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Solar tomography has progressed rapidly in recent years thanks to thedevelopment of robust algorithms and the availability of more powerfulcomputers. It can today provide crucial insights in solving issues related tothe line-of-sight integration present in the data of solar imagers andcoronagraphs. However, there remain challenges such as the increase of theavailable volume of data, the handling of the temporal evolution of theobserved structures, and the heterogeneity of the data in multi-spacecraftstudies.  We present a generic software package that can perform fast tomographicinversions that scales linearly with the number of measurements, linearly withthe length of the reconstruction cube (and not the number of voxels) andlinearly with the number of cores and can use data from different sources andwith a variety of physical models: TomograPy(http://nbarbey.github.com/TomograPy/), an open-source software freelyavailable on the Python Package Index. For performance, TomograPy uses aparallelized-projection algorithm. It relies on the World Coordinate Systemstandard to manage various data sources. A variety of inversion algorithms areprovided to perform the tomographic-map estimation. A test suite is providedalong with the code to ensure software quality. Since it makes use of theSiddon algorithm it is restricted to rectangular parallelepiped voxels but thespherical geometry of the corona can be handled through proper use of priors.  We describe the main features of the code and show three practical examplesof multi-spacecraft tomographic inversions using STEREO/EUVI and STEREO/COR1data. Static and smoothly varying temporal evolution models are presented.

TomograPy: A Fast, Instrument-Independent, Solar Tomography Software