arviz.InferenceData

class arviz.InferenceData(**kwargs: Union[xarray.core.dataset.Dataset, List[xarray.core.dataset.Dataset], Tuple[xarray.core.dataset.Dataset, xarray.core.dataset.Dataset]])

Container for inference data storage using xarray.

For a detailed introduction to InferenceData objects and their usage, see Introduction to xarray, InferenceData, and netCDF for ArviZ. This page provides help and documentation on InferenceData methods and their low level implementation.

Methods

InferenceData.__init__(**kwargs)	Initialize InferenceData object from keyword xarray datasets.
InferenceData.add_groups([group_dict, …])	Add new groups to InferenceData object.
InferenceData.assign([variables])
InferenceData.assign_coords([coords])
InferenceData.chunk([chunks, name_prefix, …])
InferenceData.compute(**kwargs)
InferenceData.copy()	Return a fresh copy of the InferenceData object.
InferenceData.cumsum([dim, skipna])
InferenceData.extend(other[, join])	Extend InferenceData with groups from another InferenceData.
InferenceData.from_netcdf(filename)	Initialize object from a netcdf file.
InferenceData.from_zarr(store)	Initialize object from a zarr store or path.
InferenceData.get(k[,d])
InferenceData.get_index(key)
InferenceData.groups()	Return all groups present in InferenceData object.
InferenceData.isel([groups, filter_groups, …])	Perform an xarray selection on all groups.
InferenceData.items()	Return a view over the groups and datasets present in the InferenceData object.
InferenceData.keys()
InferenceData.load(**kwargs)
InferenceData.map(fun[, groups, …])	Apply a function to multiple groups.
InferenceData.max([dim, skipna])
InferenceData.mean([dim, skipna])
InferenceData.median([dim, skipna])
InferenceData.min([dim, skipna])
InferenceData.persist(**kwargs)
InferenceData.quantile(q[, dim, …])
InferenceData.rename([name_dict, groups, …])	Perform xarray renaming of variable and dimensions on all groups.
InferenceData.rename_dims([name_dict, …])	Perform xarray renaming of dimensions on all groups.
InferenceData.rename_vars([name_dict, …])	Perform xarray renaming of variable or coordinate names on all groups.
InferenceData.reset_coords([names, drop])
InferenceData.reset_index(dims_or_levels[, drop])
InferenceData.sel([groups, filter_groups, …])	Perform an xarray selection on all groups.
InferenceData.set_coords(names)
InferenceData.set_index([indexes, append])
InferenceData.sortby(variables[, ascending])
InferenceData.stack([dimensions, groups, …])	Perform an xarray stacking on all groups.
InferenceData.sum([dim, skipna])
InferenceData.to_dataframe([groups, …])	Convert InferenceData to a pandas.DataFrame following xarray naming conventions.
InferenceData.to_dict([groups, filter_groups])	Convert InferenceData to a dictionary following xarray naming conventions.
InferenceData.to_json(filename[, groups, …])	Write InferenceData to a json file.
InferenceData.to_netcdf(filename[, …])	Write InferenceData to file using netcdf4.
InferenceData.to_zarr([store])	Convert InferenceData to a zarr.hierarchy.Group.
InferenceData.unify_chunks()
InferenceData.unstack([dim, groups, …])	Perform an xarray unstacking on all groups.
InferenceData.values()	Return a view over the Xarray Datasets present in the InferenceData object.

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arviz.InferenceData.__init__