#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

    * Allow values of CHANTYPE in addition to PHA and PI. (./)

    * Create model cross-reference table (under work at ["Model classification"]).

    * Add a redshift parameter to any model by prefacing the name with z.
         * Implement by passing shifted energyArray to model function.
         * This will not work for the cooling flow models which require the redshift be passed into the function.

    * Can we come up with something to help users convert v11 scripts with /b models into the equivalent v12 syntax?

    * Look at extending the projct model so it works for the case of different numbers of data sets in each annulus (see e-mail conversation with Paul Nulsen).