def create_background_mask(self, expansion=6):
"""
Creates a mask that only includes background pixels of this segment.
TODO: explain parameter
"""
if self.threshold_timepoint is None:
self._background_mask = np.logical_not(
expand_mask(self.mask, width=int(1.6 * expansion)) +
np.logical_not(self.speckle_mask))
else:
self._background_mask = np.logical_not(
expand_mask(self.mask, width=expansion) +
np.logical_not(self.speckle_mask))
def create_colony_intensity(self):
bg_intensity = np.empty(self.n_times)
col_intensity = np.empty(self.n_times)
self._colony_intensity = np.empty(self.n_times)
# Loop is necessary due to mask destroying structure
for t in range(self.n_times):
col_intensity[t] = np.mean(
color_sum(self.images[t, :, :])[self.mask])
bg_intensity[t] = np.median(
color_sum(self.images[t, :, :])[self.background_mask])
intensity = (col_intensity - bg_intensity)
self._colony_intensity = intensity
if (np.mean(intensity[:6]) < 0):
factor = 1.5 if (np.mean(intensity[:6]) < -20) else 1.8
background_px = color_sum(self.images[0])[self.background_mask]
bright_px = np.multiply(
color_sum(self.images[0]), self.background_mask
) > np.mean(background_px) + factor * np.std(background_px)
bright_px = expand_mask(bright_px, width=3)
self._background_mask &= np.logical_not(bright_px)
try:
self.create_colony_intensity()
except (RecursionError):
bg_intensity = np.empty(self.n_times)
col_intensity = np.empty(self.n_times)
# Loop is necessary due to mask destroying structure
for t in range(self.n_times):
col_intensity[t] = np.mean(
color_sum(self.images[t, :, :])[self.mask])
bg_intensity[t] = np.median(
color_sum(self.images[t, :, :])[self.background_mask])
intensity = (col_intensity - bg_intensity)
def test_point(self, apply_mask, needs_expansion):
point = tuple([np.random.randint(x) for x in size])
colour = np.random.randint(ncolours)
background = np.zeros((*size, ncolours), dtype=np.uint8)
background[(*point, colour)] = 1
dummy_plate = Plate(
images=np.zeros([times, *size, ncolours]),
bg=background,
)
mask = apply_mask(dummy_plate)
if needs_expansion:
mask = expand_mask(mask, 1)
assert mask[point]
if needs_expansion:
far_from_point = np.logical_not(
expand_mask(background[:, :, colour] > 0, 2))
assert not np.any(mask[far_from_point])
else:
assert np.sum(mask) == 1
def create_speckle_mask(
self,
gradient_threshold=1000,
intensity_factor=4,
temporal_threshold=1200,
expansion=3,
):
"""
Tries to automatically detect speckles.
TODO:
explain parameters
"""
self._speckle_mask = np.logical_not(
expand_mask(self._gradient_mask(gradient_threshold)
| self._intensity_mask(intensity_factor)
| self._temporal_mask(temporal_threshold),
width=expansion))
def test_points(self): size = (100,80) points = np.vstack([ np.random.randint(n,size=5) for n in size ]).T radius = 13 mask = np.zeros(size,dtype=bool) for point in points: mask[tuple(point)] = True expanded_mask = expand_mask(mask,radius) for i in range(size[0]): for j in range(size[1]): dist = min( np.linalg.norm(point-[i,j]) for point in points ) assert (dist<=radius) == expanded_mask[i,j]
def test_zero_radius(self): random_mask = np.random.choice([True,False],size=(100,80)) assert_array_equal( expand_mask(random_mask,0), random_mask )