void addrow( H5::DataSet& ds, const std::vector<double>& rowtowrite )
{
//Get the space (since it may have grown in length since last time of course )
H5::DataSpace origspace = ds.getSpace();
//get the rank, even though I know it is 2
int rank = origspace.getSimpleExtentNdims();
//Get the actual dimensions of the ranks.
hsize_t dims[rank];
int ndims = origspace.getSimpleExtentDims( dims, NULL);
//Want to ADD a row, so need to offset at row = nrows, and col = 0;
hsize_t offset[rank] = { dims[0], 0 };
hsize_t dims_toadd[rank] = { 1, rowtowrite.size() }; //will write 1 row, ncols columns.
//Compute "new" size (extended by 1 row).
hsize_t size[rank] = { dims[0]+dims_toadd[0], rowtowrite.size() };
//Do the extension.
ds.extend( size );
//Get the new (extended) space, and select the hyperslab to write the row to.
origspace = ds.getSpace();
origspace.selectHyperslab( H5S_SELECT_SET, dims_toadd, offset );
//Make the "memory" data space?
H5::DataSpace toaddspace(rank, dims_toadd);
ds.write( rowtowrite.data(), H5::PredType::NATIVE_DOUBLE, toaddspace, origspace );
//Can close toaddspace/origspace with no effect.
//Can also close/open data set at the beginning of each time with no effect.
}
void compare_datasets(H5::DataSet const& ds1, H5::DataSet const& ds2)
{
std::vector<hsize_t> dims(ds1.getSpace().getSimpleExtentNdims());
ds1.getSpace().getSimpleExtentDims(&*dims.begin());
// compare 2 or 3-dimensional list of vectors, e.g., box edges
BOOST_REQUIRE( dims.size() == 2 );
BOOST_REQUIRE( dims[1] == 2 || dims[1] == 3 );
if (dims[1] == 3) {
std::vector<halmd::fixed_vector<double, 3> > array1, array2;
h5xx::read_dataset(ds1, array1);
h5xx::read_dataset(ds2, array2);
BOOST_CHECK_EQUAL_COLLECTIONS(
array1.begin(), array1.end()
, array2.begin(), array2.end()
);
}
else if (dims[1] == 2) {
std::vector<halmd::fixed_vector<double, 2> > array1, array2;
h5xx::read_dataset(ds1, array1);
h5xx::read_dataset(ds2, array2);
BOOST_CHECK_EQUAL_COLLECTIONS(
array1.begin(), array1.end()
, array2.begin(), array2.end()
);
}
}
void FeaturePointsRANSAC::loadModel(std::string modelPath)
{
H5::H5File h5Model;
try {
h5Model = H5::H5File(modelPath, H5F_ACC_RDONLY);
}
catch (H5::Exception& e) {
std::string msg( std::string( "Could not open HDF5 file \n" ) + e.getCDetailMsg() );
throw msg;
}
// Load the Shape
H5::Group modelReconstructive = h5Model.openGroup("/shape/ReconstructiveModel/model");
H5::DataSet dsMean = modelReconstructive.openDataSet("./mean");
hsize_t dims[1];
dsMean.getSpace().getSimpleExtentDims(dims, NULL); // dsMean.getSpace() leaks memory... maybe a hdf5 bug, maybe vlenReclaim(...) could be a fix. No idea.
//H5::DataSpace dsp = dsMean.getSpace();
//dsp.close();
std::cout << "Dims: " << dims[0] << std::endl; // TODO: I guess this whole part could be done A LOT better!
float* testData = new float[dims[0]];
dsMean.read(testData, H5::PredType::NATIVE_FLOAT);
this->modelMeanShp.reserve(dims[0]);
for (unsigned int i=0; i < dims[0]; ++i) {
modelMeanShp.push_back(testData[i]);
}
delete[] testData;
testData = NULL;
dsMean.close();
// // Load the Texture
H5::Group modelReconstructiveTex = h5Model.openGroup("/color/ReconstructiveModel/model");
H5::DataSet dsMeanTex = modelReconstructiveTex.openDataSet("./mean");
hsize_t dimsTex[1];
dsMeanTex.getSpace().getSimpleExtentDims(dimsTex, NULL);
std::cout << "Dims: " << dimsTex[0] << std::endl; // TODO: I guess this whole part could be done A LOT better!
float* testDataTex = new float[dimsTex[0]];
dsMeanTex.read(testDataTex, H5::PredType::NATIVE_FLOAT);
this->modelMeanTex.reserve(dimsTex[0]);
for (unsigned int i=0; i < dimsTex[0]; ++i) {
modelMeanTex.push_back(testDataTex[i]);
}
delete[] testDataTex;
testDataTex = NULL;
dsMeanTex.close();
h5Model.close();
}
H5::DataSet CompartmentReportHDF5::_openDataset( const H5::H5File& file,
const uint32_t cellID )
{
std::stringstream cellName;
cellName << "a" << cellID;
const std::string datasetName = "/" + cellName.str() + "/" + _reportName +
"/" + dataDatasetName;
H5::DataSet dataset;
H5E_BEGIN_TRY
dataset = file.openDataSet( datasetName );
H5E_END_TRY
if( !dataset.getId() )
{
LBTHROW(
std::runtime_error( "ReportReaderHDF5: "
"Dataset " + datasetName + " not found "
"in file: " + file.getFileName( )));
}
if( dataset.getSpace().getSimpleExtentNdims() != 2 )
{
LBTHROW(
std::runtime_error("Compartment_Report_HDF5_File_Reader: "
"Error, not 2 dimensional array on " +
datasetName));
}
return dataset;
}
arma::Mat<uint16_t> readLUT(const std::string& path)
{
H5::H5File file (path.c_str(), H5F_ACC_RDONLY);
H5::DataSet ds = file.openDataSet("LUT");
H5::DataSpace filespace = ds.getSpace();
int ndims = filespace.getSimpleExtentNdims();
assert(ndims == 2);
hsize_t dims[2] = {1, 1};
filespace.getSimpleExtentDims(dims);
H5::DataSpace memspace (ndims, dims);
arma::Mat<uint16_t> res (dims[0], dims[1]);
ds.read(res.memptr(), H5::PredType::NATIVE_UINT16, memspace, filespace);
filespace.close();
memspace.close();
ds.close();
file.close();
// NOTE: Armadillo stores data in column-major order, while HDF5 uses
// row-major ordering. Above, we read the data directly from HDF5 into
// the arma matrix, so it was implicitly transposed. The next function
// fixes this problem.
arma::inplace_trans(res);
return res;
}
/**
* @param variable
* @return
*/
long HDF5FileReader::getNumberOfRecords(const std::string& variable)
{
//std::cout << "reading " << variable << std::endl;
//get variable number
H5::DataSet dataset = this->variableGroup->openDataSet(variable);
H5::DataSpace dataspace = dataset.getSpace();
hsize_t count[1];
// int ndims = dataspace.getSimpleExtentDims(count, NULL);
return (long)count[0];
}
/**
* @brief Returns a pointer to a std::vector<float> containing the values of the selected variable
*
* This allocates a new std::vector<float> pointer. Make sure you
* delete the contents when you done using it, or you will have a memory leak.
*
* @param variable
* @return std::vector<float> containing the values of the selected variable.
*/
std::vector<float>* HDF5FileReader::getVariable(const std::string& variable)
{
std::vector<float>* variableData = new std::vector<float>();
if (this->doesVariableExist(variable))
{
//std::cout << "reading " << variable << std::endl;
//get variable number
// long variableNum = this->getVariableID(variable);
//std::cout << "variableNum for " << variable << ": " << variableNum << std::endl;
//get dim sizes
H5::Group group = this->current_file->openGroup("Variables");
//cout << "variable: " << variable << ": " << counts[0] << endl;
H5::DataSet * dataset = new H5::DataSet(group.openDataSet(variable));
H5::DataSpace dataspace = dataset->getSpace();
int rank = dataspace.getSimpleExtentNdims(); //should be 1
hsize_t count[1];
hsize_t offset[1] = {0};
// int ndims = dataspace.getSimpleExtentDims(count, NULL);
//std::cout << "count[0]: " << count[0] << std::endl;
float * buffer = new float[count[0]];
dataspace.selectHyperslab(H5S_SELECT_SET, count, offset);
H5::DataSpace memspace( rank, count);
memspace.selectHyperslab(H5S_SELECT_SET, count, offset);
dataset->read(buffer, H5::PredType::NATIVE_FLOAT, memspace, dataspace);
//std::cout << "after read" << std::endl;
//add data to vector type, and delete original array
variableData->reserve(count[0]);
for (int i = 0; i < count[0]; i++)
{
variableData->push_back(buffer[i]);
}
//std::cout << "after adding to variableData vector" << std::endl;
delete[] buffer;
delete dataset;
//std::cout << "finished reading " << variable << std::endl;
//std::cout << "size of variable: " << variableData.size() << std::endl;
//std::cout << "dimSizes[0]: " << dimSizes[0] << std::endl;
}
return variableData;
}
void compare_datasets(H5::DataSet const& ds1, H5::DataSet const& ds2, hssize_t index1, hssize_t index2)
{
std::vector<hsize_t> dims(ds1.getSpace().getSimpleExtentNdims());
ds1.getSpace().getSimpleExtentDims(&*dims.begin());
BOOST_REQUIRE( dims.size() == 2 || dims.size() == 3 );
if (dims.size() == 2) {
// compare scalar mass, species, …
// assumes lossless conversion from integer to floating-point
std::vector<double> array1, array2;
h5xx::read_chunked_dataset(ds1, array1, index1);
h5xx::read_chunked_dataset(ds2, array2, index2);
BOOST_CHECK_EQUAL_COLLECTIONS(
array1.begin(), array1.end()
, array2.begin(), array2.end()
);
}
else if (dims.size() == 3) {
// compare 2 or 3-dimensional positions, velocities, …
BOOST_REQUIRE( dims[2] == 2 || dims[2] == 3 );
if (dims[2] == 3) {
std::vector<halmd::fixed_vector<double, 3> > array1, array2;
h5xx::read_chunked_dataset(ds1, array1, index1);
h5xx::read_chunked_dataset(ds2, array2, index2);
BOOST_CHECK_EQUAL_COLLECTIONS(
array1.begin(), array1.end()
, array2.begin(), array2.end()
);
}
else if (dims[2] == 2) {
std::vector<halmd::fixed_vector<double, 2> > array1, array2;
h5xx::read_chunked_dataset(ds1, array1, index1);
h5xx::read_chunked_dataset(ds2, array2, index2);
BOOST_CHECK_EQUAL_COLLECTIONS(
array1.begin(), array1.end()
, array2.begin(), array2.end()
);
}
}
}
const std::vector<hsize_t> TableDims(){
if(flags_ != hdf5::READ)
throw std::runtime_error("TableDims() is only valid in READ mode");
H5::DataSet dSet = file_->openDataSet("T00000000");
H5::DataSpace dSpace = dSet.getSpace();
std::vector<hsize_t> dims(dSpace.getSimpleExtentNdims());
dSpace.getSimpleExtentDims(&dims[0]);
return dims;
}
NDArray<T, Nd> NDArray<T,Nd>::ReadFromH5(const H5::DataSet& h5Dset) {
H5::DataSpace dspace = h5Dset.getSpace();
int ndim = dspace.getSimpleExtentNdims();
if (ndim>Nd)
throw std::range_error("Too many dimensions in H5 dataset for NDArray");
hsize_t dimSize[ndim];
dspace.getSimpleExtentDims(dimSize);
std::array<std::size_t, Nd> dimSizeArr;
for (int i=0; i<Nd; ++i) dimSizeArr[i] = dimSize[i];
NDArray<T, Nd> arr(dimSizeArr);
// Read in data here
H5::DataType h5DType = GetH5DataType<T>();
h5Dset.read(arr.mData, h5DType);
return arr;
}
void HDF5IO::loadStdVector(const std::string& GroupName, const std::string& Name,
std::vector<RealType>& V)
{
try{
H5::Group FG = getGroup( GroupName );
H5::DataSet DataSet = FG.openDataSet(Name.c_str());
H5::DataSpace DataSpace = DataSet.getSpace();
if(DataSpace.getSimpleExtentNdims() != 1)
throw(H5::DataSpaceIException("HDF5IO::loadRealVector()","Unexpected multidimentional dataspace."));
V.resize(DataSpace.getSimpleExtentNpoints());
DataSet.read(V.data(),H5::PredType::NATIVE_DOUBLE);
FG.close();
} catch( const H5::Exception err ){
RUNTIME_ERROR("HDF5IO::loadRealStdVector");
}
}
void HDF5IO::loadStdVector(const std::string& GroupName, const std::string& Name,
std::vector<ComplexType>& V)
{
try{
H5::CompType ComplexDataType = this->openCompType("complex");
H5::Group FG = getGroup( GroupName );
H5::DataSet DataSet = FG.openDataSet(Name.c_str());
H5::DataSpace DataSpace = DataSet.getSpace();
if(DataSpace.getSimpleExtentNdims() != 1)
throw(H5::DataSpaceIException("HDF5IO::loadComplexVector()","Unexpected multidimentional dataspace."));
V.resize(DataSpace.getSimpleExtentNpoints());
DataSet.read(V.data(),ComplexDataType);
FG.close();
} catch( const H5::Exception err ){
RUNTIME_ERROR("HDF5IO::loadComplexStdVector");
}
}
void HDF5IO::loadVector(const std::string& GroupName, const std::string& Name,
RealVectorType& V)
{
H5::Group FG = getGroup( GroupName );
H5::DataSet DataSet = FG.openDataSet(Name.c_str());
H5::DataSpace DataSpace = DataSet.getSpace();
if(DataSpace.getSimpleExtentNdims() != 1)
throw(H5::DataSpaceIException("HDF5IO::loadRealVector()",
"Unexpected multidimentional dataspace."));
V.resize(DataSpace.getSimpleExtentNpoints());
try{
DataSet.read(V.data(),H5::PredType::NATIVE_DOUBLE);
}catch( H5::GroupIException not_found_error ){
RUNTIME_ERROR("No dataset found in loadRealVector. ");
}
FG.close();
}
/**
* @brief Returns a value in the flat array of the variable and index requested.
*
* Use this method on variables that have a type of int
*
* @param variable The variable in the file
* @param index The index in the variable's array in the file
*
* @return int of the value in the array.
