Calculates number of sites that have at least k label level repetitions for all values k. This information is useful for assessing how to set the number of cross-validation splits (and repeats of labels per cross-validation split) to use in a datasource. One can also assess the number of label level repetitions separately conditioned on another site_info variable. For example, if one has recordings from different brain regions, and the brain region information is contained in a site_info variable, then one could calculate how many sites have at least k repetitions for each stimulus in each brain region.

  site_info_grouping_name = NULL,
  label_levels = NULL



A string that list a path to a file that has data in binned format, or a data frame of binned_data that is in binned format.


A string specifying which label variable should be used for calculating the minimum number of level repetitions.


A character string that specifies if the number of sites that have k repetitions should be computed separately based on the levels of a site_info variable.


A character vector specifying which levels to include. If not set, all levels will be used.


A data frame with the class label_repetition which allows the results to be plotted. The returned data frame has a row for each label level, and columns with sequential integer values k = 0, 1, ... The values in the data frame show the number of sites that have at least k repetitions of a given stimulus.


The returned value is an S3 object that inherits from data.frame that has an associated plot() method.


data_file <- system.file("extdata/ZD_150bins_50sampled.Rda", package = "NeuroDecodeR")
label_rep_info <- get_num_label_repetitions(data_file, "stimulus_ID")