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#Change Log

(v0.3) Feature Release (18 Mar 2016)

  • Fix bug in predict() for LombScargle methods when center_data=False
  • Fix bug in score() for LombScargle methods when center_data=False and fit_offset=False
  • Make supersmoother a soft dependency
  • New feature: gatspy.periodic.TrendedLombScargle extends LombScargle by adding a linear trend parameter d*t to the fitted model
  • Fixed download URL for RR Lyrae datasets
  • Dropped support for Python 2.6 and 3.3

(v0.2.1) bugfix release (19 Aug 2015)

  • Fix installation issues PR 11
  • Fix corner cases in rrlyrae_fast
  • Fix so that data does not download on import
  • Make astroML a soft dependency
  • ipython-style code snippets in documentation

(v0.2) Feature Release (07 June 2015)

  • Improved test coverage & refactored much of the code
  • Refactored datasets objects to be picklable for easier parallel analysis
  • New feature: gatspy.periodic.LombScargleFast implements the fast, O[N log(N)] periodogram of Press et al.
  • New feature: gatspy.periodic.RRLyraeTemplateModeler implements a template-based fitting method, using the RR Lyrae templates from Sesar (2010)
  • sphinx-based documentation build added: http://astroML.org/gatspy/

(v0.1.1) Bug Fix (28 January 2015)

  • Catch NaNs in generated rrlyrae light curves
  • correctly handle the period=0 case (previously led to assertion error)

(v0.1) Initial Release (28 January 2015)

  • Single-band: LombScargle, LombScargleAstroML, SuperSmoother
  • Multi-band: LombScargleMultiband, SuperSmootherMultiband
  • Datasets: Sesar 2010 RR Lyrae, generated RR Lyrae from templates.