eba7a485ba
COMP: define labelSphericalTensor::I - remove spurious 'labelI' global constant (labelSphericalTensor::I) STYLE: replace use of deprecated Tensor vectorComponent STYLE: avoid bit-wise assignment of bool (VectorSpace compare ops)
859 lines
24 KiB
C
859 lines
24 KiB
C
/*---------------------------------------------------------------------------*\
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========= |
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\\ / F ield | OpenFOAM: The Open Source CFD Toolbox
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\\ / O peration |
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\\ / A nd | www.openfoam.com
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\\/ M anipulation |
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-------------------------------------------------------------------------------
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Copyright (C) 2020-2022 OpenCFD Ltd.
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-------------------------------------------------------------------------------
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License
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This file is part of OpenFOAM.
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OpenFOAM is free software: you can redistribute it and/or modify it
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under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OpenFOAM is distributed in the hope that it will be useful, but WITHOUT
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ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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for more details.
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You should have received a copy of the GNU General Public License
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along with OpenFOAM. If not, see <http://www.gnu.org/licenses/>.
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Application
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Test-SymmTensor
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Description
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Tests for \c SymmTensor constructors, member functions and operators
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using \c floatScalar, \c doubleScalar, and \c complex base types.
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Eigen decomposition tests for \c symmTensor, i.e. SymmTensor<scalar>.
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Cross-checks were obtained from 'NumPy 1.15.1' and 'SciPy 1.1.0' if no
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theoretical cross-check exists (like eigendecomposition relations), and
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were hard-coded for elementwise comparisons.
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For \c complex base type, the cross-checks do only involve zero imag part.
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\*---------------------------------------------------------------------------*/
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#include "symmTensor.H"
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#include "transform.H"
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#include "Random.H"
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#include "scalar.H"
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#include "complex.H"
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using namespace Foam;
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// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * //
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// Total number of unit tests
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unsigned nTest_ = 0;
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// Total number of failed unit tests
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unsigned nFail_ = 0;
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// Create a random symmTensor
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symmTensor makeRandomContainer(Random& rnd)
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{
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symmTensor T(Zero);
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std::generate(T.begin(), T.end(), [&]{ return rnd.GaussNormal<scalar>(); });
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return T;
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}
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// Create a symmTensor based on a given value
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template<class Type>
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typename std::enable_if
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<
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std::is_same<floatScalar, Type>::value ||
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std::is_same<doubleScalar, Type>::value,
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symmTensor
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>::type makeContainer(const Type val)
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{
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symmTensor T(Zero);
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std::fill(T.begin(), T.end(), val);
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return T;
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}
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// Compare two floating point types, and print output.
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// Do ++nFail_ if values of two objects are not equal within a given tolerance.
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// The function is converted from PEP-485.
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template<class Type>
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typename std::enable_if<pTraits<Type>::rank == 0, void>::type
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cmp
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(
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const word& msg,
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const Type& x,
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const Type& y,
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const scalar absTol = 0, //<! useful for cmps near zero
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const scalar relTol = 1e-8 //<! are values the same within 8 decimals
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)
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{
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Info<< msg << x << "?=" << y << endl;
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unsigned nFail = 0;
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if (max(absTol, relTol*max(mag(x), mag(y))) < mag(x - y))
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{
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++nFail;
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}
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if (nFail)
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{
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Info<< nl
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<< " #### Fail in " << nFail << " comps ####" << nl << endl;
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++nFail_;
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}
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++nTest_;
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}
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// Compare two containers elementwise, and print output.
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// Do ++nFail_ if two components are not equal within a given tolerance.
