int CountResults(MData& testSet, int *predictions, int *&posSlideCnt, int *&negSlideCnt)
{
int result = 0;
int *slideIdx = testSet.GetSlideIndices();
posSlideCnt = (int*)calloc(testSet.GetNumSlides(), sizeof(int));
negSlideCnt = (int*)calloc(testSet.GetNumSlides(), sizeof(int));
if( negSlideCnt && posSlideCnt ) {
for(int i = 0; i < testSet.GetNumObjs(); i++) {
if( predictions[i] == 1 ) {
posSlideCnt[slideIdx[i]]++;
} else {
negSlideCnt[slideIdx[i]]++;
}
}
}
return result;
}
int CountTrainingObjs(MData& trainSet, MData& testSet, int *&posCount, int *&negCount)
{
int result = 0,
numTrainSlides = trainSet.GetNumSlides(),
*slideIdx = trainSet.GetSlideIndices(),
*labels = trainSet.GetLabels();
posCount = (int*)calloc(numTrainSlides, sizeof(int));
negCount = (int*)calloc(numTrainSlides, sizeof(int));
for(int i = 0; i < trainSet.GetNumObjs(); i++) {
if( labels[i] == 1 ) {
posCount[slideIdx[i]]++;
} else {
negCount[slideIdx[i]]++;
}
}
return result;
}
bool Picker::RestoreSessionData(MData& testSet)
{
bool result = true;
int numObjs = testSet.GetNumObjs(),
numDims = testSet.GetDims();
result = UpdateBuffers(numObjs, true);
if( result ) {
float *floatData = NULL;
int *intData = NULL;
intData = testSet.GetLabels();
memcpy(m_labels, intData, numObjs * sizeof(int));
intData = testSet.GetIdList();
memcpy(m_ids, intData, numObjs * sizeof(int));
floatData = testSet.GetXCentroidList();
memcpy(m_xCentroid, floatData, numObjs * sizeof(float));
floatData = testSet.GetXClickList();
// Test sets created with earlier versions of HistomicsML don't have clicks
if( floatData == NULL ) {
// Use centroids for click location if not present.
floatData = testSet.GetXCentroidList();
}
memcpy(m_xClick, floatData, numObjs * sizeof(float));
floatData = testSet.GetYCentroidList();
memcpy(m_yCentroid, floatData, numObjs * sizeof(float));
floatData = testSet.GetYClickList();
if( floatData == NULL ) {
floatData = testSet.GetYCentroidList();
}
memcpy(m_yClick, floatData, numObjs * sizeof(float));
floatData = testSet.GetData()[0];
memcpy(m_trainSet[0], floatData, numObjs * numDims * sizeof(float));
char **classNames = testSet.GetClassNames();
// Older versions of al_server did not save class names, set
// defaults if they can't be loaded.
if( classNames ) {
for(int i = 0; i < testSet.GetNumClasses(); i++) {
m_classNames.push_back(string(classNames[i]));
}
} else {
m_classNames.push_back(string("Negative"));
m_classNames.push_back(string("Positive"));
}
// Get slide indices from the dataset, NOT from the training set.
intData = testSet.GetSlideIndices();
char **slideNames = testSet.GetSlideNames();
int idx;
for(int i = 0; i < numObjs; i++) {
m_slideIdx[i] = m_dataset->GetSlideIdx(slideNames[intData[i]]);
// Keep track fo selected items
idx = m_dataset->FindItem(m_xCentroid[i], m_yCentroid[i], slideNames[intData[i]]);
if( idx == -1 ) {
gLogger->LogMsg(EvtLogger::Evt_ERROR, "Unable to find item in dataset:, %f, %f in %s",
m_xCentroid[i], m_yCentroid[i], slideNames[intData[i]]);
result = false;
break;
} else {
m_samples.push_back(idx);
}
}
}
return result;
}
