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Accuracy

The accuracy module provides functions for converting between accuracy and scale parameters.

accuracy_to_discrete_gaussian_scale()
Convert a desired accuracy (tolerance) into a discrete gaussian noise scale at a statistical significance level alpha.
accuracy_to_discrete_laplacian_scale()
Convert a desired accuracy (tolerance) into a discrete Laplacian noise scale at a statistical significance level alpha.
accuracy_to_gaussian_scale()
Convert a desired accuracy (tolerance) into a gaussian noise scale at a statistical significance level alpha.
accuracy_to_laplacian_scale()
Convert a desired accuracy (tolerance) into a Laplacian noise scale at a statistical significance level alpha.
discrete_gaussian_scale_to_accuracy()
Convert a discrete gaussian scale into an accuracy estimate (tolerance) at a statistical significance level alpha.
discrete_laplacian_scale_to_accuracy()
Convert a discrete Laplacian scale into an accuracy estimate (tolerance) at a statistical significance level alpha.
gaussian_scale_to_accuracy()
Convert a gaussian scale into an accuracy estimate (tolerance) at a statistical significance level alpha.
laplacian_scale_to_accuracy()
Convert a Laplacian scale into an accuracy estimate (tolerance) at a statistical significance level alpha.

Combinators

The combinators module provides functions for combining transformations and measurements.

make_basic_composition()
basic composition constructor
make_chain_mt()
chain mt constructor
make_chain_pm()
chain pm constructor
make_chain_tt()
chain tt constructor
make_fix_delta()
fix delta constructor
make_population_amplification()
population amplification constructor
make_pureDP_to_fixed_approxDP()
pureDP to fixed approxDP constructor
make_pureDP_to_zCDP()
pureDP to zCDP constructor
make_sequential_composition()
sequential composition constructor
make_zCDP_to_approxDP()
zCDP to approxDP constructor
then_basic_composition()
partial basic composition constructor
then_chain_mt()
partial chain mt constructor
then_chain_pm()
partial chain pm constructor
then_chain_tt()
partial chain tt constructor
then_fix_delta()
partial fix delta constructor
then_population_amplification()
partial population amplification constructor
then_pureDP_to_fixed_approxDP()
partial pureDP to fixed approxDP constructor
then_pureDP_to_zCDP()
partial pureDP to zCDP constructor
then_sequential_composition()
partial sequential composition constructor
then_zCDP_to_approxDP()
partial zCDP to approxDP constructor

Core

The core module provides functions for accessing the fields of transformations and measurements.

function_eval()
Eval the function with arg.
measurement_check()
Check the privacy relation of the measurement at the given d_in, d_out
measurement_function()
Get the function from a measurement.
measurement_input_carrier_type()
Get the input (carrier) data type of this.
measurement_input_distance_type()
Get the input distance type of measurement.
measurement_input_domain()
Get the input domain from a measurement.
measurement_input_metric()
Get the input domain from a measurement.
measurement_invoke()
Invoke the measurement with arg. Returns a differentially private release.
measurement_map()
Use the measurement to map a given d_in to d_out.
measurement_output_distance_type()
Get the output distance type of measurement.
measurement_output_measure()
Get the output domain from a measurement.
queryable_eval()
Invoke the queryable with query. Returns a differentially private release.
queryable_query_type()
Get the query type of queryable.
transformation_check()
Check the privacy relation of the measurement at the given d_in, d_out
transformation_function()
Get the function from a transformation.
transformation_input_carrier_type()
Get the input (carrier) data type of this.
transformation_input_distance_type()
Get the input distance type of transformation.
transformation_input_domain()
Get the input domain from a transformation.
transformation_input_metric()
Get the input domain from a transformation.
transformation_invoke()
Invoke the transformation with arg. Returns a differentially private release.
transformation_map()
Use the transformation to map a given d_in to d_out.
transformation_output_distance_type()
Get the output distance type of transformation.
transformation_output_domain()
Get the output domain from a transformation.
transformation_output_metric()
Get the output domain from a transformation.

Domains

The domains module provides functions for creating and using domains.

atom_domain()
Construct an instance of AtomDomain.
bitvector_domain()
Construct an instance of BitVectorDomain.
domain_carrier_type()
Get the carrier type of a domain.
domain_debug()
Debug a domain.
domain_type()
Get the type of a domain.
map_domain()
Construct an instance of MapDomain.
member()
Check membership in a domain.
option_domain()
Construct an instance of OptionDomain.
vector_domain()
Construct an instance of VectorDomain.

