EB · PyPI

https://img.shields.io/travis/rvswift/EB.svg

EnsembleBuilder uses compound activity data to train structure based ensembles to prospectively classify active and inactive compounds.

Free software: BSD license
Documentation: https://EB.readthedocs.org.

Features

Works with Python 2.6, 2.7, 3.3, 3.4

Installation

Installation prerequisites

NumPy: www.numpy.org
SciPy: www.scipy.org

Install EnsembleBuilder with pip

pip install EB

Install EnsembleBuilder by cloning the GitHub repo

git clone https://github.com/rvswift/EB
cd EB
make install

Usage

To run, type ensemblebuilder on the command line

usage:        ensemblebuilder <mode> <args>

              ensemblebuilder <mode> to show help for that mode.

modes:
  exhaustive     Determine the best performer by considering all possible ensembles, O(2^N).
  fastheuristic  Determine the best ensemble using a O(N) heuristic.
  slowheuristic  Determine the best ensemble using an O(N^2) heuristic.
  postanalysis   Plot and analyze the performance of one or more ensembles.
  splitter       Split csv input into training and test sets.

History

0.1.0 (ls)

First release on PyPI.

Release files for EB 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for EB 0.1.5
File	Size	Uploaded
EB-0.1.5.tar.gz	35.3 kB	Nov 19, 2015	Details

Built distribution (wheel)

Table of built distributions (wheels) for EB 0.1.5
File	Interpreter	ABI	Platform	Reset
EB-0.1.5-py2.py3-none-any.whl 40.2 kB Nov 19, 2015	Python 3, Python 2	none	any	Details

Total release size: 75.5 kB

Release files / EB-0.1.5.tar.gz

Download URL	EB-0.1.5.tar.gz
Size	35.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`00613bd1ba1241ccfc7b14b8eef41f1bd004ccaf95505229bc5b474f919afdd7`
BLAKE2b-256 checksum How to use checksums	`093c5f9b55473c79455e15a443973fe364123671ef0a29583fd28765bbf2752f`
Upload date	Nov 19, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No

Release files / EB-0.1.5-py2.py3-none-any.whl

Download URL	EB-0.1.5-py2.py3-none-any.whl
Size	40.2 kB
Tags	Python 2 Python 3
SHA-256 checksum How to use checksums	`c629439251a1596d1e8ed5e0c8010be57c244830cf374707ad1107eb5608c5fd`
BLAKE2b-256 checksum How to use checksums	`6139cfb7e68892d59f8dcc3f03ed6b2657cae79ba7a0e9a3ace125d6a9c5d25f`
Upload date	Nov 19, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No