Installation
adaptive
works with Python 3.7 and higher on Linux, Windows, or Mac,
and provides optional extensions for working with the Jupyter/IPython
Notebook.
The recommended way to install adaptive is using conda
:
conda install -c conda-forge adaptive
adaptive
is also available on PyPI:
pip install adaptive[notebook]
The [notebook]
above will also install the optional dependencies for
running adaptive
inside a Jupyter notebook.
To use Adaptive in Jupyterlab, you need to install the following labextensions.
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension install @pyviz/jupyterlab_pyviz
Development
Clone the repository and run setup.py develop
to add a link to the
cloned repo into your Python path:
git clone git@github.com:python-adaptive/adaptive.git
cd adaptive
python3 setup.py develop
We highly recommend using a Conda environment or a virtualenv to manage
the versions of your installed packages while working on adaptive
.
In order to not pollute the history with the output of the notebooks, please setup the git filter by executing
python ipynb_filter.py
in the repository.
We implement several other checks in order to maintain a consistent code style. We do this using pre-commit, execute
pre-commit install
in the repository.
Citing
If you used Adaptive in a scientific work, please cite it as follows.
@misc{Nijholt2019,
doi = {10.5281/zenodo.1182437},
author = {Bas Nijholt and Joseph Weston and Jorn Hoofwijk and Anton Akhmerov},
title = {\textit{Adaptive}: parallel active learning of mathematical functions},
publisher = {Zenodo},
year = {2019}
}
Credits
We would like to give credits to the following people:
Pedro Gonnet for his implementation of CQUAD, “Algorithm 4” as described in “Increasing the Reliability of Adaptive Quadrature Using Explicit Interpolants”, P. Gonnet, ACM Transactions on Mathematical Software, 37 (3), art. no. 26, 2010.
Pauli Virtanen for his
AdaptiveTriSampling
script (no longer available online since SciPy Central went down) which served as inspiration for theLearner2D
.