Handle jumps in Daylight Savings (DST) that are missing in the data

When data is imported through LightLogR and a timezone applied, it is assumed that the timestamps are correct - which is the case, e.g., if timestamps are stored in UTC, or they are in local time. Some if not most measurement devices are set to local time before a recording interval starts. If during the recording a daylight savings jump happens (in either direction), the device might not adjust timestamps for this change. This results in an unwanted shift in the data, starting at the time of the DST jump and likely continues until the end of a file. dst_change_handler is used to detect such jumps within a group and apply the correct shift in the data (i.e., the shift that should have been applied by the device).

important Note that this function is only useful if the time stamp in the raw data deviates from the actual date-time. Note also, that this function results in a gap during the DST jump, which should be handled by gap_handler() afterwards. It will also result in potentially double the timestamps during the jum back from DST to standard time. This will result in some inconsistencies with some functions, so we recommend to use aggregate_Datetime() afterwards with a unit equal to the dominant epoch. Finally, the function is not equipped to handle more than one jump per group. The jump is based on whether the group starts out with DST or not. the function will remove datetime rows with NA values.

Usage

dst_change_handler(
  dataset,
  Datetime.colname = Datetime,
  filename.colname = NULL
)

Arguments

dataset

dataset to be summarized, must be a dataframe

Datetime.colname

name of the column that contains the Datetime data, expects a symbol

filename.colname

(optional) column name that contains the filename. If provided, it will use this column as a temporary grouping variable additionally to the dataset grouping.

Value

A tibble with the same columns as the input dataset, but shifted

Details

The detection of a DST jump is based on the function lubridate::dst() and jumps are only applied within a group. During import, this function is used if dst_adjustment = TRUE is set and includes by default the filename as the grouping variable, additionally to Id.

See also

Other DST: dst_change_summary()

Examples

#create some data that crosses a DST jump
data <- 
 tibble::tibble(
 Datetime = seq.POSIXt(from = as.POSIXct("2023-03-26 01:30:00", tz = "Europe/Berlin"),
                     to = as.POSIXct("2023-03-26 03:00:00", tz = "Europe/Berlin"),
                     by = "30 mins"),
                     Value = 1)
 #as can be seen next, there is a gap in the data - this is necessary when
 #using a timezone with DST. 
 data$Datetime
#> [1] "2023-03-26 01:30:00 CET"  "2023-03-26 03:00:00 CEST"
 #Let us say now, that the device did not adjust for the DST - thus the 03:00 
 #timestamp is actually 04:00 in local time. This can be corrected for by:
 data %>% dst_change_handler() %>% .$Datetime
#> [1] "2023-03-26 01:30:00 CET"  "2023-03-26 04:00:00 CEST"