def save_timepoint_as_tiff(dask_array, idx):
# write your saving code here
writer = OmeTiffWriter(
f"//allen/aics/animated-cell/Dan/LLS2/T{idx}.ome.tif",
overwrite_file=True)
imgdata = dask_array.compute()
writer.save(imgdata, dimension_order="CZYX")
img_rna_smooth = image_smoothing_gaussian_3d(imgs_rna[i], sigma=1)
s3_param = [[1, 0.75*t_spots[i]], [2, 0.75*t_spots[i]]]
print('Identifying spots...')
bw = dot_3d_wrapper(img_rna_smooth, s3_param)
# watershed
minArea = 4
Mask = morphology.remove_small_objects(bw>0, min_size=minArea, connectivity=1, in_place=False)
labeled_mask = measure.label(Mask)
print('Performing watershed segmentation...')
peaks = feature.peak_local_max(imgs_rna[i],labels=labeled_mask, min_distance=2, indices=False)
Seed = morphology.binary_dilation(peaks, selem=morphology.ball(1))
Watershed_Map = -1*distance_transform_edt(bw)
seg = morphology.watershed(Watershed_Map, measure.label(Seed), mask=Mask, watershed_line=True)
seg = morphology.remove_small_objects(seg>0, min_size=minArea, connectivity=1, in_place=False)
print('Exporting mask...')
outname = img_name + '_mask^' + g + '.tiff'
p_out = os.path.join(outdir, 'masks', outname)
seg = seg > 0
out=seg.astype(np.uint8)
out[out>0]=255
writer = OmeTiffWriter(p_out, overwrite_file=True)
writer.save(out)
# output animation
print('Exporting animation...')
anim_name = img_name + '_mask^' + g + '.gif'
su.animate_zstacks([imgs_rna[i].transpose(1,2,0), seg.astype(int).transpose(1,2,0)], vmax=[0.2, 1], gif_name=os.path.join(outdir, 'anim', anim_name))