XSPEC_EMCEE
-----------

This is a program to use emcee to do MCMC analyses of X-ray spectra in
xspec.

This program has the advantage over the built-in Goodman Weare sampler
in xspec of being able to run multiple xspec processes simultaneously,
speeding up the analysis. It can also switch to parameterizing norm
parameters in log space.

** Please acknowledge use of this code by Jeremy Sanders in any
publications. **

As described on their website, emcee is an extensible, pure-Python
implementation of of Goodman & Weare's Affine Invariant Markov chain
Monte Carlo (MCMC) Ensemble sampler.

REQUIREMENTS:

Python:   2.x  (2.5 or better)
argparse: http://pypi.python.org/pypi/argparse (for Python < 2.7)
h5py:     http://www.h5py.org/
emcee:    http://danfm.ca/emcee/
xspec:    http://heasarc.nasa.gov/xanadu/xspec/

USAGE:

The program will run using an input XCM file (loading data+model). It
writes out an xspec-compatible chain file, plus a HDF5 data file
containing the chains and log likelihoods.

You need to choose the number of iterations, length of burn in period
and number of walkers. Remember that for every iteration you get the
number of walkers points in the output chain file. The chains from the
walkers are flattened in the output .chain file, with all the results
from one walker, followed by the next.

The walkers are started clustered around the parameters of the XCM
file given, using the delta value of the parameter as the width of a
normal distribution (clipped to the hard bounds of the parameter
range).  Make sure that the delta values of parameters are set to
values smaller than the uncertainties on each parameter. Note,
however, that xspec_emcee will do a fit on the model, and if the 0.1 *
sigma of the parameter (as calculated from the covariance matrix) is
bigger than this delta, then 0.1 * sigma is used instead. This is a
safety mechanism as xspec has poorly chosen deltas for some inbuilt
models. We don't always use sigma, as it can be very wrong (usually
too large).

The program can run multiple copies of xspec simultaneously. By
default it runs one copy on a local machine. You can run multiple
copies by providing a list of systems with the --systems option. The
name localhost runs on the local system without ssh. For instance
--systems="localhost localhost" runs two local copies of xspec. You
may also use the syntax --systems='localhost*8' to run N copies on a
system (here localhost).  You can run remote copies over ssh by using
a different system name. Note that you will probably need to edit
start_xspec.sh for non-remote systems to run appropriate
initialisation files.

The program prints out the number of times the xspec model has been
evaluated as it runs (and the likelihood value -statistic/2).

The program will flush the contents of the chain and likelihoods to
the HDF5 file every 10 minutes after the burn-in period. Pressing Ctrl+C
will also save the current state of the chain and exit. The chain can
be continued with the --continue-run option.

$ ./xspec_emcee.py --help
usage: xspec_emcee.py [-h] [--niters N] [--nburn N] [--nwalkers N]
                      [--systems LIST] [--output-hdf5 FILE]
                      [--output-chain FILE] [--continue-run] [--debug]
                      [--no-chdir] [--initial-parameters FILE] [--log-norm]
                      XCM

Xspec MCMC with EMCEE. Jeremy Sanders 2012-2016.

positional arguments:
  XCM                   Input XCM file

optional arguments:
  -h, --help            show this help message and exit
  --niters N            Number of iterations (default: 5000)
  --nburn N             Number of burn iterations (default: 500)
  --nwalkers N          Number of walkers (default: 50)
  --systems LIST        Space-separated list of computers to run on (default:
                        localhost)
  --output-hdf5 FILE    Output HDF5 file (default: emcee.hdf5)
  --output-chain FILE   Output text file (default: None)
  --continue-run        Continue from an existing chain (in HDF5) (default:
                        False)
  --no-fit              Disable fit after loading model (default: False)
  --debug               Create Xspec log files (default: False)
  --no-chdir            Do not chdir to XCM file directory before execution
                        (default: False)
  --initial-parameters FILE
                        Provide initial parameters (default: None)
  --log-norm            Use priors equivalent to using log norms (default:
                        False)
  --chunk-size N        Currently ignored (default: 4)
  --link EXPR           Link two parameters in model (default: None)

TODO:
 - Use local xspec to find remote xspecs automatically?