re: github issue https://github.com/Unidata/netcdf-fortran/issues/82
This was originally discovered in the Fortran tests, but is
a problem in the C library.
The problem only occurred when using HDF5-1.10.x. The reason it
failed is that starting with 1.10, the hid_t type was changed
from 32 bits to 64 bits.
The function libsrc4/nc4memcb.c#NC4_image_init was using type int (doh!)
to return the hdf fileid instead of hid_t type. This, of course,
caused the id to be truncated and in turn later use of the id
caused hdf5 to fail.
Fix is trivial: replace int with hid_t. This also requires a related
change in nc4mem.c.
Also added the test case derived from the original Fortran code.
You would think I would learn...
corresponding HDF5 operations.
re: github issue https://github.com/Unidata/netcdf-c/issues/908
also in reference to https://github.com/pydata/xarray/issues/2004
The netcdf-c library has implemented the nc_get_vars and nc_put_vars
operations as element at a time. This has resulted in very slow
operation.
This pr attempts to improve the situation for netcdf-4/hdf5 files
by using the slab operations provided by the hdf5 library. The new
implementation passes the get/put vars stride information down to
the hdf5 slab operations.
The result appears to improve performance significantly. Some simple
tests on large 2-D arrays shows speedups in excess of 150.
Misc. other changes:
1. fix bug in ncgen/semantics.c; using a list's allocated length
instead of actual length.
2. Added a temporary hook in the netcdf library plus a performance
test case (tst_varsperf.c) to estimate the speedup. After users
have had some experience with this, I will remove it, probably
after the 4.7 release.
