x1

Question

It looks like you are using

to generate integer partitions.

variation_models' nlocations =
  let location_list = [1..nlocations-4]
  in [[x1, x2, x3, x4, x5] |
      x1 <- location_list,
      x2 <- location_list,
      x3 <- location_list,
      x4 <- location_list,
      x5 <- location_list,
      both_conditions (adds_up_to nlocations) num_orderedq [x1, x2, x3, x4, x5]]

It seems to have better memory characteristics then the more generalvariation_models 5 15 [1,1,1,1,11]我想写这个函数

但有任何数量的X。我想

variation_models ncars nlocations =
  filter (both_conditions (adds_up_to nlocations) num_orderedq) $
  replicateM ncars [1..nlocations-ncars+1]

的有效答案 .我现在的尝试是

不过

replicateM似乎使函数占用了越来越多的内存。

import Control.Monad

orderedq f [] = True
orderedq f (x:[]) = True
orderedq f (x:y:zs) = f x y && orderedq f (y:zs)

num_orderedq = orderedq (<=)

adds_up_to n xs = n == sum xs

both_conditions f g xs = f xs && g xs

variation_models ncars nlocations =
  filter (both_conditions (adds_up_to nlocations) num_orderedq) $
  replicateM ncars [1..nlocations-ncars+1]

variation_models' nlocations =
  let location_list = [1..nlocations-4]
  in [[x1, x2, x3, x4, x5] |
      x1 <- location_list,
      x2 <- location_list,
      x3 <- location_list,
      x4 <- location_list,
      x5 <- location_list,
      both_conditions (adds_up_to nlocations) num_orderedq [x1, x2, x3, x4, x5]]

.

Answer 1

replicateM

integer_partitions :: Int -> Int -> [[Int]]
integer_partitions 0 _ = []
integer_partitions 1 n = [[n]]
integer_partitions k n =
  do x <- [1..n - k + 1]
     map (x:) (integer_partitions (k - 1) (n - x)) 

我想写这个函数variation_models' nlocations = let location_list = [1...nlocations-4] in [[x1, x2, x3, x4, x5] 。