Measurements

The measurements module provides functions that apply calibrated noise to data to ensure differential privacy.

debias_randomized_response_bitvec()
Convert a vector of randomized response bitvec responses to a frequency estimate
make_alp_queryable()
alp queryable constructor
make_gaussian()
gaussian constructor
make_geometric()
geometric constructor
make_laplace()
laplace constructor
make_laplace_threshold()
laplace threshold constructor
make_randomized_response()
randomized response constructor
make_randomized_response_bitvec()
randomized response bitvec constructor
make_randomized_response_bool()
randomized response bool constructor
make_report_noisy_max_gumbel()
report noisy max gumbel constructor
then_alp_queryable()
partial alp queryable constructor
then_gaussian()
partial gaussian constructor
then_geometric()
partial geometric constructor
then_laplace()
partial laplace constructor
then_laplace_threshold()
partial laplace threshold constructor
then_randomized_response()
partial randomized response constructor
then_randomized_response_bitvec()
partial randomized response bitvec constructor
then_randomized_response_bool()
partial randomized response bool constructor
then_report_noisy_max_gumbel()
partial report noisy max gumbel constructor

Measures

The measures modules provides functions that measure the distance between probability distributions.

fixed_smoothed_max_divergence()
Construct an instance of the FixedSmoothedMaxDivergence measure.
max_divergence()
Construct an instance of the MaxDivergence measure.
measure_debug()
Debug a measure.
measure_distance_type()
Get the distance type of a measure.
measure_type()
Get the type of a measure.
smoothed_max_divergence()
Construct an instance of the SmoothedMaxDivergence measure.
user_divergence()
Construct a new UserDivergence. Any two instances of an UserDivergence are equal if their string descriptors are equal.
zero_concentrated_divergence()
Construct an instance of the ZeroConcentratedDivergence measure.

Metrics

The metrics module provides fuctions that measure the distance between two elements of a domain.

absolute_distance()
Construct an instance of the AbsoluteDistance metric.
change_one_distance()
Construct an instance of the ChangeOneDistance metric.
discrete_distance()
Construct an instance of the DiscreteDistance metric.
hamming_distance()
Construct an instance of the HammingDistance metric.
insert_delete_distance()
Construct an instance of the InsertDeleteDistance metric.
l1_distance()
Construct an instance of the L1Distance metric.
l2_distance()
Construct an instance of the L2Distance metric.
linf_distance()
Construct an instance of the LInfDistance metric.
metric_debug()
Debug a metric.
metric_distance_type()
Get the distance type of a metric.
metric_type()
Get the type of a metric.
partition_distance()
Construct an instance of the PartitionDistance metric.
symmetric_distance()
Construct an instance of the SymmetricDistance metric.
user_distance()
Construct a new UserDistance. Any two instances of an UserDistance are equal if their string descriptors are equal.

Mod

The mod module provides the classes which implement the OpenDP Programming Framework, as well as utilities for enabling features and finding parameter values.

binary_search()
Find the closest passing value to the decision boundary of predicate
binary_search_chain()
Find the highest-utility (d_in, d_out)-close Transformation or Measurement.
binary_search_param()
Solve for the ideal constructor argument to make_chain
disable_features()
Disable features in the opendp package.
enable_features()
Enable features for the opendp package.
hashitems()
extract heterogeneously typed keys and values from a hashtab
new_domain()
new domain
new_function()
new function
new_hashtab()
create an instance of a hashtab from keys and values
new_measure()
new measure
new_measurement()
new measurement
new_metric()
new metric
new_queryable()
new queryable
new_smd_curve()
new Smoothed Max Divergence curve
new_transformation()
new transformation

Transformations

The transformations module provides functions that deterministicly transform datasets.

