def setup(self):
global tmp_dir
self.filepath = os.path.join(tmp_dir, "test_imaging_dataset.sima")
self.tiff_ds = ImagingDataset(
[Sequence.create('TIFF', example_tiff(), 1, 1)],
self.filepath)
def setup(self):
self.base_seq = sima.Sequence.create("TIFF", example_tiff(), 2, 2)
self.displacements = np.random.randint(0, 10, self.base_seq.shape[:3] + (2,))
max_disp = np.amax([np.amax(d.reshape(-1, d.shape[-1]), 0) for d in self.displacements], 0)
self.final_shape = np.array(self.base_seq.shape)[1:-1]
self.final_shape[1:3] += max_disp
def test_hmm_missing_frame(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
masked_seq = frames.mask([(5, None, None)])
corrected = self.hm2d.correct(
[masked_seq], os.path.join(tmp_dir, 'test_hmm_3.sima'))
assert_(all(np.all(np.isfinite(seq.displacements))
for seq in corrected))
def setup(self):
self.tiff_seq = sima.Sequence.create("TIFF", example_tiff(), 2, 2)
self.tmp_dir = os.path.join(os.path.dirname(__file__), "tmp")
try:
os.mkdir(self.tmp_dir)
except:
pass
def test_hmm_missing_frame(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
masked_seq = frames.mask([(5, None, None)])
corrected = self.hm2d.correct([masked_seq],
os.path.join(tmp_dir, 'test_hmm_3.sima'))
assert_(
all(np.all(np.isfinite(seq.displacements)) for seq in corrected))
assert_(np.prod(corrected.frame_shape) > 0)
def test_hmm_missing_column(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
mask = np.zeros(frames.shape[1:-1], dtype=bool)
mask[:, :, 30] = True
masked_seq = frames.mask([(None, mask, None)])
corrected = self.hm2d.correct(
[masked_seq], os.path.join(tmp_dir, 'test_hmm_3.sima'))
assert_(all(np.all(np.isfinite(seq.displacements))
for seq in corrected))
def test_hmm_missing_column(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
mask = np.zeros(frames.shape[1:-1], dtype=bool)
mask[:, :, 30] = True
masked_seq = frames.mask([(None, mask, None)])
corrected = self.hm2d.correct(
[masked_seq],
os.path.join(tmp_dir, 'test_hmm_missing_column.sima'))
assert_(all(np.all(np.isfinite(seq.displacements))
for seq in corrected))
def test_hmm_tmp(self): # TODO: remove when displacements.pkl is updated
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
corrected = self.hm2d.correct(
[frames], os.path.join(tmp_dir, 'test_hmm_2.sima'))
with open(misc.example_data() + '/displacements.pkl', 'rb') as fh:
displacements = [d.reshape((20, 1, 128, 2))
for d in pickle.load(fh)]
displacements_ = [seq.displacements for seq in corrected]
assert_(abs(displacements_[0] - displacements[0]).max() <= 1)
def test_hmm_missing_frame(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
masked_seq = frames.mask([(5, None, None)])
with warnings.catch_warnings():
warnings.simplefilter('ignore')
corrected = self.hm2d.correct(
[masked_seq], os.path.join(
tmp_dir, 'test_hmm_missing_frame.sima'))
assert_(all(np.all(np.isfinite(seq.displacements))
for seq in corrected))
assert_(np.prod(corrected.frame_shape) > 0)
def test_hmm_tmp(self): # TODO: remove when displacements.pkl is updated
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
corrected = self.hm2d.correct(
[frames], os.path.join(tmp_dir, 'test_hmm_2.sima'))
with open(misc.example_data() + '/displacements.pkl', 'rb') as fh:
displacements = [d.reshape((20, 1, 128, 2))
for d in pickle.load(fh)]
displacements_ = [seq.displacements for seq in corrected]
diffs = displacements_[0] - displacements[0]
assert_(
((diffs - diffs.mean(axis=2).mean(axis=1).mean(axis=0)) > 1).mean()
<= 0.001)
def test_hmm(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
corrected = self.hm2d.correct(
[frames], os.path.join(tmp_dir, 'test_hmm.sima'))
with open(misc.example_data() + '/displacements.pkl', 'rb') as fh:
displacements = [d.reshape((20, 1, 128, 2))
for d in pickle.load(fh)]
displacements_ = [seq.displacements for seq in corrected]
assert_almost_equal(displacements_, displacements)
def test_hmm(self):
global tmp_dir
frames = Sequence.create('TIFF', example_tiff())
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
corrected = self.hm2d.correct(
[frames], os.path.join(tmp_dir, 'test_hmm.sima'))
with open(misc.example_data() + '/displacements.pkl', 'rb') as fh:
displacements = [d.reshape((20, 1, 128, 2))
for d in pickle.load(fh)]
displacements_ = [seq.displacements for seq in corrected]
assert_almost_equal(displacements_, displacements)
def setup(self):
self.tiff_seq = sima.Sequence.create('TIFF', example_tiff(), 2, 2)
def setup(self):
global tmp_dir
self.filepath = os.path.join(tmp_dir, "test_imaging_dataset.sima")
self.tiff_ds = ImagingDataset(
[Sequence.create('TIFF', example_tiff(), 1, 1)], self.filepath)
def setup(self):
self.tiff_seq = sima.Sequence.create('TIFF', example_tiff(), 2, 2)
self.masked_mask = np.zeros((5, 2, 128, 256, 2), dtype=bool)
def setup(self):
self.tiff_seq = sima.Sequence.create('TIFF', example_tiff(), 2, 2)
def setup(self):
self.tiff_seq = sima.Sequence.create('TIFF', example_tiff(), 2, 2)
self.masked_mask = np.zeros((5, 2, 128, 256, 2), dtype=bool)
