perplexity: Calculate the perplexity of a celda model
In celda: CEllular Latent Dirichlet Allocation

Description Usage Arguments Value Examples

Perplexity is a statistical measure of how well a probability model can predict new data. Lower perplexity indicates a better model.

perplexity(x, celdaMod, ...)

## S4 method for signature 'SingleCellExperiment,ANY'
perplexity(
  x,
  useAssay = "counts",
  altExpName = "featureSubset",
  newCounts = NULL
)

## S4 method for signature 'matrix,celda_CG'
perplexity(x, celdaMod, newCounts = NULL)

## S4 method for signature 'matrix,celda_C'
perplexity(x, celdaMod, newCounts = NULL)

## S4 method for signature 'matrix,celda_G'
perplexity(x, celdaMod, newCounts = NULL)

`x`	Can be one of A SingleCellExperiment object returned by celda_C, celda_G or celda_CG, with the matrix located in the `useAssay` assay slot. Rows represent features and columns represent cells. Integer counts matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate `celdaMod`.
`celdaMod`	Celda model object. Only works if `x` is an integer counts matrix.
`...`	Ignored. Placeholder to prevent check warning.
`useAssay`	A string specifying which assay slot to use if `x` is a SingleCellExperiment object. Default "counts".
`altExpName`	The name for the altExp slot to use. Default "featureSubset".
`newCounts`	A new counts matrix used to calculate perplexity. If NULL, perplexity will be calculated for the matrix in `useAssay` slot in `x`. Default NULL.

Numeric. The perplexity for the provided x (and celdaModel).

data(sceCeldaCG)
perplexity <- perplexity(sceCeldaCG)
data(celdaCGSim, celdaCGMod)
perplexity <- perplexity(celdaCGSim$counts, celdaCGMod)
data(celdaCSim, celdaCMod)
perplexity <- perplexity(celdaCSim$counts, celdaCMod)
data(celdaGSim, celdaGMod)
perplexity <- perplexity(celdaGSim$counts, celdaGMod)