS.add_roi(pixel_mask=pix_mask[0:3], image_mask=img_mask[0])
pS.add_roi(pixel_mask=pix_mask[3:5], image_mask=img_mask[1])
return pS
def setUpContainer(self):
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('optchan1',
'a fake OpticalChannel', 500.)
return ImagingPlane('imgpln1', self.optical_channel,
'a fake ImagingPlane', self.device, 600., 300.,
'GFP', 'somewhere in the brain')
def buildPlaneSegmentation(self):
w, h = 5, 5
img_mask = [[[1.0 for x in range(w)] for y in range(h)],
[[2.0 for x in range(w)] for y in range(h)]]
pix_mask = [(1, 2, 1.0), (3, 4, 1.0), (5, 6, 1.0), (7, 8, 2.0),
(9, 10, 2.)]
ts = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
self.image_series = ImageSeries(name='test_iS',
source='a hypothetical source',
dimension=[2],
external_file=['images.tiff'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=ts)
self.optical_channel = OpticalChannel('test_optical_channel',
'optical channel source',
'optical channel description',
500.)
self.imaging_plane = ImagingPlane(
'test_imaging_plane', 'ophys integration tests',
self.optical_channel, 'imaging plane description',
'imaging_device_1', 600., '2.718', 'GFP', 'somewhere in the brain',
(1, 2, 1, 2, 3), 4.0, 'manifold unit', 'A frame to refer to')
self.img_mask = deepcopy(img_mask)
self.pix_mask = deepcopy(pix_mask)
pS = PlaneSegmentation('integration test PlaneSegmentation',
'plane segmentation description',
self.imaging_plane, 'test_plane_seg_name',
self.image_series)
pS.add_roi('1234', pix_mask[0:3], img_mask[0])
pS.add_roi('5678', pix_mask[3:5], img_mask[1])
return pS
def CreatePlaneSegmentation():
w, h = 5, 5
img_mask = [[[1.0 for x in range(w)] for y in range(h)],
[[2.0 for x in range(w)] for y in range(h)]]
pix_mask = [[1, 2, 1.0], [3, 4, 1.0], [5, 6, 1.0], [7, 8, 2.0],
[9, 10, 2.0]]
iSS = ImageSeries(name='test_iS',
source='a hypothetical source',
data=list(),
unit='unit',
external_file=['external_file'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=list())
oc = OpticalChannel('test_optical_channel', 'test_source', 'description',
'emission_lambda')
ip = ImagingPlane('test_imaging_plane', 'test_source', oc, 'description',
'device', 'excitation_lambda', 'imaging_rate',
'indicator', 'location', (1, 2, 1, 2, 3), 4.0, 'unit',
'reference_frame')
pS = PlaneSegmentation('test source', 'description', ip, 'test_name', iSS)
pS.add_roi(pix_mask[0:3], img_mask[0])
pS.add_roi(pix_mask[3:5], img_mask[1])
return pS
def buildPlaneSegmentationNoRois(self):
""" Return an PlaneSegmentation and set related objects """
ts = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
self.image_series = ImageSeries(name='test_iS',
dimension=[2],
external_file=['images.tiff'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=ts)
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel(
name='test_optical_channel',
description='optical channel description',
emission_lambda=500.)
self.imaging_plane = ImagingPlane(
name='test_imaging_plane',
optical_channel=self.optical_channel,
description='imaging plane description',
device=self.device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='GFP',
location='somewhere in the brain',
reference_frame='a frame to refer to')
return PlaneSegmentation(description='description',
imaging_plane=self.imaging_plane,
name='test_plane_seg_name',
reference_images=self.image_series)
def CreatePlaneSegmentation():
w, h = 5, 5
img_mask = [[0 for x in range(w)] for y in range(h)]
w, h = 5, 2
pix_mask = [[0 for x in range(w)] for y in range(h)]
pix_mask_weight = [0 for x in range(w)]
iSS = ImageSeries(name='test_iS',
source='a hypothetical source',
data=list(),
unit='unit',
external_file=['external_file'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=list())
roi1 = ROI('roi1', 'test source', 'roi description1', pix_mask,
pix_mask_weight, img_mask, iSS)
roi2 = ROI('roi2', 'test source', 'roi description2', pix_mask,
pix_mask_weight, img_mask, iSS)
roi_list = (roi1, roi2)
oc = OpticalChannel('test_optical_channel', 'test_source', 'description',
'emission_lambda')
ip = ImagingPlane('test_imaging_plane', 'test_source', oc, 'description',
'device', 'excitation_lambda', 'imaging_rate',
'indicator', 'location', (1, 2, 1, 2, 3), 4.0, 'unit',
'reference_frame')
ps = PlaneSegmentation('name', 'test source', 'description', roi_list, ip,
iSS)
return ps
def test_init(self):
w, h = 5, 5
img_mask = [[[1.0 for x in range(w)] for y in range(h)],
[[2.0 for x in range(w)] for y in range(h)]]
pix_mask = [[1, 2, 1.0], [3, 4, 1.0], [5, 6, 1.0], [7, 8, 2.0],
[9, 10, 2.0]]
iSS = ImageSeries(name='test_iS',
source='a hypothetical source',
data=list(),
unit='unit',
external_file=['external_file'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=list())
oc = OpticalChannel('test_optical_channel', 'test_source',
'description', 500.)
