csgfix

A simple R package for fixing data for use with the ctmm package

Installation

The package can be installed from GitHub using the devtools package.

#install.packages("devtools")
devtools::install_github("consciglobal/csgfix")

In addition, the packages move and ctmm are required. These can be downloaded from CRAN.

install.packages("move")
install.packages("ctmm")

Functions and Parameters

bank

the primary function of the package, changes data from the input format to a data frame in the Movebank format (for use with the move function)
data: dataframe, see "Data Input"
projectionType: logical or character or function, how the coordinates should be projected, FALSE or the name of a projection (like "na" for North America Equidistant Conic) or a function(lat, long, datetime) where lat and long are vectors of numbers and datetime is a vector of POSIXct corresponding to the time of those observations. Should return a data frame with two numeric columns, x and y.
timeformat: character, the format Date_Time is in (for use with as.POSIXct)
ct: logical, TRUE to use POSIXct timestamps, FALSE to use characters that are in the Movebank format
tonad83: logical, TRUE if you want to convert from WGS84 to NAD83 before projection (only used when projectionType is a character) example:

  data <- read.csv("AKgoeasHrly_ex.txt")
  data2 <- bank(data)

quickMove

shortcut for creating Move object from data
data: dataframe, the data used for bank
proj: CRS object, the projection type for move::move
timeformat: character, the format Date_Time is in for use with as.POSIXct ("%m/%d/%Y %T" by default, see: https://stat.ethz.ch/R-manual/R-devel/library/base/html/strptime.html)
removeDuplicatedTimestamps: logical, just what it says, sent to move::move (FALSE by default)
projectionType: logical or character or function, sent to bank (FALSE by default, make sure you also change proj to reflect any changes made here)
example:

  data <- read.csv("AKgoeasHrly_ex.txt")
  proj <- sp::CRS("+proj=latlong +ellps=WGS84 +datum=WGS84")
  movedata <- quickMove(data, proj=proj, timeformat="%m/%d/%Y %H:%M")

quickTelemetry

shortcut for creating a Telemetry object from a Move object from data
shortcut for ctmm::as.telemetry(quickMove(data, ...), proj), uses all the same parameters as quickMove example:

  data <- read.csv("AKgoeasHrly_ex.txt")
  proj <- sp::CRS("+proj=latlong +ellps=WGS84 +datum=WGS84")
  telemetry <- quickTelemetry(data, proj=proj, timeformat="%m/%d/%Y %H:%M")

projectionEquidistantConic

projects lat and long to x and y using equidistant conic projection
lat and long: numeric vectors of latitude and longitude (to be equivalent to ArcGIS, these must be in NAD83)
type: logical or character, FALSE or the name of a preset set of parameters (like "na" for North America Equidistant Conic) accepted values: "na"
reflat, reflong, sp1, sp2: numeric, parameters for the projection if not using type (reference latitude, reference longitude, and standard parallels)
example:

  cartesian <- projectionEquidistantConic(data$Latitude, data$Longitude, "na")

projectionNA

shortcut for projectionEquidistantConic(lat, long, "na")
lat and long: numeric vectors, same as projectionEquidistantConic
example:

  cartesian <- projectionNA(data$Latitude, data$Longitude)

generateRandomFlight

creates a dataframe of random flight data that is totally random and nothing like a real bird, but still useful for testing
origin: numeric vector of length 2, the coordinates where bird will start
names: character, "csg" or "movebank", depending on how you want the columns of the resulting data to be named
obs: numeric, number of observations to create
maxturn: numeric, the maximum change in heading in each step (measured in degrees, can turn maxturn left or right)
timestep: numeric, the number of seconds between each observation
timestart: POSIXct, the time you want the first observation to be
multi: numeric, the distance the bird travels in each observation (in change in lat/long) will be a random number with a minimum of 0 and a maximum of multi
rand: function, a function that generates random numbers in [0,1], where the first parameter is the number of numbers to generate (default is normal distribution, mean=0.5, sd=0.125, limited to [0,1])
fakemisc: logical, if you want to fake the other columns needed for bank
n: numeric, the Animal_ID or FALSE to randomize it (used only if fakemisc is TRUE)
example:

  dataG1 <- generateRandomFlight() #every parameter has a default value, running the function with no parameters will work fine
  dataG2 <- generateRandomFlight(origin=c(63.53, -150.27), obs=500)

Data Input

bank uses specific column names of the data. Specifically, it needs columns named "Animal_ID", "Date_Time", "GMT_offset", "Latitude", "Longitude", "KPH", "Heading", "Altitude", "HDOP" and either "ASY" or "Season" and "SeasonYr"