*/
int HDF5FileReader::getVariableIntAtIndex(const std::string& variable, long index)
{
// long counts[1];
int value = std::numeric_limits<int>::min();
if (this->doesVariableExist(variable))
{
//std::cout << "reading " << variable << std::endl;
//get variable number
// long variableNum = this->getVariableID(variable);
//get dim sizes
H5::Group group = this->current_file->openGroup("Variables");
//cout << "variable: " << variable << ": " << counts[0] << endl;
H5::DataSet * dataset = new H5::DataSet(group.openDataSet(variable));
H5::DataSpace dataspace = dataset->getSpace();
int rank = dataspace.getSimpleExtentNdims(); //should be 1
hsize_t count[1] = {1};
hsize_t offset[1] = {0};
//int ndims = dataspace.getSimpleExtentDims(count, NULL);
float * buffer = new float[count[0]];
dataspace.selectHyperslab(H5S_SELECT_SET, count, offset);
hsize_t dim[] = {count[0]};
H5::DataSpace memspace( rank, dim);
memspace.selectHyperslab(H5S_SELECT_SET, dim, offset);
dataset->read(buffer, H5::PredType::NATIVE_INT, memspace, dataspace);
//add data to vector type, and delete original array
value = buffer[0];
delete[] buffer;
delete dataset;
}
return value;
//std::cout << "finished reading " << variable << std::endl;
//std::cout << "size of variable: " << variableData.size() << std::endl;
//std::cout << "dimSizes[0]: " << dimSizes[0] << std::endl;
}
/** Retrieves the dimensions of the dataset */
int hdfutil::GetDsDims (const H5::DataSet & dataset, int dims[3]) {
H5::DataSpace dataspace = dataset.getSpace();
bool simple = dataspace.isSimple();
if (!simple)
throw std::runtime_error("complex HDF5 dataspace");
int rank = (int)dataspace.getSimpleExtentNdims();
if (rank > 3)
throw std::runtime_error("unsupported dimensionality");
hsize_t h5_dims[3];
dataspace.getSimpleExtentDims(h5_dims, NULL);
for (int i = 0; i < rank; i++)
dims[i] = (int)h5_dims[i];
for (int i = rank; i < 3; i++)
dims[i] = -1;
return rank;
}
bool readDataset1D(const H5::H5File &file, const std::string &name, std::vector<_Tp> &data)
{
H5::DataSet dataset = file.openDataSet(name);
H5::DataSpace dataspace = dataset.getSpace();
hsize_t dims_out[1];
int rank = dataspace.getSimpleExtentDims( dims_out, NULL);
int _type;
bool read = getNodeType(dataset, _type);
read &= (_type == StorageNode::SEQ);
read &= (rank == 1);
if (!read)
return read;
data.resize(dims_out[0]);
dataset.read(data.data(), dataset.getDataType());
return true;
}
void HDF5IO::loadMatrix(const std::string& GroupName, const std::string& Name,
ComplexMatrixType& M)
{
try{
H5::CompType ComplexDataType = this->openCompType("complex");
H5::Group FG = getGroup( GroupName );
H5::DataSet DataSet = FG.openDataSet(Name.c_str());
H5::DataSpace DataSpace = DataSet.getSpace();
if(DataSpace.getSimpleExtentNdims() != 2)
throw(H5::DataSpaceIException("HDF5IO::loadMatrix()","A dataspace must be precisely two-dimensional."));
hsize_t Dims[2];
DataSpace.getSimpleExtentDims(Dims);
M.resize(Dims[0],Dims[1]);
DataSet.read(M.data(), ComplexDataType);
FG.close();
} catch( const H5::Exception err ){
RUNTIME_ERROR("HDF5IO::loadComplexMatrix at ");
}
}
/**
* Returns a pointer to a std::vector<float> containing the values of the selected variable
* in the range specified by the startIndex and count (the number of records to read) stored
* in the selected file. This allocates a new std::vector<float> pointer. Make sure you
* delete the contents when you done using it, or you will have a memory leak.
* @param variableID
* @param startIndex
* @param count
* @return std::vector<float> containing the values of the selected variable.
*/
std::vector<float>* HDF5FileReader::getVariable(long variable, long indexOffset, long count)
{
std::vector<float>* variableData = new std::vector<float>();
//get dim sizes
H5::Group group = this->current_file->openGroup("Variables");
//cout << "variable: " << variable << ": " << counts[0] << endl;
H5::DataSet * dataset = new H5::DataSet(group.openDataSet(group.getObjnameByIdx(variable)));
H5::DataSpace dataspace = dataset->getSpace();
int rank = dataspace.getSimpleExtentNdims(); //should be 1
hsize_t length[1] = {count};
hsize_t offset[1] = {indexOffset};
//int ndims = dataspace.getSimpleExtentDims(count, NULL);
float * buffer = new float[length[0]];
dataspace.selectHyperslab(H5S_SELECT_SET, length, offset);
hsize_t dim[] = {length[0]};
H5::DataSpace memspace( rank, dim);
memspace.selectHyperslab(H5S_SELECT_SET, dim, offset);
dataset->read(buffer, H5::PredType::NATIVE_FLOAT, memspace, dataspace);
//add data to vector type, and delete original array
variableData->reserve(length[0]);
for (int i = 0; i < length[0]; i++)
{
variableData->push_back(buffer[i]);
}
delete[] buffer;
delete dataset;
//std::cout << "finished reading " << variable << std::endl;
//std::cout << "size of variable: " << variableData.size() << std::endl;
//std::cout << "dimSizes[0]: " << dimSizes[0] << std::endl;
return variableData;
}
OXSXDataSet
DataSetIO::LoadDataSet(const std::string& filename_){
// Get Data Set
H5::H5File file(filename_, H5F_ACC_RDONLY);
H5::DataSet dataSet = file.openDataSet("observations");
// read meta information
unsigned nObs = 0;
H5::Attribute nameAtt = dataSet.openAttribute("observed_quantities");
H5::Attribute countAtt = dataSet.openAttribute("n_observables");
H5std_string strreadbuf("");
nameAtt.read(nameAtt.getDataType(), strreadbuf);
countAtt.read(countAtt.getDataType(), &nObs);
// Read data out as 1D array
hsize_t nData = 0;
dataSet.getSpace().getSimpleExtentDims(&nData, NULL);
size_t nEntries = nData/nObs;
std::vector<double> flatData(nData, 0);
dataSet.read(&flatData.at(0), H5::PredType::NATIVE_DOUBLE);
assert(nData%nObs == 0); // logic error in writing file (this class!) if assert fails.
// Assemble into an OXSX data set
OXSXDataSet oxsxDataSet;
// Set the variable names
oxsxDataSet.SetObservableNames(UnpackString(strreadbuf, fDelimiter));
// then the data
std::vector<double> oneEventObs(nObs, 0);
for(size_t i = 0; i < nEntries; i++){
for(size_t j = 0; j < nObs; j++)
oneEventObs[j] = flatData.at(i * nObs + j);
oxsxDataSet.AddEntry(EventData(oneEventObs));
}
return oxsxDataSet;
}
std::vector<double> readEloss(const std::string& path)
{
H5::H5File file (path.c_str(), H5F_ACC_RDONLY);
H5::DataSet ds = file.openDataSet("eloss");
H5::DataSpace filespace = ds.getSpace();
int ndims = filespace.getSimpleExtentNdims();
assert(ndims == 1);
hsize_t dim;
filespace.getSimpleExtentDims(&dim);
H5::DataSpace memspace (ndims, &dim);
std::vector<double> res (dim);
ds.read(res.data(), H5::PredType::NATIVE_DOUBLE, memspace, filespace);
filespace.close();
memspace.close();
ds.close();
file.close();
return res;
}
std::vector<double> readlastrow( H5::DataSet& ds )
{
H5::DataSpace origspace = ds.getSpace();
int rank = origspace.getSimpleExtentNdims();
hsize_t dims[rank];
int ndims = origspace.getSimpleExtentDims( dims, NULL);
hsize_t nrows=dims[0];
hsize_t ncols=dims[1];
std::vector<double> returnvect( ncols );
hsize_t targrowoffset = nrows-1;
hsize_t targcoloffset = 0;
hsize_t dimsmem[rank] = {1, ncols};
H5::DataSpace memspace(rank, dimsmem);
hsize_t offset[rank] = { targrowoffset, targcoloffset };
origspace.selectHyperslab( H5S_SELECT_SET, dimsmem, offset );
ds.read( returnvect.data(), H5::PredType::NATIVE_DOUBLE, memspace, origspace );
return returnvect;
}
void Hdf5Handler::initialize(
const std::string& filename,
const std::vector<Hdf5ColumnData>& columns)
{
try
{
m_h5File.reset(new H5::H5File(filename, H5F_ACC_RDONLY));
}
catch (const H5::FileIException&)
{
throw hdf5_error("Could not open HDF5 file");
}
try
{
// Open each HDF5 DataSet and its corresponding DataSpace.
for (const auto& col : columns)
{
const std::string dataSetName = col.name;
const H5::PredType predType = col.predType;
const H5::DataSet dataSet = m_h5File->openDataSet(dataSetName);
const H5::DataSpace dataSpace = dataSet.getSpace();
m_columnDataMap.insert(std::make_pair(
dataSetName,
ColumnData(predType, dataSet, dataSpace)));
// Does not check whether all the columns are the same length.
m_numPoints =
std::max((uint64_t)getColumnNumEntries(dataSetName), m_numPoints);
}
}
catch (const H5::Exception&)
{
throw hdf5_error("Could not initialize data set information");
}
}
ossimRefPtr<ossimProjection> ossim_hdf5::getBilinearProjection(
H5::DataSet& latDataSet, H5::DataSet& lonDataSet, const ossimIrect& validRect )
{
ossimRefPtr<ossimProjection> proj = 0;
// Get dataspace of the dataset.
