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Refuses rather than improvises when the feature sets differ: a model trained on 11 markers cannot place cells described by 9, and quietly filling the gap with zeros would produce coordinates that look plausible and mean nothing.

Usage

project_umap(saved, mat, n_threads = 1L, transform = NULL)

Arguments

saved

A model loaded by load_umap_model().

mat

Numeric matrix, cells x features.

n_threads

Number of threads. Default 1L.

transform

this run's transform; where it differs from the one the model stored, each feature is carried onto the stored one first.