KK Sasa wrote: > 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?
It may be a version issue. I'm using >>> import ad, numpy >>> ad.__version__ '1.2.2' >>> numpy.__version__ '1.9.1' Or are you using an environment that does some imports automatically? -- https://mail.python.org/mailman/listinfo/python-list
