- GiNaC-list - ginac.de

Bug? Segmentation while inverting a matrix
by Patrick Schulz 09 Jan '18

09 Jan '18

Hi, i'm getting a segmentation fault while inverting a matrix (the matrix itself is invertable, i checked with the symbolic package for octave). Can anyone give me some pointers why this is happening? Is the matrix ill-formed in some way or is this a bug? Many thanks in advance! I'm running archlinux (Kernel 4.14.12), my compiler is g++ 7.2.1, the GiNaC version i'm using is 1.7.2. Attached is a sample listing which produces the error (at least on my system). Greetings, Patrick

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factor() hangs on a simple expression, randomly
by Vitaly Magerya 28 Dec '17

28 Dec '17

Hi, folks. I have this problem: $ ginsh ginsh - GiNaC Interactive Shell (GiNaC V1.7.2) __, _______ Copyright (C) 1999-2017 Johannes Gutenberg University Mainz, (__) * | Germany. This is free software with ABSOLUTELY NO WARRANTY. ._) i N a C | You are welcome to redistribute it under certain conditions. <-------------' For details type `warranty;'. Type ?? for a list of help topics. > factor((2*x-l)^2*(-1+6*x-l)*(-1+3*x-l)*(-2+4*x-l)*(1+4*x-l)*(4*x-l)*(2+4*x-l)); At this point ginsh either hangs (80% of cases), or gives the correct result (20% of cases). As you can see the expression is already factored, so a hang is pretty unexpected here. Note that if you'll drop two of the factors from that expression, GiNaC won't hang anymore. Here are the cumulative timings you'll typically see via 'perf top' during this hang: 91.54% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::factor_multivariate 81.32% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::hensel_multivar 79.67% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::multivar_diophant 79.67% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::univar_diophant 79.67% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::multiterm_eea_lift 72.77% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::factor_sqrfree 66.18% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::eea_lift 64.28% libginac.so.6.0.2 [.] GiNaC::factor 26.99% libginac.so.6.0.2 [.] GiNaC::(anonymous namespace)::operator* 23.67% ginsh [.] yyparse 23.67% ginsh [.] f_factor 16.91% libginac.so.6.0.2 [.] cln::cl_MI::~cl_MI 15.26% libginac.so.6.0.2 [.] cln::cl_I::~cl_I 13.66% libginac.so.6.0.2 [.] cln::cl_MI::cl_MI 13.55% libginac.so.6.0.2 [.] cln::cl_RA::~cl_RA So, any ideas on the nature of this problem, and how to fix it?

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ginac and openmp
by Tania Robens 04 Dec '17

04 Dec '17

Dear all I am trying to run ginac with openmp and get seg faults... [all in a very naive fashion at the moment]. Is the code supposed to run ad hoc with openmp (compiled accordingly of course)/ are there any pitfalls/ ... ?? Any help is appreciated Thanks Best Tania

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Subreddit for Computer Algebra Systems in General Purpose Languages
by Eduardo Cavazos 02 Nov '17

02 Nov '17

Hey folks! Just wanted to let you know, there's a new subreddit dedicated to computer algebra libraries in general purpose programming languages: https://www.reddit.com/r/gplcas/ Feel free to share GiNaC related news there. :-) Ed

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real_part and imag_part
by Jan Rheinländer 09 Aug '17

09 Aug '17

Hi, what is the logic here (example from ginsh)? > real_part(sqrt(-3)); sqrt(-3) > imag_part(sqrt(-3)); 0 > real_part(sqrt(-1)); 0 > imag_part(sqrt(-1)); 1 Greetings, Jan

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Re: [GiNaC-list] How to differentiate from a Tensor?
by Vladimir V. Kisil 18 Jul '17

18 Jul '17

>>>>> On Fri, 14 Jul 2017 13:29:37 +0430, esarcush esarcush <esarcush(a)gmail.com> said: EE> E needs to depend on x. So, symbol A("A"), x("x"); symbol EE> i_sym("i"), j_sym("j"); idx i(i_sym, 3), j(j_sym, 3); ex e = EE> indexed(A, i, j); ex de_dx = e.diff(x); cout << de_dx << "\n"; EE> returns 0. Thus, what is the way to depend "e" on "x" like EE> undefined functions? If a dependence of A on x is not defined, try to use the step function (as one without defined derivative): ex e = indexed(step(x), i, j); This keeps track on derivatives. To maintainer: I have run into similar situation working with differential operators. Shall we add "generic" functions to GiNaC with 1, 2, 3, 4 variables? -- Vladimir V. Kisil http://www.maths.leeds.ac.uk/~kisilv/ Book: Geometry of Mobius Transformations http://goo.gl/EaG2Vu Software: Geometry of cycles http://moebinv.sourceforge.net/ EE> All the bests, EE> On 7/14/17, Vladimir V. Kisil <kisilv(a)maths.leeds.ac.uk> wrote: >>>>>>> On Fri, 14 Jul 2017 12:15:49 +0430, esarcush esarcush >>>>>>> <esarcush(a)gmail.com> said: >> EE> Dear all, What is right way to have something like $ EE> \frac{\partial A^{i}_{jk}}{\partial x} $? Indeed, I defined a EE> tensor "A~i.j.k" and want to differentiate from it with respect EE> to "x" e.g. >> >> For a GiNaC object E its derivative with respect to x is obtained >> by E.diff(x) >> -- >> Vladimir V. Kisil http://www.maths.leeds.ac.uk/~kisilv/ Book: >> Geometry of Mobius Transformations http://goo.gl/EaG2Vu Software: >> Geometry of cycles http://moebinv.sourceforge.net/ >>

