Data#

Inference library converters#

`from_beanmachine`([sampler, coords, dims])	Convert Bean Machine MonteCarloSamples object into an InferenceData object.
`from_cmdstan`([posterior, ...])	Convert CmdStan data into an InferenceData object.
`from_cmdstanpy`([posterior, ...])	Convert CmdStanPy data into an InferenceData object.
`from_emcee`([sampler, var_names, slices, ...])	Convert emcee data into an InferenceData object.
`from_numpyro`([posterior, prior, ...])	Convert NumPyro data into an InferenceData object.
`from_pyjags`([posterior, prior, ...])	Convert PyJAGS posterior samples to an ArviZ inference data object.
`from_pyro`([posterior, prior, ...])	Convert Pyro data into an InferenceData object.
`from_pystan`([posterior, ...])	Convert PyStan data into an InferenceData object.

`convert_to_inference_data`(obj, *[, group, ...])	Convert a supported object to an InferenceData object.
`convert_to_dataset`(obj, *[, group, coords, dims])	Convert a supported object to an xarray dataset.
`dict_to_dataset`(data, *[, attrs, library, ...])	Convert a dictionary or pytree of numpy arrays to an xarray.Dataset.
`from_datatree`(datatree)	Create an InferenceData object from a `DataTree`.
`from_dict`([posterior, posterior_predictive, ...])	Convert Dictionary data into an InferenceData object.
`from_json`(filename)	Initialize object from a json file.
`from_netcdf`(filename, *[, engine, ...])	Load netcdf file back into an arviz.InferenceData.
`to_datatree`(data)	Convert InferenceData object to a `DataTree`.
`to_json`(idata, filename)	Save dataset as a json file.
`to_netcdf`(data, filename, *[, group, ...])	Save dataset as a netcdf file.
`from_zarr`(store)	Initialize object from a zarr store or path.
`to_zarr`(data[, store])	Convert data to zarr, optionally saving to disk if `store` is provided.

`concat`(*args[, dim, copy, inplace, reset_dim])	Concatenate InferenceData objects.
`extract`(data[, group, combined, var_names, ...])	Extract an InferenceData group or subset of it.

`list_datasets`()	Get a string representation of all available datasets with descriptions.
`load_arviz_data`([dataset, data_home])	Load a local or remote pre-made dataset.