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// The function is converted from PEP-485
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template<class Type>
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typename std::enable_if<pTraits<Type>::rank != 0, void>::type
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cmp
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(
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const word& msg,
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const Type& x,
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const Type& y,
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const scalar absTol = 0,
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const scalar relTol = 1e-8
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)
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{
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Info<< msg << x << "?=" << y << endl;
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unsigned nFail = 0;
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for (direction i = 0; i < pTraits<Type>::nComponents; ++i)
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{
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if (max(absTol, relTol*max(mag(x[i]), mag(y[i]))) < mag(x[i] - y[i]))
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{
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++nFail;
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}
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}
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if (nFail)
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{
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Info<< nl
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<< " #### Fail in " << nFail << " comps ####" << nl << endl;
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++nFail_;
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}
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++nTest_;
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}
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// Create each constructor of SymmTensor<Type>, and print output
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template<class Type>
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void test_constructors(Type)
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{
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{
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Info<< "# Construct initialized to zero:" << nl;
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const SymmTensor<Type> sT(Zero);
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Info<< sT << endl;
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}
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{
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Info<< "# Construct given VectorSpace of the same rank:" << nl;
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const VectorSpace<SymmTensor<Type>, Type, 6> M(Zero);
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const SymmTensor<Type> sT(M);
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Info<< sT << endl;
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}
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{
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Info<< "# Construct given SphericalTensor:" << nl;
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const SphericalTensor<Type> Sp(Type(5));
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const SymmTensor<Type> sT(Sp);
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Info<< sT << endl;
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}
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{
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Info<< "# Construct given the six components:" << nl;
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const SymmTensor<Type> sT
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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);
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Info<< sT << endl;
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}
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{
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Info<< "# Copy construct:" << nl;
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const SymmTensor<Type> sT(Zero);
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const SymmTensor<Type> copysT(sT);
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Info<< sT << tab << copysT << endl;
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}
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}
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// Execute each member function of SymmTensor<Type>, and print output
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template<class Type>
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void test_member_funcs(Type)
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{
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SymmTensor<Type> sT
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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);
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const SymmTensor<Type> csT
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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);
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Info<< "# Operand: " << nl
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<< " SymmTensor = " << sT << endl;
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{
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Info<< "# Component access:" << nl;
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SymmTensor<Type> cpsT
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(
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sT.xx(), sT.xy(), sT.xz(),
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sT.yy(), sT.yz(),
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sT.zz()
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);
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cmp(" 'SymmTensor' access:", sT, cpsT);
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cmp(" xy()=yx():", sT.xy(), sT.yx());
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cmp(" xz()=zx():", sT.xz(), sT.zx());
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cmp(" yz()=zy():", sT.yz(), sT.zy());
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const SymmTensor<Type> cpcsT
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(
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csT.xx(), csT.xy(), csT.xz(),
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csT.yy(), csT.yz(),
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csT.zz()
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);
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cmp(" 'const SymmTensor' access:", csT, cpcsT);
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cmp(" xy()=yx():", sT.xy(), sT.yx());
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cmp(" xz()=zx():", sT.xz(), sT.zx());
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cmp(" yz()=zy():", sT.yz(), sT.zy());
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}
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{
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Info<< "# Diagonal access:" << nl;
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cmp
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(
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" 'SymmTensor'.diag():",
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sT.diag(),
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Vector<Type>(Type(1), Type(5), Type(-9))
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);
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cmp
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(
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" 'const SymmTensor'.diag():",
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csT.diag(),
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Vector<Type>(Type(1), Type(5), Type(-9))
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);
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Info<< "# Diagonal manipulation:" << nl;
