Tutorial Adaptive
=================

.. warning::
    This documentation is not functional yet! Whenever
    `this Pull Request <https://github.com/jupyter-widgets/jupyter-sphinx/pull/22/>`__.
    is done, the documentation will be correctly build.

`Adaptive <https://gitlab.kwant-project.org/qt/adaptive-evaluation>`__
is a package for adaptively sampling functions with support for parallel
evaluation.

This is an introductory notebook that shows some basic use cases.

``adaptive`` needs at least Python 3.6, and the following packages:

- ``scipy``
- ``sortedcontainers``

Additionally ``adaptive`` has lots of extra functionality that makes it
simple to use from Jupyter notebooks. This extra functionality depends
on the following packages

- ``ipykernel>=4.8.0``
- ``jupyter_client>=5.2.2``
- ``holoviews``
- ``bokeh``
- ``ipywidgets``


.. note::
    Because this documentation consists of static html, the ``live_plot``
    and ``live_info`` widget is not live. Download the notebooks
    in order to see the real behaviour.

.. toctree::
    :hidden:

    tutorial.Learner1D
    tutorial.Learner2D
    tutorial.custom_loss
    tutorial.AverageLearner
    tutorial.BalancingLearner
    tutorial.DataSaver
    tutorial.IntegratorLearner
    tutorial.LearnerND
    tutorial.SKOptLearner
    tutorial.parallelism
    tutorial.advanced-topics