H5::DataSpace latDataSpace = latDataSet.getSpace();
H5::DataSpace lonDataSpace = lonDataSet.getSpace();
// Number of dimensions of the input dataspace:
const ossim_int32 DIM_COUNT = latDataSpace.getSimpleExtentNdims();
if ( DIM_COUNT == 2 )
{
// Get the extents. Assuming dimensions are same for lat lon dataset.
std::vector<hsize_t> dimsOut(DIM_COUNT);
latDataSpace.getSimpleExtentDims( &dimsOut.front(), 0 );
if ( dimsOut[0] && dimsOut[1] )
{
std::vector<hsize_t> inputCount(DIM_COUNT);
std::vector<hsize_t> inputOffset(DIM_COUNT);
inputOffset[0] = 0;
inputOffset[1] = 0;
inputCount[0] = 1;
inputCount[1] = 1;
// Output dataspace dimensions.
const ossim_int32 OUT_DIM_COUNT = 3;
std::vector<hsize_t> outputCount(OUT_DIM_COUNT);
outputCount[0] = 1; // single band
outputCount[1] = 1; // single line
outputCount[2] = 1; // single sample
// Output dataspace offset.
std::vector<hsize_t> outputOffset(OUT_DIM_COUNT);
outputOffset[0] = 0;
outputOffset[1] = 0;
outputOffset[2] = 0;
ossimScalarType scalar = ossim_hdf5::getScalarType( &latDataSet );
if ( scalar == OSSIM_FLOAT32 )
{
// See if we need to swap bytes:
ossimEndian* endian = 0;
if ( ( ossim::byteOrder() != ossim_hdf5::getByteOrder( &latDataSet ) ) )
{
endian = new ossimEndian();
}
// Native type:
H5::DataType latDataType = latDataSet.getDataType();
H5::DataType lonDataType = lonDataSet.getDataType();
std::vector<ossimDpt> ipts;
std::vector<ossimGpt> gpts;
ossimGpt gpt(0.0, 0.0, 0.0); // Assuming WGS84...
ossim_float32 latValue = 0.0;
ossim_float32 lonValue = 0.0;
// Only grab every 256th value.:
const ossim_int32 GRID_SIZE = 256;
// Output dataspace always the same one pixel.
H5::DataSpace bufferDataSpace( OUT_DIM_COUNT, &outputCount.front());
bufferDataSpace.selectHyperslab( H5S_SELECT_SET,
&outputCount.front(),
&outputOffset.front() );
//---
// Dataset sample has NULL lines at the end so scan for valid rect.
// Use "<= -999" for test as per NOAA as it seems the NULL value is
// fuzzy. e.g. -999.3.
//---
const ossim_float32 NULL_VALUE = -999.0;
//---
// Get the tie points within the valid rect:
//---
ossimDpt ipt = validRect.ul();
while ( ipt.y <= validRect.lr().y )
{
inputOffset[0] = static_cast<hsize_t>(ipt.y);
// Sample loop:
ipt.x = validRect.ul().x;
while ( ipt.x <= validRect.lr().x )
{
inputOffset[1] = static_cast<hsize_t>(ipt.x);
latDataSpace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
lonDataSpace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
// Read data from file into the buffer.
latDataSet.read( &latValue, latDataType, bufferDataSpace, latDataSpace );
lonDataSet.read( &lonValue, lonDataType, bufferDataSpace, lonDataSpace );
if ( endian )
{
// If the endian pointer is initialized(not zero) swap the bytes.
endian->swap( latValue );
endian->swap( lonValue );
}
if ( ( latValue > NULL_VALUE ) && ( lonValue > NULL_VALUE ) )
{
gpt.lat = latValue;
gpt.lon = lonValue;
gpts.push_back( gpt );
// Add the image point subtracting the image offset.
ossimIpt shiftedIpt = ipt - validRect.ul();
ipts.push_back( shiftedIpt );
}
// Go to next point:
if ( ipt.x < validRect.lr().x )
{
ipt.x += GRID_SIZE;
if ( ipt.x > validRect.lr().x )
{
ipt.x = validRect.lr().x; // Clamp to last sample.
}
}
else
{
break; // At the end:
}
} // End sample loop.
if ( ipt.y < validRect.lr().y )
{
ipt.y += GRID_SIZE;
if ( ipt.y > validRect.lr().y )
{
ipt.y = validRect.lr().y; // Clamp to last line.
}
}
else
{
break; // At the end:
}
} // End line loop.
if ( ipts.size() )
{
// Create the projection:
ossimRefPtr<ossimBilinearProjection> bp = new ossimBilinearProjection();
// Add the tie points:
bp->setTiePoints( ipts, gpts );
// Assign to output projection:
proj = bp.get();
}
// Cleanup:
if ( endian )
{
delete endian;
endian = 0;
}
}
else // Matches: if ( scalar == OSSIM_FLOAT32 ){...}
{
ossimNotify(ossimNotifyLevel_WARN)
<< "ossim_hdf5::getBilinearProjection WARNING!"
<< "\nUnhandled scalar type: "
<< ossimScalarTypeLut::instance()->getEntryString( scalar )
<< std::endl;
}
} // Matches: if ( dimsOut...
} // Matches: if ( IN_DIM_COUNT == 2 )
latDataSpace.close();
lonDataSpace.close();
return proj;
} // End: ossim_hdf5::getBilinearProjection()
void Bundle2::loadGeometry_(H5::H5File& file) {
H5::Group geometryGroup = file.openGroup("/Geometry");
// Loading poses
H5::DataSet posesDataSet = geometryGroup.openDataSet("Poses");
double* posesData = (double*)malloc(frames_.size()*12*sizeof(double));
posesDataSet.read((void*)posesData, H5::PredType::NATIVE_DOUBLE, H5::DataSpace::ALL, H5::DataSpace::ALL);
posesDataSet.close();
size_t i = 0;
for(deque<Frame*>::iterator it = frames_.begin(); it != frames_.end(); ++it) {
Pose* pose = new Pose;
pose->sett(core::RealPoint3D<double>(posesData[i*12], posesData[i*12 + 1], posesData[i*12 + 2]));
core::Matrix<double> R(3, 3);
R[0][0] = posesData[i*12 + 3]; R[1][0] = posesData[i*12 + 4]; R[2][0] = posesData[i*12 + 5];
R[0][1] = posesData[i*12 + 6]; R[1][1] = posesData[i*12 + 7]; R[2][1] = posesData[i*12 + 8];
R[0][2] = posesData[i*12 + 9]; R[1][2] = posesData[i*12 + 10]; R[2][2] = posesData[i*12 + 11];
pose->setR(R);
pose->calcEulerAngles();
pose->setorientationSynchronWithAngles(true);
pose->setderivationsSynchronWithAngles(false);
(*it)->setpose(pose);
++i;
}
free((void*)posesData);
// Loading points
H5::DataSet pointsDataSet = geometryGroup.openDataSet("Points");
double* pointsData = (double*)malloc(tracks_.size()*3*sizeof(double));
pointsDataSet.read((void*)pointsData, H5::PredType::NATIVE_DOUBLE, H5::DataSpace::ALL, H5::DataSpace::ALL);
pointsDataSet.close();
i = 0;
for(deque<Track*>::iterator it = tracks_.begin(); it != tracks_.end(); it++) {
Point* point = new Point(core::RealPoint3D<double>(pointsData[i*3], pointsData[i*3 + 1], pointsData[i*3 + 2]));
(*it)->setpoint(point);
++i;
}
free((void*)pointsData);
// Loading inlier information
H5::DataSet inliersDataSet = geometryGroup.openDataSet("Inliers");
hvl_t* inliersData = (hvl_t*)malloc(frames_.size()*sizeof(hvl_t));
H5::VarLenType memType(&H5::PredType::NATIVE_UCHAR);
inliersDataSet.read((void*)inliersData, memType, H5::DataSpace::ALL, H5::DataSpace::ALL);
memType.close();
inliersDataSet.close();
i = 0;
for(deque<Frame*>::iterator it = frames_.begin(); it != frames_.end(); it++) {
unsigned char* inl = (unsigned char*)(inliersData[i].p);
