This grant proposes the continued maintenance, testing, and evaluation of the Neuroimaging in Python (NiPy) project. In particular, we propose to apply best practices and proven methods for software design, construction, and implementation to extend the applicability of NiPy to the larger neuroimaging research community. By addressing the parallel achievements and increased interdependence of neuroimaging research and computing sciences, we will benefit the existing NiPy user community as well as increasing the potential for NiPy to attract significantly more developers and users. We will modernize, refactor, and further develop NiPy into an easy to modify and extend software environment with the ability to be repaired and evolved as the needs of the community of users change. Working closely with the existing NiPy developer community, we aim to improve and enhance NiPy in terms of infrastructure, architecture, interoperability, usability, and reproducibility.
