Here is the mpmath mailing list https://groups.google.com/forum/#!forum/mpmath.
Aaron Meurer On Thu, Jan 14, 2016 at 11:17 AM, Tobias Hartung <[email protected]> wrote: > Thank you and sorry about the wrong group post. Do you happen to know, how I > can crosspost it? > > Tobias > > On Thursday, January 14, 2016 at 3:35:34 PM UTC, Aaron Meurer wrote: >> >> You may want to crosspost this to the mpmath list. >> >> Aaron Meurer >> >> On Thu, Jan 14, 2016 at 10:14 AM, Tobias Hartung >> <[email protected]> wrote: >> > Hi everyone, >> > >> > I am trying to integrate polynomials on an n-sphere and implemented (see >> > attached) the algorithm published in Alan Genz "Fully Symmetric >> > Interpolatory Rules for Multiple Integrals over Hyper-Spherical >> > Surfaces" >> > Journal of Computational and Applied Mathematics 157: 187-195, 2003. On >> > double precision, everything is fine; however, I lose precision in some >> > integrals using more than double prec. >> > >> > I am using randomized samples on the sphere which (by construction) >> > should >> > integrate the polynomials (that I tested) exactly. However, integrating >> > all >> > polynomials up to degree 6 on a 5-dimensional sphere with points that >> > should >> > integrate all polynomials up to degree 7 exactly, I obtain the following >> > test results : >> > >> > mp.prec = 1024 (aka mp.dps = 307) >> > >> > polynomial | degree of polynomial | log_10 ( difference of two >> > randomized integrations ) | log_10 ( relative error of weights ) | >> > analytic value of integral >> > >> > [0, 0, 0, 0, 0, 0] 0 -inf -306.962262 >> > 31.0062767 >> > [1, 0, 0, 0, 0, 0] 1 -308.111506 -306.962262 0.0 >> > [2, 0, 0, 0, 0, 0] 2 -14.519354 -306.962262 >> > 5.16771278 >> > [1, 1, 0, 0, 0, 0] 2 -14.8787358 -306.962262 0.0 >> > [3, 0, 0, 0, 0, 0] 3 -308.583548 -306.962262 0.0 >> > [2, 1, 0, 0, 0, 0] 3 -309.157806 -306.962262 0.0 >> > [1, 1, 1, 0, 0, 0] 3 -309.759866 -306.962262 0.0 >> > [4, 0, 0, 0, 0, 0] 4 -14.6442927 -306.962262 >> > 1.93789229 >> > [3, 1, 0, 0, 0, 0] 4 -15.3047045 -306.962262 0.0 >> > [2, 2, 0, 0, 0, 0] 4 -15.0673319 -306.962262 >> > 0.645964098 >> > [2, 1, 1, 0, 0, 0] 4 -16.0594155 -306.962262 0.0 >> > [1, 1, 1, 1, 0, 0] 4 -31.8146065 -306.962262 0.0 >> > [5, 0, 0, 0, 0, 0] 5 -309.37189 -306.962262 0.0 >> > [4, 1, 0, 0, 0, 0] 5 -309.481766 -306.962262 0.0 >> > [3, 2, 0, 0, 0, 0] 5 -309.739262 -306.962262 0.0 >> > [3, 1, 1, 0, 0, 0] 5 -310.095075 -306.962262 0.0 >> > [2, 2, 1, 0, 0, 0] 5 -310.474598 -306.962262 0.0 >> > [2, 1, 1, 1, 0, 0] 5 -310.714154 -306.962262 0.0 >> > [1, 1, 1, 1, 1, 0] 5 -311.46643 -306.962262 0.0 >> > [6, 0, 0, 0, 0, 0] 6 -14.7692314 -306.962262 >> > 0.968946146 >> > [5, 1, 0, 0, 0, 0] 6 -15.6057345 -306.962262 0.0 >> > [4, 2, 0, 0, 0, 0] 6 -15.4314091 -306.962262 >> > 0.193789229 >> > [3, 3, 0, 0, 0, 0] 6 -15.8275833 -306.962262 0.0 >> > [4, 1, 1, 0, 0, 0] 6 -16.5822942 -306.962262 0.0 >> > [3, 2, 1, 0, 0, 0] 6 -16.4753651 -306.962262 0.0 >> > [2, 2, 2, 0, 0, 0] 6 -16.0997045 -306.962262 >> > 0.0645964098 >> > [3, 1, 1, 1, 0, 0] 6 -32.3374853 -306.962262 0.0 >> > [2, 2, 1, 1, 0, 0] 6 -17.3552924 -306.962262 0.0 >> > [2, 1, 1, 1, 1, 0] 6 -33.4100353 -306.962262 0.0 >> > [1, 1, 1, 1, 1, 1] 6 -49.1751847 -306.962262 0.0 >> > >> > It should be noted that the polynomial are written in the following >> > form: a >> > list p of length n represents the polynomial >> > >> > z_0^{p[0]} z_1^{p[1]} z_2^{p[2]} ... z_{n-1}^{p[n-1]}. >> > >> > If we look at the second to last column, we can see that the weights add >> > are >> > exact with respect to mp.prec=1024 but do not add up to 1.0 exactly. >> > Hence, >> > the loss in precision is unlikely to be caused by the weights being only >> > on >> > double prec (and even if it is, then I don't understand why because they >> > are >> > calculated with mp.prec=1024, as well). >> > >> > The really interesting column is the middle one. Here, I took two >> > randomized >> > set of integration points (both should integrate all polynomials exactly >> > up >> > to machine error) and printed the decadic logarithm of the absolute >> > value of >> > their difference. In other words, we are expecting the middle column to >> > be >> > populated with numbers in the vicinity of -307 (just like the fourth >> > column). However, we only get these values for odd degree polynomials >> > (and >> > the constant 1 but that is just the sum of weights, i.e., the >> > randomization >> > doesn't do anything). For even degree polynomials, we have significantly >> > reduced precision. >> > >> > Does anyone have an idea what might be the reason for such behavior? >> > >> > Thank you very much, >> > Tobias >> > >> > -- >> > You received this message because you are subscribed to the Google >> > Groups >> > "sympy" group. >> > To unsubscribe from this group and stop receiving emails from it, send >> > an >> > email to [email protected]. >> > To post to this group, send email to [email protected]. >> > Visit this group at https://groups.google.com/group/sympy. >> > To view this discussion on the web visit >> > >> > https://groups.google.com/d/msgid/sympy/cf76f223-96a0-4789-8530-db224622f6bb%40googlegroups.com. >> > For more options, visit https://groups.google.com/d/optout. > > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/sympy. > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/015dd6ad-d2e8-495c-82f7-1c157b0c7ab0%40googlegroups.com. > > For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups "sympy" group. 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