size_t k = 0;
for(size_t j = 0; j < (*it)->size(); ++j) {
View& v = (**it)[j];
for(unsigned int cam = 0; cam < v.numCameras(); ++cam) {
if(v.inCamera(cam)) {
Ray ray;
if(inl[k]) ray.setinlier(true);
else ray.setinlier(false);
v.addRay(cam, ray);
++k;
}
}
}
++i;
}
for(size_t j = 0; j < frames_.size(); ++j) free(inliersData[j].p);
free((void*)inliersData);
// Loading curves if they exists
bool curvesFound = false;
const hsize_t maxObjs = geometryGroup.getNumObjs();
for(hsize_t obj = 0; obj < maxObjs; ++obj) {
string objName = geometryGroup.getObjnameByIdx(obj);
if(objName == string("Curves")) curvesFound = true;
}
if(curvesFound) {
H5::DataSet curvesDataSet = geometryGroup.openDataSet("Curves");
hsize_t curvesDim[1];
H5::DataSpace curvesDS = curvesDataSet.getSpace();
curvesDS.getSimpleExtentDims(curvesDim);
curvesDS.close();
hvl_t* curvesData = (hvl_t*)malloc(curvesDim[0]*sizeof(hvl_t));
H5::VarLenType memType(&H5::PredType::NATIVE_HSIZE);
curvesDataSet.read((void*)curvesData, memType, H5::DataSpace::ALL, H5::DataSpace::ALL);
memType.close();
curvesDataSet.close();
for(size_t c = 0; c < curvesDim[0]; ++c) {
const size_t cur_c = addCurve();
for(size_t p = 0; p < curvesData[c].len; ++p) {
curves_[cur_c].addPoint(((size_t*)(curvesData[c].p))[p]);
}
}
for(size_t i = 0; i < curvesDim[0]; ++i) free(curvesData[i].p);
free((void*)curvesData);
}
geometryGroup.close();
}
bool TStellarData::load(const std::string& fname, const std::string& group, const std::string& dset,
double err_floor, double default_EBV) {
H5::H5File *file = H5Utils::openFile(fname);
if(file == NULL) { return false; }
H5::Group *gp = H5Utils::openGroup(file, group);
if(gp == NULL) {
delete file;
return false;
}
H5::DataSet dataset = gp->openDataSet(dset);
/*
* Photometry
*/
// Datatype
hsize_t nbands = NBANDS;
H5::ArrayType f4arr(H5::PredType::NATIVE_FLOAT, 1, &nbands);
H5::ArrayType u4arr(H5::PredType::NATIVE_UINT32, 1, &nbands);
H5::CompType dtype(sizeof(TFileData));
dtype.insertMember("obj_id", HOFFSET(TFileData, obj_id), H5::PredType::NATIVE_UINT64);
dtype.insertMember("l", HOFFSET(TFileData, l), H5::PredType::NATIVE_DOUBLE);
dtype.insertMember("b", HOFFSET(TFileData, b), H5::PredType::NATIVE_DOUBLE);
dtype.insertMember("mag", HOFFSET(TFileData, mag), f4arr);
dtype.insertMember("err", HOFFSET(TFileData, err), f4arr);
dtype.insertMember("maglimit", HOFFSET(TFileData, maglimit), f4arr);
dtype.insertMember("nDet", HOFFSET(TFileData, N_det), u4arr);
dtype.insertMember("EBV", HOFFSET(TFileData, EBV), H5::PredType::NATIVE_FLOAT);
// Dataspace
hsize_t length;
H5::DataSpace dataspace = dataset.getSpace();
dataspace.getSimpleExtentDims(&length);
// Read in dataset
TFileData* data_buf = new TFileData[length];
dataset.read(data_buf, dtype);
//std::cerr << "# Read in dimensions." << std::endl;
// Fix magnitude limits
for(int n=0; n<nbands; n++) {
float tmp;
float maglim_replacement = 25.;
// Find the 95th percentile of valid magnitude limits
std::vector<float> maglimit;
for(hsize_t i=0; i<length; i++) {
tmp = data_buf[i].maglimit[n];
if((tmp > 10.) && (tmp < 40.) && (!isnan(tmp))) {
maglimit.push_back(tmp);
}
}
//std::sort(maglimit.begin(), maglimit.end());
if(maglimit.size() != 0) {
maglim_replacement = percentile(maglimit, 95.);
}
// Replace missing magnitude limits with the 95th percentile magnitude limit
for(hsize_t i=0; i<length; i++) {
tmp = data_buf[i].maglimit[n];
if(!((tmp > 10.) && (tmp < 40.)) || isnan(tmp)) {
//std::cout << i << ", " << n << ": " << tmp << std::endl;
data_buf[i].maglimit[n] = maglim_replacement;
}
}
}
//int n_filtered = 0;
//int n_M_dwarfs = 0;
TMagnitudes mag_tmp;
for(size_t i=0; i<length; i++) {
mag_tmp.set(data_buf[i], err_floor);
star.push_back(mag_tmp);
//int n_informative = 0;
// Remove g-band
//mag_tmp.m[0] = 0.;
//mag_tmp.err[0] = 1.e10;
//double g_err = mag_tmp.err[0];
//mag_tmp.err[0] = sqrt(g_err*g_err + 0.1*0.1);
// Filter bright end
// TODO: Put this into query_lsd.py
/*for(int j=0; j<NBANDS; j++) {
if((mag_tmp.err[j] < 1.e9) && (mag_tmp.m[j] < 14.)) {
mag_tmp.err[j] = 1.e10;
mag_tmp.m[j] = 0.;
}
if(mag_tmp.err[j] < 1.e9) {
n_informative++;
}
}*/
// Filter M dwarfs based on color cut
//bool M_dwarf = false;
/*bool M_dwarf = true;
double A_g = 3.172;
double A_r = 2.271;
double A_i = 1.682;
if(mag_tmp.m[0] - A_g / (A_g - A_r) * (mag_tmp.m[0] - mag_tmp.m[1] - 1.2) > 20.) {
M_dwarf = false;
} else if(mag_tmp.m[1] - mag_tmp.m[2] - (A_r - A_i) / (A_g - A_r) * (mag_tmp.m[0] - mag_tmp.m[1]) < 0.) {
M_dwarf = false;
} else {
n_M_dwarfs++;
}
*/
/*if(n_informative >= 4) { //&& (!M_dwarf)) {
star.push_back(mag_tmp);
} else {
n_filtered++;
}*/
}
//std::cerr << "# of stars filtered: " << n_filtered << std::endl;
//std::cerr << "# of M dwarfs: " << n_M_dwarfs << std::endl;
/*
* Attributes
*/
H5::Attribute att = dataset.openAttribute("healpix_index");
H5::DataType att_dtype = H5::PredType::NATIVE_UINT64;
att.read(att_dtype, reinterpret_cast<void*>(&healpix_index));
att = dataset.openAttribute("nested");
att_dtype = H5::PredType::NATIVE_UCHAR;
att.read(att_dtype, reinterpret_cast<void*>(&nested));
att = dataset.openAttribute("nside");
att_dtype = H5::PredType::NATIVE_UINT32;
att.read(att_dtype, reinterpret_cast<void*>(&nside));
att = dataset.openAttribute("l");
att_dtype = H5::PredType::NATIVE_DOUBLE;
att.read(att_dtype, reinterpret_cast<void*>(&l));
att = dataset.openAttribute("b");
att_dtype = H5::PredType::NATIVE_DOUBLE;
att.read(att_dtype, reinterpret_cast<void*>(&b));
att = dataset.openAttribute("EBV");
att_dtype = H5::PredType::NATIVE_DOUBLE;
att.read(att_dtype, reinterpret_cast<void*>(&EBV));
// TEST: Force l, b to anticenter
//l = 180.;
//b = 0.;
if((EBV <= 0.) || (EBV > default_EBV) || isnan(EBV)) { EBV = default_EBV; }
delete[] data_buf;
delete gp;
delete file;
return true;
}
H5RandomReader::H5RandomReader(const std::string fileName, const std::string groupPath) throw (InvalidFileException) {
try {
file.openFile(fileName, H5F_ACC_RDONLY);}
catch ( H5::FileIException ) {
throw InvalidFileException("Cannot acces file");}
try {
group = file.openGroup(groupPath);}
catch ( H5::GroupIException ) {
file.close();
throw InvalidFileException("Cannot access group");}
/*
* extract timeline. This is also necessary to get the nbSteps.
