opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
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# type: ignore
class CompositionMeasure(ZeroConcentratedDivergence):
    def composability(  # |\label{line:composability}|
        self, adaptivity: Adaptivity
    ) -> Composability:
        match adaptivity:
            case Adaptivity.FullyAdaptive:
                return Composability.Sequential
            case _:
                return Composability.Concurrent

    def compose(self, d_mids: Vec[Self_Distance]) -> Self_Distance:
        d_out = 0.0
        for d_mid in d_mids:
            d_out = d_out.inf_add(d_mid)
        return d_out