fa998619dc
Centralizes common math operations used across core/go-ai, core/go, and core/mining into Poindexter as the math pillar (alongside Borg=data, Enchantrix=encryption). New modules: - stats: Sum, Mean, Variance, StdDev, MinMax, IsUnderrepresented - scale: Lerp, InverseLerp, Remap, RoundToN, Clamp, MinMaxScale - epsilon: ApproxEqual, ApproxZero - score: WeightedScore, Ratio, Delta, DeltaPercent - signal: RampUp, SineWave, Oscillate, Noise (seeded RNG) 235 LOC implementation, 509 LOC tests, zero external deps, WASM-safe. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
46 lines
1.6 KiB
Markdown
46 lines
1.6 KiB
Markdown
# Poindexter Math Expansion
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**Date:** 2026-02-16
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**Status:** Approved
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## Context
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Poindexter serves as the math pillar (alongside Borg=data, Enchantrix=encryption) in the Lethean ecosystem. It currently provides KD-Tree spatial queries, 5 distance metrics, sorting utilities, and normalization helpers.
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Analysis of math operations scattered across core/go, core/go-ai, and core/mining revealed common patterns that Poindexter should centralize: descriptive statistics, scaling/interpolation, approximate equality, weighted scoring, and signal generation.
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## New Modules
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### stats.go — Descriptive statistics
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Sum, Mean, Variance, StdDev, MinMax, IsUnderrepresented.
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Consumers: ml/coverage.go, lab/handler/chart.go
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### scale.go — Normalization and interpolation
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Lerp, InverseLerp, Remap, RoundToN, Clamp, MinMaxScale.
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Consumers: lab/handler/chart.go, i18n/numbers.go
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### epsilon.go — Approximate equality
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ApproxEqual, ApproxZero.
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Consumers: ml/exact.go
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### score.go — Weighted composite scoring
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Factor type, WeightedScore, Ratio, Delta, DeltaPercent.
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Consumers: ml/heuristic.go, ml/compare.go
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### signal.go — Time-series primitives
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RampUp, SineWave, Oscillate, Noise (seeded RNG).
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Consumers: mining/simulated_miner.go
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## Constraints
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- Zero external dependencies (WASM-compilable)
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- Pure Go, stdlib only (math, math/rand)
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- Same package (`poindexter`), flat structure
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- Table-driven tests for every function
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- No changes to existing files
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## Not In Scope
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- MLX tensor ops (hardware-accelerated, stays in go-ai)
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- DNS tools migration to go-netops (separate PR)
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- gonum backend integration (future work)
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