To see whether we did a good enough job in providing data and methods, and to check how the code has aged with respect to current libraries.
Low Energy Electron Microscopy (LEEM) is a somewhat specific form of electron microscopy used to study surfaces and 2D materials. In this paper we describe a set of data processing techniques applied to LEEM and adapted to the peculiarities of LEEM. This is combined with a parallelized Python implementation using Dask in separate notebooks. So if you are interested in microscopy, image analysis, clustering of experimental physics data or parallel Python, this paper should be interesting to you.
We propose a simple method to retrieve optical constants from single optical transmittance measurements, in particular in the fundamental absorption region. The construction of needed envelopes is arbitrary and will depend on the user. However, the method should still be robust and deliver similar results.
This paper shows a fun and interesting simulation result. I find it (of course) very important that our results are reproducible. In this paper, however, we did not include the exact code for these specific simulations, but the results should be reproducible using the code of our previous paper in PLOS Computational Biology (Van Oers, Rens et al. https://doi.org/10.1371/journal.pcbi.1003774). I am genuinely curious to see if there is sufficient information for the Biophys J paper or if we should have done better. Other people have already successfully built upon the 2014 (PLOS) paper using our code; see e.g., https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.012408 and https://doi.org/10.1101/701037).
We made a huge effort to ensure the paper is reproducible. But is it?
The original data took quite a while to produce for a previous paper, but for this paper, all tables and figures should be exactly reproducible by simply running the jupyter notebook.
We've tried to make it as easy as possible to reproduce. There's some fun physics on the paper and it's all done with Python!
This is one of the very few papers in biomolecular simulation for which code and data are available and which should be reproducible. But it is also three years old, so it is an interesting test case for the longevity of reproducible research. The infrastructure software is available at http://www.activepapers.org/python-edition/ (with instructions for installation and use)
I believe this represents the only example of a reproducible paper from scattering data collected at Diamond Light Source (UK) and the Institute Laue-Langevin (France)
This was my third attempt at making a paper fully reproducible. To date I it's the most reproducible that I have published. I'm interested to know what stumbling blocks exist that I'm not aware of (aside from needing software like ArcGIS to fully rerun the complete analysis).
