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nasa / prog_algs

The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.
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Fix UT Horizon Bug #202

Closed teubert closed 2 years ago

teubert commented 2 years ago

Fix bug in UT when horizon is set and is before the event occurs.

codecov-commenter commented 2 years ago

Codecov Report

Merging #202 (785daf7) into dev (aeb4931) will decrease coverage by 0.84%. The diff coverage is 93.50%.

@@            Coverage Diff             @@
##              dev     #202      +/-   ##
==========================================
- Coverage   90.53%   89.69%   -0.85%     
==========================================
  Files          52       52              
  Lines        3266     3281      +15     
==========================================
- Hits         2957     2943      -14     
- Misses        309      338      +29
Impacted Files Coverage Δ
src/prog_algs/predictors/unscented_transform.py 93.18% <71.42%> (-2.89%) :arrow_down:
...g_algs/state_estimators/unscented_kalman_filter.py 90.00% <71.42%> (-8.37%) :arrow_down:
src/prog_algs/state_estimators/particle_filter.py 84.26% <81.81%> (-11.03%) :arrow_down:
src/prog_algs/predictors/monte_carlo.py 91.76% <85.41%> (-2.49%) :arrow_down:
tests/test_state_estimators.py 92.01% <98.87%> (-1.94%) :arrow_down:
examples/basic_example.py 96.49% <100.00%> (+0.06%) :arrow_up:
examples/benchmarking_example.py 97.36% <100.00%> (+0.14%) :arrow_up:
examples/horizon.py 96.66% <100.00%> (+0.11%) :arrow_up:
examples/kalman_filter.py 90.00% <100.00%> (ø)
examples/measurement_eqn_example.py 85.18% <100.00%> (ø)
... and 18 more

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