glatos_receivers: Construct, check, and validate a glatos_receivers object

In ocean-tracking-network/glatos: A package for the Great Lakes Acoustic Telemetry Observation System

Construct, check, and validate a glatos_receivers object

Description

Creates, checks, or validates a glatos_receivers object.

Usage

glatos_receivers(..., validate = TRUE)

as_glatos_receivers(x, validate = TRUE)

is_glatos_receivers(x)

validate_glatos_receivers(x)

Arguments

...	Named vectors, minimally one for each required column of the specified class: deploy_lat numeric, latitude, in decimal degrees, WGS84, southern hemisphere is negative. deploy_long numeric, longitude, in decimal degrees, WGS84, western hemistphere is negative. deploy_date_time must be POSIXct, timestamp (in UTC) when receiver was deployed (i.e., start of telemetry sampling interval.) recover_date_time must be POSIXct, timestamp (in UTC) when receiver was recovered (i.e., end of telemetry sampling interval.) ins_serial_no must be character, unique serial number of receiver.
validate	logical, indicates if column names and classes should be checked against requirements.
x	A data.frame or object that inherits from data.frame (e.g., data.table, tibble) and contains all required columns (see ...).

Construction

glatos_receivers() creates a glatos_receivers from individual vectors (one for each column) and optionally checks for required column names and classes using validate_glatos_receivers().

Coercion

as_glatos_receivers() coerces a data.frame, or object that inherits from data.frame, to glatos_receivers and optionally checks for required column names and classes using validate_glatos_receivers().

Validation

is_glatos_receivers() checks class attribute for "glatos_receivers"

validate_glatos_receivers() checks for required column names and classes

Examples

#  glatos_receivers
x <- data.frame(
  station = c("WHT-009", "FDT-001", "FDT-004", "FDT-003"),
  deploy_lat = c(43.7, 45.9, 45.9, 45.9),
  deploy_long = c(-82.5, -83.5, -83.5, -83.5),
  deploy_date_time = as.POSIXct(
    c(
      "2010-09-22 18:05:00",
      "2010-11-12 15:07:00",
      "2010-11-12 15:36:00",
      "2010-11-12 15:56:00"
    ),
    tz = "UTC"
  ),
  recover_date_time = as.POSIXct(
    c(
      "2012-08-15 16:52:00",
      "2012-05-15 13:25:00",
      "2012-05-15 14:15:00",
      "2012-05-15 14:40:00"
    ),
    tz = "UTC"
  ),
  ins_serial_no = c("109450", "442", "441", "444")
)

gr_df1 <- glatos_receivers(
  station = x$station,
  deploy_lat = x$deploy_lat,
  deploy_long = x$deploy_long,
  deploy_date_time = x$deploy_date_time,
  recover_date_time = x$recover_date_time,
  ins_serial_no = x$ins_serial_no
)


# as_glatos_receivers
gr_df2 <- as_glatos_receivers(x)


# sf input

library(sf)

# use remove = FALSE to keep required columns
x_sf <- sf::st_as_sf(x,
  coords = c("deploy_long", "deploy_lat"),
  remove = FALSE
)

gr_sf <- as_glatos_receivers(x_sf)


# tibble input
library(dplyr)

x_tbl <- dplyr::as_tibble(x)

gr_tbl <- as_glatos_receivers(x_tbl)

# All below will error as invalid

# data.frame input; missing column name
x2 <- rename(x,
  receiver_loc = station,
  deploy_timestamp = deploy_date_time
)

try(
  gr2 <- as_glatos_receivers(x2)
)

# data.frame input; wrong column class
x3 <- mutate(x,
  ins_serial_no = as.integer(ins_serial_no),
  deploy_date_time = as.character(deploy_date_time)
)

try(
  gr3 <- as_glatos_receivers(x3)
)

# Validation and checking

validate_glatos_receivers(x)

is_glatos_receivers(x) # FALSE

is_glatos_receivers(gr_df1) # TRUE

ocean-tracking-network/glatos documentation built on April 17, 2025, 10:38 p.m.