How do I optimize my Python code for balancing a centrifuge with a given input size?











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So, the problem is, given an input N as the size of a centrifuge, I need to find out the number of balanced configurations. The full description is here. This is my code:



import numpy as np

N=int(input())
angle = 2*np.pi/N
z = complex(np.cos(angle), np.sin(angle))


import itertools
combs =
lst = range(1,N)
for i in range(2, N-1):
combs.append(i)
els = [list(x) for x in itertools.combinations(lst, i)]
combs.append(els)


count=1
lis =
while count<=len(combs):
for a in range(len(combs[count])):
s=0
for b in range(len(combs[count][a])):
s+=z**combs[count][a][b]
if abs(s)<1e-10:
lis.append(combs[count][a])
count+=2


lengths =
for i in lis:
if len(i) not in lengths:
lengths.append(len(i))

print(len(lengths)+1)


The code works fine, but slows down after input size of above 20, and is practically unusable after the input grows to 50 or above, due to the for loops. How do I optimize it?









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    up vote
    0
    down vote

    favorite












    So, the problem is, given an input N as the size of a centrifuge, I need to find out the number of balanced configurations. The full description is here. This is my code:



    import numpy as np

    N=int(input())
    angle = 2*np.pi/N
    z = complex(np.cos(angle), np.sin(angle))


    import itertools
    combs =
    lst = range(1,N)
    for i in range(2, N-1):
    combs.append(i)
    els = [list(x) for x in itertools.combinations(lst, i)]
    combs.append(els)


    count=1
    lis =
    while count<=len(combs):
    for a in range(len(combs[count])):
    s=0
    for b in range(len(combs[count][a])):
    s+=z**combs[count][a][b]
    if abs(s)<1e-10:
    lis.append(combs[count][a])
    count+=2


    lengths =
    for i in lis:
    if len(i) not in lengths:
    lengths.append(len(i))

    print(len(lengths)+1)


    The code works fine, but slows down after input size of above 20, and is practically unusable after the input grows to 50 or above, due to the for loops. How do I optimize it?









    share







    New contributor




    Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.






















      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      So, the problem is, given an input N as the size of a centrifuge, I need to find out the number of balanced configurations. The full description is here. This is my code:



      import numpy as np

      N=int(input())
      angle = 2*np.pi/N
      z = complex(np.cos(angle), np.sin(angle))


      import itertools
      combs =
      lst = range(1,N)
      for i in range(2, N-1):
      combs.append(i)
      els = [list(x) for x in itertools.combinations(lst, i)]
      combs.append(els)


      count=1
      lis =
      while count<=len(combs):
      for a in range(len(combs[count])):
      s=0
      for b in range(len(combs[count][a])):
      s+=z**combs[count][a][b]
      if abs(s)<1e-10:
      lis.append(combs[count][a])
      count+=2


      lengths =
      for i in lis:
      if len(i) not in lengths:
      lengths.append(len(i))

      print(len(lengths)+1)


      The code works fine, but slows down after input size of above 20, and is practically unusable after the input grows to 50 or above, due to the for loops. How do I optimize it?









      share







      New contributor




      Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      So, the problem is, given an input N as the size of a centrifuge, I need to find out the number of balanced configurations. The full description is here. This is my code:



      import numpy as np

      N=int(input())
      angle = 2*np.pi/N
      z = complex(np.cos(angle), np.sin(angle))


      import itertools
      combs =
      lst = range(1,N)
      for i in range(2, N-1):
      combs.append(i)
      els = [list(x) for x in itertools.combinations(lst, i)]
      combs.append(els)


      count=1
      lis =
      while count<=len(combs):
      for a in range(len(combs[count])):
      s=0
      for b in range(len(combs[count][a])):
      s+=z**combs[count][a][b]
      if abs(s)<1e-10:
      lis.append(combs[count][a])
      count+=2


      lengths =
      for i in lis:
      if len(i) not in lengths:
      lengths.append(len(i))

      print(len(lengths)+1)


      The code works fine, but slows down after input size of above 20, and is practically unusable after the input grows to 50 or above, due to the for loops. How do I optimize it?







      python performance python-3.x programming-challenge





      share







      New contributor




      Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.










      share







      New contributor




      Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      share



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      New contributor




      Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      Kristada673

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      New contributor





      Kristada673 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






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      Check out our Code of Conduct.



























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