Dear Bill,
thank you for your help. I think, I finally understood your advice. At least,
this one worked:
library(package = lubridate) # for a more convenient display of times
i <- 12 # number of time intervals per hour
# creating a data.frame (original example)
business_hours <- data.frame(t = hm(paste(rep(x = 0:23, each = i), rep(x =
seq(from = 0, to = 60/i * (i - 1), by = 60/i), times = 24))),
A = c(rep(x = 0, times = (8 - (1/i)) * i), 1,
rep(x = 0, times = (12 - (1/i)) * i), -1, rep(x = 0, times = (4 ) *
i)),
B = c(rep(x = 0, times = (9 - (1/i)) * i), 1,
rep(x = 0, times = (2.75 - (1/i)) * i), -1, rep(x = 0, times = (1.75 - (1/i)) *
i), 1, rep(x = 0, times = (3.5 - (1/i)) * i), -1, rep(x = 0, times = 7 * i)))
# some data analysis
plot(x = rowSums(x = cumsum(business_hours[, -1])), type = "s")
I find some elegance in this solution; still, Jims proposal looks easier to
handle to me.
Best regards,
Alex
--
Alexander Sommer
wissenschaftlicher Mitarbeiter
Technische Universität Dortmund
Fakultät Erziehungswissenschaft, Psychologie und Soziologie
Forschungsverbund Deutsches Jugendinstitut/Technische Universität Dortmund
Vogelpothsweg 78
44227 Dortmund
Telefon: +49 231 755-8189
Telefax: +49 231 755-6553
E-Mail: alexander.som...@tu-dortmund.de
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