add multi-mode reduction, percentiles, and log comparison to log_parser - #398
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Jacob-Chmura merged 2 commits intoMar 20, 2026
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Great contribution. We can at some point update the CI script to properly diff integration test runs using this logic.
Triggering a small integration test to check parsing
| MetricSummary with count, mean, std, min, max, and optional percentiles. | ||
| """ | ||
| n = len(values) | ||
| mean = sum(values) / n |
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| mean = sum(values) / n | |
| mean = statistics.mean(values) if n > 1 else 0.0 |
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| idx = (p / 100.0) * (n - 1) | ||
| lo = int(idx) | ||
| hi = min(lo + 1, n - 1) | ||
| pct[f'p{p:g}'] = sorted_vals[lo] + (sorted_vals[hi] - sorted_vals[lo]) * (idx - lo) |
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Mar 16, 2026
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Approving to unblock, just try to run the ruff formatter before merging.
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Summary / Description
The log parser only did mean reduction and had no way to compare runs. Added a
MetricSummarydataclass, acompute_summaryfn for full stats (count, mean, std, min, max, configurable percentiles), and areduce_metricsfn that supports mean/median/min/max/last/full strategies. Also addedcompare_logswhich diffs two log files side by side and reports absolute and relative deltas per metric.collect_raw_metricssplits out the file reading from reduction so both pieces are testable independently.parse_log_fileis kept as a thin wrapper for backward compat. CLI gets three new args:--reduction,--percentiles, and--compare.Related Issues: #
Type of Change
Test Evidence
Manual testing with existing log files. The old default behavior (mean reduction, no comparison) is unchanged.
Questions / Discussion Points
The percentile interpolation uses linear interp between adjacent sorted values, same approach as numpy percentile with
interpolation='linear'. Open to switching to a different method if there is a project preference.