Fixing Hyperslab Slices: Simplify with H5CPP Column Reads

The Issue (Bert Bril, Apr 26, 2018)

Bert was trying to extract an entire column from a really large 3D dataset—perhaps terabyte scale—into a 1D array using neat hyperslab coordinate selection. But the results were all wrong: Two out of every three values ended up zero, even though his start/count looked correct. He wasn’t even requesting broad slicing—just first column, full depth—yet the read was skipping data.

Steven Varga’s Insight (Apr 27, 2018)

Steve led with a reality check and a practical recommendation: Bang it into a simpler problem: If the dataset fits in memory, load the whole cube into an arma::cube and slice from there. If it doesn’t fit: Switch to a chunked column reader with H5CPP:

double* pd = static_cast<double*>(calloc(ROW_SIZE, sizeof(double)));
hid_t fd = h5::open("your_datafile.h5", H5F_ACC_RDONLY);
hid_t ds = h5::open(fd, "your_dataset");

for (int i = 0; i < data_rows; ++i) {
    h5::read(ds, pd, {0, i, 0}, {COL_SIZE, 1, 1});
    // 'start': {row, col, slice}; 'count': {row_count, 1, 1}
    // Apply your own stride/sieve logic here if needed
}

H5Dclose(ds);
H5Fclose(fd);

He noted that stride support is coming—but often manual subsetting is easier and just as fast. In short: don’t fight the API; control your data fetch with a clean loop and let H5CPP handle the heavy lifting.

Why This Fixes It

Step	Reason
Simplify the problem	Verifies hyperslab logic without third-party complexity
Use H5CPP for reads	Offers clear, chunked access that's easy to reason about and debug
Manual sieve control	Keeps logic explicit—no hidden behavior or unexpected flattening