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September 28, 2018 10:58
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There is a publicly available library for DLX algorithm (also known as 'Algorithm X' or 'Dancing Links' algorithm) available at https://pypi.org/project/dlx/
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from dlx import DLX | |
def genInstance(labels, rows) : | |
columns = [] | |
indices_l = {} | |
for i in range(len(labels)) : | |
label = labels[i] | |
indices_l[label] = i | |
columns.append(tuple([label,0])) | |
return labels, rows, columns, indices_l | |
def solveInstance(instance) : | |
labels, rows, columns, indices_l = instance | |
instance = DLX(columns) | |
indices = {} | |
for l, i in zip(rows, range(len(rows))) : | |
h = instance.appendRow(l, 'r'+str(i)) | |
indices[str(hash(tuple(sorted(l))))] = i | |
sol = instance.solve() | |
lst = list(sol) | |
selected = [] | |
for i in lst[0] : | |
l = instance.getRowList(i) | |
l2 = [indices_l[label] for label in l] | |
idx = indices[str(hash(tuple(sorted(l2))))] | |
selected.append(idx) | |
return selected | |
def printColumnsPerRow(instance, selected) : | |
labels, rows, columns, indices_l = instance | |
print 'covered columns per selected row' | |
for s in selected : | |
A = [] | |
for z in rows[s-1] : | |
c, _ = columns[z] | |
A.append(c) | |
print s, A | |
def printInstance(instance) : | |
labels, rows, columns, indices_l = instance | |
print 'columns' | |
print labels | |
print 'rows' | |
print rows | |
''' | |
example instance #1 | |
source: https://www.cs.mcgill.ca/~aassaf9/python/algorithm_x.html | |
A B C D E F G | |
0 1 0 0 1 0 0 1 (0, 3, 6) | |
1 1 0 0 1 0 0 0 (0, 3) | |
2 0 0 0 1 1 0 1 (3, 4, 6) | |
3 0 0 1 0 1 1 0 (2, 4, 5) | |
4 0 1 1 0 0 1 1 (1, 2, 5, 6) | |
5 0 1 0 0 0 0 1 (1, 6) | |
expected solution: 1, 3, 5 | |
A B C D E F G | |
1 1 _ _ 1 _ _ _ (0, 3) | |
3 _ _ 1 _ 1 1 _ (2, 4, 5) | |
5 _ 1 _ _ _ _ 1 (1, 6) | |
''' | |
labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] | |
print 'instance #1' | |
rows = [[0,3,6],[0,3],[3,4,6],[2,4,5],[1,2,5,6],[1,6]] | |
instance = genInstance(labels, rows) | |
selected = solveInstance(instance) | |
printInstance(instance) | |
printColumnsPerRow(instance, selected) | |
print '' | |
''' | |
example instance #2 | |
source: https://lanl.arxiv.org/pdf/cs/0011047 | |
A B C D E F G | |
0 0 0 1 0 1 1 0 (2, 4, 5) | |
1 1 0 0 1 0 0 1 (0, 3, 6) | |
2 0 1 1 0 0 1 0 (1, 2, 5) | |
3 1 0 0 1 0 0 0 (0, 3) | |
4 0 1 0 0 0 0 1 (1, 6) | |
5 0 0 0 1 1 0 1 (3, 4, 6) | |
expected solution: 0, 3, 4 | |
A B C D E F G | |
0 _ _ 1 _ 1 1 _ (2, 4, 5) | |
3 1 _ _ 1 _ _ _ (0, 3) | |
4 _ 1 _ _ _ _ 1 (1, 6) | |
''' | |
print 'instance #2' | |
rows = [[2, 4, 5], [0, 3, 6], [1, 2, 5], [0, 3], [1, 6], [3, 4, 6]] | |
instance = genInstance(labels, rows) | |
selected = solveInstance(instance) | |
printInstance(instance) | |
printColumnsPerRow(instance, selected) |
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instance #1 | |
columns | |
['A', 'B', 'C', 'D', 'E', 'F', 'G'] | |
rows | |
[[0, 3, 6], [0, 3], [3, 4, 6], [2, 4, 5], [1, 2, 5, 6], [1, 6]] | |
covered columns per selected row | |
1 ['A', 'D', 'G'] | |
3 ['D', 'E', 'G'] | |
5 ['B', 'C', 'F', 'G'] | |
instance #2 | |
columns | |
['A', 'B', 'C', 'D', 'E', 'F', 'G'] | |
rows | |
[[2, 4, 5], [0, 3, 6], [1, 2, 5], [0, 3], [1, 6], [3, 4, 6]] | |
covered columns per selected row | |
3 ['B', 'C', 'F'] | |
0 ['D', 'E', 'G'] | |
4 ['A', 'D'] |
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