Analysis

Loaders

excee.load_result_tree(path, engine='h5netcdf', posterior_only=True, groups=None, **kwargs)

excee.io.to_dataarray(ds, dim='variable')

excee.io.to_dataset(da, dim='variable')

excee.io.restore_dsets(dt, vkey='variable')

excee.io.compress(data)

excee.io.decompress(data)

excee.io.extract_posterior(dt)

excee.io.construct_dt(data, best_fit=None, fixed_parameters=None, compressed=False, vkey=None, encode_attrs=False)

excee.io.construct_dt_for_storage(data, best_fit=None, fixed_parameters=None, compressed=True, vkey='variable', encode_attrs=True)

excee.io.deconstruct_dt(dt, vkey='variable')

Autocorrelation analysis

excee.autocorr_time(x, discard=0, thin=1, chain_dim='chain', draw_dim='draw', has_chain_axis=None, **kwargs)

excee.autocorr_time_over_time(x, ns, draw_dim='draw', **kwargs)

excee.discard_and_thin(data, discard_per_autocorr, thin_per_autocorr, *, autocorr_discard=100)

Other utilities

excee.get_random_sample(data, size, rng, reindex=False)

excee.project_sample(sample, func, *, filter_kw=None, exclude_attrs=False, pool=None, progress=True, progress_kwargs=None, **kwargs)

excee.analysis.split_vector_vars(data, keep_dims=('chain', 'draw', 'sample'))

Diagnostic plots

excee.plot_trace_2d(data, width=8, height=2, split_at=None, ratio=None, cbar_kwargs=None, subplots_layout='tight', **kwargs)

excee.plot_autocorr_evolution(data, n0, nn=20, **kwargs)

Statistics

excee.eff_gaussian_tension(x, y, *, quiet=False, sample_dims=('chain', 'draw'))