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Re: [GiNaC-list] Tricky way to control over dummy indices
by esarcush esarcush 14 Jul '17

14 Jul '17

On 7/15/17, esarcush esarcush <esarcush(a)gmail.com> wrote: > Agreement: Every dummy index have a hidden sigma. > > Based on the page you linked (and in common also), there are two ways > to illustrate a dummy index in a term: > 1) "j" is a dummy one iff it appears as superscript and subscript. > > 2) "j" is a dummy one iff it appears in two (or more that two) > tensor coefficients making that term. > > GiNaC is using second approach. This makes some troubles to somebodies > that are using first one. For example, I'd like to deal with some > tensorials that have in-common indices as e.g. subscripts but free (as > mentioned example). I think second approach is more physical vs first > one more diff-geometrical. ;) > > All the best, > Esa > > > > > > > > > On 7/14/17, Vladimir V. Kisil <kisilv(a)maths.leeds.ac.uk> wrote: >>>>>>> On Fri, 14 Jul 2017 22:54:35 +0430, esarcush esarcush >>>>>>> <esarcush(a)gmail.com> said: >> >> EE> Dear all, in expression >> >> EE> { indexed(A, i, j) * indexed(B, j, k) } >> >> EE> GiNaC is saying that the dummy index is "j" and "i, k" are >> EE> free. Is there a way to determine dummy indices based on >> EE> Einstein summation notation; namely all the indices in the >> EE> latter be free. >> >> My understanding of >> >> https://en.wikipedia.org/wiki/Einstein_notation >> >> is that in the above expression there is summation over j, thus it is >> not free. >> -- >> Vladimir V. Kisil http://www.maths.leeds.ac.uk/~kisilv/ >> Book: Geometry of Mobius Transformations http://goo.gl/EaG2Vu >> Software: Geometry of cycles http://moebinv.sourceforge.net/ >> >

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Tricky way to control over dummy indices
by esarcush esarcush 14 Jul '17

14 Jul '17

Dear all, in expression { indexed(A, i, j) * indexed(B, j, k) } GiNaC is saying that the dummy index is "j" and "i, k" are free. Is there a way to determine dummy indices based on Einstein summation notation; namely all the indices in the latter be free. All the bests, Esa

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Re: [GiNaC-list] How to differentiate from a Tensor?
by esarcush esarcush 14 Jul '17

14 Jul '17

On 7/14/17, Vladimir V. Kisil <kisilv(a)maths.leeds.ac.uk> wrote: >>>>>> On Fri, 14 Jul 2017 12:15:49 +0430, esarcush esarcush >>>>>> <esarcush(a)gmail.com> said: > > EE> Dear all, What is right way to have something like $ > EE> \frac{\partial A^{i}_{jk}}{\partial x} $? Indeed, I defined a > EE> tensor "A~i.j.k" and want to differentiate from it with respect > EE> to "x" e.g. > > For a GiNaC object E its derivative with respect to x is obtained by > E.diff(x) > -- > Vladimir V. Kisil http://www.maths.leeds.ac.uk/~kisilv/ > Book: Geometry of Mobius Transformations http://goo.gl/EaG2Vu > Software: Geometry of cycles http://moebinv.sourceforge.net/ > E needs to depend on x. So, symbol A("A"), x("x"); symbol i_sym("i"), j_sym("j"); idx i(i_sym, 3), j(j_sym, 3); ex e = indexed(A, i, j); ex de_dx = e.diff(x); cout << de_dx << "\n"; returns 0. Thus, what is the way to depend "e" on "x" like undefined functions? All the bests,

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How to differentiate from a Tensor?
by esarcush esarcush 14 Jul '17

14 Jul '17

Dear all, What is right way to have something like $ \frac{\partial A^{i}_{jk}}{\partial x} $? Indeed, I defined a tensor "A~i.j.k" and want to differentiate from it with respect to "x" e.g. All the bests, Esa

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