R/writeTUMNodeNetwork.R

In BiomarkABS/PITcleanr: Cleans up PIT tag capture histories

#' @title Tumwater Node Network
#'
#' @description Create data.frame describing all the observation nodes in the Tumwater dam version of DABOM, including how they are related to one another
#'
#' @author Kevin See
#'
#'
#' @import dplyr tibble stringr tidyr
#' @return NULL
#' @examples writeTUMNodeNetwork()

writeTUMNodeNetwork = function() {

  bin_all = list('TUM' =
                   list('TUM',
                        list('PES' =
                               list('PES',
                                    'PEU')),
                        list('ICL' =
                               list('ICL',
                                    'LNF' =
                                      list('LNF',
                                           'LEAV'),
                                    'ICM' =
                                      list('ICM',
                                           'ICU'))),
                        'CHW',
                        list('CHL' =
                               list('CHL',
                                    'CHU')),
                        list('UWE' =
                               list('UWE',
                                    'WTL',
                                    'LWN',
                                    'NAL' =
                                      list('NAL',
                                           'NAU')))))



  site_df_init = unlist(bin_all) %>%
    tibble::enframe(name = 'path',
                    value = 'SiteID') %>%
    dplyr::select(SiteID, path) %>%
    mutate_at(vars(path),
              list(~ str_remove_all(., '[[:digit:]]+$'))) %>%
    rowwise() %>%
    mutate(path = if_else(stringr::str_sub(path, start = -nchar(SiteID)) != SiteID,
                          paste(path, SiteID, sep = '.'),
                          path)) %>%
    ungroup()

  network_descrip = stringr::str_split(site_df_init$path,
                                       '\\.',
                                       simplify = T) %>%
    as_tibble(.name_repair = "unique") %>%
    rlang::set_names(paste0('Step', 1:ncol(.)))

  site_df = site_df_init %>%
    bind_cols(network_descrip) %>%
    tidyr::gather(brk, upstrm_site, matches('Step')) %>%
    mutate(upstrm_site = ifelse(upstrm_site == '', NA, upstrm_site)) %>%
    tidyr::spread(brk, upstrm_site,
                  fill = '') %>%
    mutate(SiteID = factor(SiteID,
                           levels = site_df_init$SiteID)) %>%
    arrange(SiteID)

  return(site_df)
}