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@@ -1,46 +1,42 @@ |
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import os, sys |
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import time |
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import multiprocessing as mp |
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import numpy as np |
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import time |
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from matplotlib import pyplot as plt |
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from permanent import permanent |
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import itertools as it |
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def permanent(a): |
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""" Slow way to compute the permanent """ |
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r = range(len(a)) |
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return sum([np.prod(a[r, p]) for p in it.permutations(r)]) |
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if __name__ == '__main__': |
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maxtime=1 |
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dimensions=range(1,11) |
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for (function, label) in zip((permanent, perm_ryser), ("C", "Python")): |
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counts=[] |
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for dimension in dimensions: |
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print dimension |
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real=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension)) |
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imag=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension)) |
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submatrix=real+1j*imag |
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t=time.clock() |
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n=0 |
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while time.clock()-t < maxtime: |
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for i in range(5): |
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function(submatrix) |
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n+=5 |
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counts.append(n) |
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plt.plot(dimensions, counts, ".-", label=label) |
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def perm_ryser(a): |
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''' the permanent calculated using the ryser formula. much faster than the naive approach ''' |
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n,n2=a.shape |
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z=np.arange(n) |
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irange=xrange(2**n) |
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get_index=lambda i: (i & (1 << z)) != 0 |
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get_term=lambda index: ((-1)**np.sum(index))*np.prod(np.sum(a[index,:], 0)) |
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indeces=map(get_index, irange) |
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terms=map(get_term, indeces) |
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return np.sum(terms)*((-1)**n) |
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maxtime=1 |
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dimensions=range(1,11) |
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for (function, label) in zip((permanent, perm_ryser), ("C", "Python")): |
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counts=[] |
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for dimension in dimensions: |
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print dimension |
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real=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension)) |
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imag=np.random.uniform(-1, 1, dimension*dimension).reshape((dimension, dimension)) |
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submatrix=real+1j*imag |
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t=time.clock() |
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n=0 |
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while time.clock()-t < maxtime: |
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for i in range(5): |
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function(submatrix) |
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n+=5 |
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counts.append(n) |
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plt.plot(dimensions, counts, '.-', label=label) |
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plt.ylabel('Number of permanents per second') |
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plt.xlabel('Dimension') |
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plt.xlim(min(dimensions), max(dimensions)) |
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plt.legend() |
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plt.semilogy() |
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plt.savefig('out.pdf') |
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plt.ylabel("Number of permanents per second") |
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plt.xlabel("Dimension") |
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plt.xlim(min(dimensions), max(dimensions)) |
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plt.legend() |
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plt.semilogy() |
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plt.savefig("out.pdf") |