:py:mod:`cotengra.hyperoptimizers.hyper_random`
===============================================

.. py:module:: cotengra.hyperoptimizers.hyper_random

.. autoapi-nested-parse::

   Fake hyper optimization using random sampling.



Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   cotengra.hyperoptimizers.hyper_random.RandomSpace
   cotengra.hyperoptimizers.hyper_random.RandomSampler



Functions
~~~~~~~~~

.. autoapisummary::

   cotengra.hyperoptimizers.hyper_random.sample_bool
   cotengra.hyperoptimizers.hyper_random.sample_int
   cotengra.hyperoptimizers.hyper_random.sample_option
   cotengra.hyperoptimizers.hyper_random.sample_uniform
   cotengra.hyperoptimizers.hyper_random.sample_loguniform
   cotengra.hyperoptimizers.hyper_random.random_init_optimizers
   cotengra.hyperoptimizers.hyper_random.random_get_setting
   cotengra.hyperoptimizers.hyper_random.random_report_result



.. py:function:: sample_bool(rng)


.. py:function:: sample_int(rng, low, high)


.. py:function:: sample_option(rng, options)


.. py:function:: sample_uniform(rng, low, high)


.. py:function:: sample_loguniform(rng, low, high)


.. py:class:: RandomSpace(space, seed=None)


   .. py:method:: sample()



.. py:class:: RandomSampler(methods, spaces, seed=None)


   .. py:method:: ask()



.. py:function:: random_init_optimizers(self, methods, space, seed=None)

   Initialize a completely random sampling optimizer.

   :param space: The search space.
   :type space: dict[str, dict[str, dict]]


.. py:function:: random_get_setting(self)


.. py:function:: random_report_result(*_, **__)