Consider a 1D numpy array and two constants as shown: import numpy as np arr = np.arange(60) n = 5 s = 120 arr is always of the form [0,1,2,3,4, … 59,60] for example. QUESTION: From a 1D array (arr), I need to find all subsets exactly n UNIQUE elements that have a specified sum […]

- Tags "14", 1, 10, 15, 2, 26, 3, 35, 4, 40, 42, 47, 59, 60] for example. QUESTION: From a 1D array (arr), 9, but is VERY slow, but it is not required. (ie: combinations, Consider a 1D numpy array and two constants as shown: import numpy as np arr = np.arange(60) n = 5 s = 120 arr is always of the form [0, each holding the elements of arr. This works, especially if n gets as large as 12 or so. Is there a way to efficiently and quickly do this in Python/Numpy?, etc... I have shown the row elements in order. This would be nice, I handle this computation in an SQL variant by using a cross-product of identical tables, I need to find all subsets exactly n UNIQUE elements that have a specified sum s. A solution could start like: [[2, not permutations) Currently