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sT.diag(Vector<Type>(Type(-10), Type(-15), Type(-20)));
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cmp
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(
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" 'SymmTensor'.diag('Vector'):",
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sT.diag(),
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Vector<Type>(Type(-10), Type(-15), Type(-20))
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);
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}
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{
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Info<< "# Tensor operations:" << nl;
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Info<< " Transpose:" << nl;
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cmp(" 'SymmTensor'.T():", sT.T(), sT);
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}
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{
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Info<< "# Member operators:" << nl;
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sT = SphericalTensor<Type>(Type(5));
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cmp
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(
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" Assign to a SphericalTensor:",
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sT,
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SymmTensor<Type>
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(
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Type(5), Zero, Zero,
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Type(5), Zero,
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Type(5)
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)
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);
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}
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}
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// Execute each global function of SymmTensor<Type>, and print output
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template<class Type>
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void test_global_funcs(Type)
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{
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const SymmTensor<Type> sT
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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);
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Info<< "# Operand: " << nl
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<< " SymmTensor = " << sT << nl << endl;
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cmp(" Trace = ", tr(sT), Type(-3));
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cmp(" Spherical part = ", sph(sT), SphericalTensor<Type>(tr(sT)/Type(3)));
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cmp(" Symmetric part = ", symm(sT), sT);
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cmp(" Twice the symmetric part = ", twoSymm(sT), 2*sT);
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cmp
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(
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" Deviatoric part = ",
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dev(sT),
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SymmTensor<Type>
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(
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Type(2), Type(2), Type(-3),
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Type(6), Type(-6),
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Type(-8)
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)
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);
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cmp(" Two-third deviatoric part = ", dev2(sT), sT - 2*sph(sT));
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cmp(" Determinant = ", det(sT), Type(-17.999999999999996));
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cmp
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(
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" Cofactor tensor = ",
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cof(sT),
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SymmTensor<Type>
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(
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Type(-81), Type(36), Type(3),
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Type(-18), Type(0),
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Type(1)
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)
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);
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cmp
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(
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" Inverse = ",
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inv(sT, det(sT)),
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SymmTensor<Type>
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(
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Type(4.5), Type(-2), Type(-0.16666667),
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Type(1), Type(0),
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Type(-0.05555556)
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),
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1e-8
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);
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cmp
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(
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" Inverse (another) = ",
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inv(sT),
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SymmTensor<Type>
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(
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Type(4.5), Type(-2), Type(-0.16666667),
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Type(1), Type(0),
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Type(-0.05555556)
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),
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1e-8
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);
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cmp(" First invariant = ", invariantI(sT), Type(-3));
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cmp(" Second invariant = ", invariantII(sT), Type(-98));
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cmp(" Third invariant = ", invariantIII(sT), Type(-17.999999999999996));
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cmp
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(
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" Inner-product with self = ",
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innerSqr(sT),
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SymmTensor<Type>
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(
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Type(14), Type(30), Type(12),
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Type(65), Type(18),
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Type(126)
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)
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);
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cmp(" Square of Frobenius norm = ", magSqr(sT), Type(205));
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}
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// Execute each global operator of SymmTensor<Type>, and print output
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template<class Type>
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void test_global_opers(Type)
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{
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const Tensor<Type> T
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(
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Type(1), Type(2), Type(-3),
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Type(4), Type(5), Type(-6),
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Type(7), Type(8), Type(-9)
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);
