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Having this data:
> data
[1] 1290603356 1290603360 1290603350 1290603344 1290603340 1290603373
[7] 1290603354 1290603359 1290603345 1290603363 1290603357 1290603354
[13] 1290603364 1290603349 1290603352 1290603365 1290603349 1290603343
[19] 1290603339 1290603343
> offsets <- c(0, 0.5,1,2,4,8,24,4*24,7*24) * 3600)
[1] 1800 3600 7200 14400 28800 86400 345600 604800
> myoffsets <- min(data)+offsets
being, a list of UNIX epochs and a list of offsets (0.5 hours, 1h, 2h, 4h...) I want to be able to graph how many of the epochs are <= than the min(data) + offset
In this example it would be
1 20 20 20 20 20 20 20
I have found how to do this with a for loop:
for(i in c(1:length(myoffsets))) myres$x[i] <- length(data[data <= myoffsets[i]])
But I'm sure there's a more idiomatic way if doing this that is not as convoluted?
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To check if all elements of a List satisfy a given condition/predicate in Kotlin, call all() function on this List object and pass the predicate as argument to this function. The Kotlin List. all() function checks if all the elements of the list match a given predicate, and returns a boolean value.
Use len() & List comprehension to count elements in list based on conditions. We can use list comprehension to create a new list of elements that satisfies our given condition and then get the length of this new list to find out number of elements in original list that satisfies our condition i.e.
Use all() to check if every element of a list satisfies a condition. Use the syntax condition for item in list to build a generator expression that checks each item in list against a given condition .
Suggestion 1: A slightly more idiomatic way would be to replace
length(data[data <= myoffsets[i]])
with
sum(data <= myoffsets[i])
This way you don't end up taking a subset of data for each value in myoffsets, only to compute its length and discard.
Suggestion 2: The c() in the for is redundant. The following would do exactly the same with fewer keystrokes: for(i in 1:length(myoffsets)).
Lastly, if you prefer to get rid of the explicit loop, something like this might be to your taste:
myres$x <- sapply(myoffsets, function(o)sum(data<=o))
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