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Published October 16, 2018 | Version 4.10.1
Software Open

sherpa/sherpa: Sherpa 4.10.1

  • 1. Smithsonian Astrophysical Observatory
  • 2. Harvard / Smithsonian Center for Astrophysics
  • 3. DIRAC Institute, UW
  • 4. MPI for Nuclear Physics
  • 5. @TIBHannover


Sherpa 4.10.1

This release fixes several bugs and introduces a few new features, notably the ability to evaluate model components on arbitrary grids and generate user-defined ARFs and RMFs. Also, as of this release Sherpa will no longer rely on any Fortran code. See the following section for details.

It is now possible to build the Sherpa documentation using Sphinx. Additionally, the Sphinx documentation is automatically built and hosted on ReadTheDocs:

Details 407 Ensure 0-length array is an error in filter_resp (fix #405)
Add an explicit check in the C++ filter_resp code to error out if the noticed channels array
is empty.
422 Improve error message with wrong xspec version
Improve the handling of XSPEC versions mismatch.
466 Fix bounding box out-of-bounds memory read
Avoid an out-of-bounds memory read when calling pad_bounding_box (when the data is not 
matching the expected conditions for this call).
469 Evaluate model on finer grid
Sherpa users can now define arbitrary grids, called evaluation spaces, on which to 
evaluate individual model components, both in 1D and 2D. This can be useful in a number
of cases, for instance when it is desirable to evaluate models on a finer grid than the one
defined by the data, or in convolution models where information outside of the data range
can be used to reduce boundary effects or to inform the evaluation inside the data space. 
Also, when plotting individual 1D model components (plot_source_component), if a specific
evaluation space was attached to the model then the plot will be of the model evaluated
over that evaluation space, not the data space. Other plotting commands should be
unaffected by this change.
470 Order for np.ones() should be a one length string not a bool
Fixed a `DeprecationWarning` in the optimization module.
471 Using overwrite rather than clobber of
`clobber` in astropy has been deprecated for a while now in favour of overwrite and thus
issues a `DeprecationWarning`. Sherpa now uses `overwrite` instead.
475 Fix unecessary runtime warning (fix #402)
A condition check in the optimization code was modified so as not to produce a warning
when the value is a NaN.
481 Remove Fortran code
Sherpa does not rely on any Fortran routines anymore, except those compiled in XSPEC.
The existing Fortran code, which was used mainly in some of the optimization routines, has 
been replaced by equivalent C++ code. This means that gfortran is no longer required for
building Sherpa, although a version of libgfortran compatible with the one used to link the
XSPEC libraries would still be needed at runtime if the XSPEC extension is
482 ARF/RMF creation functions
The `create_rmf` and `create_arf` functions now allow users to easily generate user
defined response objects.
486 ZeroDivisionError in calc_stat_info (fix #476)
Sherpa did not catch divisions by zero in the calc_stat_info command. That has been fixed.
484 Equivalent Width errors
Several optional arguments `(params=None, error=False, otherids=(), niter=1000)`, were
added to `eqwidth`. If `error = True`, then get_draws shall be run if the fit stat is one of the
following: (Cash,  CStat, WStat) otherwise a multivariate normal distribution shall be run to
generate the samples. The optional niter parameter is used to generate the number of 
samples. The optional parameter otherids is only used if get_draws is used internally when
multiple data sets were used to fit. Alternatively, the user can enter the samples via the
`params` option where the samples must be a `numpy.ndarray` of dimension `(num, npar)`.
487 PSF bin size warning
Sherpa assumes that the PSF image and the data have the same pixel size. When this is
not true Sherpa ignores the difference, which results in a larger PSF being applied. From
now on Sherpa will issue a warning when the PSF image
pixel size and the data image pixel size are different.



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