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const SymmTensor<Type> sT
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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);
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const SphericalTensor<Type> spT(Type(1));
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const Vector<Type> v(Type(3), Type(2), Type(1));
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const Type x(4);
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Info<< "# Operands:" << nl
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<< " Tensor = " << T << nl
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<< " SymmTensor = " << sT << nl
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<< " SphericalTensor = " << spT << nl
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<< " Vector = " << v << nl
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<< " Type = " << x << endl;
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cmp
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(
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" Sum of SpTensor-SymmTensor = ",
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(spT + sT),
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SymmTensor<Type>
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(
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Type(2), Type(2), Type(-3),
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Type(6), Type(-6),
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Type(-8)
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)
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);
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cmp
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(
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" Sum of SymmTensor-SpTensor = ",
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(sT + spT),
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SymmTensor<Type>
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(
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Type(2), Type(2), Type(-3),
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Type(6), Type(-6),
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Type(-8)
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)
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);
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cmp
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(
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" Subtract SymmTensor from SpTensor = ",
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(spT - sT),
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SymmTensor<Type>
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(
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Type(0), Type(-2), Type(3),
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Type(-4), Type(6),
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Type(10)
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)
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);
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cmp
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(
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" Subtract SpTensor from SymmTensor = ",
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(sT - spT),
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SymmTensor<Type>
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(
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Type(0), Type(2), Type(-3),
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Type(4), Type(-6),
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Type(-10)
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)
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);
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cmp
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(
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" Hodge dual of a SymmTensor",
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*sT,
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Vector<Type>(Type(-6), Type(3), Type(2))
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);
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cmp
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(
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" Division of a SymmTensor by a Type",
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sT/x,
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SymmTensor<Type>
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(
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Type(0.25), Type(0.5), Type(-0.75),
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Type(1.25), Type(-1.5),
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Type(-2.25)
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)
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);
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cmp
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(
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" Inner-product of SymmTensor-SymmTensor = ",
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(sT & sT),
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Tensor<Type>
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(
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Type(14), Type(30), Type(12),
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Type(30), Type(65), Type(18),
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Type(12), Type(18), Type(126)
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)
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);
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cmp
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(
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" Inner-product of SpTensor-SymmTensor = ",
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(spT & sT),
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SymmTensor<Type>
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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)
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);
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cmp
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(
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" Inner-product of SymmTensor-SpTensor = ",
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(sT & spT),
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SymmTensor<Type>
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(
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Type(1), Type(2), Type(-3),
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Type(5), Type(-6),
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Type(-9)
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)
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);
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cmp
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(
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" Inner-product of SymmTensor-Vector = ",
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(sT & v),
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Vector<Type>(Type(4), Type(10), Type(-30)) // Column-vector
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);
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cmp
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(
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" Inner-product of Vector-SymmTensor = ",
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(v & sT),
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Vector<Type>(Type(4), Type(10), Type(-30)) // Row-vector
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);
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cmp(" D-inner-product of SymmTensor-SymmTensor = ", (sT && sT), Type(205));
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cmp(" D-inner-product of SymmTensor-SpTensor = ", (sT && spT), Type(-3));
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cmp(" D-inner-product of SpTensor-SymmTensor = ", (spT && sT), Type(-3));
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}
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// Return false if given eigenvalues fail to satisy eigenvalue relations
