R: Read comma-delimited file with "TDR" data

createTDR {diveMove} | R Documentation

## Read comma-delimited file with "TDR" data

### Description

Read a delimited (*.csv) file containing time-depth recorder (TDR) data from various TDR models. Return a `TDR` or `TDRspeed` object. `createTDR` creates an object of one of these classes from other objects.

### Usage

    createTDR(
      time,
      depth,
      concurrentData = data.frame(matrix(ncol = 0, nrow = length(time))),
      speed = FALSE,
      dtime,
      file
    )

    readTDR(
      file,
      dateCol = 1,
      timeCol = 2,
      depthCol = 3,
      speed = FALSE,
      subsamp = 5,
      concurrentCols = 4:6,
      dtformat = "%d/%m/%Y %H:%M:%S",
      tz = "GMT",
      ...
    )

### Arguments

`time` | A `POSIXct` object with date and time readings for each reading.
`depth` | numeric vector with depth readings.
`concurrentData` | `data.frame` with additional, concurrent data collected.
`speed` | logical: whether speed is included in one of the columns of concurrentCols.
`dtime` | numeric scalar: sampling interval used in seconds. If missing, it is calculated from the `time` argument.
`file` | character: a string indicating the path to the file to read. This can also be a text-mode connection, as allowed in `read.csv`.
`dateCol` | integer: column number containing dates, and optionally, times.
`timeCol` | integer: column number with times.
`depthCol` | integer: column number containing depth readings.
`subsamp` | numeric scalar: subsample rows in `file` with `subsamp` interval, in s.
`concurrentCols` | integer vector of column numbers to include as concurrent data collected.
`dtformat` | character: a string specifying the format in which the date and time columns, when pasted together, should be interpreted (see `strptime`).
`tz` | character: a string indicating the time zone assumed for the date and time readings.
`...` | Passed to `read.csv`

### Details

The input file is assumed to have a header row identifying each field, and all rows must be complete (i.e. have the same number of fields). Field names need not follow any convention. However, depth and speed are assumed to be in m, and m/s, respectively, for further analyses.

If speed is TRUE and concurrentCols contains a column named speed or velocity, then an object of class `TDRspeed` is created, where speed is considered to be the column matching this name.

### Value

An object of class `TDR` or `TDRspeed`.

### Functions

- `readTDR`: Create TDR object from file

### Note

Although `TDR` and `TDRspeed` classes check that time stamps are in increasing order, the integrity of the input must be thoroughly verified for common errors present in text output from TDR devices such as duplicate records, missing time stamps and non-numeric characters in numeric fields. These errors are much more efficiently dealt with outside of GNU using tools like `GNU awk` or `GNU sed`, so `diveMove` does not currently attempt to fix these errors.

### Author(s)

Sebastian P. Luque spluque@gmail.com

### Examples

    ## Do example to define object zz with location of dataset
    utils::example("dives", package="diveMove",
                   ask=FALSE, echo=FALSE)
    srcfn <- basename(zz)
    readTDR(zz, speed=TRUE, sep=";", na.strings="", as.is=TRUE)

    ## Or more pedestrian
    tdrX <- read.csv(zz, sep=";", na.strings="", as.is=TRUE)
    date.time <- paste(tdrX$date, tdrX$time)
    tdr.time <- as.POSIXct(strptime(date.time, format="%d/%m/%Y %H:%M:%S"),
                           tz="GMT")
    createTDR(tdr.time, tdrX$depth, concurrentData=data.frame(speed=tdrX$speed),
              file=srcfn, speed=TRUE)

[Package diveMove version 1.6.0 Index]