def test_allen_smFISH_cropped_data():
# set random seed to errors provoked by optimization functions
np.random.seed(777)
# load the experiment
experiment = starfish.data.allen_smFISH(use_test_data=True)
primary_image = experiment.fov().get_image(FieldOfView.PRIMARY_IMAGES)
clip = Filter.Clip(p_min=10, p_max=100)
clipped_image = clip.run(primary_image, in_place=False)
bandpass = Filter.Bandpass(lshort=0.5, llong=7, threshold=0.0, truncate=4)
bandpassed_image = bandpass.run(clipped_image, in_place=False)
clip = Filter.Clip(p_min=10, p_max=100, is_volume=False)
clipped_bandpassed_image = clip.run(bandpassed_image, in_place=False)
sigma = (1, 0, 0) # filter only in z, do nothing in x, y
glp = Filter.GaussianLowPass(sigma=sigma, is_volume=True)
z_filtered_image = glp.run(clipped_bandpassed_image, in_place=False)
tlmpf = FindSpots.TrackpyLocalMaxPeakFinder(
spot_diameter=5, # must be odd integer
min_mass=0.02,
max_size=2, # this is max radius
separation=7,
noise_size=0.65, # this is not used because preprocess is False
preprocess=False,
percentile=10,
# this is irrelevant when min_mass, spot_diameter, and max_size are set properly
verbose=True,
is_volume=True,
)
spots = tlmpf.run(z_filtered_image) # noqa
decoder = starfish.spots.DecodeSpots.PerRoundMaxChannel(
codebook=experiment.codebook,
trace_building_strategy=TraceBuildingStrategies.SEQUENTIAL
)
decoder.run(spots=spots)
from starfish.image import Filter
from starfish.spots import FindSpots
experiment = data.allen_smFISH(use_test_data=True)
img = experiment['fov_001'].get_image(FieldOfView.PRIMARY_IMAGES)
# filter to remove noise, remove background, blur, and clip
bandpass = Filter.Bandpass(lshort=.5, llong=7, threshold=0.0)
glp = Filter.GaussianLowPass(
sigma=(1, 0, 0),
is_volume=True
)
clip1 = Filter.Clip(p_min=50, p_max=100)
clip2 = Filter.Clip(p_min=99, p_max=100, is_volume=True)
clip1.run(img, in_place=True)
bandpass.run(img, in_place=True)
glp.run(img, in_place=True)
clip2.run(img, in_place=True)
tlmpf = FindSpots.TrackpyLocalMaxPeakFinder(
spot_diameter=5, # must be odd integer
min_mass=0.02,
max_size=2, # this is max radius
separation=7,
preprocess=False,
percentile=10, # this has no effect when min_mass, spot_diameter, and max_size are set properly
verbose=True,
)
spots = tlmpf.run(img)
threshold=0.1,
is_volume=True,
measurement_type='mean',
)
lmp = FindSpots.LocalMaxPeakFinder(min_distance=2,
stringency=8,
min_obj_area=6,
max_obj_area=600,
is_volume=True)
tlmpf = FindSpots.TrackpyLocalMaxPeakFinder(
spot_diameter=11,
min_mass=0.2,
max_size=8,
separation=3,
preprocess=False,
percentile=80,
verbose=True,
)
# crop imagestacks
crop_selection = {Axes.X: (300, 700), Axes.Y: (300, 700)}
cropped_imgs = imgs.sel(crop_selection)
cropped_dots = dots.sel(crop_selection)
# find spots on cropped images
bd_spots = bd.run(image_stack=cropped_imgs, reference_image=cropped_dots)
lmp_spots = lmp.run(image_stack=cropped_imgs, reference_image=cropped_dots)
tlmpf_spots = tlmpf.run(image_stack=cropped_imgs, reference_image=cropped_dots)