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// Relations: (Beauregard & Fraleigh (1973), ISBN 0-395-14017-X, p. 307)
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void test_eigenvalues(const symmTensor& T, const vector& EVals)
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{
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{
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const scalar determinant = det(T);
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const scalar EValsProd = EVals.x()*EVals.y()*EVals.z();
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cmp("# Product of eigenvalues = det(T):", EValsProd, determinant, 1e-6);
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}
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{
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const scalar trace = tr(T);
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scalar EValsSum = 0.0;
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for (const auto& val : EVals)
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{
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EValsSum += val;
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}
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cmp("# Sum of eigenvalues = trace(T):", EValsSum, trace);
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}
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}
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// Return false if a given eigenvalue-eigenvector pair
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// fails to satisfy the characteristic equation
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void test_characteristic_equation
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(
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const symmTensor& T,
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const vector& EVals,
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const tensor& EVecs
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)
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{
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Info<< "# Characteristic equation:" << nl;
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for (direction dir = 0; dir < pTraits<vector>::nComponents; ++dir)
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{
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Info<< "EVal = " << EVals[dir] << nl
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<< "EVec = " << EVecs.row(dir) << endl;
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const vector leftSide(T & EVecs.row(dir));
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const vector rightSide(EVals[dir]*EVecs.row(dir));
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const vector X(leftSide - rightSide);
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for (const auto x : X)
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{
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cmp(" (T & EVec - EVal*EVec) = 0:", x, 0.0, 1e-5);
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}
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}
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}
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|
|
|
// Return false if the eigen functions fail to satisfy relations
|
|
void test_eigen_funcs(const symmTensor& T)
|
|
{
|
|
Info<< "# Operand:" << nl
|
|
<< " symmTensor = " << T << nl;
|
|
|
|
|
|
Info<< "# Return eigenvalues of a given symmTensor:" << nl;
|
|
const vector EVals(eigenValues(T));
|
|
Info<< EVals << endl;
|
|
test_eigenvalues(T, EVals);
|
|
|
|
Info<< "# Return eigenvectors of a given symmTensor corresponding to"
|
|
<< " given eigenvalues:" << nl;
|
|
const tensor EVecs0(eigenVectors(T, EVals));
|
|
Info<< EVecs0 << endl;
|
|
test_characteristic_equation(T, EVals, EVecs0);
|
|
|
|
Info<< "# Return eigenvectors of a given symmTensor by computing"
|
|
<< " the eigenvalues of the symmTensor in the background:" << nl;
|
|
const tensor EVecs1(eigenVectors(T));
|
|
Info<< EVecs1 << endl;
|
|
}
|
|
|
|
|
|
// Do compile-time recursion over the given types
|
|
template<std::size_t I = 0, typename... Tp>
|
|
inline typename std::enable_if<I == sizeof...(Tp), void>::type
|
|
run_tests(const std::tuple<Tp...>& types, const List<word>& typeID){}
|
|
|
|
|
|
template<std::size_t I = 0, typename... Tp>
|
|
inline typename std::enable_if<I < sizeof...(Tp), void>::type
|
|
run_tests(const std::tuple<Tp...>& types, const List<word>& typeID)
|
|
{
|
|
Info<< nl << " ## Test constructors: "<< typeID[I] <<" ##" << nl;
|
|
test_constructors(std::get<I>(types));
|
|
|
|
Info<< nl << " ## Test member functions: "<< typeID[I] <<" ##" << nl;
|
|
test_member_funcs(std::get<I>(types));
|
|
|
|
Info<< nl << " ## Test global functions: "<< typeID[I] << " ##" << nl;
|
|
test_global_funcs(std::get<I>(types));
|
|
|
|
Info<< nl << " ## Test global operators: "<< typeID[I] <<" ##" << nl;
|
|
test_global_opers(std::get<I>(types));
|
|
|
|
run_tests<I + 1, Tp...>(types, typeID);
|
|
}
|
|
|
|
|
|
// * * * * * * * * * * * * * * * Main Program * * * * * * * * * * * * * * * //
|
|
|
|
int main()
|
|
{
|
|
const std::tuple<floatScalar, doubleScalar, complex> types
|
|
(
|
|
std::make_tuple(Zero, Zero, Zero)
|
|
);
|
|
|
|
const List<word> typeID
|
|
({
|
|
"SymmTensor<floatScalar>",
|
|
"SymmTensor<doubleScalar>",
|
|
"SymmTensor<complex>"
|
|
});
|
|
|
|
run_tests(types, typeID);
|
|
|
|
|
|
Info<< nl << " ## Test symmTensor eigen functions: ##" << nl;
|
|
const label numberOfTests = 10000;
|
|
Random rndGen(1234);
|
|
|
|
for (label i = 0; i < numberOfTests; ++i)
|
|
{
|
|
const symmTensor T(makeRandomContainer(rndGen));
|
|
test_eigen_funcs(T);
|
|
}
|
|
|
|
{
|
|
Info<< nl << " ## A zero symmTensor: ##"<< nl;
|
|
const symmTensor zeroT(Zero);
|
|
test_eigen_funcs(zeroT);
|
|
}
|
|
{
|
|
Info<< nl
|
|
<< " ## A symmTensor with 2 repeated eigenvalues: ##"
|
|
<< nl;
|
|
const symmTensor T
|
|
(
|
|
1.0, 0.0, Foam::sqrt(2.0),
|
|
2.0, 0.0,
|
|
0.0
|
|
);
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
Info<< nl
|
|
<< " ## A symmTensor with 3 repeated eigenvalues: ##"
|
|
<< nl;
|
|
const symmTensor T
|
|
(
|
|
0.023215, -5.0739e-09, -7.0012e-09,
|
|
0.023215, -8.148e-10,
|
|
0.023215
|
|
);
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
Info<< nl << " ## A stiff symmTensor: ##" << nl;
|
|
const symmTensor stiff
|
|
(
|
|
pow(10.0, 10), pow(10.0, 8), pow(10.0, -8),
|
|
pow(10.0, -8), pow(10.0, 8),
|
|
pow(10.0, 7)
|
|
);
|
|
test_eigen_funcs(stiff);
|
|
}
|
|
{
|
|
Info<< nl
|
|
<< " ## Random symmTensors with tiny off-diag elements: ##"
|
|
<< nl;
|
|
|
|
const List<scalar> epsilons
|
|
({
|
|
0, SMALL, Foam::sqrt(SMALL), sqr(SMALL), Foam::cbrt(SMALL),
|
|
-SMALL, -Foam::sqrt(SMALL), -sqr(SMALL), -Foam::cbrt(SMALL)
|
|
});
|
|
|
|
for (label i = 0; i < numberOfTests; ++i)
|
|
{
|
|
for (const auto& eps : epsilons)
|
|
{
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.yz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps*rndGen.GaussNormal<scalar>();
|
|
T.xz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps*rndGen.GaussNormal<scalar>();
|
|
T.yz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xz() = eps*rndGen.GaussNormal<scalar>();
|
|
T.yz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps*rndGen.GaussNormal<scalar>();
|
|
T.xz() = eps*rndGen.GaussNormal<scalar>();
|
|
T.yz() = eps*rndGen.GaussNormal<scalar>();
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps;
|
|
T.xz() = eps;
|
|
T.yz() = eps;
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = eps;
|
|
T.xz() = eps;
|
|
T.yz() = eps;
|
|
T.zz() = eps;
|
|
test_eigen_funcs(T);
|
|
}
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
T.xy() = 0;
|
|
T.xz() = eps*rndGen.GaussNormal<scalar>();
|
|
T.yz() = 0;
|
|
test_eigen_funcs(T);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
#if 0
|
|
// Numerical diagonalisation of 2x2 or 3x3 matrices with analytic methods
|
|
// are, like the methods currently being used in OpenFOAM, inherently error
|
|
// prone. Despite its speed, the analytic methods may becomes inaccurate or
|
|
// may even fail completely if the matrix entries differ greatly in
|
|
// magnitude, particularly with large off-diagonal elements.
