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Tutorial Adaptive
=================
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`Adaptive <https://github.com/python-adaptive/adaptive>`__
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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``
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- ``sortedcollections >= 1.1``
- ``sortedcontainers >= 2.0``
- ``atomicwrites``
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Additionally ``adaptive`` has lots of extra functionality that makes it
simple to use from Jupyter notebooks. This extra functionality depends
on the following packages
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- ``ipython``
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- ``ipykernel>=4.8.0``
- ``jupyter_client>=5.2.2``
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- ``holoviews>=1.9.1``
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- ``ipywidgets``
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- ``bokeh``
- ``matplotlib``
- ``plotly``
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We recommend to start with the :ref:`Tutorial `~adaptive.Learner1D``.
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.. 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
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tutorial.SequenceLearner
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tutorial.SKOptLearner
tutorial.parallelism
tutorial.advanced-topics
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