Module opendp::measurements
source · Expand description
Various measurement constructors.
The different crate::core::Measurement
implementations in this module are accessed by calling the appropriate constructor function.
Constructors are named in the form make_xxx()
, where xxx
indicates what the resulting Measurement
does.
Modules§
Enums§
Traits§
Functions§
- Measurement to release a queryable containing a DP projection of bounded sparse data.
- Measurement to compute a DP projection of bounded sparse data.
- Measurement to compute a DP projection of bounded sparse data.
- Make a Measurement that adds noise from the discrete_gaussian(
scale
) distribution to the input. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input, using an efficient algorithm on rational bignums. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input, using a linear-time algorithm on finite data types. - Make a Measurement that adds noise from the gaussian(
scale
) distribution to the input. - An alias for
make_base_discrete_laplace_linear
. If you don’t need timing side-channel protections viabounds
,make_base_discrete_laplace
is more efficient. - Make a Measurement that adds noise from the Laplace(
scale
) distribution to a scalar value. - Make a Measurement that uses propose-test-release to privatize a hashmap of counts.
- Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input, directly using bignum rational types. - Make a Measurement that adds noise from the gaussian(
scale
) distribution to the input. - Make a Measurement that adds noise from the laplace(
scale
) distribution to the input. - Make a Measurement that implements randomized response on a categorical value.
- Make a Measurement that implements randomized response on a boolean value.
- Make a Measurement that takes a vector of scores and privately selects the index of the highest score.
- Make a postprocessor that wraps the AlpState in a Queryable object.
- Measurement to release a queryable containing a DP projection of bounded sparse data.
- Make a Measurement that adds noise from the discrete_gaussian(
scale
) distribution to the input. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input, using an efficient algorithm on rational bignums. - Make a Measurement that adds noise from the discrete_laplace(
scale
) distribution to the input, using a linear-time algorithm on finite data types. - Make a Measurement that adds noise from the gaussian(
scale
) distribution to the input. - An alias for
make_base_discrete_laplace_linear
. If you don’t need timing side-channel protections viabounds
,make_base_discrete_laplace
is more efficient. - Make a Measurement that adds noise from the Laplace(
scale
) distribution to a scalar value. - Make a Measurement that uses propose-test-release to privatize a hashmap of counts.
- Make a Measurement that adds noise from the gaussian(
scale
) distribution to the input. - Make a Measurement that adds noise from the laplace(
scale
) distribution to the input. - Make a Measurement that takes a vector of scores and privately selects the index of the highest score.