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caimira's Issues

Optimizing Docker File(calculator-app)

#.Combine RUN commands::Combining multiple commands using && in a single RUN instruction reduces the number of layers
in the image ,making it smaller and more efficient

Some colors are not displayed when printing report

image
Hi, i'll try to post here issues we encountered with CARA. For this issue it is just necessary to add :

body {
-webkit-print-color-adjust: exact; /chrome & webkit browsers/
color-adjust: exact; /*firefox & IE */
}

in report.css

Flaky Tests Question

Flaky tests, such as test_conditional_prob_inf_given_vl_dist, are due to their non-deterministic nature. Monte Carlo simulations, such as those used in the baseline_exposure_model fixture and test_conditional_prob_inf_given_vl_dist, fail because they're probabilistic. For modelling this is great - but for unit tests its not ๐Ÿ˜… It's a nice feeling to have a ๐ŸŸข CI.

All you'd have to do to fix this test is set the random seed, like np.random.seed(42). However, this is misleading if the goal (as I suspect) is to ensure the models accuracy within a certain tolerance.

If the goal is to measure the models accuracy, what if you removed the 3x retry and instead ran the model 10 times, gathering the results each time? Then you could do a statistical analysis against the mean/median/standard deviation/percentiles etc.

Another alternative is to change the fixed 0.002 tolerance. What if you calculated the tolerance based on the number of runs? Could an absolute tolerance of 0.002 be wishful thinking?

It could also help to log model deviations and store them with a timestamp. Then you can monitor deviations over time.

I'm happy to fix this test (and get that CI โœ…). Its a cool project. Just let me know what the expected behavior is & how I can help out.

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