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Steps to first violation with clean runs right-censored at the budget, since per-run yield is a binary at 11 to 45 percent and separating two arms on it would need roughly 80 runs per arm. Kaplan-Meier, log-rank, Wilcoxon rank-sum with Vargha-Delaney A12, Holm within each family. A hand-rolled log-rank that is subtly wrong is a silent-wrong-number generator and would be believed, so every statistic is validated against a published worked example with the source named in the test: R survdiff on aml, Freireich 6-MP, Hollander and Wolfe 1973 for the rank sum, printed p.adjust output for Holm. Two could not be: the k>2 log-rank, guarded by calibration instead, and the tie-corrected variance, checked against an exact permutation variance. Failed and timed-out runs are excluded as missing data and counted by reason, never treated as censored observations, which would bias the result. Claude-Session: https://claude.ai/code/session_01A5KmftdEJ49A9z5mF5ESrX
155 lines
4.6 KiB
Go
155 lines
4.6 KiB
Go
package main
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import (
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"fmt"
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"io"
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"maps"
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"math"
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"slices"
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"strconv"
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"strings"
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"text/tabwriter"
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)
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func writeReport(result analysis, out io.Writer) {
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fmt.Fprintf(out, "primary outcome: %s\n\n", result.Outcome)
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writeTable(out, []string{"arm", "runs", "violated", "censored", "excluded", "missing", "median steps", "violation rate"},
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func(add func(...string)) {
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for _, summary := range result.Arms {
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add(
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summary.Arm,
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strconv.Itoa(summary.Usable),
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strconv.Itoa(summary.Violated),
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strconv.Itoa(summary.Censored),
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strconv.Itoa(summary.Excluded),
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strconv.Itoa(len(summary.MissingSeeds)),
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formatMedian(summary.MedianStepsToFirstViolation),
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formatRatio(summary.ViolationRate, 3),
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)
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}
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})
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fmt.Fprintln(out)
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fmt.Fprintln(out, "a detection is one distinct property violated in one run; run hours sum the per-run wall clock")
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writeTable(out, []string{"arm", "actions", "run hours", "detections", "defects/1k actions", "defects/hour", "distinct defects", "found in one run"},
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func(add func(...string)) {
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for _, summary := range result.Arms {
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add(
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summary.Arm,
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strconv.Itoa(summary.TotalActions),
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fmt.Sprintf("%.2f", summary.TotalRunHours),
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strconv.Itoa(summary.Detections),
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formatRatio(summary.DefectsPerThousandActions, 2),
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formatRatio(summary.DefectsPerHour, 2),
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strconv.Itoa(summary.DistinctDefects),
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formatSingletons(summary),
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)
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}
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})
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for _, summary := range result.Arms {
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if len(summary.ExcludedByReason) == 0 {
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continue
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}
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var parts []string
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for _, reason := range sortedKeys(summary.ExcludedByReason) {
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parts = append(parts, fmt.Sprintf("%s=%d", reason, summary.ExcludedByReason[reason]))
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}
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fmt.Fprintf(out, "\n%s excluded %d run(s) as missing data, not as censored observations: %s",
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summary.Arm, summary.Excluded, strings.Join(parts, ", "))
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}
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for _, summary := range result.Arms {
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if summary.EventsHeldAtBudget > 0 {
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fmt.Fprintf(out, "\n%s held %d violation(s) reported past the budget at %d steps",
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summary.Arm, summary.EventsHeldAtBudget, summary.StepBudget)
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}
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}
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if len(result.Arms) > 0 {
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fmt.Fprintln(out)
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}
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if result.LogRank != nil {
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fmt.Fprintf(out, "\nlog-rank across %d arms: chi-square %.4f on %d df, p %s\n",
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len(result.LogRank.Groups), result.LogRank.ChiSquare, result.LogRank.DegreesOfFreedom,
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formatPValue(result.LogRank.PValue))
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writeTable(out, []string{"arm", "n", "observed", "expected"}, func(add func(...string)) {
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for index, name := range result.LogRank.Groups {
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add(name,
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strconv.Itoa(result.LogRank.Sizes[index]),
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fmt.Sprintf("%.0f", result.LogRank.Observed[index]),
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fmt.Sprintf("%.2f", result.LogRank.Expected[index]))
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}
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})
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}
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if len(result.Pairwise) > 0 {
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fmt.Fprintln(out, "\npairwise wilcoxon rank-sum, censored runs held at the budget")
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fmt.Fprintln(out, "a12 above 0.5 means the first arm takes more steps to its first violation")
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writeTable(out, []string{"comparison", "n1", "n2", "u", "a12", "p", "holm p"}, func(add func(...string)) {
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for _, pair := range result.Pairwise {
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add(
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pair.First+" vs "+pair.Second,
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strconv.Itoa(pair.FirstSize),
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strconv.Itoa(pair.SecondSize),
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fmt.Sprintf("%.1f", pair.Statistic),
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fmt.Sprintf("%.3f", pair.A12),
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formatPValue(pair.PValue),
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formatPValue(pair.HolmPValue),
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)
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}
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})
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}
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for _, note := range result.Notes {
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fmt.Fprintf(out, "\nnote: %s\n", note)
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}
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}
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func sortedKeys(counts map[string]int) []string {
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return slices.Sorted(maps.Keys(counts))
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}
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func writeTable(out io.Writer, header []string, rows func(add func(...string))) {
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writer := tabwriter.NewWriter(out, 0, 0, 2, ' ', 0)
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fmt.Fprintln(writer, strings.Join(header, "\t"))
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rows(func(cells ...string) {
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fmt.Fprintln(writer, strings.Join(cells, "\t"))
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})
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writer.Flush()
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}
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// formatMedian says undefined rather than substituting a mean, because a curve
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// that never reaches one half has no median to report.
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func formatMedian(value *float64) string {
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if value == nil {
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return "undefined"
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}
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return strconv.FormatFloat(*value, 'f', -1, 64)
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}
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func formatRatio(value *float64, digits int) string {
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if value == nil {
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return "n/a"
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}
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return strconv.FormatFloat(*value, 'f', digits, 64)
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}
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func formatSingletons(summary armSummary) string {
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if summary.SingletonFraction == nil {
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return "n/a"
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}
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return fmt.Sprintf("%d/%d (%.3f)", summary.SingletonDefects, summary.DistinctDefects, *summary.SingletonFraction)
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}
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func formatPValue(value float64) string {
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switch {
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case math.IsNaN(value):
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return "n/a"
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case value < 1e-4:
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return fmt.Sprintf("%.3e", value)
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default:
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return fmt.Sprintf("%.4f", value)
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}
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}
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