ip = ImagingPlane('test_imaging_plane', 'test_source', oc,
'description', 'device', 600., 'imaging_rate',
'indicator', 'location', (1, 2, 1, 2, 3), 4.0,
'unit', 'reference_frame')
pS = PlaneSegmentation('test source', 'description', ip, 'test_name',
iSS)
pS.add_roi("1234", pix_mask[0:3], img_mask[0])
pS.add_roi("5678", pix_mask[3:5], img_mask[1])
self.assertEqual(pS.description, 'description')
self.assertEqual(pS.source, 'test source')
self.assertEqual(pS.imaging_plane, ip)
self.assertEqual(pS.reference_images, iSS)
self.assertEqual(pS.pixel_masks.data, pix_mask)
self.assertEqual(pS.image_masks.data, img_mask)
def test_init(self):
oc = OpticalChannel('test_name', 'description', 500.)
self.assertEqual(oc.description, 'description')
self.assertEqual(oc.emission_lambda, 500.)
device = Device(name='device_name')
ip = ImagingPlane('test_imaging_plane', oc, 'description', device, 600.,
300., 'indicator', 'location', (50, 100, 3), 4.0, 'unit', 'reference_frame')
self.assertEqual(ip.optical_channel[0], oc)
self.assertEqual(ip.device, device)
self.assertEqual(ip.excitation_lambda, 600.)
self.assertEqual(ip.imaging_rate, 300.)
self.assertEqual(ip.indicator, 'indicator')
self.assertEqual(ip.location, 'location')
self.assertEqual(ip.manifold, (50, 100, 3))
self.assertEqual(ip.conversion, 4.0)
self.assertEqual(ip.unit, 'unit')
self.assertEqual(ip.reference_frame, 'reference_frame')
tPS = TwoPhotonSeries('test_tPS', unit='unit', field_of_view=[2., 3.],
imaging_plane=ip, pmt_gain=1.0, scan_line_rate=2.0, external_file=['external_file'],
starting_frame=[1, 2, 3], format='tiff', timestamps=list())
self.assertEqual(tPS.name, 'test_tPS')
self.assertEqual(tPS.unit, 'unit')
self.assertEqual(tPS.field_of_view, [2., 3.])
self.assertEqual(tPS.imaging_plane, ip)
self.assertEqual(tPS.pmt_gain, 1.0)
self.assertEqual(tPS.scan_line_rate, 2.0)
self.assertEqual(tPS.external_file, ['external_file'])
self.assertEqual(tPS.starting_frame, [1, 2, 3])
self.assertEqual(tPS.format, 'tiff')
self.assertIsNone(tPS.dimension)
def test_init(self):
oc, device = self.set_up_dependencies()
ip = ImagingPlane(name='test_imaging_plane',
optical_channel=oc,
description='description',
device=device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='indicator',
location='location',
reference_frame='reference_frame',
origin_coords=[10, 20],
origin_coords_unit='oc_unit',
grid_spacing=[1, 2, 3],
grid_spacing_unit='gs_unit')
self.assertEqual(ip.optical_channel[0], oc)
self.assertEqual(ip.device, device)
self.assertEqual(ip.excitation_lambda, 600.)
self.assertEqual(ip.imaging_rate, 300.)
self.assertEqual(ip.indicator, 'indicator')
self.assertEqual(ip.location, 'location')
self.assertEqual(ip.reference_frame, 'reference_frame')
self.assertEqual(ip.origin_coords, [10, 20])
self.assertEqual(ip.origin_coords_unit, 'oc_unit')
self.assertEqual(ip.grid_spacing, [1, 2, 3])
self.assertEqual(ip.grid_spacing_unit, 'gs_unit')
def make_imaging_plane(self, source):
self.optical_channel = OpticalChannel('optchan1', source,
'a fake OpticalChannel', 500.)
