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PTB-M4D / PyDynamic

Python library for the analysis of dynamic measurements
https://ptb-m4d.github.io/PyDynamic/
GNU Lesser General Public License v3.0
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Add option to LSIIR to return rms-value #289

Closed mgrub closed 2 years ago

mgrub commented 2 years ago

This PR will add the option to return the rms-value that is already printed in the case of verbose=True.

This addresses issue #288 .

mgrub commented 2 years ago

Note: I am currently unable to reproduce the failing pipeline on my local development machine.

codecov-commenter commented 2 years ago

Codecov Report

Merging #289 (7ca1b4c) into main (cfc10b5) will increase coverage by 0.00%. The diff coverage is 88.88%.

@@           Coverage Diff           @@
##             main     #289   +/-   ##
=======================================
  Coverage   77.33%   77.34%           
=======================================
  Files          29       29           
  Lines        2233     2242    +9     
  Branches      363      366    +3     
=======================================
+ Hits         1727     1734    +7     
+ Misses        380      379    -1     
- Partials      126      129    +3
Impacted Files Coverage Δ
src/PyDynamic/model_estimation/fit_filter.py 91.63% <88.88%> (+0.25%) :arrow_up:
src/PyDynamic/uncertainty/interpolate.py 87.65% <0.00%> (-2.47%) :arrow_down:

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BjoernLudwigPTB commented 2 years ago

Note: I am currently unable to reproduce the failing pipeline on my local development machine.

This was definitely not your fault. The tests can still and will probably always be improved, as long as we randomize the inputs and do not implement any proven error bounds but find our bounds via trial and error. Thanks for your effort and patience.