choose_branching_factor()
Returns an approximation to the ideal branching_factor for a dataset of a given size, that minimizes error in cdf and quantile estimates based on b-ary trees.
make_b_ary_tree()
b ary tree constructor
make_bounded_float_checked_sum()
bounded float checked sum constructor
make_bounded_float_ordered_sum()
bounded float ordered sum constructor
make_bounded_int_monotonic_sum()
bounded int monotonic sum constructor
make_bounded_int_ordered_sum()
bounded int ordered sum constructor
make_bounded_int_split_sum()
bounded int split sum constructor
make_cast()
cast constructor
make_cast_default()
cast default constructor
make_cast_inherent()
cast inherent constructor
make_cdf()
cdf constructor
make_clamp()
clamp constructor
make_consistent_b_ary_tree()
consistent b ary tree constructor
make_count()
count constructor
make_count_by()
count by constructor
make_count_by_categories()
count by categories constructor
make_count_distinct()
count distinct constructor
make_create_dataframe()
create dataframe constructor
make_df_cast_default()
df cast default constructor
make_df_is_equal()
df is equal constructor
make_drop_null()
drop null constructor
make_find()
find constructor
make_find_bin()
find bin constructor
make_identity()
identity constructor
make_impute_constant()
impute constant constructor
make_impute_uniform_float()
impute uniform float constructor
make_index()
index constructor
make_is_equal()
is equal constructor
make_is_null()
is null constructor
make_lipschitz_float_mul()
lipschitz float mul constructor
make_mean()
mean constructor
make_metric_bounded()
metric bounded constructor
make_metric_unbounded()
metric unbounded constructor
make_ordered_random()
ordered random constructor
make_quantile_score_candidates()
quantile score candidates constructor
make_quantiles_from_counts()
quantiles from counts constructor
make_resize()
resize constructor
make_select_column()
select column constructor
make_sized_bounded_float_checked_sum()
sized bounded float checked sum constructor
make_sized_bounded_float_ordered_sum()
sized bounded float ordered sum constructor
make_sized_bounded_int_checked_sum()
sized bounded int checked sum constructor
make_sized_bounded_int_monotonic_sum()
sized bounded int monotonic sum constructor
make_sized_bounded_int_ordered_sum()
sized bounded int ordered sum constructor
make_sized_bounded_int_split_sum()
sized bounded int split sum constructor
make_split_dataframe()
split dataframe constructor
make_split_lines()
split lines constructor
make_split_records()
split records constructor
make_subset_by()
subset by constructor
make_sum()
sum constructor
make_sum_of_squared_deviations()
sum of squared deviations constructor
make_unordered()
unordered constructor
make_variance()
variance constructor
then_b_ary_tree()
partial b ary tree constructor
then_bounded_float_checked_sum()
partial bounded float checked sum constructor
then_bounded_float_ordered_sum()
partial bounded float ordered sum constructor
then_bounded_int_monotonic_sum()
partial bounded int monotonic sum constructor
then_bounded_int_ordered_sum()
partial bounded int ordered sum constructor
then_bounded_int_split_sum()
partial bounded int split sum constructor
then_cast()
partial cast constructor
then_cast_default()
partial cast default constructor
then_cast_inherent()
partial cast inherent constructor
then_cdf()
partial cdf constructor
then_clamp()
partial clamp constructor
then_consistent_b_ary_tree()
partial consistent b ary tree constructor
then_count()
partial count constructor
then_count_by()
partial count by constructor
then_count_by_categories()
partial count by categories constructor
then_count_distinct()
partial count distinct constructor
then_create_dataframe()
partial create dataframe constructor
then_df_cast_default()
partial df cast default constructor
then_df_is_equal()
partial df is equal constructor
then_drop_null()
partial drop null constructor
then_find()
partial find constructor
then_find_bin()
partial find bin constructor
then_identity()
partial identity constructor
then_impute_constant()
partial impute constant constructor
then_impute_uniform_float()
partial impute uniform float constructor
then_index()
partial index constructor
then_is_equal()
partial is equal constructor
then_is_null()
partial is null constructor
then_lipschitz_float_mul()
partial lipschitz float mul constructor
then_mean()
partial mean constructor
then_metric_bounded()
partial metric bounded constructor
then_metric_unbounded()
partial metric unbounded constructor
then_ordered_random()
partial ordered random constructor
then_quantile_score_candidates()
partial quantile score candidates constructor
then_quantiles_from_counts()
partial quantiles from counts constructor
then_resize()
partial resize constructor
then_select_column()
partial select column constructor
then_sized_bounded_float_checked_sum()
partial sized bounded float checked sum constructor
then_sized_bounded_float_ordered_sum()
partial sized bounded float ordered sum constructor
then_sized_bounded_int_checked_sum()
partial sized bounded int checked sum constructor
then_sized_bounded_int_monotonic_sum()
partial sized bounded int monotonic sum constructor
then_sized_bounded_int_ordered_sum()
partial sized bounded int ordered sum constructor
then_sized_bounded_int_split_sum()
partial sized bounded int split sum constructor
then_split_dataframe()
partial split dataframe constructor
then_split_lines()
partial split lines constructor
then_split_records()
partial split records constructor
then_subset_by()
partial subset by constructor
then_sum()
partial sum constructor
then_sum_of_squared_deviations()
partial sum of squared deviations constructor
then_unordered()
partial unordered constructor
then_variance()
partial variance constructor

Typing

The typing module provides utilities that bridge between R and Rust types. OpenDP relies on precise descriptions of data types to make its security guarantees: These are more natural in Rust with its fine-grained type system, but they may feel out of place in R. These utilities try to fill that gap.

BitVector
type signature for a BitVector
String
type signature for a string
bool
type signature for a boolean
f32
type signature for a 32-bit floating point number
f64
type signature for a 64-bit floating point number
i128
type signature for a 128-bit signed integer
i16
type signature for a 16-bit signed integer
i32
type signature for a 32-bit signed integer
i64
type signature for a 64-bit signed integer
i8
type signature for an 8-bit signed integer
u128
type signature for a 128-bit unsigned integer
u16
type signature for a 16-bit unsigned integer
u32
type signature for a 32-bit unsigned integer
u64
type signature for a 64-bit unsigned integer
u8
type signature for an 8-bit unsigned integer
usize
type signature for a pointer-sized unsigned integer

Other

This should be empty if correctly configured. Please file an issue if any functions are listed here.