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#' Title
#'
#' @inheritParams otsu_mx_dataset
#'
#' @param tdat data in the `mx_dataset` object used to calculate Otsu thresholds
#' @param cols columns of markers in the `mx_dataset` object used to calculate Otsu threshold
#' @param slide column identifying different slides in the `mx_dataset` object used to calculate Otsu threshold
#' @param use_np_array boolean indicating if np_arrays are necessary
#'
#' @importFrom magrittr %>%
#'
#' @return list of calculated Otsu thresholds
#' @noRd
get_otsu_tab <- function(tdat,
cols,
slide,
table,
threshold,
use_np_array){
## if a python threshold, use np_array
if(use_np_array){
lapply(X=cols,function(x){
tdat %>%
dplyr::group_by_at(slide) %>%
dplyr::summarise(table=table,
slide_threshold=threshold(reticulate::np_array(.data[[x]])),
.groups = 'drop') %>%
dplyr::mutate(marker_threshold=(tdat %>% dplyr::summarise(m=threshold(reticulate::np_array(.data[[x]]))))$m) %>%
dplyr::mutate(marker=x) %>% dplyr::relocate(marker,.after=slide)
})
} else{ ##otherwise just use the data
lapply(X=cols,function(x){
tdat %>%
dplyr::group_by_at(slide) %>%
dplyr::summarise(table=table,
slide_threshold=threshold(.data[[x]]),
.groups = 'drop') %>%
dplyr::mutate(marker_threshold=(tdat %>% dplyr::summarise(m=threshold(.data[[x]])))$m) %>%
dplyr::mutate(marker=x) %>% dplyr::relocate(marker,.after=slide)
})
}
}
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