#acl All:read

This page tracks our priorities for future enhancements to xspec. It is divided into two categories : large projects and small projects based on the estimated amount of effort required.

 * Large Projects

    * Provide XSPEC functions in Python. 
         * The best approach is to use a package such as SWIG to provide access to XSPEC objects from Python. 
         * This is likely to require some reworking of top-level objects. 
         * It is probably not a good idea to provide access to lower-level objects.

    * Use bootstrap resampling to provide goodness-of-fit measures.

    * Provide options for different units in plots.

    * Parallelization for multi-core machines.
         * OpenMP is included in gcc since 4.2 and provides simple #pragma commands.
         * This is shared memory so need to avoid race conditions.
         * Identify cpu-intensive models and try to add multi-threading.

 * Small Projects

    * Add html help tarball to release and have it install itself in spectral/help (issue #1699) (./)

    * Allow convolution components to operate directly on multiplicative models (issue #1685)
         * eg (CM)A in addition to the currently allowed C(MA)
         * One such component would be a partial covering modification to absorption models
         * A redshifting model would also be useful.

    * Add /* option in response to fit continue prompt to allow jumping out of nested fits (issue #1739) (./)