Uses the pattern and parser returned by detect_time_pattern()
to parse the date embedded in filename and computes derived
units (month, semester, quarter).
Arguments
- filename
Character string of file path or name
- info
List as returned by
detect_time_pattern(), containing:- pattern
One of
"monthly"or"yearly".- parser
Function to parse character dates into Date/POSIXct.
- year_extractor
Optional function to extract year from filename. If provided, this function is used instead of automatic year detection for yearly data. Should take a character string (filename) and return a character string (year). Useful for filenames with multiple 4-digit numbers where heuristics may fail.
Value
A list with:
- year
Integer year
- month
Integer month (1–12) or
NAfor yearly data- semester
Integer semester (1–2) or
NA- quarter
Integer quarter (1–4) or
NA- date
Date object for the first day of the period
Note
For yearly data, when multiple plausible years (1980-2099) are
present in the filename, the last one is returned. This heuristic
assumes dataset version stamps appear early in the filename and data
years appear later. For deterministic control, pass a custom
year_extractor function.
Examples
info <- detect_time_pattern("rainfall_2022-01.tif")
extract_time_components("rainfall_2022-01.tif", info)
#> $year
#> [1] 2022
#>
#> $month
#> [1] 1
#>
#> $semester
#> [1] 1
#>
#> $quarter
#> [1] 1
#>
#> $date
#> [1] "2022-01-01"
#>
info <- detect_time_pattern("temp_2020.tif")
extract_time_components("temp_2020.tif", info)
#> $year
#> [1] 2020
#>
#> $month
#> [1] NA
#>
#> $semester
#> [1] NA
#>
#> $quarter
#> [1] NA
#>
#> $date
#> [1] "2020-01-01"
#>
# Custom year extractor for complex filenames
my_extractor <- function(f) {
stringr::str_extract(f, "Rate\\.(\\d{4})\\.tiff$", group = 1)
}
extract_time_components("Malaria_Rate.2020.tiff", info, my_extractor)
#> $year
#> [1] 2020
#>
#> $month
#> [1] NA
#>
#> $semester
#> [1] NA
#>
#> $quarter
#> [1] NA
#>
#> $date
#> [1] "2020-01-01"
#>