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dense AD: introduce convenience functions

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this PR was inspired by one of @atgeirr's recent comments. it allows
to get rid if the `MathToolbox<Eval>` detour for the dense AD code in
most cases: e.g. instead of writing

```c++
template <class Eval>
Eval f(const Eval& val)
{ return Opm::MathToolbox<Eval>::sqrt(val); }
```

one can simply write

```c++
template <class Eval>
Eval f(const Eval& val)
{ return Opm::sqrt(val); }
```

and it will work transparently with DenseAD `Evaluation` objects and
primitive floating point values.

one complication of this is that the type of the `Evaluation` object
does not need to be explicitly defined. for functions which take more
than one argument (like e.g. `pow()`, `min()` and `max()`), it is thus
assumed that the type of the result is the same as the type of the
first argument.

another drawback is that when both, the contents of the `Opm::` and
the `std::` namespaces are implicitly available, it is not clear to me
what's used for primitive floating point values. (it seems to compile
but IMO it could lead to surprising behaviour. thus, please only merge
if you consider the benefits of these convenience functions to be
greater than their drawbacks.)
This commit is contained in:
Andreas Lauser
2016-08-10 17:09:52 +02:00
parent 32e5630ae7
commit 9f465784a8
4 changed files with 115 additions and 0 deletions
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43
tests/test_densead.cpp
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@@ -566,6 +566,49 @@ inline void testAll()
test1DFunction<Scalar>(Opm::DenseAd::log<Scalar, numVars>,
static_cast<Scalar (*)(Scalar)>(std::log),
1e-6, 1e9);
while (false) {
// make sure that the convenince functions work (i.e., that everything can be
// accessed without the MathToolbox<Scalar> detour.)
Scalar val1(0.0), val2(1.0), resultVal;
resultVal = Opm::constant<Scalar>(val1);
resultVal = Opm::variable<Scalar>(val1, /*idx=*/0);
resultVal = Opm::min(val1, val2);
resultVal = Opm::max(val1, val2);
resultVal = Opm::atan2(val1, val2);
resultVal = Opm::pow(val1, val2);
resultVal = Opm::abs(val1);
resultVal = Opm::atan(val1);
resultVal = Opm::sin(val1);
resultVal = Opm::asin(val1);
resultVal = Opm::cos(val1);
resultVal = Opm::acos(val1);
resultVal = Opm::sqrt(val1);
resultVal = Opm::exp(val1);
resultVal = Opm::log(val1);
typedef Opm::DenseAd::Evaluation<Scalar, numVars> TmpEval;
TmpEval eval1, eval2, resultEval;
resultEval = Opm::constant<TmpEval>(val1);
resultEval = Opm::variable<TmpEval>(val1, /*idx=*/0);
resultEval = Opm::min(eval1, eval2);
resultEval = Opm::min(eval1, val2);
resultEval = Opm::max(eval1, eval2);
resultEval = Opm::max(eval1, val2);
resultEval = Opm::atan2(eval1, eval2);
resultEval = Opm::atan2(eval1, val2);
resultEval = Opm::pow(eval1, eval2);
resultEval = Opm::pow(eval1, val2);
resultEval = Opm::abs(eval1);
resultEval = Opm::atan(eval1);
resultEval = Opm::sin(eval1);
resultEval = Opm::asin(eval1);
resultEval = Opm::cos(eval1);
resultEval = Opm::acos(eval1);
resultEval = Opm::sqrt(eval1);
resultEval = Opm::exp(eval1);
resultEval = Opm::log(eval1);
}
}
int main(int argc, char **argv)