self.imaging_plane = ImagingPlane('imgpln1', source,
self.optical_channel,
'a fake ImagingPlane',
'imaging_device_1', 600., '2.718',
'GFP', 'somewhere in the brain')
def make_imaging_plane(self):
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('optchan1',
'a fake OpticalChannel', 500.)
self.imaging_plane = ImagingPlane('imgpln1', self.optical_channel,
'a fake ImagingPlane', self.device,
600., 300., 'GFP',
'somewhere in the brain')
def addContainer(self, file):
oc = OpticalChannel('optchan1', 'unit test TestImagingPlaneIO',
'a fake OpticalChannel', '3.14')
ip = ImagingPlane('imgpln1', 'unit test TestImagingPlaneIO', oc,
'a fake ImagingPlane', 'imaging_device_1', '6.28',
'2.718', 'GFP', 'somewhere in the brain')
file.set_imaging_plane(ip)
return ip
def setUpContainer(self):
self.optical_channel = OpticalChannel('optchan1',
'unit test TestImagingPlaneIO',
'a fake OpticalChannel', 500.)
return ImagingPlane('imgpln1', 'unit test TestImagingPlaneIO',
self.optical_channel, 'a fake ImagingPlane',
'imaging_device_1', 600., '2.718', 'GFP',
'somewhere in the brain')
def test_args(self):
oc = OpticalChannel('test_name', 'description', 500.)
device = Device(name='device_name')
ip = ImagingPlane('test_imaging_plane', oc, 'description', device, 600.,
300., 'indicator', 'location', (50, 100, 3), 4.0, 'unit', 'reference_frame')
with self.assertRaises(ValueError): # no data or external file
TwoPhotonSeries('test_tPS', unit='unit', field_of_view=[2., 3.],
imaging_plane=ip, pmt_gain=1.0, scan_line_rate=2.0,
starting_frame=[1, 2, 3], format='tiff', timestamps=[1., 2.])
def getBoilerPlateObjects(self):
iSS = ImageSeries(name='test_iS', data=np.ones((2, 2, 2)), unit='unit',
external_file=['external_file'], starting_frame=[1, 2, 3], format='tiff', timestamps=list())
device = Device(name='device_name')
oc = OpticalChannel('test_optical_channel', 'description', 500.)
ip = ImagingPlane('test_imaging_plane', oc, 'description', device, 600.,
300., 'indicator', 'location', (1, 2, 1, 2, 3), 4.0, 'unit', 'reference_frame')
return iSS, ip
def test_conversion_deprecated(self):
oc = OpticalChannel('test_name', 'description', 500.)
self.assertEqual(oc.description, 'description')
self.assertEqual(oc.emission_lambda, 500.)
device = Device(name='device_name')
msg = "The 'conversion' argument is deprecated in favor of 'origin_coords' and 'grid_spacing'."
with self.assertWarnsWith(DeprecationWarning, msg):
ImagingPlane('test_imaging_plane', oc, 'description', device, 600., 300., 'indicator', 'location',
None, 2.0)
def make_imaging_plane(self):
""" Make an ImagingPlane and related objects """
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('optchan1',
'a fake OpticalChannel', 500.)
self.imaging_plane = ImagingPlane('imgpln1',
self.optical_channel,
'a fake ImagingPlane',
self.device,
600.,
300.,
'GFP',
'somewhere in the brain',
reference_frame='unknown')
def setUpContainer(self):
""" Return the test ImagingPlane to read/write """
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('optchan1',
'a fake OpticalChannel', 500.)
return ImagingPlane('imgpln1',
self.optical_channel,
'a fake ImagingPlane',
self.device,
600.,
300.,
'GFP',
'somewhere in the brain',
reference_frame='unknonwn')
def test_conversion_deprecated(self):
oc, device = self.set_up_dependencies()
msg = "The 'conversion' argument is deprecated in favor of 'origin_coords' and 'grid_spacing'."
with self.assertWarnsWith(DeprecationWarning, msg):
ImagingPlane(name='test_imaging_plane',
optical_channel=oc,
description='description',
device=device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='indicator',
location='location',
conversion=2.0)
def make_imaging_plane(self):
""" Make an ImagingPlane and related objects """
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel(
name='optchan1',
description='a fake OpticalChannel',
emission_lambda=500.)
