https://github.com/lmfit/lmfit-py
Revision 071b97ad88545f33cdbeede903ff156646bd8618 authored by Matthew Newville on 30 May 2017, 02:28:41 UTC, committed by Matthew Newville on 30 May 2017, 02:28:41 UTC
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Tip revision: 071b97ad88545f33cdbeede903ff156646bd8618 authored by Matthew Newville on 30 May 2017, 02:28:41 UTC
update asv conf
Tip revision: 071b97a
THANKS.txt
Many people have contributed to lmfit.  The attribution of credit in a project such as
this is very difficult to get perfect, and there are no doubt important contributions
missing or under-represented here.  Please consider this file as part of the documentation
that may have bugs that need fixing.

Some of the largest and most important contributions (approximately in order of
contribution in size to the existing code) are from:

  Matthew Newville wrote the original version and maintains the project.

  Till Stensitzki wrote the improved estimates of confidence intervals, and contributed
  many tests, bug fixes, and documentation.

  A. R. J. Nelson added differential_evolution, emcee, and greatly improved the code,
  docstrings, and overall project.

  Daniel B. Allan wrote much of the high level Model code, and many improvements to the
  testing and documentation.

  Antonino Ingargiola wrote much of the high level Model code and has provided many bug
  fixes and improvements.

  Renee Otten wrote the brute force method, and has improved the code  and documentation
  in many places.

  Michal Rawlik added plotting capabilities for Models.

  J. J. Helmus wrote the MINUT bounds for leastsq, originally in leastsqbounds.py, and
  ported to lmfit.

  E. O. Le Bigot wrote the uncertainties package, a version of which is used by lmfit.


Additional patches, bug fixes, and suggestions have come from Christoph Deil, Francois
Boulogne, Thomas Caswell, Colin Brosseau, nmearl, Gustavo Pasquevich, Clemens Prescher,
LiCode, Ben Gamari, Yoav Roam, Alexander Stark, Alexandre Beelen, and many others.

The lmfit code obviously depends on, and owes a very large debt to the code in
scipy.optimize.  Several discussions on the scipy-user and lmfit mailing lists have also
led to improvements in this code.
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