moscot.base.output.MatrixSolverOutput.sparsify#

MatrixSolverOutput.sparsify(mode, value=None, batch_size=1024, n_samples=None, seed=None)#

Sparsify the transport_matrix.

This function sets all entries of the transport matrix below a certain threshold to \(0\) and returns a MatrixSolverOutput with sparsified transport matrix stored as a csr_matrix.

Warning

This function only serves for interfacing software which has to instantiate the transport matrix, moscot never uses the sparsified transport matrix.

Parameters:
  • mode (Literal['threshold', 'percentile', 'min_row']) –

    How to determine the value below which entries are set to \(0\). Valid options are:

    • ’threshold’ - value is the threshold below which entries are set to \(0\).

    • ’percentile’ - value is the percentile in \([0, 100]\) of the transport_matrix. below which entries are set to \(0\).

    • ’min_row’ - value is not used, it is chosen such that each row has at least 1 non-zero entry.

  • value (Optional[float]) – Value to use for sparsification.

  • batch_size (int) – How many rows to materialize when sparsifying the transport_matrix.

  • n_samples (Optional[int]) – If mode = 'percentile', determine the number of samples based on which the percentile is computed stochastically. Note this means that a matrix of shape [n_samples, min(transport_matrix.shape)] has to be instantiated. If None, n_samples is set to batch_size.

  • seed (Optional[int]) – Random seed needed for sampling if mode = 'percentile'.

Return type:

MatrixSolverOutput

Returns:

: Output with sparsified transport matrix.