1. 16 Nov, 2016 4 commits
  2. 15 Nov, 2016 1 commit
  3. 10 Nov, 2016 1 commit
    • Gregory Ashton's avatar
      Adds initial check of the typical number of segments · d6edafae
      Gregory Ashton authored
      The motivating idea here is to give the user an idea of how well the
      MCMC is likely to perform: if the typical number of templates is of
      order millions or more then the MCMC will work like a random template
      back, jumping back and forth without finding a peak (for a long time).
  4. 08 Nov, 2016 3 commits
  5. 07 Nov, 2016 2 commits
  6. 06 Nov, 2016 1 commit
  7. 04 Nov, 2016 1 commit
  8. 03 Nov, 2016 3 commits
    • Gregory Ashton's avatar
      Adds MCMCFollowUpSearch · 88856d78
      Gregory Ashton authored
      This adds a class to perform follow ups from semi-coherent to
      fully-coherent using an MCMC search.
      - Also changes the logic of the MCMC search to check for old data only
        in the run method.
      - The nsteps argument exists for the MCMCFOllowUP, but is unused.
      - Some work on the plot_walkers to allow for overplotting. It may be
        useful to use this for the usual calls as well so that we don't have
        an initial and walkers plot?
    • Gregory Ashton's avatar
      Adds missing check for thet0indx · 17f9dffc
      Gregory Ashton authored
    • Gregory Ashton's avatar
      Minor improvements · a7671bb2
      Gregory Ashton authored
      1) Adds binary to transient search
      2) Ignores nans when generating histogram
  9. 02 Nov, 2016 3 commits
    • Gregory Ashton's avatar
      Adds a semi-coherent search class · 0624fc7e
      Gregory Ashton authored
      - Also changes the parameter vector in the normal fully coherent search
        to remove the tstart and tend. This is done by wrappin the
        run_computefstatistic_single_point in a compute_fullycoherent_det_stat
      - Removes theta0 from the saved data dict for the MCMCSearch
      - Adds example usage of the semi-coherent search
    • Gregory Ashton's avatar
      Adds basic functionality to compute the Bayes factor and an example · c323cf14
      Gregory Ashton authored
      Note - There appears to be some difference between the integration plot
      and the output value. This may be related to the Riemann sum issue in
      emcee itself. Eventually, we should have a case where we calculate the
      Bayes factor directly and compare this.
    • Gregory Ashton's avatar
      Removal of the BSGL_PREFACTOR and BSGL_FLOOR · 07cec5ce
      Gregory Ashton authored
      These where potentially confusing, deprecated values for arbitrarily
      modifying the BSGL value. This will break some current search codes
      (most notably for A14 glitches), but it is better to do so now and keep
      future code clean
  10. 01 Nov, 2016 3 commits
    • Gregory Ashton's avatar
      Several combined improvements/fixes in the main pyftsat code · e7f3abe5
      Gregory Ashton authored
      1) Fixes missing passing of binary argument ot the search tool
      (previouslly, the binary parameters where not searched over!)
      2) Adds min/maxfraction to cumulative plot and fixed start times
      3) Adds binary parameters to cumulative plot call
    • Gregory Ashton's avatar
      Adds transient MCMC search · be55d032
      Gregory Ashton authored
      Also adds ability to write transient data and a search script to show
      the results of such a transient search
    • Gregory Ashton's avatar
      Loosen test constrains · 9de0e2bc
      Gregory Ashton authored
      It seems the tests have been failing, but only falling out of range by
      ~0.11 rather than 0.1. This increases the allowed range to 0.2
  11. 31 Oct, 2016 1 commit
  12. 26 Oct, 2016 2 commits
  13. 25 Oct, 2016 2 commits
  14. 24 Oct, 2016 1 commit
  15. 23 Oct, 2016 1 commit
  16. 22 Oct, 2016 3 commits
  17. 21 Oct, 2016 6 commits
  18. 20 Oct, 2016 2 commits