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KeyboardInterrupt                         Traceback (most recent call last)
 in ()
     26             q = 2*x # due to monotonicity of mode
     27         name = '%s-%s-plain.pdf' % (args.dataset, args.problem)
---> 28         epss, em, pf = get_lines2(q)
     29 
     30         fig = plt.figure()

 in get_lines2(q)
      5     max_eps = expected_epsilon(q, 1.0, pmf=em_pmf)
      6     epss = np.linspace(min_eps, max_eps, 100)
----> 7     pf = [expected_error(q, eps, pf_pmf) for eps in epss]
      8     em = [expected_error(q, eps, em_pmf) for eps in epss]
      9     #due to numerical issues sometimes pf = maxerr (for near-zero epsilon)

 in (.0)
      5     max_eps = expected_epsilon(q, 1.0, pmf=em_pmf)
      6     epss = np.linspace(min_eps, max_eps, 100)
----> 7     pf = [expected_error(q, eps, pf_pmf) for eps in epss]
      8     em = [expected_error(q, eps, em_pmf) for eps in epss]
      9     #due to numerical issues sometimes pf = maxerr (for near-zero epsilon)

~/Dropbox/UMass/research/permute-and-flip/mechanisms.py in expected_error(q, eps, pmf)
     81 def expected_error(q, eps, pmf=em_pmf):
     82     # compute the expected error of the mechanism (given it's probability mass function)
---> 83     ans = q.max() - pmf(q,eps) @ q
     84     maxerr = q.max() - q.mean()
     85     if ans > maxerr or ans < 0:

~/Dropbox/UMass/research/permute-and-flip/mechanisms.py in pf_pmf(q, eps, sensitivity, monotonic)
     43         new[0] -= p[i]
     44         for j in range(1,n):
---> 45             new[j] -= new[j-1]*p[i]
     46 
     47         ans[i] = p[i] * (1 + new @ coef)

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