self.imaging_plane = ImagingPlane(name='imgpln1',
optical_channel=self.optical_channel,
description='a fake ImagingPlane',
device=self.device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='GFP',
location='somewhere in the brain',
reference_frame='unknown')
def setBoilerPlateObjects(self):
ts = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
self.image_series = ImageSeries(name='test_iS', dimension=[2],
external_file=['images.tiff'],
starting_frame=[1, 2, 3], format='tiff', timestamps=ts)
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('test_optical_channel',
'optical channel description', 500.)
self.imaging_plane = ImagingPlane('test_imaging_plane',
self.optical_channel,
'imaging plane description',
self.device,
600., 300., 'GFP', 'somewhere in the brain',
(1, 2, 1, 2, 3), 4.0, 'manifold unit', 'A frame to refer to')
return PlaneSegmentation('description', self.imaging_plane, 'test_plane_seg_name',
self.image_series)
def test_init(self):
oc = OpticalChannel('test_name', 'test_source', 'description',
'emission_lambda')
self.assertEqual(oc.description, 'description')
self.assertEqual(oc.emission_lambda, 'emission_lambda')
ip = ImagingPlane('test_imaging_plane', 'test source', oc,
'description', 'device', 'excitation_lambda',
'imaging_rate', 'indicator', 'location',
(1, 2, 1, 2, 3), 4.0, 'unit', 'reference_frame')
self.assertEqual(ip.optical_channel[0], oc)
self.assertEqual(ip.device, 'device')
self.assertEqual(ip.excitation_lambda, 'excitation_lambda')
self.assertEqual(ip.imaging_rate, 'imaging_rate')
self.assertEqual(ip.indicator, 'indicator')
self.assertEqual(ip.location, 'location')
self.assertEqual(ip.manifold, (1, 2, 1, 2, 3))
self.assertEqual(ip.conversion, 4.0)
self.assertEqual(ip.unit, 'unit')
self.assertEqual(ip.reference_frame, 'reference_frame')
tPS = TwoPhotonSeries('test_tPS',
'a hypothetical source',
data=list(),
unit='unit',
field_of_view=list(),
imaging_plane=ip,
pmt_gain=1.0,
scan_line_rate=2.0,
external_file=['external_file'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=list())
self.assertEqual(tPS.name, 'test_tPS')
self.assertEqual(tPS.source, 'a hypothetical source')
self.assertEqual(tPS.unit, 'unit')
self.assertEqual(tPS.field_of_view, list())
self.assertEqual(tPS.imaging_plane, ip)
self.assertEqual(tPS.pmt_gain, 1.0)
self.assertEqual(tPS.scan_line_rate, 2.0)
self.assertEqual(tPS.external_file, ['external_file'])
self.assertEqual(tPS.starting_frame, [1, 2, 3])
self.assertEqual(tPS.format, 'tiff')
self.assertEqual(tPS.dimension, [np.nan])
def buildPlaneSegmentation(self):
""" Return an PlaneSegmentation and set related objects """
w, h = 5, 5
img_mask = [[[1.0 for x in range(w)] for y in range(h)],
[[2.0 for x in range(w)] for y in range(h)]]
pix_mask = [(1, 2, 1.0), (3, 4, 1.0), (5, 6, 1.0), (7, 8, 2.0),
(9, 10, 2.)]
ts = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
self.image_series = ImageSeries(name='test_iS',
dimension=[2],
external_file=['images.tiff'],
starting_frame=[1, 2, 3],
format='tiff',
timestamps=ts)
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel('test_optical_channel',
'optical channel description',
500.)
self.imaging_plane = ImagingPlane('imgpln1',
self.optical_channel,
'a fake ImagingPlane',
self.device,
600.,
200.,
'GFP',
'somewhere in the brain',
(((1., 2., 3.), (4., 5., 6.)), ),
2.,
'a unit',
reference_frame='unknown')
self.img_mask = deepcopy(img_mask)
self.pix_mask = deepcopy(pix_mask)
self.pxmsk_index = [3, 5]
pS = PlaneSegmentation('plane segmentation description',
self.imaging_plane, 'test_plane_seg_name',
self.image_series)
pS.add_roi(pixel_mask=pix_mask[0:3], image_mask=img_mask[0])
pS.add_roi(pixel_mask=pix_mask[3:5], image_mask=img_mask[1])
return pS
def create_imaging_plane():
oc = OpticalChannel(name='test_optical_channel',
description='description',
emission_lambda=500.)
