pseudodynamics.functions.eval_funs.continuous_params

pseudodynamics.functions.eval_funs.continuous_params(pde_model, DataSet, param='g', n_interval=10, groupby_key=None, agg_fun='mean', chunk_size=1000, device='cpu')

Predict the continuous change of dynamic parameters. The cellstate observed at the last timepoint is used.

Args:

pde_model : nn.Module, sub-class of pdp.models.pde_params_base DataSet : sub-class of pdp.readers.HighdimAnnDS param : str, one of [‘g’, ‘v’, ‘D’, ‘u’] n_interval : number of intermediate point between two timepoints groupby_key : str, aggregate the predicted param according to cell type or cluster, one of the obs_key of the adata agg_fun : aggregtion function chunk_size : int, minibatch size device : str, on which device to compute the parameters i.e. cpu or cuda:0, cuda:1 …