anchor-bio 1.1.1

Description:

anchorbio 1.1.1

[](https://travis-ci.org/YeoLab/anchor)[](https://pypi.python.org/pypi/anchor)[](https://codecov.io/gh/YeoLab/anchor)## What is `anchor`?Anchor is a python package to find unimodal, bimodal, and multimodal features in any data that is normalized between 0 and 1, for example alternative splicing or other percent-based units.* Free software: BSD license* Documentation: https://YeoLab.github.io/anchor## InstallationTo install `anchor`, we recommend using the[Anaconda Python Distribution](http://anaconda.org/) and creating anenvironment, so the `anchor` code and dependencies don't interfere withanything else. Here is the command to create an environment:```conda create -n anchor-env pandas scipy numpy matplotlib seaborn```### Stable (recommended)To install this code from the Python Package Index, you'll need to specify ``anchor-bio`` (``anchor`` was already taken - boo).```pip install anchor-bio```### Bleeding-edge (for the brave)If you want the latest and greatest version, clone this github repository and use `pip` to install```git clone [email protected]:YeoLab/anchorcd anchorpip install . # The "." means "install *this*, the folder where I am now"```## Usage`anchor` was structured like `scikit-learn`, where if you want the "finalanswer" of your estimator, you use `fit_transform()`, but if you want to see theintermediates, you use `fit()`.If you want the modality assignments for your data, first make sure that youhave a `pandas.DataFrame`, here it is called `data`, in the format (samples,features). This uses a log2 Bayes Factor cutoff of 5, and the default Betadistribution parameterizations (shown [here]())```pythonimport anchorbm = anchor.BayesianModalities()modalities = bm.fit_transform(data)```If you want to see all the intermediate Bayes factors, then you can do:```pythonimport anchorbm = anchor.BayesianModalities()bayes_factors = bm.fit(data)```## History### 1.1.1 (2017-06-29)- In `infotheory.binify`, round the decimal numbers before they are written as strings### 1.0.1 (2017-06-28)- Documentation and build fixes### 1.0.0 (2017-06-28)* Updated to Python 3.5, 3.6### 0.1.0 (2015-07-08)* First release on PyPI.