Peter Otten於 2014年12月12日星期五UTC+8下午8時32分55秒寫道： > Jussi Piitulainen wrote: > > > KK Sasa writes: > > > >> def p(x,t,point,z,obs): > >> d = x[0] > >> tau = [0]+[x[1:point]] > >> a = x[point:len(x)] > >> at = sum(i*j for i, j in zip(a, t)) > >> nu = [exp(z[k]*(at-d)-sum(tau[k])) for k in xrange(point)] > >> de = sum(nu, axis=0) > >> probability = [nu[k]/de for k in xrange(point)] > >> return probability[obs] > > > > I must be blind, but this looks like computing a whole probability > > distribution and then throwing almost all of it away. > > > > Can't this just return nu[obs]/de? > > > > The expression for tau also seems weird to me. Isn't it equivalent to > > [0, x[1:point]], a two-element list with the second element a list? > > How can sum(tau[k]) work at all then, for any k > 1? > > Also, after adding > > from numpy.random import seed > > to the code I run into the next problem: > > Traceback (most recent call last): > File "hessian.py", line 34, in <module> > re = [d2(x,t[k],2,z,1) for k in range_people] > File "/home/petto/.local/lib/python2.7/site-packages/ad/__init__.py", line > 1114, in hess > return func(xa, *args).hessian([xa]) > File "hessian.py", line 26, in p > nu = [exp(z[k]*(at-d)-sum(tau[k])) for k in xrange(point)] > TypeError: 'int' object is not iterable > > OP: Optimizations only make sense when you can start from a known-good base. > You should sort out the logic of your problem (we probably can't help you > with that), then fix the bugs in your code and only then revisit the "speed > issue".
I have no idea why you added "from numpy.random import seed" to this syntax. Even I added that, my python didn't complain any bugs inside. Maybe your ad package was not be installed correctly? -- https://mail.python.org/mailman/listinfo/python-list
