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Add power method for general f^g in the AutoDiffBlock

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A power method where both f and g are ADB variables is added
using the general derivative rule
(f^g)' = f^g * ln(f) * g' + g * f^(g-1) * f'

Tests are added to test_block.cpp
This commit is contained in:
Tor Harald Sandve
2016-03-07 14:23:45 +01:00
parent 96938548c1
commit b2e02f6d2b
2 changed files with 79 additions and 1 deletions
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45
opm/autodiff/AutoDiffBlock.hpp
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@@ -1,5 +1,6 @@
/*
Copyright 2013 SINTEF ICT, Applied Mathematics.
Copyright 2016 IRIS AS
This file is part of the Open Porous Media project (OPM).
@@ -676,6 +677,50 @@ namespace Opm
return AutoDiffBlock<Scalar>::function( std::move(val), std::move(jac) );
}
/**
* @brief Computes the value of base raised to the power of exp
*
* @param base The base AD forward block
* @param exp The exponent AD forward block
* @return The value of base raised to the power of exp
*/ template <typename Scalar>
AutoDiffBlock<Scalar> pow(const AutoDiffBlock<Scalar>& base,
const AutoDiffBlock<Scalar>& exp)
{
const int num_elem = base.value().size();
assert(exp.value().size() == num_elem);
typename AutoDiffBlock<Scalar>::V val (num_elem);
for (int i = 0; i < num_elem; ++i) {
val[i] = std::pow(base.value()[i], exp.value()[i]);
}
// (f^g)' = f^g * ln(f) * g' + g * f^(g-1) * f'
typename AutoDiffBlock<Scalar>::V der1 = val;
for (int i = 0; i < num_elem; ++i) {
der1[i] *= std::log(base.value()[i]);
}
std::vector< typename AutoDiffBlock<Scalar>::M > jac1 (base.numBlocks());
const typename AutoDiffBlock<Scalar>::M der1_diag(der1.matrix().asDiagonal());
for (int block = 0; block < base.numBlocks(); block++) {
fastSparseProduct(der1_diag, exp.derivative()[block], jac1[block]);
}
typename AutoDiffBlock<Scalar>::V der2 = exp.value();
for (int i = 0; i < num_elem; ++i) {
der2[i] *= std::pow(base.value()[i], exp.value()[i] - 1.0);
}
std::vector< typename AutoDiffBlock<Scalar>::M > jac2 (base.numBlocks());
const typename AutoDiffBlock<Scalar>::M der2_diag(der2.matrix().asDiagonal());
for (int block = 0; block < base.numBlocks(); block++) {
fastSparseProduct(der2_diag, base.derivative()[block], jac2[block]);
}
std::vector< typename AutoDiffBlock<Scalar>::M > jac (base.numBlocks());
for (int block = 0; block < base.numBlocks(); block++) {
jac[block] = jac1[block] + jac2[block];
}
return AutoDiffBlock<Scalar>::function(std::move(val), std::move(jac));
}
} // namespace Opm