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 pip install -e ".[notebook,testing,other]" to add a link to the cloned repo into your Python path:
git clone git@github.com:python-adaptive/adaptive.git
cd adaptive
pip install -e ".[notebook,testing,other]"
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
AdaptiveTriSamplingscript (no longer available online since SciPy Central went down) which served as inspiration for theadaptive.Learner2D.