FUNDAMENTALS
PERFORMANCE
ALGORITHMS
Let us consider this example (array written in general format):
ls = [0, 1, 3, 6, 10]
Its following parts:
ls = [0, 1, 3, 6, 10]
ls = [1, 3, 6, 10]
ls = [3, 6, 10]
ls = [6, 10]
ls = [10]
ls = []
The corresponding sums are (put together in a list): [20, 20, 19, 16, 10, 0]
The function parts_sums
(or its variants in other languages) will take as parameter a list ls
and return a list of the sums of its parts as defined above.
Other Examples:
ls = [1, 2, 3, 4, 5, 6]
parts_sums(ls) -> [21, 20, 18, 15, 11, 6, 0]
ls = [744125, 935, 407, 454, 430, 90, 144, 6710213, 889, 810, 2579358]
parts_sums(ls) -> [10037855, 9293730, 9292795, 9292388, 9291934, 9291504, 9291414, 9291270, 2581057, 2580168, 2579358, 0]
Notes
- Take a look at performance: some lists have thousands of elements.
- Please ask before translating.
const partsSums = ls => {
let sum = ls.reduce((acc, curr) => acc + curr, 0)
const result = [sum]
for (let i = 0; i < ls.length; i++) {
sum -= ls[i]
result.push(sum)
}
return result
}