In this case (more details could be found in this question: Count how many observations in the rest of the dat fits multiple conditions? (R))
This is a dataset called event, containing thousands of events (observations) and I selected several rows to show you the data structure. It contains the "STATEid", "date" of occurrence, and geographical coordinates in two variables "LON" "LAT". I am writing to calculate a new variable (column) for each row. This new variable should be: "Given any specific incident, count the rest of the dataset and calculate the number of events that's happened in the same state, within the circle of 50/100KM radius, in the next 30/60 days.
I have written a user-defined function with a while loop - to make this easier, I only included 2 conditions, within 30 days and in the same state:
n = 1
f = function(i) {
a = i[n,]
b = a$date
# c = a$LON
# d = a$LAT
e = a$STATEid
f = a$RID
g1 = sum(i$CASE [i$date<= b+30 & i$date>b & i$STATEid==e], na.rm=T)
# g2 = sum(i$viold [i$date<= b+30 & i$date>b], na.rm=T)
# g3 = sum(i$CASE [i$date<= b+60 & i$date>b], na.rm=T)
# g4 = sum(i$viold [i$date<= b+60 & i$date>b], na.rm=T)
# h = cbind(g1, g2, g3, g4)
g1 = data.frame(g1)
n = n+1
assign(as.character(f), g1, envir = .GlobalEnv)
}
for (n in 1:20) (f(event2))
This has been taking too long since it contains 23,000 cases. My PC with a 16GB Ram cannot nail it when the loop only needs to run twice! So I think avoiding loops would be preferable. Could you please suggest a way to vectorize my codes and avoid the looping?
My main problem is that I don't know how to write user-defined problems when I need to refer to each row, each variable properly when multiple conditions are required - that's why in my loop function, I created objects such as "a", "b", "c", "d", "e" to call them properly... Inefficient - I know...
My dput outcome looks like so:
> dput(tail(event2[,c("RID", "STATEid", "date", "LON", "LAT")]))
structure(list(RID = c("023610", "023611", "023613", "023614",
"023615", "023616"), STATEid = structure(c(36L, 36L, 23L, 23L,
5L, 14L), .Label = c("alabama", "alaska", "arizona", "arkansas",
"california", "colorado", "connecticut", "delaware", "district of columbia",
"florida", "georgia", "hawaii", "idaho", "illinois", "indiana",
"iowa", "kansas", "kentucky", "louisiana", "maine", "maryland",
"massachusetts", "michigan", "minnesota", "mississippi", "missouri",
"montana", "nebraska", "nevada", "new hampshire", "new jersey",
"new mexico", "new york", "north carolina", "north dakota", "ohio",
"oklahoma", "oregon", "pennsylvania", "rhode island", "south carolina",
"south dakota", "tennessee", "texas", "utah", "vermont", "virginia",
"washington", "west virginia", "wisconsin", "wyoming"), class = "factor"),
date = structure(c(3620, -633, 131, -315, 5421, 3558), class = "Date"),
LON = c(-80.6495194, -80.6495194, -83.6129939, -83.6129939,
-121.6169108, -87.8328505), LAT = c(41.0997803, 41.0997803,
42.2411499, 42.2411499, 39.1404477, 42.4461322)), .Names = c("RID",
"STATEid", "date", "LON", "LAT"), row.names = c(23610L, 23611L,
23613L, 23614L, 23615L, 23616L), class = "data.frame")
>
Many thanks. I appreciate your help.
Best,
---------- Jan.20, 2018 updates ---------
I have created a loop that works and correctly reflects what I am hoping for:
g = event2[FALSE,]
USERFUN = function(i) {
a = i[n,] # retrieve each row from the object, make it a data object
b = a$date # get date
# c = a$LON # for now I dropped the idea of calculating radius
# d = a$LAT # for now I dropped the idea of calculating radius
e = a$STATEid # get STATE
f = a$RID # get case ID to name the objects generated!
PostAct30 = sum(i$CASE [i$date<= b+30 & i$date>b & i$STATEid == e], na.rm=T) # multiple conditions defined here - i is the entire dataset
PostAct60 = sum(i$CASE [i$date<= b+60 & i$date>b & i$STATEid == e], na.rm=T) # multiple conditions defined here - b, e are dynamic, retrieving from each line!!!
PreAct30 = sum(i$CASE [i$date<= b & i$date>b-30 & i$STATEid == e], na.rm=T)
PreAct60 = sum(i$CASE [i$date<= b & i$date>b-30 & i$STATEid == e], na.rm=T)
PostVio30 = sum(i$viold [i$date<= b+30 & i$date>b & i$STATEid == e], na.rm=T)
PostVio60 = sum(i$viold [i$date<= b+60 & i$date>b & i$STATEid == e], na.rm=T)
PreVio30 = sum(i$viold [i$date<= b & i$date>b-30 & i$STATEid == e], na.rm=T)
PreVio60 = sum(i$viold [i$date<= b & i$date>b-30 & i$STATEid == e], na.rm=T)
g1 = data.frame(f, PostAct30, PostAct60, PreAct30, PreAct60, PostVio30, PostVio60, PreVio30, PreVio60)
n = n+1
return(g1)
}
# sum(event2$ca)
n = 1
for (n in 1:19446) {
g2 = USERFUN(event2)
g = rbind(g, g2)
}
AND the output looks like so:
> tail(event3 [c("date","STATEid", "PostAct30", "PostAct60", "PostVio30", "PostVio60")])
date STATEid PostAct30 PostAct60 PostVio30 PostVio60
23611 1968-04-08 ohio 3 4 0 0
23612 <NA> arizona NA NA NA NA
23613 1970-05-12 michigan 4 6 2 4
23614 1969-02-20 michigan 2 3 1 1
23615 1984-11-04 california 4 5 0 0
23616 1979-09-29 illinois 0 2 0 1
Consider mapply to add new columns in place by iterating date and STATEid elementwise into a defined function. Specifically, mapply produces a matrix of 7 columns which you assign to event2.
dates_calc_fct <- function(b, e)
c(sum(event2$CASE [event2$date<= b+30 & event2$date>b & event2$STATEid == e], na.rm=T),
sum(event2$CASE [event2$date<= b+60 & event2$date>b & event2$STATEid == e], na.rm=T),
sum(event2$CASE [event2$date<= b & event2$date>b-30 & event2$STATEid == e], na.rm=T),
sum(event2$CASE [event2$date<= b & event2$date>b-30 & event2$STATEid == e], na.rm=T),
sum(event2$viold [event2$date<= b+30 & event2$date>b & event2$STATEid == e], na.rm=T),
sum(event2$viold [event2$date<= b+60 & event2$date>b & event2$STATEid == e], na.rm=T),
sum(event2$viold [event2$date<= b & event2$date>b-30 & event2$STATEid == e], na.rm=T),
sum(event2$viold [event2$date<= b & event2$date>b-30 & event2$STATEid == e], na.rm=T)
)
event2[c("PostAct30", "PostAct60",
"PreAct30", "PreAct60",
"PostVio30", "PostVio60",
"PreVio30", "PreVio60")] <- mapply(dates_calc_fct, event$date, event$STATEid)
来源：https://stackoverflow.com/questions/48351931/r-how-to-vectorize-with-apply-family-function-and-avoid-while-for-loops-in-thi