Skip to main content

A tool for Approximate Bayesian Computation

Project description

![Logo](abrox/gui/icons/readme_logo.png)

# Approximate Bayes rocks!

`ABrox` is a python package for Approximate Bayesian Computation accompanied by a user-friendly graphical interface.

## Features

* Model comparison via approximate Bayes factors
+ rejection
+ random forest
* Parameter inference
+ rejection
+ MCMC
* Cross-validation

## Installation

Note that `ABrox`only works with Python 3.

`ABrox` can be installed via pip. Simply open a terminal and type:

```bash
pip install abrox
```

It might take a few seconds since there are several dependencies that you might have to install as well.

### MacPorts

If you installed Python via MacPorts, the `abrox-gui` command after installation of `abrox` does not work.
You can alternatively start the GUI via (assuming Python version 3.5):

```bash
cd /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/abrox/gui/
python3.5 main.py
```

### Windows

Unfortunately, the installation under Windows is a bit cumbersome. We explain the relevant steps below.

If not already done, install a Python3 version from [here](https://www.python.org/).

Check the version of Python that is installed by typing `python` into the console.

![Python on Windows](abrox/gui/icons/python_windows2.png)

Now, install Visual Studio Build Tools from:

1. [here](http://landinghub.visualstudio.com/visual-cpp-build-tools)

Now visit the following page to install the Scipy wheel. Choose the link that fits
your Python version (see picture above). `cp` should be followed by the actual version (e.g. `cp36`) while
the last part of the link should match the bit-version (e.g. `win32`).

2. [here](http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy)

After the installation, open a console in the directory the wheel has been downloaded into and type:

```bash
python -m pip install #name_of_the_whl_file
```

Repeat the same steps for the Numpy wheel:

3. [here](http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy)

Now, open a terminal and type:

```bash
python -m pip install abrox
```

You are now ready to use `ABrox`!

## ABrox using the GUI

After `ABrox` has been installed, you can start the user interface by typing `abrox-gui`.
We provide several templates in order to get more familiar with the GUI.

## ABrox using Python

If you are more comfortable with plain Python, you can run your project once from the GUI and
continue working with the Python-file that has been generated in the output folder.

## Templates

We provide a few example project files so you can see how `ABrox` works ([here](https://github.com/mertensu/ABrox/tree/master/project_files)).
Currently, we provide:

* Two-sample t-test
* Levene-Test

### Contributors

* [Ulf Mertens](http://www.psychologie.uni-heidelberg.de/ae/meth/team/mertens/)
* Stefan Radev

Project details


Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
abrox-2.0.2.tar.gz (1.1 MB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page