Teie kommentaarid
= R2019b:
% Calculate cross product
c1 = conj(a(2).*b(3)-a(3).*b(2));
c2 = conj(a(3).*b(1)-a(1).*b(3));
c3 = conj(a(1).*b(2)-a(2).*b(1));
if iscolumn(a) && iscolumn(b)
c = [c1; c2; c3];
else
c = [c1, c2, c3];
end
= R2019b_update3:
% Calculate cross product c1 = a(2).*b(3)-a(3).*b(2); c2 = a(3).*b(1)-a(1).*b(3); c3 = a(1).*b(2)-a(2).*b(1); if iscolumn(a) && iscolumn(b) c = [c1; c2; c3]; else c = [c1, c2, c3]; end
>> mp.Info
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Multiprecision Computing Toolbox, (c) 2008-2019 Advanpix LLC.
Version : 4.7.0 Build 13560
Release : 2019-11-06
Platform : Win64
Processor: Lynnfield (Core i7) / Intel(R) Core(TM) i7 CPU 860 @ 2.80GHz
MachineID: =CD00FF5FEA5F98CD00155D11736DCD6C626D57F933CD0A002700000DCD00FF415B375DAC2465FDC0FC95318A5F4D4B630C0C50B0=
Licensed to: Michal Kvasnicka
Maintenance: 2020-01-20
Open Source Libraries Acknowledgements:
MPIR 3.0.0 C Library for Multiple Precision Integers and Rationals.
MPFR 4.1.0-dev C Library for Multiple-Precision Floating-point computations with correct Rounding.
MPC 1.1.1dev C Library for the Arithmetic of Complex numbers with arbitrary high precision.
ARB 2.17.0 C library for arbitrary-precision ball arithmetic.
MPFR C++ 3.6.6 C++ multi-precision floating point number class.
Eigen 3.2.90 C++ template library for linear algebra.
QRUPDATE 1.1.2 Library for fast updating of QR and Cholesky decompositions.
SLICOT 5.5.0 The Control and Systems Library.
LIBCPUID 0.4.0 CPU identification and feature extraction on the x86.
Boost 1.49.0 Free peer-reviewed portable C++ source libraries.
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Similar problem with R2019b_update3 ... (only Windows platform tested so far)
cross() : 2 <- fail
3 <- fail
9 <- fail
10 <- fail
<- success
Thanks for fast fix!!!
I mean Matlab R2019b ... sorry for typo
But cooperation with any commercial optimization solver developers is always very problematic task. My personal experience in this domain is very negative. Any idea how will the final product look like?
I am afraid, that this suggestion is a bit out of scope for MCT. All above mentioned commercial solvers are realized typically at C/C++ and available Matlab toolboxes (all supports only double-precision class) plays only a role of interface between these low-level solvers (implemented as C/C++ MEX files) and Matlab environment.
The only way, in this case, is incorporation of multi-precision computing libraries (like MPIR C Library for Multiple Precision Integers and Rationals, MPFR C Library for Multiple-Precision Floating-point computations with correct Rounding, MPC C Library for the Arithmetic of Complex numbers with arbitrary high precision, MPFR C++ multi-precision floating point number class, etc.), to these low-level solvers source code, which is definitely not simple task at all.
By my best knowledge of MCT, the only possible way, how to perform multi-precision optimization via MCT is modification of suitable optimization solvers, which are completely implemented at MATLAB to use mp class. But, I am sure (!!!), that for above mentioned commercial solvers are not available any strictly MATLAB coded solvers.
I did not observed this problem with any other matlab algorithms (linear algebra, FFT, statistics, etc.). Degradation of ODE's algorithm is so significant (benchmark problem is only very simple example to show this problem in natura), that is really not acceptable.
Finally, to avoid this problem, you propose only remove MCT from the path? Am I right? But this is off/on solution. In a case of active MCT user will be always suffered by significant ODE's slowdown.
Customer support service by UserEcho
When will be available next release with fixed cross product function?