Python C extension to compute the permanent.
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  1. import os
  2. import time
  3. import multiprocessing as mp
  4. import numpy as np
  5. import lib
  6. import time
  7. def perm_ryser(a):
  8. ''' the permanent calculated using the ryser formula. much faster than the naive approach '''
  9. n,n2=a.shape
  10. z=np.arange(n)
  11. irange=xrange(2**n)
  12. get_index=lambda i: (i & (1 << z)) != 0
  13. get_term=lambda index: ((-1)**np.sum(index))*np.prod(np.sum(a[index,:], 0))
  14. indeces=map(get_index, irange)
  15. terms=map(get_term, indeces)
  16. return np.sum(terms)*((-1)**n)
  17. def explain_ryser(a):
  18. ''' the permanent calculated using the ryser formula. much faster than the naive approach '''
  19. n,n2=a.shape
  20. z=np.arange(n)
  21. irange=xrange(2**n)
  22. get_index=lambda i: (i & (1 << z)) != 0
  23. for q in irange:
  24. print get_index(q)
  25. #get_term=lambda index: ((-1)**np.sum(index))*np.prod(np.sum(a[index,:], 0))
  26. #indeces=map(get_index, irange)
  27. #terms=map(get_term, indeces)
  28. #return np.sum(terms)*((-1)**n)
  29. dimension=5
  30. real=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension))
  31. imag=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension))
  32. submatrix=real+1j*imag
  33. t=time.clock()
  34. for i in range(1000):
  35. perm_ryser(submatrix)
  36. print time.clock()-t
  37. t=time.clock()
  38. for i in range(1000):
  39. lib.permanent(submatrix)
  40. print time.clock()-t