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..
.. Licensed under the Apache License, Version 2.0 (the "License");
.. you may not use this file except in compliance with the License.
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..
..     http://www.apache.org/licenses/LICENSE-2.0
..
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.. See the License for the specific language governing permissions and
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#####################
Mechanism Calibration
#####################

.. currentmodule:: dp_accounting.mechanism_calibration

A `PrivacyAccountant` and a `DpEvent` can be used to compute the privacy
parameters of a mechanism, given the mechanism's parameters. This module
reverses that process: it offers functions to compute the minimal/maximal
parameter of a mechanism that is needed to achieve a given level of privacy.

As a simple example, this snippet calibrates the noise multiplier for a
Gaussian mechanism to achieve `(1, 1e-5)`-DP:

.. code-block:: python

   noise_multiplier = dp_accounting.calibrate_dp_mechanism(
       make_fresh_accountant=dp_accounting.pld.PLDAccountant,
       make_event_from_param=dp_accounting.GaussianDpEvent,
       target_epsilon=1.0,
       target_delta=1e-5,
   )

Functions
---------

.. autofunction:: calibrate_dp_mechanism

Classes
-------

.. autoclass:: BracketInterval
   :members:
   :undoc-members:

.. autoclass:: ExplicitBracketInterval
   :members:
   :undoc-members:
   :show-inheritance:

.. autoclass:: LowerEndpointAndGuess
   :members:
   :undoc-members:
   :show-inheritance:

Exceptions
----------

.. autoexception:: NoBracketIntervalFoundError
   :members:

.. autoexception:: NonEmptyAccountantError
   :members: