bw.time: Time conversion and plotting for bellwether data

In pcvr: Plant Phenotyping and Bayesian Statistics

Time conversion and plotting for bellwether data

Description

Time conversion and plotting for bellwether data

Usage

bw.time(
  df = NULL,
  mode = c("DAS", "DAP", "DAE"),
  plantingDelay = NULL,
  phenotype = NULL,
  cutoff = 1,
  timeCol = "timestamp",
  group = "Barcodes",
  plot = TRUE,
  format = "%Y-%m-%d %H:%M:%S",
  traitCol = "trait",
  valueCol = "value",
  index = NULL,
  digits = 0
)

Arguments

df	Data frame to use, this can be in wide or long format.
mode	One of "DAS", "DAP" or "DAE" (Days After Planting and Days After Emergence). Defaults to adding all columns. Note that if timeCol is not numeric then DAS is always returned.
plantingDelay	If 'mode' includes "DAP" then 'plantingDelay' is used to adjust "DAS"
phenotype	If 'mode' includes "DAE" then this is the phenotype used to classify emergence.
cutoff	If 'mode' includes "DAE" then this value is used to classify emergence. Defaults to 1, meaning an image with a value of 1 or more for 'phenotype' has "emerged".
timeCol	Column of input time values, defaults to "timestamp". If this is not numeric then it is assumed to be a timestamp in the format of the format argument.
group	Grouping variables to specify unique plants as a character vector. This defaults to "Barcodes". These taken together should identify a unique plant across time, although often "angle" or "rotation" should be added.
plot	Logical, should plots of the new time variables be printed?
format	An R POSIXct format, defaults to lemnatech standard format. This is only used if timeCol is not a numeric.
traitCol	Column with phenotype names, defaults to "trait". This should generally not need to be changed from the default. If this and valueCol are present in colnames(df) then the data is assumed to be in long format.
valueCol	Column with phenotype values, defaults to "value". This should generally not need to be changed from the default.
index	Optionally a time to use as the beginning of the experiment. This may be useful if you have multiple datasets or you are adding data from bw.water and plants were watered before being imaged or if you want to index days off of midnight. This defaults to NULL but will take any value coercible to POSIXct by as.POSIXct(... , tz="UTC") such as "2020-01-01 18:30:00"
digits	Number of digits to round DAS to if timeCol is not numeric, defaults to 0.

Value

The input dataframe with new numeric columns for different ways of describing time in the experiment. If plot is TRUE then a ggplot is also returned as part of a list.

Examples

f <- "https://raw.githubusercontent.com/joshqsumner/pcvrTestData/main/pcv4-single-value-traits.csv"
tryCatch(
  {
    sv <- read.pcv(
      f,
      mode = "wide", reader = "fread"
    )
    sv$genotype = substr(sv$barcode, 3, 5)
    sv$genotype = ifelse(sv$genotype == "002", "B73",
      ifelse(sv$genotype == "003", "W605S",
        ifelse(sv$genotype == "004", "MM", "Mo17")
      )
    )
    sv$fertilizer = substr(sv$barcode, 8, 8)
    sv$fertilizer = ifelse(sv$fertilizer == "A", "100",
      ifelse(sv$fertilizer == "B", "50", "0")
    )
    sv <- bw.time(sv,
      plantingDelay = 0, phenotype = "area_pixels", cutoff = 10,
      timeCol = "timestamp", group = c("barcode", "rotation"), plot = FALSE
    )

    svl <- read.pcv(
      f,
      mode = "long", reader = "fread"
    )
    svl$genotype = substr(svl$barcode, 3, 5)
    svl$genotype = ifelse(svl$genotype == "002", "B73",
      ifelse(svl$genotype == "003", "W605S",
        ifelse(svl$genotype == "004", "MM", "Mo17")
      )
    )
    svl$fertilizer = substr(svl$barcode, 8, 8)
    svl$fertilizer = ifelse(svl$fertilizer == "A", "100",
      ifelse(svl$fertilizer == "B", "50", "0")
    )
    svl <- bw.time(svl,
      plantingDelay = 0, phenotype = "area_pixels", cutoff = 10, timeCol = "timestamp",
      group = c("barcode", "rotation"), plot = FALSE
    )
  },
  error = function(e) {
    message(e)
  }
)

pcvr documentation built on April 16, 2025, 5:12 p.m.