# ![][logo] adaptive

 [![pipeline status](https://gitlab.kwant-project.org/qt/adaptive/badges/master/pipeline.svg)](https://gitlab.kwant-project.org/qt/adaptive/pipelines)

 [![asv](http://img.shields.io/badge/benchmarked%20by-asv-green.svg?style=flat)](benchmarks)

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 **Tools for adaptive parallel evaluation of functions.**
 

 Adaptive is an [open-source](LICENSE) Python library designed to make adaptive parallel function evaluation simple. With adaptive, you can adaptively sample functions by only supplying (in general) a function and its bounds, and run it on a cluster in a few lines of code. Since `adaptive` knows the problem it is solving, it can plot the data for you (even live as the data returns) without any boilerplate. 

 Check out the Adaptive [example notebook `learner.ipynb`](learner.ipynb) (or run it [live on Binder](https://mybinder.org/v2/gh/python-adaptive/adaptive/master?filepath=learner.ipynb)) to see examples of how to use `adaptive`.

 
 
 **WARNING: `adaptive` is still in an early alpha development stage**
 
 
 ## Installation
 Adaptive works with Python 3.5 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 `pip`:

 ```bash

 pip install https://gitlab.kwant-project.org/qt/adaptive/repository/master/archive.zip
 ```
 
 

 ## Development
 
 In order to not pollute the history with the output of the notebooks, please setup the git filter by executing
 

 ```bash

 git config filter.nbclearoutput.clean "jupyter nbconvert --to notebook --ClearOutputPreprocessor.enabled=True --ClearOutputPreprocessor.remove_metadata_fields='[\"deletable\", \"editable\", \"collapsed\", \"scrolled\"]' --stdin --stdout"
 ```
 in the repository.

 ## Credits
 We would like to give credits to the following people:
 - Pedro Gonnet for his implementation of [`CQUAD`](https://cran.r-project.org/web/packages/cquad/index.html), "Algorithm 3" 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.
 - Christoph Groth for his Python implementation of [`CQUAD`](https://gitlab.kwant-project.org/cwg/python-cquad) which served as inspiration for the [`IntegratorLearner`](adaptive/learner/integrator_learner.py)
 - Pauli Virtanen for his `AdaptiveTriSampling` (no longer available online since SciPy Central went down) script which served as inspiration for the [`Learner2D`](adaptive/learner/learner2D.py)
 

 For general discussion, we have a [chat channel](https://chat.quantumtinkerer.tudelft.nl/external/channels/adaptive). If you find any bugs or have any feature suggestions please file a GitLab [issue](https://gitlab.kwant-project.org/qt/adaptive/issues/new?issue) or submit a [merge request](https://gitlab.kwant-project.org/qt/adaptive/merge_requests).

 
 [logo]: /uploads/d20444093920a4a0499e165b5061d952/logo.png "adaptive logo"