Fix Hodges-Lehmann distribution ratio calculation #111
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mgrzaslewicz
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src/test/kotlin/com/atlassian/performance/tools/report/ShiftedDistributionRegressionTestTest.kt
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...ain/kotlin/com/atlassian/performance/tools/report/api/distribution/DistributionComparator.kt
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| @@ -2,7 +2,7 @@ package com.atlassian.performance.tools.report.api.judge | |||
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| import com.atlassian.performance.tools.jiraactions.api.ActionType | |||
| import com.atlassian.performance.tools.report.ActionMetricsReader | |||
| import com.atlassian.performance.tools.report.api.ShiftedDistributionRegressionTest | |||
| import com.atlassian.performance.tools.report.api.distribution.DistributionComparator | |||
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No difference detected by RelativeNonparametricPerformanceJudgeTest?
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So we don't see why the new one is better.
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How do you define better? Classification has not changed for unit tested cases and as stated in first PR comment, it's expected
src/main/kotlin/com/atlassian/performance/tools/report/api/ShiftedDistributionRegressionTest.kt
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| values[k++] = func(baseline[i], experiment[j]) | ||
| } | ||
| } | ||
| return Median().withNaNStrategy(NaNStrategy.MINIMAL).evaluate(values) |
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When used on a set of latency measurements, why would we inject fake negative infinities?
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It's needed for cases when part of the distribution is the same and other part is different. Without it small difference will be calculated as whole distribution difference and instead of NaN you will get -0.45623836126629425 in attached example
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Yes, but the workaround injects fake extreme values. Both "before" and "after" seem wrong.
PS. this case is untested, right?
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The only value of this PR is to have a relativeShift correctly calculated, it does not improve classification as I hoped. I will prepare a small PR to fix ShiftedDistributionRegressionTest and decline this one
...in/com/atlassian/performance/tools/report/api/judge/RelativeNonparametricPerformanceJudge.kt
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mgrzaslewicz
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I hoped to see classification change for added distribution. As it should be detected as an improvement, while in production we have
no impact:However previous classification was fine for default tolerance. We're just using a different production tolerance in
RegressionCheckITand improvement is below threshold.So at least we have a properly calculated Hodges-Lehmann coming with this change.