nasa / prog_models

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.
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Switch from Typing to collections.abc #547

Closed teubert closed 1 year ago

teubert commented 1 year ago

abstract base classes in typing are deprecated. Switching to collections.abc.

github-actions[bot] commented 1 year ago

Thank you for opening this PR. Each PR into dev requires a code review. For the code review, look at the following:

codecov-commenter commented 1 year ago

Codecov Report

Merging #547 (4b07ee0) into dev (4b07ee0) will not change coverage. The diff coverage is n/a.

:exclamation: Current head 4b07ee0 differs from pull request most recent head 6751097. Consider uploading reports for the commit 6751097 to get more accurate results

@@           Coverage Diff           @@
##              dev     #547   +/-   ##
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  Coverage   80.13%   80.13%           
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  Files          30       30           
  Lines        2447     2447           
=======================================
  Hits         1961     1961           
  Misses        486      486           
github-actions[bot] commented 1 year ago
Benchmarking Results [Update] From: Test Time (s)
import main 0.1473852
import thrown object 0.5461318
model initialization 0.1281162
set noise 0.7175366000000001
simulate 0.3120775
simulate with saving 0.9840703999999998
simulate with saving, dt 1.0791598000000002
simulate with printing results, dt 1.2933103999999993
Plot results 15.2788694
Metrics 0.037493200000000115
Surrogate Model Generation 1.6742640000000009
surrogate sim 1.1353486000000004
surrogate sim, dt 3.114103199999999

To:

Test Time (s)
import main 0.14500089999999988
import thrown object 0.5437871000000001
model initialization 0.1258463999999997
set noise 0.7176538999999997
simulate 0.31152729999999984
simulate with saving 0.9828861999999998
simulate with saving, dt 1.0724793999999997
simulate with printing results, dt 1.2843536000000002
Plot results 14.994731499999999
Metrics 0.03770190000000184
Surrogate Model Generation 1.676371600000003
surrogate sim 1.1476237000000005
surrogate sim, dt 3.089949400000002
github-actions[bot] commented 1 year ago
Benchmarking Results [Update] From: Test Time (s)
import main 0.1706574999999999
import thrown object 0.6278267
model initialization 0.16942379999999968
set noise 0.8250114000000002
simulate 0.41568549999999993
simulate with saving 1.3169229999999996
simulate with saving, dt 1.4779442999999999
simulate with printing results, dt 1.8833825000000006
Plot results 22.5124261
Metrics 0.0483867999999994
Surrogate Model Generation 2.434478700000003
surrogate sim 1.7410646999999955
surrogate sim, dt 4.259183800000002

To:

Test Time (s)
import main 0.17685449999999991
import thrown object 0.6677694000000001
model initialization 0.16512400000000005
set noise 0.8210291000000001
simulate 0.42101409999999984
simulate with saving 1.2915318999999998
simulate with saving, dt 1.4540967
simulate with printing results, dt 1.8617862
Plot results 22.3816616
Metrics 0.04692680000000138
Surrogate Model Generation 2.4220597999999995
surrogate sim 1.6803804000000042
surrogate sim, dt 4.302267200000003