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Releases: ECSHackWeek/impedance.py

Release v1.7.1

10 Jul 02:12
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Bump version number

v1.7.0

10 Jul 02:04
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Full Changelog: v1.6.0...v1.7.0

Release v1.6.0

24 Jun 04:34
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Full Changelog: v1.5.0...v1.6.0

Release v1.5.0

20 Feb 20:44
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Full Changelog: v1.4.3...v1.5.0

Bugfixes 1.4.3

28 Jan 22:55
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@kevinsmia1939 fixed incorrect naming in the preprocessing docstrings 📖
@oslopanda made bode/nyquist plots more flexible by allowing customizing label/title size 📈
@oslopanda fixed a bug in how constants were parsed during fitting 🐞

New Contributors

Full Changelog: v1.4.2...v1.4.3

Bugfixes 1.4.2

28 Jan 21:53
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Fixes several small bugs:

  • issues with np.complex for numpy versions > 1.20 (#236, #220). Thanks @SaftMacki for the fix and @oslopanda and @pililac for pointing out the issues! ☄️
  • max_M could be off by one in linKK tests. Thanks @markbouman! 🧪
  • frequency and impedance inputs can now be np.array in addition to list. Thanks @edmundsj for the suggestion!

Also added publishing to PyPI via GitHub Actions (so hopefully these releases come faster and can be made by more folks) and removed support for EOL Python v3.6

Bugfix v1.4.1

25 Apr 02:49
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Fixes a bug in the Randles circuit class circuit definition 🐞

Big thanks to @lucasfdvx for the bug report ⚡ and @BGerwe for the fix 🛠️

v1.4 release

20 Oct 03:32
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  • adds the weight_by_modulus option for makinig fitting spectra easier 🏋️ @stephendkang
  • improves the documentation and uses the new GitHub citation feature 🐧 @petermattia @hkennyv
  • transitions CI to use GitHub Actions instead of TravisCI 📦 @ml-evs

As always, you can update via pip install --upgrade impedance

v1.3 updates

04 May 03:47
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Big thanks to @petermattia for contributing to this update!

  • Adds convenient method for saving (and reading) impedance data to .csv files 🖨️
  • Improves the basinhopping global optimization functionaliity 🪂
  • Standardizes the circuit element code format ☕

As always, you can update via pip install --upgrade impedance ❇️

v1.2.2

18 Mar 04:15
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Adds bounds to the global optimization fitting functions 🏖️