|
|
// The remedy is to use iterative or hybrid analytic/iterative methods
|
|
// such as published here (for 3x3/2x2 matrices):
|
|
// (Kopp, 2008) arXiv.org: physics/0610206
|
|
// mpi-hd.mpg.de/personalhomes/globes/3x3/index.html
|
|
{
|
|
Info<< nl << " ## symmTensors consisting machine epsilons: ##" << nl;
|
|
Info<< " # floatScalar" << nl;
|
|
const List<floatScalar> floatEpsilons
|
|
({
|
|
floatScalarGREAT, floatScalarVGREAT, floatScalarROOTVGREAT,
|
|
floatScalarSMALL, floatScalarVSMALL, floatScalarROOTVSMALL,
|
|
Foam::sqrt(floatScalarSMALL), 0
|
|
});
|
|
|
|
for (const auto& eps : floatEpsilons)
|
|
{
|
|
const symmTensor T(makeContainer(eps));
|
|
test_eigen_funcs(T);
|
|
}
|
|
|
|
Info<< " # doubleScalar" << nl;
|
|
const List<doubleScalar> doubleEpsilons
|
|
({
|
|
doubleScalarGREAT, doubleScalarROOTVGREAT, // doubleVGREAT fails
|
|
doubleScalarSMALL, doubleScalarVSMALL, doubleScalarROOTVSMALL,
|
|
Foam::sqrt(doubleScalarSMALL), 0
|
|
});
|
|
|
|
for (const auto& eps : doubleEpsilons)
|
|
{
|
|
const symmTensor T(makeContainer(eps));
|
|
test_eigen_funcs(T);
|
|
}
|
|
}
|
|
{
|
|
Info<< nl
|
|
<< " ## Random symmTensors with machine eps off-diag elmes: ##"
|
|
<< nl;
|
|
|
|
const List<floatScalar> floatEpsilons
|
|
({
|
|
floatScalarGREAT, floatScalarVGREAT, floatScalarROOTVGREAT,
|
|
floatScalarSMALL, floatScalarVSMALL, floatScalarROOTVSMALL
|
|
});
|
|
|
|
const List<doubleScalar> doubleEpsilons
|
|
({
|
|
doubleScalarGREAT, doubleScalarVGREAT, doubleScalarROOTVGREAT,
|
|
doubleScalarSMALL, doubleScalarVSMALL, doubleScalarROOTVSMALL
|
|
});
|
|
|
|
for (label i = 0; i < numberOfTests; ++i)
|
|
{
|
|
symmTensor T(makeRandomContainer(rndGen));
|
|
|
|
for (const auto& eps : floatEpsilons)
|
|
{
|
|
T.xy() = eps;
|
|
T.xz() = eps;
|
|
T.yz() = eps;
|
|
test_eigen_funcs(T);
|
|
}
|
|
|
|
for (const auto& eps : doubleEpsilons)
|
|
{
|
|
T.xy() = eps;
|
|
T.xz() = eps;
|
|
T.yz() = eps;
|
|
test_eigen_funcs(T);
|
|
}
|
|
}
|
|
}
|
|
#endif
|
|
|
|
|
|
if (nFail_)
|
|
{
|
|
Info<< nl << " #### "
|
|
<< "Failed in " << nFail_ << " tests "
|
|
<< "out of total " << nTest_ << " tests "
|
|
<< "####\n" << endl;
|
|
return 1;
|
|
}
|
|
|
|
Info<< nl << " #### Passed all " << nTest_ <<" tests ####\n" << endl;
|
|
return 0;
|
|
}
|
|
|
|
|
|
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * //
|