""" kruskal.py an implementation of Kruskal's Algorithm for MST by Andrew Jacobson """ import UnionFind # Takes a graph represented by a series of edges # which are represented as a list of tuples # def kruskal(): return None if __name__ == "__main__": #these edges need weights edges = [(1,2),(1,3),(2,3),(3,4),(2,4),(5,4)] a = UnionFind.UF(10) print edges print a
text_file = open("clustering1.txt", "r")
lines = text_file.read().splitlines()
num = int(lines[0])
arr = np.zeros((len(lines) - 1, 3))
for i, line in enumerate(lines[1:]):
arr[i, :] = line.split()
df = pd.DataFrame(arr, columns=np.array(['edge1', 'edge2', 'cost']))
sortdf = df.sort_values(['cost'], axis=0, ascending=True)
sortdf = sortdf.applymap(int)
sortarr = sortdf.values
print("load and sort--- %s seconds ---" % (time.time() - start_time))
start_time = time.time()
test = UnionFind.UF(num)
count = 0
k = 4
space = math.inf
for row in sortarr:
i, j = row[0], row[1]
if count < num - k:
if not test.connected(i - 1, j - 1):
test.union(i - 1, j - 1)
count += 1
else:
if not test.connected(i - 1, j - 1):
space = min(space, row[2])
print("maximum spacing:", space) # 106
print("--- %s seconds ---" % (time.time() - start_time))
#https://www.coursera.org/learn/algorithms-greedy/discussions/weeks/2/threads/mSGCyQULEemZUwrw3z8SgA
