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(RenyiDivergence):
    def composability(  # |\label{line:composability}|
        self, adaptivity: Adaptivity
    ) -> Composability:
        return Composability.Concurrent

    def compose(self, d_mids: Vec[Self_Distance]) -> Self_Distance:
        def curve(alpha: float) -> float: # |\label{line:curve}|
            epsilons = [d_mid(alpha) for d_mid in d_mids]

            d_out = 0.0
            for d_mid in epsilons:
                d_out = d_out.inf_add(d_mid)
            return d_out

        return Function.new_fallible(curve)