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Data version control with DataLad and git-annex, a modest example
Git is my Captain’s Log. I can get back to a project that I left months, perhaps years ago, and retrace my steps to get ready to work on that project again. I can rewind and go back in time, then continue on a parallel history. Git works great for code. Except that in science not everything is code. How about data?
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Disabling multithreading for numpy, scikit-learn, etc. in conda
I was running
RidgeCV
fromscikit-learn
and realized that it was devouring all my cores. Moreover, I wrapped everything into ajoblib
parallel loop, so my poor server was hanging there, starving for more power. -
Exploring diffusion weighted imaging with dipy
I love Python and its ecosystem of scientific packages because it makes it very easy to experiment with new techniques. My undergraduate research assistant Manon and I have been recently playing with Diffusion Weighted Imaging (DWI) using
dipy
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Using Singularity to make analyses reproducible
Science should be reproducible. I like to think of an experiment as a recipe: you follow the steps described in the recipe, and you get results that are similar to the original ones (that amazing taste when your mom made it).