# get_radolan_urls_for_days ----------------------------------------------------
# dates <- seq(as.Date("2018-07-01"), as.Date("2018-08-01"), by = 1)
# urls <- get_radolan_urls_for_days(dates)
get_radolan_urls_for_days <- function(dates, diff_days = 10, time = "1050")
{
# Call fhpredict:::test_performance_get_radolan_urls() to find a good value
# for diff_days
stopifnot(! is.unsorted(dates))
# Create date ranges from the vector of dates
date_ranges <- group_dates_by_diff(dates, diff_days = diff_days)
# Get URLs for each of the ranges
urls_list <- get_radolan_urls_in_date_ranges(date_ranges, time = time)
# Put all URLs into an atomic vector
urls <- unlist(urls_list)
# Return if there is not at least one URL
if (length(urls) == 0) {
return(character())
}
# Check if all URLs are unique
stopifnot(all(! duplicated(urls)))
# Convert URL names to dates
url_dates <- extract_date_from_url_name(names(urls))
# Check if all dates to which the URLs relate are unique
stopifnot(all(! duplicated(url_dates)))
# Return only the URLs related to dates that were requested
urls[url_dates %in% dates]
}
# extract_date_from_url_name ---------------------------------------------------
extract_date_from_url_name <- function(name)
{
stopifnot(all(grepl("^\\d{12}$", name)))
as.Date(substr(name, 1, 8), format = "%Y%m%d")
}
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