I'm using Silo with HDF5, and I'm having trouble accessing some of the metadata with h5py. It spits out some rather unusual HDF5 structuring, where it puts a DATATYPE
inside a DATATYPE
. Here's an excerpt of the output from h5dump
:
DATATYPE "sigma_t" H5T_STD_I32LE;
ATTRIBUTE "silo" {
DATATYPE H5T_COMPOUND {
H5T_STRING {
STRSIZE 5;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
} "meshid";
H5T_STRING {
STRSIZE 15;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
} "value0";
H5T_STD_I32LE "ndims";
H5T_STD_I32LE "nvals";
H5T_STD_I32LE "nels";
H5T_IEEE_F32LE "time";
H5T_STD_I32LE "use_specmf";
H5T_STD_I32LE "centering";
H5T_ARRAY { [3] H5T_STD_I32LE } "dims";
H5T_ARRAY { [3] H5T_STD_I32LE } "zones";
H5T_ARRAY { [3] H5T_STD_I32LE } "min_index";
H5T_ARRAY { [3] H5T_STD_I32LE } "max_index";
H5T_ARRAY { [3] H5T_IEEE_F32LE } "align";
}
DATASPACE SCALAR
DATA {
(0): {
"mesh",
"/.silo/#000004",
2,
1,
100,
0,
-1000,
111,
[ 10, 10, 0 ],
[ 9, 9, 0 ],
[ 0, 0, 0 ],
[ 9, 9, 0 ],
[ 0.5, 0.5, 0 ]
}
}
}
ATTRIBUTE "silo_type" {
DATATYPE H5T_STD_I32LE
DATASPACE SCALAR
DATA {
(0): 501
}
}
Basically, f['sigma_t'].attrs['silo']
returns a tuple
with all of the correctly formatted data but without any of the associated labels for the data types. (I need to know the names meshid
, value0
, etc.) Is there a way to get this? I'm at a loss.
HDF5 file contains the "sigma_t" field, and the actual data is stored in /.silo/#000004
.
Script:
import h5py
f = h5py.File('xsn.silo', 'r')
print f['sigma_t'].attrs['silo']
Result:
('mesh', '/.silo/#000004', 2, 1, 100, 0.0, -1000, 111, array([10, 10, 0], dtype=int32), array([9, 9, 0], dtype=int32), array([0, 0, 0], dtype=int32), array([9, 9, 0], dtype=int32), array([ 0.5, 0.5, 0. ], dtype=float32))
What I also want is something like:
('meshid','value0','ndims', ..., 'align')
Is this possible?
I got an answer from the developer via the h5py Google groups page: it's a bug that will be fixed in h5py 1.4.
What I ended up doing is:
import h5py
f = h5py.File('xsn.silo', 'r')
group = f['sigma_t']
attr_id = h5py.h5a.open(group.id, 'silo')
data = dict(zip(attr_id.dtype.names, group.attrs['silo'],))