Fix Hodges-Lehmann distribution ratio calculation#111
Fix Hodges-Lehmann distribution ratio calculation#111mgrzaslewicz wants to merge 2 commits intomasterfrom
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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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...ain/kotlin/com/atlassian/performance/tools/report/api/distribution/DistributionComparator.kt
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...ain/kotlin/com/atlassian/performance/tools/report/api/distribution/DistributionComparator.kt
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...ain/kotlin/com/atlassian/performance/tools/report/api/distribution/DistributionComparator.kt
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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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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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...ain/kotlin/com/atlassian/performance/tools/report/api/distribution/DistributionComparator.kt
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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.