h5netcdf.File.create_variable#
- File.create_variable(name, dimensions=(), dtype=None, data=None, fillvalue=None, chunks=None, chunking_heuristic=None, **kwargs)#
Creates a new variable.
- Parameters:
name (
str) – Name of the new variable. If given as a path, intermediate groups will be created, if not existent.dimensions (
tuple) – Tuple containing dimension name strings. Defaults to empty tuple, effectively creating a scalar variable.dtype (
numpy.dtype,str,UserType (Enum,VL,Compound), optional) – Datatype of the new variable. Defaults to None.fillvalue (scalar, optional) – Specify fillvalue for uninitialized parts of the variable. Defaults to
None.chunks (
tuple, optional) – Tuple of integers specifying the chunksizes of each variable dimension.chunking_heuristic (
str, optional) – Specify auto-chunking approach. Can be either ofh5pyorh5netcdf. Defaults toh5netcdf. Discussion onh5netcdfchunking can be found in (GH52) and (PR127).compression (
str, optional) – Compression filter to apply, defaults togzip.zlibis an alias forgzip.compression_opts (
int) – Parameter for compression filter. Forcompression="gzip"/compression="zlib"Integer from 1 to 9 specifying the compression level. Defaults to 4.fletcher32 (
bool) – IfTrue, HDF5 Fletcher32 checksum algorithm is applied. Defaults toFalse.shuffle (
bool, optional) – IfTrue, HDF5 shuffle filter will be applied. Defaults toTrue.
Note
Please refer to
h5pydocumentation for further parameters via keyword arguments. Any parameterizations which do not adhere to netCDF4 standard will only work on files created withinvalid_netcdf=True,- Returns:
var (
h5netcdf.Variable) – Variable class instance