Summary
Summary#
- class liesel.goose.summary_m.Summary(results, additional_chain=None, quantiles=(0.05, 0.5, 0.95), hdi_prob=0.9, selected=None, deselected=None, per_chain=False)[source]#
Bases:
object
A summary object.
Allows easy programmatic access via
quantities[quantity_name][var_name]
. The array has a similar shape as the parameter withvar_name
. However, ifper_chain
isTrue
, and additionally for the quantitieshdi
andquantile
, the dimensions are different. Please refer to the documentation of the attributequantities
for details.The summary object can be turned into a
DataFrame
usingto_dataframe()
.- Parameters
results (
SamplingResults
) – The sampling results to summarize.additional_chain (
Optional
[NewType
(Position
,dict
[str
,Any
])]) – can be supplied to add more parameters to the summary output. Must be a position (default:None
) chain which matches chain and time dimension of the posterior chain as returned bySamplingResults.get_posterior_samples()
.hdi_prob (
float
) – Level on which to return posterior highest density intervals. (default:0.9
)selected (
Optional
[list
[str
]]) – Allow to get a summary only for a subset of the position keys. (default:None
)deselected (
Optional
[list
[str
]]) – Allow to get a summary only for a subset of the position keys. (default:None
)per_chain (bool) – If True, the summary is calculated on a per-chain basis. Certain measures like (default:
False
)rhat
are not available ifper_chain
is True.
Notes
This class is still considered experimental. The API may still undergo larger changes.
Methods
from_result
(result[, additional_chain, ...])Alias for
from_results()
for backwards compatibility.from_results
(results[, additional_chain, ...])Creates a
Summary
object from a results object.Turns Summary object into a
DataFrame
object.Attributes
Dict of summarizing quantities.