In [1]:

    

from scipy.sparse.csgraph import minimum_spanning_tree
from scipy.sparse import csr_matrix, coo_matrix


    

In [2]:

    

l = [[0, 8, 0, 3],
     [0, 0, 2, 5],
     [0, 0, 0, 6],
     [0, 0, 0, 0]]


    

In [3]:

    

%%timeit
minimum_spanning_tree(l)


    

    




378 µs ± 9.78 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [4]:

    

%%timeit
minimum_spanning_tree(l, True)


    

    




383 µs ± 16.1 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [5]:

    

csr = csr_matrix(l)


    

In [6]:

    

%%timeit
minimum_spanning_tree(csr)


    

    




158 µs ± 5.95 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

In [7]:

    

%%timeit
minimum_spanning_tree(csr, True)


    

    




108 µs ± 2.19 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

In [8]:

    

coo = coo_matrix(l)


    

In [9]:

    

%%timeit
minimum_spanning_tree(coo)


    

    




185 µs ± 11.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [10]:

    

%%timeit
minimum_spanning_tree(coo, True)


    

    




184 µs ± 9.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [11]:

    

%%timeit
minimum_spanning_tree(csr_matrix(l))


    

    




364 µs ± 4.11 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [12]:

    

%%timeit
minimum_spanning_tree(csr_matrix(l), True)


    

    




319 µs ± 11.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [13]:

    

mst = minimum_spanning_tree(csr, True)


    

In [14]:

    

print(csr)


    

    




  (0, 3)	8
  (1, 2)	3
  (1, 3)	2
  (1, 3)	5
  (2, 3)	6

In [15]:

    

print(mst)


    

    




  (0, 3)	3.0
  (1, 2)	2.0
  (1, 3)	5.0