DressRehearsalResult#

class causalpy.experiments.sc_results.DressRehearsalResult[source]#

Result of a dress-rehearsal design validation.

Produced by SyntheticControl.validate_design().

injected_effect#

The effect that was injected into the pseudo-post window.

Type:: float

effect_type#

Whether the injected effect was "relative" or "absolute".

Type:: str

recovered_effect_mean#

Posterior mean of the cumulative impact in the pseudo-post window.

Type:: float

recovered_effect_hdi#

94% HDI of the cumulative impact posterior.

Type:: tuple[float, float]

hdi_covers_truth#

Whether the HDI interval contains the injected truth.

Type:: bool

posterior_samples#

Raw posterior draws of cumulative impact.

Type:: xr.DataArray

injected_truth#

The actual numeric value injected (after conversion from relative to absolute if applicable).

Type:: float

Methods

`DressRehearsalResult.__init__`(...)
`DressRehearsalResult.plot`()	Plot injected vs recovered effect with HDI band.
`DressRehearsalResult.summary`()	Return a DataFrame with recovery statistics.
`DressRehearsalResult.to_check_result`()	Convert to a `CheckResult` for sensitivity pipeline integration.

Attributes

`injected_effect`
`effect_type`
`recovered_effect_mean`
`recovered_effect_hdi`
`hdi_covers_truth`
`posterior_samples`
`injected_truth`

__init__(injected_effect, effect_type, recovered_effect_mean, recovered_effect_hdi, hdi_covers_truth, posterior_samples, injected_truth)#

Parameters:

injected_effect (float)
effect_type (str)
recovered_effect_mean (float)
recovered_effect_hdi (tuple[float, float])
hdi_covers_truth (bool)
posterior_samples (DataArray)
injected_truth (float)

Return type:

None

classmethod __new__(*args, **kwargs)#