How to use the h5netcdf.legacyapi.Group function in h5netcdf
To help you get started, we’ve selected a few h5netcdf examples, based on popular ways it is used in public projects.
Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.
shoyer / h5netcdf / h5netcdf / legacyapi.py View on Github 
def _group_cls(self):
return Groupzlib = False
fletcher32 = False
shuffle = False
if datatype is str:
datatype = h5py.special_dtype(vlen=unicode)
kwds = {}
if zlib:
# only add compression related keyword arguments if relevant (h5py
# chokes otherwise)
kwds['compression'] = 'gzip'
kwds['compression_opts'] = complevel
kwds['shuffle'] = shuffle
return super(Group, self).create_variable(
varname, dimensions, dtype=datatype, fletcher32=fletcher32,
chunks=chunksizes, fillvalue=fill_value, **kwds)
Popular h5netcdf functions
- h5netcdf.attrs.Attributes
- h5netcdf.compat.ChainMap
- h5netcdf.compat.OrderedDict
- h5netcdf.compat.unicode
- h5netcdf.core._LazyObjectLookup
- h5netcdf.core.BaseVariable
- h5netcdf.core.CompatibilityError
- h5netcdf.core.File
- h5netcdf.core.Group
- h5netcdf.core.Group._create_dimension
- h5netcdf.core.Group.create_group
- h5netcdf.dimensions.Dimensions
- h5netcdf.File
- h5netcdf.legacyapi.Group
- h5netcdf.legacyapi.HasAttributesMixin
- h5netcdf.utils.Frozen