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refactor: use welford's algorithm for one-pass avg/std dev. calculations, input logging tweaks

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Ryan Walters
2025-09-05 15:32:06 -05:00
parent 07bd127596
commit a38423f006
2 changed files with 34 additions and 25 deletions
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46
src/systems/profiling.rs
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@@ -102,28 +102,36 @@ impl SystemTimings {
.expect("SystemId not found in pre-populated map - this is a bug");
let queue_guard = queue.lock();
if queue_guard.is_empty() {
// Return zero timing for systems that haven't submitted any data
stats.insert(id, (Duration::ZERO, Duration::ZERO));
continue;
// Welford's algorithm for a single-pass mean and variance calculation.
let mut sample_count = 0.0;
let mut running_mean = 0.0;
let mut sum_squared_diff = 0.0;
for duration in queue_guard.iter() {
let duration_secs = duration.as_secs_f64();
sample_count += 1.0;
let diff_from_mean = duration_secs - running_mean;
running_mean += diff_from_mean / sample_count;
let diff_from_new_mean = duration_secs - running_mean;
sum_squared_diff += diff_from_mean * diff_from_new_mean;
}
let durations: Vec<f64> = queue_guard.iter().map(|d| d.as_secs_f64() * 1000.0).collect();
let count = durations.len() as f64;
let sum: f64 = durations.iter().sum();
let mean = sum / count;
let variance = durations.iter().map(|x| (x - mean).powi(2)).sum::<f64>() / (count - 1.0).max(1.0);
let std_dev = variance.sqrt();
stats.insert(
id,
let (average, standard_deviation) = if sample_count > 0.0 {
let variance = if sample_count > 1.0 {
sum_squared_diff / (sample_count - 1.0)
} else {
0.0
};
(
Duration::from_secs_f64(mean / 1000.0),
Duration::from_secs_f64(std_dev / 1000.0),
),
);
Duration::from_secs_f64(running_mean),
Duration::from_secs_f64(variance.sqrt()),
)
} else {
(Duration::ZERO, Duration::ZERO)
};
stats.insert(id, (average, standard_deviation));
}
stats