LightLogR (version 0.5.3)

period_above_threshold: Length of longest continuous period above/below threshold

Description

This function finds the length of the longest continous period above/below a specified threshold light level or within a specified range of light levels.

Usage

period_above_threshold(
  Light.vector,
  Time.vector,
  comparison = c("above", "below"),
  threshold,
  epoch = "dominant.epoch",
  loop = FALSE,
  na.replace = FALSE,
  na.rm = FALSE,
  as.df = FALSE
)

Value

A duration object (see duration) as single value, or single column data frame.

Arguments

Light.vector

Numeric vector containing the light data.

Time.vector

Vector containing the time data. Can be POSIXct, hms, duration, or difftime.

comparison

String specifying whether the period of light levels above or below threshold should be calculated. Can be either "above" (the default) or "below". If two values are provided for threshold, this argument will be ignored.

threshold

Single numeric value or two numeric values specifying the threshold light level(s) to compare with. If a vector with two values is provided, the period of light levels within the two thresholds will be calculated.

epoch

The epoch at which the data was sampled. Can be either a duration or a string. If it is a string, it needs to be either "dominant.epoch" (the default) for a guess based on the data, or a valid duration string, e.g., "1 day" or "10 sec".

loop

Logical. Should the data be looped? Defaults to FALSE.

na.replace

Logical. Should missing values (NA) be replaced for the calculation? If TRUE missing values will not be removed but will result in FALSE when comparing Light.vector with threshold. Defaults to FALSE.

na.rm

Logical. Should missing values (NA) be removed for the calculation? If TRUE, this argument will override na.replace. Defaults to FALSE.

as.df

Logical. Should a data frame be returned? If TRUE, a data frame with a single column named period_{comparison}_{threshold} will be returned. Defaults to FALSE.

See Also

Other metrics: bright_dark_period(), centroidLE(), disparity_index(), duration_above_threshold(), exponential_moving_average(), frequency_crossing_threshold(), interdaily_stability(), intradaily_variability(), midpointCE(), nvRC(), nvRD(), nvRD_cumulative_response(), pulses_above_threshold(), threshold_for_duration(), timing_above_threshold()

Examples

N <- 60
# Dataset with continous period of >250lx for 35min
dataset1 <-
  tibble::tibble(
    Id = rep("A", N),
    Datetime = lubridate::as_datetime(0) + lubridate::minutes(1:N),
    MEDI = c(sample(1:249, N-35, replace = TRUE), 
             sample(250:1000, 35, replace = TRUE))
  )

dataset1 %>%
  dplyr::reframe("Period >250lx" = period_above_threshold(MEDI, Datetime, threshold = 250))

dataset1 %>%
  dplyr::reframe("Period <250lx" = period_above_threshold(MEDI, Datetime, "below", threshold = 250))

# Dataset with continous period of 100-250lx for 20min
dataset2 <-
  tibble::tibble(
    Id = rep("B", N),
    Datetime = lubridate::as_datetime(0) + lubridate::minutes(1:N),
    MEDI = c(sample(c(1:99, 251-1000), N-20, replace = TRUE), 
             sample(100:250, 20, replace = TRUE)),
  )
dataset2 %>%
  dplyr::reframe("Period 250lx" = period_above_threshold(MEDI, Datetime, threshold = c(100,250)))

# Return data frame
dataset1 %>%
  dplyr::reframe(period_above_threshold(MEDI, Datetime, threshold = 250, as.df = TRUE))