*/
try {
timeline = group.openDataSet("timeline");
nSteps = timeline.getSpace().getSimpleExtentNpoints();}
catch ( H5::DataSetIException error ) {
//error.printError();
group.close();
file.close();
throw InvalidFileException("Cannot access timeline dataset");}
if (logging::info)
std::cerr << "Opened group \"" << fileName << groupPath << "\" which has " << nSteps << " steps.\n";
/*
* extract objects names in the xpGroup
*/
std::vector<std::string> names;
H5Literate(group.getId(), H5_INDEX_NAME, H5_ITER_INC, NULL, iterInGroup, &names);
/*
* extract data from object in xpGroup
* these data can be of 3 types: matrix, translate or wrench
* each data are saved in related map
*/
for (unsigned int i=0; i<names.size(); i++){ //TODO: skip timeline
H5::DataSet dSet = group.openDataSet(names[i]);
if (H5Aexists(dSet.getId(), "ArborisViewerType")) {
H5::Attribute att = dSet.openAttribute("ArborisViewerType");
std::string type;
att.read(att.getDataType(), type);
if (type == "matrix"){
H5::DataSpace dSpace = dSet.getSpace();
bool dimension_ok = false;
if (dSpace.getSimpleExtentNdims()==3) {
hsize_t dims[3];
dSpace.getSimpleExtentDims (dims);
if (dims[0] == nSteps && dims[1] == 4 && dims[2] == 4)
dimension_ok = true;}
if (dimension_ok)
matrices[names[i]] = dSet;
else {
if (logging::warning)
std::cerr << "Skipping dataset \"" << names[i] << "\" which has wrong dimensions. I was expecting (" << nSteps << ",4,4).\n";
dSet.close();}}
else if (type == "translate"){
H5::DataSpace dSpace = dSet.getSpace();
bool dimension_ok = false;
if (dSpace.getSimpleExtentNdims()==2) {
hsize_t dims[2];
dSpace.getSimpleExtentDims (dims);
if (dims[0] == nSteps && dims[1] == 3)
dimension_ok = true;}
if (dimension_ok)
translates[names[i]] = dSet;
else {
if (logging::warning)
std::cerr << "Skipping dataset \"" << names[i] << "\" which has wrong dimensions. I was expecting (" << nSteps << ",3).\n";
dSet.close();}}
else if (type == "wrench") {
H5::DataSpace dSpace = dSet.getSpace();
bool dimension_ok = false;
if (dSpace.getSimpleExtentNdims()==2) {
hsize_t dims[2];
dSpace.getSimpleExtentDims (dims);
if (dims[0] == nSteps && dims[1] == 6)
dimension_ok = true;}
if (dimension_ok)
wrenches[names[i]] = dSet;
else {
if (logging::warning)
std::cerr << "Skipping dataset \"" << names[i] << "\" which as wrong dimensions. I was expecting (" << nSteps << ",6).\n";
dSet.close();}}
else {
if (logging::warning)
std::cerr << "Skipping dataset \"" << names[i] << "\" whose ArborisViewerType attribute as unknown value \"" << type << "\".\n";
dSet.close();}
att.close();
}
else {
if (logging::info)
std::cerr << "Skipping dataset \"" << names[i] << "\" which has no ArborisViewerType attribute.\n";
dSet.close();
}
}
};
bool ossim_hdf5::crossesDateline( H5::DataSet& dataset, const ossimIrect& validRect )
{
bool result = false;
H5::DataSpace dataspace = dataset.getSpace();
// Number of dimensions of the input dataspace:
const ossim_int32 DIM_COUNT = dataspace.getSimpleExtentNdims();
if ( DIM_COUNT == 2 )
{
const ossim_uint32 ROWS = validRect.height();
const ossim_uint32 COLS = validRect.width();
// Get the extents. Assuming dimensions are same for lat lon dataset.
std::vector<hsize_t> dimsOut(DIM_COUNT);
dataspace.getSimpleExtentDims( &dimsOut.front(), 0 );
if ( (ROWS <= dimsOut[0]) && (COLS <= dimsOut[1]) )
{
std::vector<hsize_t> inputCount(DIM_COUNT);
std::vector<hsize_t> inputOffset(DIM_COUNT);
inputCount[0] = 1; // row
inputCount[1] = COLS; // col
// Output dataspace dimensions.
const ossim_int32 OUT_DIM_COUNT = 3;
std::vector<hsize_t> outputCount(OUT_DIM_COUNT);
outputCount[0] = 1; // single band
outputCount[1] = 1; // single line
outputCount[2] = COLS; // single sample
// Output dataspace offset.
std::vector<hsize_t> outputOffset(OUT_DIM_COUNT);
outputOffset[0] = 0;
outputOffset[1] = 0;
outputOffset[2] = 0;
ossimScalarType scalar = ossim_hdf5::getScalarType( &dataset );
if ( scalar == OSSIM_FLOAT32 )
{
// See if we need to swap bytes:
ossimEndian* endian = 0;
if ( ( ossim::byteOrder() != ossim_hdf5::getByteOrder( &dataset ) ) )
{
endian = new ossimEndian();
}
// Native type:
H5::DataType datatype = dataset.getDataType();
// Output dataspace always the same one line.
H5::DataSpace bufferDataSpace( OUT_DIM_COUNT, &outputCount.front());
bufferDataSpace.selectHyperslab( H5S_SELECT_SET,
&outputCount.front(),
&outputOffset.front() );
//---
// Dataset sample has NULL lines at the end so scan for valid rect.
// Use "<= -999" for test as per NOAA as it seems the NULL value is
// fuzzy. e.g. -999.3.
//---
// Buffer to hold a line:
std::vector<ossim_float32> lineBuffer(validRect.width());
// Read the first line:
inputOffset[0] = static_cast<hsize_t>(validRect.ul().y);
inputOffset[1] = static_cast<hsize_t>(validRect.ul().x);
dataspace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
dataset.read( &(lineBuffer.front()), datatype, bufferDataSpace, dataspace );
if ( endian )
{
// If the endian pointer is initialized(not zero) swap the bytes.
endian->swap( &(lineBuffer.front()), COLS );
}
// Test the first line:
result = ossim_hdf5::crossesDateline( lineBuffer );
if ( !result )
{
// Test the last line:
inputOffset[0] = static_cast<hsize_t>(validRect.ll().y);
inputOffset[1] = static_cast<hsize_t>(validRect.ll().x);
dataspace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
dataset.read( &(lineBuffer.front()), datatype, bufferDataSpace, dataspace );
result = ossim_hdf5::crossesDateline( lineBuffer );
}
if ( endian )
{
delete endian;
endian = 0;
}
}
else // Matches: if ( scalar == OSSIM_FLOAT32 ){...}
{
ossimNotify(ossimNotifyLevel_WARN)
<< "ossim_hdf5::crossesDateline WARNING!"
<< "\nUnhandled scalar type: "
<< ossimScalarTypeLut::instance()->getEntryString( scalar )
<< std::endl;
}
} // Matches: if ( dimsOut...
} // Matches: if ( IN_DIM_COUNT == 2 )
dataspace.close();
return result;
} // End: ossim_hdf5::crossesDateline(...)
//--------------------------------------------------------------------------------------------------
///
//--------------------------------------------------------------------------------------------------
TEST(DISABLED_HDFTests, BasicFileRead)
{
std::string file_path = "D:/ResInsight/SourSim/PKMUNK_NOV_TEST_SS.sourpre.00001";
try
{
H5::Exception::dontPrint(); // Turn off auto-printing of failures to handle the errors appropriately
H5::H5File file(file_path.c_str(), H5F_ACC_RDONLY);
{
H5::Group timestep = file.openGroup("Timestep_00001");
H5::Attribute attr = timestep.openAttribute("timestep");
double timestep_value = 0.0;
H5::DataType type = attr.getDataType();
attr.read(type, ×tep_value);
//std::cout << "Timestep value " << timestep_value << std::endl;
EXPECT_NEAR(timestep_value, 1.0, 1e-1);
}
{
// Group size is not an attribute!
