Ian,
Seems I have joined a blog site re Eigen.
I am a 77 year old blitzer of a programmer (started out with FORTRAN in
1961!) and I may be only looking over the fence and should go away?
I will describe myself and you might tell me what I need to do...
My aim is to find a general matrix inverter.
I want it to solve 3D hydrodynamic equations per book “Hydrodynamics” by
Horace Lamb.
I run Borland’s Builder version 1.0 and am fluent with STL C++.
I have loaded and tried to get Eigen going only to find to my
frustration it does not seem to know about anything about AnsiString -
using only “>>’s” and String.h.
Bad luck and bye bye for me?
Any tips?
Happy days,
Trevor Smith
Sydney, Australia
------ Original Message ------
On Monday, 4 Jan, 2021 At 1:11 AM, Ian Bell<ian.h.bell@xxxxxxxxx> wrote:
I can certainly file a bug report. Thanks for confirming that I didn't
just do something stupid on my side.
On Fri, Jan 1, 2021 at 6:07 PM Christoph Hertzberg
<chtz@xxxxxxxxxxxxxxxxxxxxxxxx <mailto:chtz@xxxxxxxxxxxxxxxxxxxxxxxx> >
wrote:
The breaking commit for your minimal example is this:
https://gitlab.com/libeigen/eigen/-/commit/39c2cba810a573ae4d0efd2b0b80e08c934b99b3
<https://gitlab.com/libeigen/eigen/-/commit/39c2cba810a573ae4d0efd2b0b80e08c934b99b3>
Apparently that was necessary for cuda support -- not sure if this is
actually still necessary. On the 3.3 branch your code compiles fine:
https://godbolt.org/z/nnqPEn <https://godbolt.org/z/nnqPEn>
Boost is actually not supposed to fiddle around in Eigen's internal
namespace. OTOH, we don't properly document how one should add support
for complex custom types.
Could you file an issue for this?
Cheers,
Christoph
On 01/01/2021 22.12, Ian Bell wrote:
> It seems that at version 3.3.3 things were all good, and since then
there
> have a been quite a few regressions for extended precision things. I'm
> trying to track down a couple of bugs on my side. My hypothesis is that
> there is somewhere a precision-destroying cast, but I'm not quite sure.
>
> On Thu, Dec 31, 2020 at 3:47 PM Ian Bell <ian.h.bell@xxxxxxxxx
<mailto:ian.h.bell@xxxxxxxxx> > wrote:
>
>> I have no idea whether this is a problem with boost or Eigen, but
putting
>> boost::multiprecision into Eigen Array/Matrix worked in older
versions of
>> Eigen from circa 2017, but no longer does. For instance this
example (
>>
https://www.boost.org/doc/libs/1_75_0/libs/multiprecision/doc/html/boost_multiprecision/tut/eigen.html
<https://www.boost.org/doc/libs/1_75_0/libs/multiprecision/doc/html/boost_multiprecision/tut/eigen.html>
>> ; copied below) used to work, but now when I compile with master, I
get
>> complaints about the NumTraits. I'm at
>> commit fdf2ee62c5174441076fb64c9737d89bbe102759. I tried to look
into this
>> a bit, but template-fu needs work.
>>
>> On Visual Studio 2019:
>>
>> Build started...
>> 1>------ Build started: Project: boosteigen, Configuration: Release
x64
>> ------
>> 1>boosteigentest.cpp
>> 1>C:\Users\ihb\PapersInProgress\Working\03a.
>>
UlrichCubicSuperAncillary\code\bld\_deps\boost-src\boost/multiprecision/eigen.hpp(147,23):
>> error C2977: 'Eigen::internal::conj_impl': too many template arguments
>> 1>C:\Users\ihb\PapersInProgress\Working\03a.
>>
UlrichCubicSuperAncillary\code\bld\_deps\boost-src\boost/multiprecision/eigen.hpp(147):
>> message : see declaration of 'Eigen::internal::conj_impl'
>> 1>C:\Users\ihb\PapersInProgress\Working\03a.
