View source: R/metric_midpointCE.R
midpointCE | R Documentation |
This function calculates the timing corresponding to half of the cumulative light exposure within the given time series.
midpointCE(Light.vector, Time.vector, na.rm = FALSE, as.df = FALSE)
Light.vector |
Numeric vector containing the light data. |
Time.vector |
Vector containing the time data. Can be POSIXct, hms, duration, or difftime. |
na.rm |
Logical. Should missing values be removed for the calculation? If |
as.df |
Logical. Should the output be returned as a data frame? If |
Single column data frame or vector.
Shochat, T., Santhi, N., Herer, P., Flavell, S. A., Skeldon, A. C., & Dijk, D.-J. (2019). Sleep Timing in Late Autumn and Late Spring Associates With Light Exposure Rather Than Sun Time in College Students. Frontiers in Neuroscience, 13. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3389/fnins.2019.00882")}
Hartmeyer, S.L., Andersen, M. (2023). Towards a framework for light-dosimetry studies: Quantification metrics. Lighting Research & Technology. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/14771535231170500")}
Other metrics:
bright_dark_period()
,
centroidLE()
,
disparity_index()
,
duration_above_threshold()
,
exponential_moving_average()
,
frequency_crossing_threshold()
,
interdaily_stability()
,
intradaily_variability()
,
nvRC()
,
nvRD()
,
nvRD_cumulative_response()
,
period_above_threshold()
,
pulses_above_threshold()
,
threshold_for_duration()
,
timing_above_threshold()
dataset1 <-
tibble::tibble(
Id = rep("A", 24),
Datetime = lubridate::as_datetime(0) + lubridate::hours(0:23),
MEDI = c(rep(1, 6), rep(250, 13), rep(1, 5))
)
dataset1 %>%
dplyr::reframe(
"Midpoint of cmulative exposure" = midpointCE(MEDI, Datetime)
)
# Dataset with HMS time vector
dataset2 <-
tibble::tibble(
Id = rep("A", 24),
Time = hms::as_hms(lubridate::as_datetime(0) + lubridate::hours(0:23)),
MEDI = c(rep(1, 6), rep(250, 13), rep(1, 5))
)
dataset2 %>%
dplyr::reframe(
"Midpoint of cmulative exposure" = midpointCE(MEDI, Time)
)
# Dataset with duration time vector
dataset3 <-
tibble::tibble(
Id = rep("A", 24),
Hour = lubridate::duration(0:23, "hours"),
MEDI = c(rep(1, 6), rep(250, 13), rep(1, 5))
)
dataset3 %>%
dplyr::reframe(
"Midpoint of cmulative exposure" = midpointCE(MEDI, Hour)
)
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