H5::Group GridFunctions = file.openGroup("Timestep_00001/GridParts/GridPart_00000/GridFunctions");
hsize_t group_size = GridFunctions.getNumObjs();
//std::cout << "GridFunctions group_size " << group_size << std::endl;
EXPECT_EQ(size_t(20), group_size);
/* for (hsize_t i = 0; i < group_size; i++)
{
// H5std_string node_name = GridFunctions.getObjnameByIdx(i); // crashes on VS2017 due to lib/heap/runtime differences to HDF5 VS2015 lib
std::string node_name;
node_name.resize(1024);
ssize_t slen = GridFunctions.getObjnameByIdx(i, &node_name[0], 1023);
node_name.resize(slen + 1);
std::cout << "GridFunctions sub-node name " << node_name << std::endl;
}
*/
std::string first_subnode(1024, '\0');
ssize_t slen = GridFunctions.getObjnameByIdx(0, &first_subnode[0], 1023);
first_subnode.resize(slen + 1);
EXPECT_TRUE(first_subnode.compare(0, slen, "GridFunction_00002") == 0);
}
{
H5::Group GridFunction_00002 = file.openGroup("Timestep_00001/GridParts/GridPart_00000/GridFunctions/GridFunction_00002");
H5::Attribute attr = GridFunction_00002.openAttribute("limits_max");
double limits_max = 0.0;
H5::DataType type = attr.getDataType();
attr.read(type, &limits_max);
// std::cout << "limits_max " << limits_max << std::endl;
EXPECT_NEAR(limits_max, 0.3970204292629652, 1e-10);
}
{
H5::Group GridFunction_00002 = file.openGroup("Timestep_00001/GridParts/GridPart_00000/GridFunctions/GridFunction_00002");
H5::DataSet dataset = H5::DataSet(GridFunction_00002.openDataSet("values"));
hsize_t dims[2];
H5::DataSpace dataspace = dataset.getSpace();
dataspace.getSimpleExtentDims(dims, nullptr);
std::vector<double> values;
values.resize(dims[0]);
dataset.read(values.data(), H5::PredType::NATIVE_DOUBLE);
/* for (hsize_t i = 0; i < dims[0]; i++)
{
std::cout << "value " << i << " " << values[i] << std::endl;
}
*/
EXPECT_NEAR(values[0], 0.32356910366452146, 1e-10);
EXPECT_NEAR(values[dims[0] - 1], 0.12200070891582514, 1e-10);
}
} // end of try block
catch (H5::FileIException error) // catch failure caused by the H5File operations
{
std::cout << error.getCDetailMsg();
}
catch (H5::DataSetIException error) // catch failure caused by the DataSet operations
{
std::cout << error.getCDetailMsg();
}
catch (H5::DataSpaceIException error) // catch failure caused by the DataSpace operations
{
std::cout << error.getCDetailMsg();
}
catch (H5::DataTypeIException error) // catch failure caused by the DataSpace operations
{
std::cout << error.getCDetailMsg();
}
}
PcaModel PcaModel::loadStatismoModel(path h5file, PcaModel::ModelType modelType)
{
logging::Logger logger = Loggers->getLogger("shapemodels");
PcaModel model;
// Load the shape or color model from the .h5 file
string h5GroupType;
if (modelType == ModelType::SHAPE) {
h5GroupType = "shape";
} else if (modelType == ModelType::COLOR) {
h5GroupType = "color";
}
H5::H5File h5Model;
try {
h5Model = H5::H5File(h5file.string(), H5F_ACC_RDONLY);
}
catch (H5::Exception& e) {
string errorMessage = "Could not open HDF5 file: " + string(e.getCDetailMsg());
logger.error(errorMessage);
throw errorMessage;
}
// Load either the shape or texture mean
string h5Group = "/" + h5GroupType + "/model";
H5::Group modelReconstructive = h5Model.openGroup(h5Group);
// Read the mean
H5::DataSet dsMean = modelReconstructive.openDataSet("./mean");
hsize_t dims[2];
dsMean.getSpace().getSimpleExtentDims(dims, NULL); // dsMean.getSpace() leaks memory... maybe a hdf5 bug, maybe vlenReclaim(...) could be a fix. No idea.
//H5::DataSpace dsp = dsMean.getSpace();
//dsp.close();
Loggers->getLogger("shapemodels").debug("Dimensions of the model mean: " + lexical_cast<string>(dims[0]));
model.mean = Mat(1, dims[0], CV_32FC1); // Use a row-vector, because of faster memory access and I'm not sure the memory block is allocated contiguously if we have multiple rows.
dsMean.read(model.mean.ptr<float>(0), H5::PredType::NATIVE_FLOAT);
model.mean = model.mean.t(); // Transpose it to a col-vector
dsMean.close();
// Read the eigenvalues
dsMean = modelReconstructive.openDataSet("./pcaVariance");
dsMean.getSpace().getSimpleExtentDims(dims, NULL);
Loggers->getLogger("shapemodels").debug("Dimensions of the pcaVariance: " + lexical_cast<string>(dims[0]));
model.eigenvalues = Mat(1, dims[0], CV_32FC1);
dsMean.read(model.eigenvalues.ptr<float>(0), H5::PredType::NATIVE_FLOAT);
model.eigenvalues = model.eigenvalues.t();
dsMean.close();
// Read the PCA basis matrix
dsMean = modelReconstructive.openDataSet("./pcaBasis");
dsMean.getSpace().getSimpleExtentDims(dims, NULL);
Loggers->getLogger("shapemodels").debug("Dimensions of the PCA basis matrix: " + lexical_cast<string>(dims[0]) + ", " + lexical_cast<string>(dims[1]));
model.pcaBasis = Mat(dims[0], dims[1], CV_32FC1);
dsMean.read(model.pcaBasis.ptr<float>(0), H5::PredType::NATIVE_FLOAT);
dsMean.close();
modelReconstructive.close(); // close the model-group
// Read the noise variance (not implemented)
/*dsMean = modelReconstructive.openDataSet("./noiseVariance");
float noiseVariance = 10.0f;
dsMean.read(&noiseVariance, H5::PredType::NATIVE_FLOAT);
dsMean.close(); */
// Read the triangle-list
string representerGroupName = "/" + h5GroupType + "/representer";
H5::Group representerGroup = h5Model.openGroup(representerGroupName);
dsMean = representerGroup.openDataSet("./reference-mesh/triangle-list");
dsMean.getSpace().getSimpleExtentDims(dims, NULL);
Loggers->getLogger("shapemodels").debug("Dimensions of the triangle-list: " + lexical_cast<string>(dims[0]) + ", " + lexical_cast<string>(dims[1]));
Mat triangles(dims[0], dims[1], CV_32SC1);
dsMean.read(triangles.ptr<int>(0), H5::PredType::NATIVE_INT32);
dsMean.close();
representerGroup.close();
model.triangleList.resize(triangles.rows);
for (unsigned int i = 0; i < model.triangleList.size(); ++i) {
model.triangleList[i][0] = triangles.at<int>(i, 0);
model.triangleList[i][1] = triangles.at<int>(i, 1);
model.triangleList[i][2] = triangles.at<int>(i, 2);
}
// Load the landmarks mappings:
// load the reference-mesh
representerGroup = h5Model.openGroup(representerGroupName);
dsMean = representerGroup.openDataSet("./reference-mesh/vertex-coordinates");
dsMean.getSpace().getSimpleExtentDims(dims, NULL);
Loggers->getLogger("shapemodels").debug("Dimensions of the reference-mesh vertex-coordinates matrix: " + lexical_cast<string>(dims[0]) + ", " + lexical_cast<string>(dims[1]));
Mat referenceMesh(dims[0], dims[1], CV_32FC1);
dsMean.read(referenceMesh.ptr<float>(0), H5::PredType::NATIVE_FLOAT);
dsMean.close();
representerGroup.close();
// convert to 3 vectors with the x, y and z coordinates for easy searching
vector<float> refx(referenceMesh.col(0).clone());
vector<float> refy(referenceMesh.col(1).clone());
vector<float> refz(referenceMesh.col(2).clone());
// load the landmarks info (mapping name <-> reference (x, y, z)-coords)
H5::Group landmarksGroup = h5Model.openGroup("/metadata/landmarks");
dsMean = landmarksGroup.openDataSet("./text");
H5std_string outputString;
Loggers->getLogger("shapemodels").debug("Reading landmark information from the model.");
dsMean.read(outputString, dsMean.getStrType());
dsMean.close();
landmarksGroup.close();
vector<string> landmarkLines;
boost::split(landmarkLines, outputString, boost::is_any_of("\n"), boost::token_compress_on);
for (const auto& l : landmarkLines) {
if (l == "") {
continue;
}
vector<string> line;
boost::split(line, l, boost::is_any_of(" "), boost::token_compress_on);
string name = line[0];
int visibility = lexical_cast<int>(line[1]);
float x = lexical_cast<float>(line[2]);
float y = lexical_cast<float>(line[3]);
float z = lexical_cast<float>(line[4]);
// Find the x, y and z values in the reference
const auto ivx = std::find(begin(refx), end(refx), x);
const auto ivy = std::find(begin(refy), end(refy), y);
const auto ivz = std::find(begin(refz), end(refz), z);
// TODO Check for .end()!
