Description:
autocontrol 1.0.0
========Overview========* Free software: MIT licenseActivate virtual environment==================Together with the autoCorrection package you will get 'tensorflow', 'toolz', 'keras', 'numpy', 'kopt', 'scipy', 'h5py', 'sklearn', 'dask', 'pandas', 'statsmodels'packages automatically installed, if not present.If you don't wannt to install these packages globally, please use virtual environment.If you have problems with virtualenv, installing using conda may help:(Installation of conda: https://conda.io/docs/user-guide/install/index.html)Make sure you are using python 3. conda create -n mypyth3 python=3.6 source activate mypyth3 conda install virtualenvactivate new environment in active python 3 environment: virtualenv env-with-autoCorrection source env-with-autoCorrection/bin/activateCheck if you are still using python 3: python --versionPackage Installation============:: pip install autocontrolDeactivate virtual environment============:: deactivateUsage============:: #in python: python import autocontrol import numpy as np counts = np.random.negative_binomial(n = 20, p=0.2, size = (10,8)) sf = np.ones((10,8)) corrector = autocontrol.correctors.AECorrector() c = corrector.correct(counts = counts, size_factors = sf) #in R: library(reticulate) autoCorrection <- import("autocontrol") corrected <- autoCorrectioncorrectorsAECorrector(model_name, model_directory)$correct(COUNTS, SIZE_FACTORS, only_predict=FALSE)Documentation=============https://i12g-gagneurweb.in.tum.de/public/docs/autocontrol/Changelog=========0.0.1 (2017-11-01)------------------* First release on PyPI.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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