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

Reproducible Research Training at Scipy 2014

Luis Ibanez1*,Matt McCormick,Jean-Christophe Fillon,Aashish Chaudri,Ana Nelson,Steve Smith
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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