I am trying to extract all subsets from a list of elements which add up to a certain value.
Example -
Have tried different approaches and getting the expected output but on a huge list of elements it is taking a significant amount of time. Can this be optimized using Dynamic Programming or any other technique.
Approach-1
def subset(array, num):
result = []
def find(arr, num, path=()):
if not arr:
return
if arr[0] == num:
result.append(path + (arr[0],))
else:
find(arr[1:], num - arr[0], path + (arr[0],))
find(arr[1:], num, path)
find(array, num)
return result
numbers = [2, 2, 1, 12, 15, 2, 3]
x = 7
subset(numbers,x)
Approach-2
def isSubsetSum(arr, subset, N, subsetSize, subsetSum, index , sum):
global flag
if (subsetSum == sum):
flag = 1
for i in range(0, subsetSize):
print(subset[i], end = " ")
print("")
else:
for i in range(index, N):
subset[subsetSize] = arr[i]
isSubsetSum(arr, subset, N, subsetSize + 1,
subsetSum + arr[i], i + 1, sum)
Here is the optimized solution to the problem with a complexity of O(n^2).
def get_subsets(data: list, target: int):
# initialize final result which is a list of all subsets summing up to target
subsets = []
# records the difference between the target value and a group of numbers
differences = {}
for number in data:
prospects = []
# iterate through every record in differences
for diff in differences:
# the number complements a record in differences, i.e. a desired subset is found
if number - diff == 0:
new_subset = [number] + differences[diff]
new_subset.sort()
if new_subset not in subsets:
subsets.append(new_subset)
# the number fell short to reach the target; add to prospect instead
elif number - diff < 0:
prospects.append((number, diff))
# update the differences record
for prospect in prospects:
new_diff = target - sum(differences[prospect[1]]) - prospect[0]
differences[new_diff] = differences[prospect[1]] + [prospect[0]]
differences[target - number] = [number]
return subsets