device = Device(name='device_name')
ip = ImagingPlane(name='test_imaging_plane',
optical_channel=oc,
description='description',
device=device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='indicator',
location='location',
reference_frame='reference_frame',
origin_coords=[10, 20],
origin_coords_unit='oc_unit',
grid_spacing=[1, 2, 3],
grid_spacing_unit='gs_unit')
return ip
def setUpContainer(self):
""" Return the test ImagingPlane to read/write """
self.device = Device(name='dev1')
self.optical_channel = OpticalChannel(
name='optchan1',
description='a fake OpticalChannel',
emission_lambda=500.)
return ImagingPlane(
name='imgpln1',
optical_channel=self.optical_channel,
description='a fake ImagingPlane',
device=self.device,
excitation_lambda=600.,
imaging_rate=300.,
indicator='GFP',
location='somewhere in the brain',
reference_frame='unknown',
origin_coords=[10., 20.],
origin_coords_unit='millimeters',
grid_spacing=[0.001, 0.001],
grid_spacing_unit='millimeters',
)
def addContainer(self, file):
oc = OpticalChannel('optchan1', 'unit test TestImagingPlaneIO',
'a fake OpticalChannel', '3.14')
ip = ImagingPlane('imgpln1', 'unit test TestImagingPlaneIO', oc,
'a fake ImagingPlane', 'imaging_device_1', '6.28',
'2.718', 'GFP', 'somewhere in the brain')
file.set_imaging_plane(ip)
data = list(zip(range(10), range(10, 20)))
timestamps = list(range(10))
fov = [2.0, 2.0, 5.0]
tps = TwoPhotonSeries('test_2ps',
'unit test TestTwoPhotonSeries',
data,
ip,
'image_unit',
'raw',
fov,
1.7,
3.4,
timestamps=timestamps,
dimension=[2])
file.add_acquisition(tps)
def setUpClass(self):
device = Device("imaging_device_1")
optical_channel = OpticalChannel("my_optchan", "description", 500.0)
self.imaging_plane = ImagingPlane(
name="imgpln1",
optical_channel=optical_channel,
description="a fake ImagingPlane",
device=device,
excitation_lambda=600.0,
imaging_rate=300.0,
indicator="GFP",
location="somewhere in the brain",
reference_frame="unknown",
origin_coords=[10, 20],
origin_coords_unit="millimeters",
grid_spacing=[0.001, 0.001],
grid_spacing_unit="millimeters",
)
self.image_series = TwoPhotonSeries(
name="test_image_series",
data=np.random.randn(100, 5, 5),
imaging_plane=self.imaging_plane,
starting_frame=[0],
rate=1.0,
unit="n.a",
)
self.img_seg = ImageSegmentation()
self.ps2 = self.img_seg.create_plane_segmentation(
"output from segmenting my favorite imaging plane",
self.imaging_plane,
"2d_plane_seg",
self.image_series,
)
self.ps2.add_column("type", "desc")
self.ps2.add_column("type2", "desc")
w, h = 3, 3
img_mask1 = np.zeros((w, h))
img_mask1[0, 0] = 1.1
img_mask1[1, 1] = 1.2
img_mask1[2, 2] = 1.3
self.ps2.add_roi(image_mask=img_mask1, type=1, type2=0)
img_mask2 = np.zeros((w, h))
img_mask2[0, 0] = 2.1
img_mask2[1, 1] = 2.2
self.ps2.add_roi(image_mask=img_mask2, type=1, type2=1)
img_mask2 = np.zeros((w, h))
img_mask2[0, 0] = 9.1
img_mask2[1, 1] = 10.2
self.ps2.add_roi(image_mask=img_mask2, type=2, type2=0)
img_mask2 = np.zeros((w, h))
img_mask2[0, 0] = 3.5
img_mask2[1, 1] = 5.6
self.ps2.add_roi(image_mask=img_mask2, type=2, type2=1)
fl = Fluorescence()
rt_region = self.ps2.create_roi_table_region("the first of two ROIs",
region=[0, 1, 2, 3])
rois_shape = 5
data = np.arange(10 * rois_shape).reshape([10, -1], order='F')
timestamps = np.array(
[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
rrs = fl.create_roi_response_series(name="my_rrs",
data=data,
rois=rt_region,
unit="lumens",
timestamps=timestamps)
self.df_over_f = DfOverF(rrs)
