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ENH: Distribution. Adding operator+ to allow

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reduce(dist, sumOp< Distribution<scalar> >());

operations for parallel data.  Combines distributions using the
coarsest binWidth.

Changed write function to write normalised and raw to the same file.

BUG: Distribution. Corrected inaccurate median calculation.
This commit is contained in:
graham
2010-02-11 17:21:16 +00:00
parent 93dd3050b1
commit abd1ee0f1d
3 changed files with 304 additions and 168 deletions
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127
applications/test/Distribution/DistributionTest.C
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@ -45,7 +45,8 @@ Description
#include "Distribution.H"
#include "Random.H"
#include "dimensionedTypes.H"
#include "argList.H"
#include "PstreamReduceOps.H"
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * //
@ -53,6 +54,8 @@ using namespace Foam;
int main(int argc, char *argv[])
{
# include "setRootCase.H"
Random R(918273);
{
@ -76,7 +79,67 @@ int main(int argc, char *argv[])
<< "Median " << dS.median()
<< endl;
dS.write("Distribution_scalar_test", dS.normalised());
dS.write("Distribution_scalar_test_1");
Distribution<scalar> dS2(scalar(1e-2));
Info<< nl << "Distribution<scalar>" << nl
<< "Sampling "
<< randomDistributionTestSize
<< " times from GaussNormal distribution."
<< endl;
for (label i = 0; i < randomDistributionTestSize; i++)
{
dS2.add(1.5*R.GaussNormal() -6.0);
}
Info<< "Mean " << dS2.mean() << nl
<< "Median " << dS2.median()
<< endl;
dS2.write("Distribution_scalar_test_2");
Info<< nl << "Adding previous two Distribution<scalar>" << endl;
dS = dS + dS2;
dS.write("Distribution_scalar_test_1+2");
}
if (Pstream::parRun())
{
// scalar in parallel
label randomDistributionTestSize = 100000000;
Distribution<scalar> dS(scalar(1e-1));
Pout<< "Distribution<scalar>" << nl
<< "Sampling "
<< randomDistributionTestSize
<< " times from uniform distribution."
<< endl;
for (label i = 0; i < randomDistributionTestSize; i++)
{
dS.add(R.scalar01() + 10*Pstream::myProcNo());
}
Pout<< "Mean " << dS.mean() << nl
<< "Median " << dS.median()
<< endl;
reduce(dS, sumOp< Distribution<scalar> >());
if (Pstream::master())
{
Info<< "Reducing parallel Distribution<scalar>" << nl
<< "Mean " << dS.mean() << nl
<< "Median " << dS.median()
<< endl;
dS.write("Distribution_scalar_test_parallel_reduced");
}
}
{
@ -114,40 +177,40 @@ int main(int argc, char *argv[])
<< "Median " << dV.median()
<< endl;
dV.write("Distribution_vector_test", dV.normalised());
dV.write("Distribution_vector_test");
}
{
// labelVector
Distribution<labelVector> dLV(labelVector::one*10);
// {
// // labelVector
// Distribution<labelVector> dLV(labelVector::one*10);
label randomDistributionTestSize = 2000000;
// label randomDistributionTestSize = 2000000;
Info<< nl << "Distribution<labelVector>" << nl
<< "Sampling "
<< randomDistributionTestSize
<< " times from uniform distribution."
<< endl;
// Info<< nl << "Distribution<labelVector>" << nl
// << "Sampling "
// << randomDistributionTestSize
// << " times from uniform distribution."
// << endl;
for (label i = 0; i < randomDistributionTestSize; i++)
{
dLV.add
(
labelVector
(
R.integer(-1000, 1000),
R.integer(-5000, 5000),
R.integer(-2000, 7000)
)
);
}
// for (label i = 0; i < randomDistributionTestSize; i++)
// {
// dLV.add
// (
// labelVector
// (
// R.integer(-1000, 1000),
// R.integer(-5000, 5000),
// R.integer(-2000, 7000)
// )
// );
// }
Info<< "Mean " << dLV.mean() << nl
<< "Median " << dLV.median()
<< endl;
// Info<< "Mean " << dLV.mean() << nl
// << "Median " << dLV.median()
// << endl;
dLV.write("Distribution_labelVector_test", dLV.normalised());
}
// dLV.write("Distribution_labelVector_test");
// }
{
// tensor
@ -170,7 +233,7 @@ int main(int argc, char *argv[])
<< "Median " << dT.median()
<< endl;
dT.write("Distribution_tensor_test", dT.normalised());
dT.write("Distribution_tensor_test");
}
{
@ -194,7 +257,7 @@ int main(int argc, char *argv[])
<< "Median " << dSyT.median()
<< endl;
dSyT.write("Distribution_symmTensor_test", dSyT.normalised());
dSyT.write("Distribution_symmTensor_test");
}
{
@ -218,7 +281,7 @@ int main(int argc, char *argv[])
<< "Median " << dSpT.median()
<< endl;
dSpT.write("Distribution_sphericalTensor_test", dSpT.normalised());
dSpT.write("Distribution_sphericalTensor_test");
}
Info<< nl << "End" << nl << endl;