Function make_sized_bounded_float_ordered_sum 

pub fn make_sized_bounded_float_ordered_sum<S>(
    size: usize,
    bounds: (S::Item, S::Item),
) -> Fallible<Transformation<VectorDomain<AtomDomain<S::Item>>, InsertDeleteDistance, AtomDomain<S::Item>, AbsoluteDistance<S::Item>>>
where
    S: SaturatingSum,
    S::Item: 'static + Float,

Make a Transformation that computes the sum of bounded floats with known ordering and dataset size.

Only useful when make_bounded_float_checked_sum returns an error due to potential for overflow. This uses a restricted-sensitivity proof that takes advantage of known dataset size for better utility. You may need to use make_ordered_random to impose an ordering on the data.

S (summation algorithm)	input type
Sequential<S::Item>	Vec<S::Item>
Pairwise<S::Item>	Vec<S::Item>

S::Item is the type of all of the following: each bound, each element in the input data, the output data, and the output sensitivity.

For example, to construct a transformation that pairwise-sums f32 half-precision floats, set S to Pairwise<f32>.

Citations

• CSVW22 Widespread Underestimation of Sensitivity…
• DMNS06 Calibrating Noise to Sensitivity in Private Data Analysis

Arguments

• size - Number of records in input data.
• bounds - Tuple of lower and upper bounds for data in the input domain.

Generics

• S - Summation algorithm to use over some data type T (T is shorthand for S::Item)