const auto vertexIdX = std::distance(begin(refx), ivx);
const auto vertexIdY = std::distance(begin(refy), ivy);
const auto vertexIdZ = std::distance(begin(refz), ivz);
// assert vx=vy=vz
// Hmm this is not perfect. If there's another vertex where 1 or 2 coords are the same, it fails.
// We should do the search differently: Find _all_ the vertices that are equal, then take the one that has the right x, y and z.
model.landmarkVertexMap.insert(make_pair(name, vertexIdX));
}
h5Model.close();
return model;
}
bool ossim_hdf5::getValidBoundingRect( H5::DataSet& dataset,
const std::string& name,
ossimIrect& rect )
{
bool result = false;
H5::DataSpace imageDataspace = dataset.getSpace();
const ossim_int32 IN_DIM_COUNT = imageDataspace.getSimpleExtentNdims();
if ( IN_DIM_COUNT == 2 )
{
// Get the extents. Assuming dimensions are same for lat lon dataset.
std::vector<hsize_t> dimsOut(IN_DIM_COUNT);
imageDataspace.getSimpleExtentDims( &dimsOut.front(), 0 );
if ( dimsOut[0] && dimsOut[1] )
{
//---
// Capture the rectangle:
// dimsOut[0] is height, dimsOut[1] is width:
//---
rect = ossimIrect( 0, 0,
static_cast<ossim_int32>( dimsOut[1]-1 ),
static_cast<ossim_int32>( dimsOut[0]-1 ) );
const ossim_int32 WIDTH = rect.width();
std::vector<hsize_t> inputCount(IN_DIM_COUNT);
std::vector<hsize_t> inputOffset(IN_DIM_COUNT);
inputOffset[0] = 0;
inputOffset[1] = 0;
inputCount[0] = 1;
inputCount[1] = WIDTH;
// Output dataspace dimensions.
const ossim_int32 OUT_DIM_COUNT = 3;
std::vector<hsize_t> outputCount(OUT_DIM_COUNT);
outputCount[0] = 1; // single band
outputCount[1] = 1; // single line
outputCount[2] = WIDTH; // whole line
// Output dataspace offset.
std::vector<hsize_t> outputOffset(OUT_DIM_COUNT);
outputOffset[0] = 0;
outputOffset[1] = 0;
outputOffset[2] = 0;
ossimScalarType scalar = ossim_hdf5::getScalarType( &dataset );
if ( scalar == OSSIM_FLOAT32 )
{
// See if we need to swap bytes:
ossimEndian* endian = 0;
if ( ( ossim::byteOrder() != ossim_hdf5::getByteOrder( &dataset ) ) )
{
endian = new ossimEndian();
}
// Native type:
H5::DataType datatype = dataset.getDataType();
// Output dataspace always the same one line.
H5::DataSpace bufferDataSpace( OUT_DIM_COUNT, &outputCount.front());
bufferDataSpace.selectHyperslab( H5S_SELECT_SET,
&outputCount.front(),
&outputOffset.front() );
//---
// Dataset sample has NULL lines at the end so scan for valid rect.
// Use "<= -999" for test as per NOAA as it seems the NULL value is
// fuzzy. e.g. -999.3.
//---
const ossim_float32 NULL_VALUE = -999.0;
//---
// VIIRS Radiance data has a -1.5e-9 in the first column.
// Treat this as a null.
//---
const ossim_float32 NULL_VALUE2 = ( name == "/All_Data/VIIRS-DNB-SDR_All/Radiance" )
? -1.5e-9 : NULL_VALUE;
const ossim_float32 TOLERANCE = 0.1e-9; // For ossim::almostEqual()
// Hold one line:
std::vector<ossim_float32> values( WIDTH );
// Find the ul pixel:
ossimIpt ulIpt = rect.ul();
bool found = false;
// Line loop to find upper left pixel:
while ( ulIpt.y <= rect.lr().y )
{
inputOffset[0] = static_cast<hsize_t>(ulIpt.y);
imageDataspace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
// Read data from file into the buffer.
dataset.read( (void*)&values.front(), datatype, bufferDataSpace, imageDataspace );
if ( endian )
{
// If the endian pointer is initialized(not zero) swap the bytes.
endian->swap( scalar, (void*)&values.front(), WIDTH );
}
// Sample loop:
ulIpt.x = rect.ul().x;
ossim_int32 index = 0;
while ( ulIpt.x <= rect.lr().x )
{
if ( !ossim::almostEqual(values[index], NULL_VALUE2, TOLERANCE) &&
( values[index] > NULL_VALUE ) )
{
found = true; // Found valid pixel.
break;
}
++ulIpt.x;
++index;
} // End: sample loop
if ( found )
{
break;
}
++ulIpt.y;
} // End line loop to find ul pixel:
// Find the lower right pixel:
ossimIpt lrIpt = rect.lr();
found = false;
// Line loop to find last pixel:
while ( lrIpt.y >= rect.ul().y )
{
inputOffset[0] = static_cast<hsize_t>(lrIpt.y);
imageDataspace.selectHyperslab( H5S_SELECT_SET,
&inputCount.front(),
&inputOffset.front() );
// Read data from file into the buffer.
dataset.read( (void*)&values.front(), datatype, bufferDataSpace, imageDataspace );
if ( endian )
{
// If the endian pointer is initialized(not zero) swap the bytes.
endian->swap( scalar, (void*)&values.front(), WIDTH );
}
// Sample loop:
lrIpt.x = rect.lr().x;
ossim_int32 index = WIDTH-1;
while ( lrIpt.x >= rect.ul().x )
{
if ( !ossim::almostEqual(values[index], NULL_VALUE2, TOLERANCE) &&
( values[index] > NULL_VALUE ) )
{
found = true; // Found valid pixel.
break;
}
--lrIpt.x;
--index;
} // End: sample loop
if ( found )
{
break;
}
--lrIpt.y;
} // End line loop to find lower right pixel.
rect = ossimIrect( ulIpt, lrIpt );
// Cleanup:
if ( endian )
{
delete endian;
endian = 0;
}
result = true;
}
else // Matches: if ( scalar == OSSIM_FLOAT32 ){...}
{
ossimNotify(ossimNotifyLevel_WARN)
<< "ossim_hdf5::getBoundingRect WARNING!"
<< "\nUnhandled scalar type: "
<< ossimScalarTypeLut::instance()->getEntryString( scalar )
<< std::endl;
}
} // Matches: if ( dimsOut...
} // Matches: if ( IN_DIM_COUNT == 2 )
imageDataspace.close();
return result;
} // End: ossim_hdf5::getBoundingRect(...)