Open Science Article Submitted: July 7, 2014https://doi.org/10.54294/2jpext

Reproducible Research Training at Scipy 2014

Ibanez, Luis1*,McCormick, Matt,Fillon, Jean-Christophe,Chaudri, Aashish,Nelson, Ana,Smith, Steve
1.KITWARE Inc.
Abstract
Reproducible Research Training at Scipy 2014

Abstract

This article illustrates the process of performing reproducible research with existing open source tools.

Keywords

notebookReproducibilityTardigradesScipyIPythondexygithubdocker
Manuscript
Source Code and Data

Source Code and Data

.nojekyll.gitignore849 BLICENSE11.1 KBREADME.md896 B_template.html425 Bassetsstyle.css2.2 KBdocumentsComputationalEnvironment.md3.2 KBDataAcquisition.md4.2 KBDataProcessing.md1.8 KBDataSharing.md1.8 KBLiterateProgramming.md614 BPreparation.md1.4 KBRegressionTesting.md1.7 KBVersionControl.md1.8 KBWorkflow.md1.8 KBindex.md3.7 KBdexy.conf47 Bdexy.yaml705 BenvironmentREADME.md306 BbashREADME.md144 Binitial_ubuntu_server_setup.sh1.6 KBdockerDockerfile1.8 KBDockerfile-dexy121 BDockerfile-ipython168 Bbuild-and-run.sh548 BREADME.md3.6 KBhelp.sh64 Benter-environment.sh75 Bhub-docker-image.sh91 BvagrantREADME.md783 BVagrantfile258 Bplaybook.yml1.8 KBinstall-and-generate.sh336 Bcheck_env.py1.3 KBnotebooks01-SimpleITK-Filtering.ipynb16.6 KB02-DataSharing.ipynb8.3 KB03-DataProcessing.ipynb366.7 KBREADME.md133 B04-RegressionTesting.ipynb8.1 KBdexydexy.yaml145 Bdexy.conf16 B00.py858 Beyesize.py1.4 KBimagedownloader.py611 Bsand-hopper.tex3.7 KBtesteyesize_0_basic_test.py613 Beyesize_1_noisy_test.py750 Beyesize_2_cleanplate_test.py1.1 KBeyesize_3_withorigin_test.py1.4 KBcheckipnb.py1.8 KBrun-ipython.sh54 Bwebsitegenerate-and-serve.sh870 Bpublish.sh768 Bgenerate.sh657 B

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