An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook.
An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook.
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DOI:
10.3389/fninf.2013.00044
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发表时间:
2013
影响因子:
3.5
通讯作者:
Bednar JA
中科院分区:
文献类型:
--
作者:
Stevens JL;Elver M;Bednar JA
Lancet is a new, simulator-independent Python utility for succinctly specifying, launching, and collating results from large batches of interrelated computationally demanding program runs. This paper demonstrates how to combine Lancet with IPython Notebook to provide a flexible, lightweight, and agile workflow for fully reproducible scientific research. This informal and pragmatic approach uses IPython Notebook to capture the steps in a scientific computation as it is gradually automated and made ready for publication, without mandating the use of any separate application that can constrain scientific exploration and innovation. The resulting notebook concisely records each step involved in even very complex computational processes that led to a particular figure or numerical result, allowing the complete chain of events to be replicated automatically. Lancet was originally designed to help solve problems in computational neuroscience, such as analyzing the sensitivity of a complex simulation to various parameters, or collecting the results from multiple runs with different random starting points. However, because it is never possible to know in advance what tools might be required in future tasks, Lancet has been designed to be completely general, supporting any type of program as long as it can be launched as a process and can return output in the form of files. For instance, Lancet is also heavily used by one of the authors in a separate research group for launching batches of microprocessor simulations. This general design will allow Lancet to continue supporting a given research project even as the underlying approaches and tools change.
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影响因子:
3.5
作者:
Bednar JA
通讯作者:
Bednar JA
影响因子:
3.5
作者:
Goodman, Dan;Brette, Romain
通讯作者:
Brette, Romain
影响因子:
3.5
作者:
Antolík J;Davison AP
通讯作者:
Davison AP
影响因子:
2.1
作者:
Davison, Andrew P.
通讯作者:
Davison, Andrew P.
影响因子:
4.3
作者:
Nordlie E;Gewaltig MO;Plesser HE
通讯作者:
Plesser HE