syncell.trajectory.Trajectory

class syncell.trajectory.Trajectory

A toolset for single-cell trajectory modeling. See:

Danger

This code, currently, should be considered as an untested pre-release version

References

Jeremy Copperman, Sean M. Gross, Young Hwan Chang, Laura M. Heiser, and Daniel M. Zuckerman. Morphodynamical cell-state description via live-cell imaging trajectory embedding. Biorxiv 10.1101/2021.10.07.463498, 2021.

__init__()

Work-in-progress init function. For now, just start adding attribute definitions in here. .. todo:

- Most logic from initialize() should be moved in here.
- Also, comment all of these here. Right now most of them have comments throughout the code.
- Reorganize these attributes into some meaningful structure

Methods

__init__()	Work-in-progress init function. For now, just start adding attribute definitions in here. .. todo::.
afft(img)
align_image(img, msk)
assemble_dmat([symmetrize])
cluster_cells(n_clusters[, x])
cluster_trajectories(n_clusters[, x])
dist(img1, img2)
dist_with_masks(x1, x2, m1, m2)
explore_2D_celltraj(x, traj, cell_traj[, ...])
explore_2D_celltraj_nn(x, traj[, pts, npts, ...])
explore_2D_img(x[, cell_traj, dm1, dm2, ...])
explore_2D_nn(x[, dm1, dm2, pathto, nvis, ...])
featBoundary(msk[, ncomp, center, nth])
featBoundaryCB(msk, fmsk[, ncomp, center, nth])
featHaralick(img[, levels])
featZernike(img[, radius, degree])
feat_comdx(indcell[, bmsk, bunch_clusters])
get_Xtraj_celltrajectory(cell_traj[, Xtraj, ...])
get_all_trajectories([cell_inds])
get_alpha(i1, i2)
get_beta(i1, i2)
get_border_profile(imgcell, mskcell, fmskcell)
get_borders(msk)
get_bunch_clusters(bmsk[, t])
get_cc_cs_border(mskcell, fmskcell[, bordersize])
get_cell_blocks(msk[, minsize])
get_cell_boundary_size(indcell[, msk, cpix])
get_cell_bunches(fmsk[, bunchcut])
get_cell_data()
get_cell_images([indcells])
get_cell_neighborhood(indcell[, bmsk, ...])
get_cell_positions()
get_cell_trajectory(cell_ind[, n_hist])
get_cellborder_images([indcells, bordersize])
get_clean_mask(msk[, minsize])
get_comdx_features([cell_inds])
get_dmat(x1[, x2])
get_dmatF_row([rows])
get_dmatRT_row([rows])
get_dx(i1)
get_dx_alpha([cell_inds, thbins, nth, rcut])
get_dx_rdf([cell_inds, rbins, nr, rmax])
get_dx_tcf([trajectories])
get_dx_theta([cell_inds, thbins, nth, rcut])
get_embedding([sigma, k, nN, inds])
get_entropy_production([clusters, Mt, ...])
get_fmaskSet(start_frame, end_frame)
get_fmask_data(n_frame)	Returns a list of bluepy.blte.Service objects representing the services offered by the device.
get_frames()
get_imageSet(start_frame, end_frame)
get_imageSet_trans()
get_imageSet_trans_turboreg()
get_image_data(n_frame)	Example function with PEP 484 type annotations.
get_kscore(Mt[, eps])
get_lineage_bunch_overlap([distcut, ...])
get_lineage_mindist([distcut, pathto])
get_minRT(x1, x2, m1, m2[, nth, dth, dx])
get_minT(m1, m2[, nt, dt])
get_neg_overlap(t, *args)
get_pair_cluster_rdf([cell_indsA, ...])
get_pair_distRT(t, *args)
get_pair_rdf([cell_indsA, cell_indsB, ...])
get_path_entropy_2point(x0, x1[, clusters, ...])
get_path_ll_2point(x0, x1[, clusters, Mt, ...])
get_pca([dim, var_cutoff])
get_pca_fromdata(data[, dim, var_cutoff])
get_scaled_sigma([neps, nr])
get_stack_trans(mskSet)
get_stack_trans_frompoints(mskSet)
get_stack_trans_turboreg(imgs)
get_tcf([trajectories, x])
get_traj_ll_gmean(xt[, clusters, Mt, ...])
get_traj_segments(seg_length)
get_trajectory_embedding(trajl[, inds, ...])
get_trajectory_steps([inds, traj, Xtraj, ...])
get_transition_matrix(x0, x1[, clusters])
get_transition_matrix_CG(x0, x1, clusters, ...)
get_unique_trajectories([cell_inds, ...])
get_xtraj_tcf([trajectories])
initialize(fileSpecifier, modelName)	Returns a list of bluepy.blte.Service objects representing the services offered by the device.
pad_image(img, maxedge)
plot_embedding([colors])
plot_pca([nd, colors])
prepare_cell_features([apply_znorm])
prepare_cell_images([znormalize])
prune_embedding([rcut, nd, sigma, k, nN, inds])
save_all()
save_dmat_row(row, dmat_row[, overwrite])
seq_in_seq(sub, full)
show_cells(cell_inds[, show_segs, stride])
show_cells_from_image(img, msk, cellblocks)
show_cells_queue([X])
show_image_pair(img1, img2[, msk1, msk2])
transform_image(x1, t)
znorm(x)