Prepare a Partition for Habitat Classification

Extract a stream network subset, enrich with channel width, and pre-compute access and habitat gradient breaks. Returns a list of species classification jobs ready for frs_habitat_species().

Usage

frs_habitat_partition(
  conn,
  aoi,
  label,
  species,
  params_all,
  params_fresh,
  source = "whse_basemapping.fwa_stream_networks_sp",
  break_sources = NULL,
  verbose = TRUE
)

Arguments

conn

A DBI::DBIConnection object (from frs_db_conn()).

aoi

AOI specification passed to frs_extract(). Character watershed group code, sf polygon, named list, or NULL.

label

Character. Short label for table naming (e.g. "bulk", "study_area"). Used in table names like working.streams_{label}, working.breaks_access_{label}_{thr}.

species

Data frame with columns species_code, access_gradient, and spawn_gradient_max. One row per species.

params_all

Named list from frs_params().

params_fresh

Data frame from parameters_fresh.csv.

source

Character. Source table for the stream network. Default "whse_basemapping.fwa_stream_networks_sp".

break_sources

List of break source specs passed to frs_habitat_access(), or NULL for gradient-only. See frs_habitat_access() for spec format.

verbose

Logical. Print progress. Default TRUE.

Value

A list with:

jobs

List of job specs for frs_habitat_species()

cleanup_tables

Character vector of intermediate table names

Details

A partition is any spatial subset of a stream network — a watershed group, a custom polygon, a study area. The function does not assume the partition is a BC watershed group; that fish-specific lookup happens in frs_habitat() before calling this function.

See also

Other habitat: frs_aggregate(), frs_break(), frs_break_apply(), frs_break_find(), frs_break_validate(), frs_categorize(), frs_classify(), frs_col_generate(), frs_col_join(), frs_extract(), frs_habitat(), frs_habitat_access(), frs_habitat_species()

Examples

if (FALSE) { # \dontrun{
conn <- frs_db_conn()
params_all <- frs_params(csv = system.file("extdata",
  "parameters_habitat_thresholds.csv", package = "fresh"))
params_fresh <- read.csv(system.file("extdata",
  "parameters_fresh.csv", package = "fresh"))

# Prepare BULK partition
species <- data.frame(
  species_code = c("CO", "BT"),
  access_gradient = c(0.15, 0.25),
  spawn_gradient_max = c(0.0549, 0.0549))

prep <- frs_habitat_partition(conn, aoi = "BULK", label = "bulk",
  species = species, params_all = params_all,
  params_fresh = params_fresh)

# Run one species from the prepared jobs
job <- prep$jobs[[1]]
frs_habitat_species(conn, job$species_code, job$base_tbl,
  breaks = job$acc_tbl, breaks_habitat = job$hab_tbl,
  params_sp = job$params_sp, fresh_sp = job$fresh_sp,
  to = job$to)

DBI::dbDisconnect(conn)
} # }