>>
UlrichCubicSuperAncillary\code\bld\_deps\boost-src\boost/multiprecision/eigen.hpp(164,8):
>> error C2977: 'Eigen::internal::conj_impl': too many template arguments
>> 1>C:\Users\ihb\PapersInProgress\Working\03a.
>>
UlrichCubicSuperAncillary\code\bld\_deps\boost-src\boost/multiprecision/eigen.hpp(157):
>> message : see declaration of 'Eigen::internal::conj_impl'
>>
>> And on gcc 9.3.0:
>>
>> [100%] Building CXX object
CMakeFiles/boosteigen.dir/boosteigentest.cpp.o
>> In file included from /input/boosteigentest.cpp:3:
>> /bld/_deps/boost-src/boost/multiprecision/eigen.hpp:147:14: error:
>> redeclared with 2 template parameters
>> 147 | struct conj_impl;
>> | ^~~~~~~~~
>> In file included from
>> /input/externals/ChebTools/externals/Eigen/Eigen/Core:164,
>> from
>> /bld/_deps/boost-src/boost/multiprecision/eigen.hpp:10,
>> from /input/boosteigentest.cpp:3:
>>
/input/externals/ChebTools/externals/Eigen/Eigen/src/Core/MathFunctions.h:263:34:
>> note: previous declaration 'template<class Scalar> struct
>> Eigen::internal::conj_impl' used 1 template parameter
>> 263 | template<typename Scalar> struct conj_impl :
>> conj_default_impl<Scalar> {};
>> | ^~~~~~~~~
>> In file included from /input/boosteigentest.cpp:3:
>> /bld/_deps/boost-src/boost/multiprecision/eigen.hpp:157:100: error:
wrong
>> number of template arguments (2, should be 1)
>> 157 | struct
>> conj_impl<boost::multiprecision::detail::expression<tag, Arg1,
Arg2, Arg3,
>> Arg4>, true>
>> |
>> ^
>> In file included from
>> /input/externals/ChebTools/externals/Eigen/Eigen/Core:164,
>> from
>> /bld/_deps/boost-src/boost/multiprecision/eigen.hpp:10,
>> from /input/boosteigentest.cpp:3:
>>
/input/externals/ChebTools/externals/Eigen/Eigen/src/Core/MathFunctions.h:263:34:
>> note: provided for 'template<class Scalar> struct
>> Eigen::internal::conj_impl'
>> 263 | template<typename Scalar> struct conj_impl :
>> conj_default_impl<Scalar> {};
>> | ^~~~~~~~~
>>
>>
>> Example:
>>
>> #include <iostream>#include
<boost/multiprecision/cpp_complex.hpp>#include
<boost/multiprecision/eigen.hpp>#include <Eigen/Dense>
>> int main(){
>> using namespace Eigen;
>> typedef boost::multiprecision::cpp_complex_quad complex_type;
>> //
>> // We want to solve Ax = b for x,
>> // define A and b first:
>> //
>> Matrix<complex_type, 2, 2> A, b;
>> A << complex_type(2, 3), complex_type(-1, -2), complex_type(-1,
-4), complex_type(3, 6);
>> b << 1, 2, 3, 1;
>> std::cout << "Here is the matrix A:\n" << A << std::endl;
>> std::cout << "Here is the right hand side b:\n" << b << std::endl;
>> //
>> // Solve for x:
>> //
>> Matrix<complex_type, 2, 2> x = A.fullPivHouseholderQr().solve(b);
>> std::cout << "The solution is:\n" << x << std::endl;
>> //
>> // Compute the error in the solution by using the norms of Ax -
b and b:
>> //
>> complex_type::value_type relative_error = (A*x - b).norm() /
b.norm();
>> std::cout << "The relative error is: " << relative_error <<
std::endl;
>> return 0;}
>>
>>
>