scientific computing posts

Getting a big scientific prize for open-source software


An important acknowledgement for a different view of doing science: open, collaborative, and more than a proof of concept.

A few days ago, Loïc Estève, Alexandre Gramfort, Olivier Grisel, Bertrand Thirion, and myself received the “Académie des Sciences Inria prize for transfer”, for our contributions to the scikit-learn project …

Beyond computational reproducibility, let us aim for reusability


Scientific progress calls for reproducing results. Due to limited resources, this is difficult even in computational sciences. Yet, reproducibility is only a means to an end. It is not enough by itself to enable new scientific results. Rather, new discoveries must build on reuse and modification of the state …

Nilearn 0.2: more powerful machine learning for neuroimaging

After 6 months of efforts, We just released version 0.2 of nilearn, dedicated to making machine learning in neuroimaging easier and more powerful.

This release integrates the features of the july sprint, and more.


Better documentation …

Job offer: data crunching brain functional connectivity for biomarkers

My research group is looking to fill a post-doc position on learning biomarkers from functional connectivity.

Scientific context

The challenge is to use resting-state fMRI at the level of a population to understand how intrinsic functional connectivity captures pathologies and other cognitive phenotypes. Rest fMRI is a promising tool for …

Nilearn sprint: hacking neuroimaging machine learning

A couple of weeks ago, we had in Paris the second international nilearn sprint, dedicated to making machine learning in neuroimaging easier and more powerful.

It was such a fantastic experience, as nilearn is really shaping up as a simple yet powerful tool, and there is a lot of enthusiasm …

MLOSS: machine learning open source software workshop @ ICML 2015


This year again we will have an exciting workshop on the leading-edge machine-learning open-source software. This subject is central to many, because software is how we propagate, reuse, and apply progress in machine learning.

Want to present a project? The deadline for the call for papers is Apr 28th …

Publishing scientific software matters

Christophe Pradal, Hans Peter Langtangen, and myself recently edited a version of the Journal of Computational Science on scientific software, in particular those written in Python. We wrote an editorial defending writing and publishing open source scientific software that I wish to summarize here. The full text preprint is openly …

A journal promoting high-quality research code: dream and reality

Open research computation (ORC) was an attempt to create a scientific publication promoting high-quality and open source scientific code. The project went public in falls 2010, but last month, facing the low volume of submission, the editorial board chose to reorient it as a special track of an existing journal …

Want features? Just code

Somebody just sent an email on a user’s mailing list for an open-source scientific package entitled “Feature foo: why is package bar not up to the task?”. To quote him:

Is there ANY plan for having such a module in package bar?? I think (personally) that this is a …

Book review: NumPy 1.5 Beginner’s guide

Packt publishing sent me a copy of NumPy 1.5 Beginner’s guide by Ivan Idris.

The book actually covers more than only numpy: it is a full introduction to numerical computing with Python. The table of contents is the following:

  • NumPy Quick Start
  • Beginning with NumPy Fundamentals
  • Get into …