If I'm outputting 2D slices (such as the 'buoyancy' task in the 2D RBC example) and pass, say, scales=(1/4, 1/2) to file_handler.add_task(), then the output will be down-sampled by 1/4 along the first axis, and 1/2 along the second axis. If I try this with the 2D RBC IVP example (MWE attached), this down-sampling is applied as intended to the data, but the axes that are output (the stuff in h5py.dset.dims, or in file['scales/...']) are not down-sampled appropriately. They are down-sampled, just by the wrong amount. In the attached, I'm running the 2D RBC example on an (Nx, Nz) = (128, 32) grid and outputting snapshots with scales=(1/4, 1/2), which correctly outputs 32 x 16 data slices. However, the z array inappropriately has length 8, not 16. Am I right that this is unintended behavior? Unfortunately, I'm having a hard time tracing the cause.
2D_RBC_IVP_MWE.py
If I'm outputting 2D slices (such as the 'buoyancy' task in the 2D RBC example) and pass, say,
scales=(1/4, 1/2)tofile_handler.add_task(), then the output will be down-sampled by 1/4 along the first axis, and 1/2 along the second axis. If I try this with the 2D RBC IVP example (MWE attached), this down-sampling is applied as intended to the data, but the axes that are output (the stuff inh5py.dset.dims, or infile['scales/...']) are not down-sampled appropriately. They are down-sampled, just by the wrong amount. In the attached, I'm running the 2D RBC example on an (Nx, Nz) = (128, 32) grid and outputting snapshots with scales=(1/4, 1/2), which correctly outputs 32 x 16 data slices. However, the z array inappropriately has length 8, not 16. Am I right that this is unintended behavior? Unfortunately, I'm having a hard time tracing the cause.2D_RBC_IVP_MWE.py