ToolsΒΆ

functions.reader_funs.sample_deltax_from_knn(adata)

the Key function defines the noise sampling process given the starting point i

functions.reader_funs.compute_mellon_timesense_u(...)

wrapping mellon time-sense density

functions.reader_funs.train_test_split_adata(adata)

functions.reader_funs.make_coord_adata(...)

construct adata based on cellstate coodinates from expression matrix based adata the new adata is mainly for visualizing v

functions.eval_funs.agg_param(adata, param)

Aggregate dynamic parameters by specific cell state label

functions.eval_funs.continuous_params(...[, ...])

Predict the continuous change of dynamic parameters.

functions.eval_funs.density_shortterm_simulation(...)

simulate density for each cells for any two consecutive timepoints

functions.eval_funs.project_params_to_pseudotime(...)

Project the parameters to the pseudotime and aggregate them by bins

functions.eval_funs.assign_nearest_cell(...)

functions.eval_funs.W_distance(u_b, u_simulate)

Normalize the density and compute the Wasserstein distance between observation and prediction.

functions.eval_funs.KLD_density(u_b, u_simulate)

Normalize the density and compute the KL-divergence between observation and prediction