Module opendp::measurements

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

• alp 🔒
• gaussian 🔒
• geometric 🔒
• gumbel_max 🔒
• laplace 🔒
• laplace_threshold 🔒
• make_user_measurement 🔒
• randomized_response 🔒

Enums

• Optimize

Traits

• GaussianDomain
• GaussianMeasure
• GeometricDomain
• LaplaceDomain

Functions

• make_alp_queryable
  Measurement to release a queryable containing a DP projection of bounded sparse data.
• make_alp_state
  Measurement to compute a DP projection of bounded sparse data.
• make_alp_state_with_hashers
  Measurement to compute a DP projection of bounded sparse data.
• make_gaussian
  Make a Measurement that adds noise from the Gaussian(scale) distribution to the input.
• make_geometric
  Equivalent to make_laplace but restricted to an integer support. Can specify bounds to run the algorithm in near constant-time.
• make_laplace
  Make a Measurement that adds noise from the Laplace(scale) distribution to the input.
• make_laplace_threshold
  Make a Measurement that uses propose-test-release to privatize a hashmap of counts.
• make_randomized_response
  Make a Measurement that implements randomized response on a categorical value.
• make_randomized_response_bool
  Make a Measurement that implements randomized response on a boolean value.
• make_report_noisy_max_gumbel
  Make a Measurement that takes a vector of scores and privately selects the index of the highest score.
• make_scalar_float_gaussian
  Make a Measurement that adds noise from the Gaussian(scale) distribution to a scalar-valued float input.
• make_scalar_float_laplace
  Make a Measurement that adds noise from the Laplace(scale) distribution to a scalar value.
• make_scalar_integer_gaussian
  Make a Measurement that adds noise from the discrete_gaussian(scale) distribution to the input.
• make_scalar_integer_laplace
  Make a Measurement that adds noise from the discrete_laplace(scale) distribution to the input, using an efficient algorithm on rational bignums.
• make_vector_float_gaussian
  Make a Measurement that adds noise from the Gaussian(scale) distribution to the vector-valued input.
• make_vector_float_laplace
  Make a Measurement that adds noise from the Laplace(scale) distribution to a vector value.
• make_vector_integer_gaussian
  Make a Measurement that adds noise from the discrete_gaussian(scale) distribution to the input.
• make_vector_integer_laplace
  Make a Measurement that adds noise from the discrete_laplace(scale) distribution to the input, using an efficient algorithm on rational bignums.
• opendp_measurements__make_user_measurement
• post_alp_state_to_queryable
  Make a postprocessor that wraps the AlpState in a Queryable object.
• then_alp_queryable
  Measurement to release a queryable containing a DP projection of bounded sparse data.
• then_gaussian
  Make a Measurement that adds noise from the Gaussian(scale) distribution to the input.
• then_geometric
  Equivalent to make_laplace but restricted to an integer support. Can specify bounds to run the algorithm in near constant-time.
• then_laplace
  Make a Measurement that adds noise from the Laplace(scale) distribution to the input.
• then_laplace_threshold
  Make a Measurement that uses propose-test-release to privatize a hashmap of counts.
• then_report_noisy_max_gumbel
  Make a Measurement that takes a vector of scores and privately selects the index of the highest score.