Summing All Possible Combinations Of An Arbitrary Number Of Arrays And Applying Limits And Returning Indices
This is a modification of this question in which I would like to return the indices of the arrays elements in addition to the elements themselves. I've successfully modified arrays
Solution 1:
A key feature of arraysums_recursive
is that it throws out values which can not possibly contribute to the result:
subarrays = [[item2 for item2 in arr if item2 <= upper-item]
for arr in arrays[1:]]
While throwing things out complicates the recording of indices, it's not too hard.
First, in arraysums_recursive
expand arrays
to include the index as well as the item value:
defarraysums_recursive(arrays, lower, upper):
arrays = [[(i, item) for i, item inenumerate(arr)] for arr in arrays]
...
index, result = zip(*arraysums_recursive_all_positive(arrays, lower, upper))
return result, index
Now rewrite arraysums_recursive_all_positive
to handle arrays
which consist of a list of lists of (index, item)
tuples.
defarraysums_recursive(arrays, lower, upper):
arrays = [[(i, item) for i, item inenumerate(arr)] for arr in arrays]
minval = min(item for arr in arrays for i, item in arr)
# Subtract minval from arrays to guarantee all the values are positive
arrays = [[(i, item-minval) for i, item in arr] for arr in arrays]
# Adjust the lower and upper bounds accordingly
lower -= minval*len(arrays)
upper -= minval*len(arrays)
index, result = zip(*arraysums_recursive_all_positive(arrays, lower, upper))
# Readjust the result by adding back minval
result = [tuple([item+minval for item in tup]) for tup in result]
return result, index
defarraysums_recursive_all_positive(arrays, lower, upper):
# Assumes all values in arrays are positiveiflen(arrays) <= 1:
result = [((i,), (item,)) for i, item in arrays[0] if lower <= item <= upper]
else:
result = []
for i, item in arrays[0]:
subarrays = [[(i, item2) for i, item2 in arr if item2 <= upper-item]
for arr in arrays[1:]]
ifmin(len(arr) for arr in subarrays) == 0:
continue
result.extend(
[((i,)+i_tup, (item,)+item_tup) for i_tup, item_tup in
arraysums_recursive_all_positive(subarrays, lower-item, upper-item)])
return result
import numpy as np
N = 8
a = np.arange(N)
b = np.arange(N)-N/2
result, index = arraysums_recursive((a,b),lower=5,upper=6)
yields result
:
[(2.0, 3.0),
(3.0, 2.0),
(3.0, 3.0),
(4.0, 1.0),
(4.0, 2.0),
(5.0, 0.0),
(5.0, 1.0),
(6.0, -1.0),
(6.0, 0.0),
(7.0, -2.0),
(7.0, -1.0)]
and index
:
((2, 7),
(3, 6),
(3, 7),
(4, 5),
(4, 6),
(5, 4),
(5, 5),
(6, 3),
(6, 4),
(7, 2),
(7, 3))
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