wradlib.io.xarray_depr.OdimH5

class wradlib.io.xarray_depr.OdimH5(filename=None, flavour=None, **kwargs)

Class for xarray based retrieval of ODIM_H5 data files

Initialize xarray structure from hdf5 data structure.

Parameters:

• filename (str) – Source data file name.

• flavour (str) – Name of hdf5 flavour (‘ODIM’ or ‘GAMIC’). Defaults to ‘ODIM’.

Keyword Arguments:

• decode_times (bool) – If True, decode cf times to np.datetime64. Defaults to True.

• decode_coords (bool) – If True, use the ‘coordinates’ attribute on variable to assign coordinates. Defaults to True.

• mask_and_scale (bool) – If True, lazily scale (using scale_factor and add_offset) and mask (using _FillValue). Defaults to True.

• chunks (int or dict, optional) – If chunks is provided, it used to load the new dataset into dask arrays. chunks={} loads the dataset with dask using a single chunk for all arrays.

• georef (bool) – If True, adds 2D AEQD x,y,z-coordinates, ground_range (gr) and 2D (rays,bins)-coordinates for easy georeferencing (eg. cartopy)

• standard (str) –

  • none - data is read as verbatim as possible, no metadata

  • odim - data is read, odim metadata added to datasets

  • cf-mandatory - data is read according to cfradial2 standard importing mandatory metadata

  • cf-full - data is read according to cfradial2 standard importing all available cfradial2 metadata (not fully implemented)

• dim0 (str) –

  name of the ray-dimension of DataArrays and Dataset:

  • time - cfradial2 standard

  • azimuth - better for working with xarray

__init__(filename=None, flavour=None, **kwargs)

Initialize xarray structure from hdf5 data structure.

Parameters:

• filename (str) – Source data file name.

• flavour (str) – Name of hdf5 flavour (‘ODIM’ or ‘GAMIC’). Defaults to ‘ODIM’.

Keyword Arguments:

• decode_times (bool) – If True, decode cf times to np.datetime64. Defaults to True.

• decode_coords (bool) – If True, use the ‘coordinates’ attribute on variable to assign coordinates. Defaults to True.

• mask_and_scale (bool) – If True, lazily scale (using scale_factor and add_offset) and mask (using _FillValue). Defaults to True.

• chunks (int or dict, optional) – If chunks is provided, it used to load the new dataset into dask arrays. chunks={} loads the dataset with dask using a single chunk for all arrays.

• georef (bool) – If True, adds 2D AEQD x,y,z-coordinates, ground_range (gr) and 2D (rays,bins)-coordinates for easy georeferencing (eg. cartopy)

• standard (str) –

  • none - data is read as verbatim as possible, no metadata

  • odim - data is read, odim metadata added to datasets

  • cf-mandatory - data is read according to cfradial2 standard importing mandatory metadata

  • cf-full - data is read according to cfradial2 standard importing all available cfradial2 metadata (not fully implemented)

• dim0 (str) –

  name of the ray-dimension of DataArrays and Dataset:

  • time - cfradial2 standard

  • azimuth - better for working with xarray

Methods

__init__([filename, flavour])	Initialize xarray structure from hdf5 data structure.
assign_data(filename[, flavour])	Assign xarray dataset from hdf5 data structure.
assign_root()
clear()
georeference([sweeps])	Georeference sweeps
get(k[,d])
items()
keys()
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised.
popitem()	as a 2-tuple; but raise KeyError if D is empty.
setdefault(k[,d])
to_cfradial2(filename)	Save volume to CfRadial2.0 compliant file.
to_odim(filename)	Save volume to ODIM_H5/V2_2 compliant file.
update([E, ]**F)	If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()

Attributes

Conventions	Return CF/ODIM Conventions.
location	Return location of data source.
root	Return root dataset.
sweep	Return sweep dimension count.
sweep_angles
sweep_names
sweeps	Return zip sweep names, sweep_angles
version	Return CF/ODIM version