An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook
Jean-Luc Richard Stevens, Marco eElver, James A Bednar
Frontiers in Neuroinformatics · 2013
doi:10.3389/fninf.2013.00044 (opens in a new tab)
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Abstract
Lancet is a new, simulator-independent Python utility for succinctly<br/>specifying, launching, and collating results from large batches of<br/>interrelated computationally demanding program runs. This paper<br/>demonstrates how to combine Lancet with IPython Notebook to provide a<br/>flexible, lightweight, and agile workflow for fully reproducible<br/>scientific research. This informal and pragmatic approach uses<br/>IPython Notebook to capture the steps in a scientific computation as<br/>it is gradually automated and made ready for publication, without<br/>mandating the use of any separate application that can constrain<br/>scientific exploration and innovation. The resulting notebook<br/>concisely records each step involved in even very complex<br/>computational processes that led to a particular figure or numerical<br/>result, allowing the complete chain of events to be replicated<br/>automatically.<br/><br/>Lancet was originally designed to help solve problems in computational<br/>neuroscience, such as analyzing the sensitivity of a complex<br/>simulation to various parameters, or collecting the results from<br/>multiple runs with different random starting points. However, because<br/>it is never possible to know in advance what tools might be required<br/>in future tasks, Lancet has been designed to be completely general,<br/>supporting any type of program as long as it can be launched as a<br/>process and can return output in the form of files. For instance,<br/>Lancet is also heavily used by one of the authors in a separate<br/>research group for launching batches of microprocessor simulations.<br/>This general design will allow Lancet to continue supporting a given<br/>research project even as the underlying approaches and tools change.
Abstract licence: CC BY
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