Python C extension to compute the permanent.
Nevar pievienot vairāk kā 25 tēmas Tēmai ir jāsākas ar burtu vai ciparu, tā var saturēt domu zīmes ('-') un var būt līdz 35 simboliem gara.

47 rindas
1.3KB

  1. import os, sys
  2. import time
  3. import multiprocessing as mp
  4. import numpy as np
  5. import time
  6. from matplotlib import pyplot as plt
  7. from permanent import permanent
  8. def perm_ryser(a):
  9. ''' the permanent calculated using the ryser formula. much faster than the naive approach '''
  10. n,n2=a.shape
  11. z=np.arange(n)
  12. irange=xrange(2**n)
  13. get_index=lambda i: (i & (1 << z)) != 0
  14. get_term=lambda index: ((-1)**np.sum(index))*np.prod(np.sum(a[index,:], 0))
  15. indeces=map(get_index, irange)
  16. terms=map(get_term, indeces)
  17. return np.sum(terms)*((-1)**n)
  18. maxtime=1
  19. dimensions=range(1,11)
  20. for (function, label) in zip((permanent, perm_ryser), ("C", "Python")):
  21. counts=[]
  22. for dimension in dimensions:
  23. print dimension
  24. real=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension))
  25. imag=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension))
  26. submatrix=real+1j*imag
  27. t=time.clock()
  28. n=0
  29. while time.clock()-t < maxtime:
  30. for i in range(5):
  31. function(submatrix)
  32. n+=5
  33. counts.append(n)
  34. plt.plot(dimensions, counts, '.-', label=label)
  35. plt.ylabel('Number of permanents per second')
  36. plt.xlabel('Dimension')
  37. plt.xlim(min(dimensions), max(dimensions))
  38. plt.legend()
  39. plt.semilogy()
  40. plt.savefig('out.pdf')