fix: implement fee distribution summary, IQR outliers, and analysis benchmarks#211
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Tinna23 merged 2 commits intoApr 25, 2026
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…mmons#153, StellarCommons#154 - StellarCommons#151: Add FeeDistributionSummary struct and fee_distribution_summary() to percentile.rs returning min/max/mean/median/std_dev/p10-p99 - StellarCommons#152: Add iqr_outliers() to spike_classifier.rs flagging fees outside 1.5x IQR as outlier indices - StellarCommons#153: Add benches/percentile_bench.rs benchmarking nearest_rank, linear_interpolation, and fee_distribution_summary on 1M samples - StellarCommons#154: Add benches/rolling_window_bench.rs benchmarking SMA/EMA/WMA on 100k samples; implement SMA/EMA/WMA in rolling_window.rs - Update Cargo.toml to register percentile_bench and rolling_window_bench
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@temiport25 Great news! 🎉 Based on an automated assessment of this PR, the linked Wave issue(s) no longer count against your application limits. You can now already apply to more issues while waiting for a review of this PR. Keep up the great work! 🚀 |
Tinna23
approved these changes
Apr 25, 2026
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Summary
Resolves four issues assigned to @temiport25 in the
devkit/analysispackage.Changes
#151 — Fee distribution summary (
percentile.rs)FeeDistributionSummarystruct withmin,max,mean,median,std_dev, andpercentiles(p10–p99)Percentile::fee_distribution_summary(sorted: &[u64]) -> Option<FeeDistributionSummary>#152 — IQR outlier detection (
spike_classifier.rs)SpikeClassifier::iqr_outliers(fees: &[u64]) -> Vec<usize>#153 — Percentile benchmark (
benches/percentile_bench.rs)nearest_rank,linear_interpolation, andfee_distribution_summaryon 1,000,000 samples#154 — Rolling window benchmark (
benches/rolling_window_bench.rs)RollingWindow::sma,ema,wmainrolling_window.rsCloses
Closes #151
Closes #152
Closes #153
Closes #154