// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void SineParamsSegmentFeatures::execute()
{
setErrorCondition(0);
dataCheck();
if(getErrorCondition() < 0) { return; }
DataContainer::Pointer m = getDataContainerArray()->getDataContainer(getDataContainerName());
QVector<size_t> tDims(1, 1);
m->getAttributeMatrix(getCellFeatureAttributeMatrixName())->resizeAttributeArrays(tDims);
// This runs a subfilter
int64_t totalPoints = m_FeatureIdsPtr.lock()->getNumberOfTuples();
// Tell the user we are starting the filter
notifyStatusMessage(getMessagePrefix(), getHumanLabel(), "Starting");
//Convert user defined tolerance to radians.
//angleTolerance = m_AngleTolerance * SIMPLib::Constants::k_Pi / 180.0f;
for(int64_t i = 0; i < totalPoints; i++)
{
m_FeatureIds[i] = 0;
}
// Generate the random voxel indices that will be used for the seed points to start a new grain growth/agglomeration
const size_t rangeMin = 0;
const size_t rangeMax = totalPoints - 1;
initializeVoxelSeedGenerator(rangeMin, rangeMax);
SegmentFeatures::execute();
size_t totalFeatures = m->getAttributeMatrix(getCellFeatureAttributeMatrixName())->getNumTuples();
if (totalFeatures < 2)
{
setErrorCondition(-87000);
notifyErrorMessage(getHumanLabel(), "The number of Features was 0 or 1 which means no features were detected. Is a threshold value set to high?", getErrorCondition());
return;
}
// By default we randomize grains
if (true == m_RandomizeFeatureIds)
{
randomizeFeatureIds(totalPoints, totalFeatures);
}
// If there is an error set this to something negative and also set a message
notifyStatusMessage(getHumanLabel(), "Completed");
}
// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void VectorSegmentFeatures::execute()
{
setErrorCondition(0);
dataCheck();
if(getErrorCondition() < 0) { return; }
DataContainer::Pointer m = getDataContainerArray()->getDataContainer(getDataContainerName());
QVector<size_t> tDims(1, 1);
m->getAttributeMatrix(getCellFeatureAttributeMatrixName())->resizeAttributeArrays(tDims);
updateFeatureInstancePointers();
int64_t totalPoints = static_cast<int64_t>(m_FeatureIdsPtr.lock()->getNumberOfTuples());
m_BeenPickedPtr = BoolArrayType::CreateArray(totalPoints, "BeenPicked INTERNAL ARRAY ONLY");
m_BeenPickedPtr->initializeWithValue(0);
m_BeenPicked = m_BeenPickedPtr->getPointer(0);
// Convert user defined tolerance to radians.
angleTolerance = m_AngleTolerance * SIMPLib::Constants::k_Pi / 180.0f;
// Generate the random voxel indices that will be used for the seed points to start a new grain growth/agglomeration
const int64_t rangeMin = 0;
const int64_t rangeMax = totalPoints - 1;
initializeVoxelSeedGenerator(rangeMin, rangeMax);
SegmentFeatures::execute();
int32_t totalFeatures = static_cast<int32_t>(m->getAttributeMatrix(getCellFeatureAttributeMatrixName())->getNumTuples());
if (totalFeatures < 2)
{
setErrorCondition(-87000);
notifyErrorMessage(getHumanLabel(), "The number of Features was 0 or 1 which means no Features were detected. A threshold value may be set too high", getErrorCondition());
return;
}
// By default we randomize grains
if (true == m_RandomizeFeatureIds)
{
randomizeFeatureIds(totalPoints, totalFeatures);
}
// If there is an error set this to something negative and also set a message
notifyStatusMessage(getHumanLabel(), "Completed");
}
// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void GroupMicroTextureRegions::randomizeFeatureIds(int64_t totalPoints, int64_t totalFeatures)
{
notifyStatusMessage(getHumanLabel(), "Randomizing Parent Ids");
// Generate an even distribution of numbers between the min and max range
const int32_t rangeMin = 0;
const int32_t rangeMax = totalFeatures - 1;
initializeVoxelSeedGenerator(rangeMin, rangeMax);
// Get a reference variable to the Generator object
Generator& numberGenerator = *m_NumberGenerator;
DataArray<int32_t>::Pointer rndNumbers = DataArray<int32_t>::CreateArray(totalFeatures, "_INTERNAL_USE_ONLY_NewFeatureIds");
int32_t* gid = rndNumbers->getPointer(0);
gid[0] = 0;
for (int64_t i = 1; i < totalFeatures; ++i)
{
gid[i] = i;
}
int32_t r = 0;
int32_t temp;
//--- Shuffle elements by randomly exchanging each with one other.
for (int64_t i = 1; i < totalFeatures; i++)
{
r = numberGenerator(); // Random remaining position.
if (r >= totalFeatures)
{
continue;
}
temp = gid[i];
gid[i] = gid[r];
gid[r] = temp;
}
// Now adjust all the Grain Id values for each Voxel
for (int64_t i = 0; i < totalPoints; ++i)
{
m_CellParentIds[i] = gid[m_CellParentIds[i]];
m_FeatureParentIds[m_FeatureIds[i]] = m_CellParentIds[i];
}
}
// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void EBSDSegmentFeatures::execute()
{
setErrorCondition(0);
dataCheck();
if(getErrorCondition() < 0) { return; }
DataContainer::Pointer m = getDataContainerArray()->getDataContainer(getDataContainerName());
int64_t totalPoints = static_cast<int64_t>(m_FeatureIdsPtr.lock()->getNumberOfTuples());
QVector<size_t> tDims(1, 1);
m->getAttributeMatrix(getCellFeatureAttributeMatrixName())->resizeAttributeArrays(tDims);
updateFeatureInstancePointers();
// Convert user defined tolerance to radians.
misoTolerance = m_MisorientationTolerance * DREAM3D::Constants::k_Pi / 180.0f;
// Generate the random voxel indices that will be used for the seed points to start a new grain growth/agglomeration
const int64_t rangeMin = 0;
const int64_t rangeMax = totalPoints - 1;
initializeVoxelSeedGenerator(rangeMin, rangeMax);
SegmentFeatures::execute();
int64_t totalFeatures = static_cast<int64_t>(m_ActivePtr.lock()->getNumberOfTuples());
if (totalFeatures < 2)
{
setErrorCondition(-87000);
notifyErrorMessage(getHumanLabel(), "The number of Features was 0 or 1 which means no Features were detected. A threshold value may be set too high", getErrorCondition());
return;
}
// By default we randomize grains
if (true == getRandomizeFeatureIds())
{
totalPoints = static_cast<int64_t>(m->getGeometryAs<ImageGeom>()->getNumberOfElements());
randomizeFeatureIds(totalPoints, totalFeatures);
}
// If there is an error set this to something negative and also set a message
notifyStatusMessage(getHumanLabel(), "Complete");
}
