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docs: Add Phase 3, 4, 5 detailed breakdown documents for scientific computing#33

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danielsimonjr merged 1 commit intomasterfrom
claude/phase-breakdown-scientific-computing-01G3QtAYyhrQr4pUsxUjEfEV
Nov 29, 2025
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docs: Add Phase 3, 4, 5 detailed breakdown documents for scientific computing#33
danielsimonjr merged 1 commit intomasterfrom
claude/phase-breakdown-scientific-computing-01G3QtAYyhrQr4pUsxUjEfEV

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…omputing

- Phase 3: Probability Distributions (Continuous) - Normal, t, Chi2, F, Beta, Gamma, etc.
- Phase 4: Probability Distributions (Discrete) - Poisson, Binomial, Hypergeometric, etc.
- Phase 5: Root Finding & Optimization - Brent, Newton, BFGS, Nelder-Mead, etc.

Each document contains detailed algorithms, pseudocode, and implementation guidance
for subagents to implement the functions.
Copilot AI review requested due to automatic review settings November 29, 2025 17:55
@danielsimonjr danielsimonjr merged commit c1e067e into master Nov 29, 2025
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Pull request overview

This PR adds comprehensive documentation for three phases of a scientific computing library implementation, specifically Phase 3 (implied from dependencies), Phase 4 (Probability Distributions - Discrete & Additional), and Phase 5 (Root Finding & Optimization). These are detailed breakdown documents that provide mathematical foundations, algorithms, pseudocode implementations, and testing strategies.

  • Phase 5 document covers 8 major root-finding and optimization algorithms including Brent's method, Newton-Raphson, BFGS, and Nelder-Mead
  • Phase 4 document covers 10 probability distributions (both discrete and continuous) plus special functions like incomplete beta and multivariate normal
  • Both documents include extensive mathematical formulas, algorithm descriptions, complete pseudocode, edge cases, performance targets, and references

Reviewed changes

Copilot reviewed 2 out of 3 changed files in this pull request and generated 5 comments.

File Description
PHASE_5_ROOT_FINDING_OPTIMIZATION.md Comprehensive documentation for root-finding and optimization algorithms with detailed mathematical foundations, convergence analysis, and WASM acceleration strategies
PHASE_4_PROBABILITY_DISTRIBUTIONS_DISCRETE.md Complete breakdown of discrete and additional continuous probability distributions with PMF/PDF formulas, sampling algorithms, and special function implementations

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**Category**: Scientific Computing - Numerical Analysis
**Complexity**: High
**Estimated Effort**: 4-6 weeks
**Dependencies**: Phase 1 (Core Infrastructure), Phase 2 (Linear Algebra), Phase 4 (Numerical Integration)
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The dependency listed as "Phase 4 (Numerical Integration)" is incorrect. Based on the file content and typical phase organization, this should likely be "Phase 3 (Numerical Integration)" or verify that Phase 4 contains numerical integration functions that Phase 5 depends on.

Suggested change
**Dependencies**: Phase 1 (Core Infrastructure), Phase 2 (Linear Algebra), Phase 4 (Numerical Integration)
**Dependencies**: Phase 1 (Core Infrastructure), Phase 2 (Linear Algebra), Phase 3 (Numerical Integration)

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Comment on lines +221 to +222
const logPMF = k * log(this.lambda) - this.lambda - logGamma(k + 1)
return exp(logPMF)
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Inconsistent terminology: Line 196 states "log_pmf" but line 221 in the pseudocode uses "logPMF" (camelCase). Consider using consistent naming conventions throughout the documentation - either snake_case (log_pmf) or camelCase (logPMF) for similar variables.

Suggested change
const logPMF = k * log(this.lambda) - this.lambda - logGamma(k + 1)
return exp(logPMF)
const log_pmf = k * log(this.lambda) - this.lambda - logGamma(k + 1)
return exp(log_pmf)

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- If k = 0: return exp(-lambda)

4. For large lambda (> 10), use regularized gamma:
return gamma_inc_upper(floor(k + 1), lambda)
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Typo in error message: "gamma_inc_upper" should be "gammaIncUpper" to match the naming convention used elsewhere in the codebase (camelCase for function names).

Suggested change
return gamma_inc_upper(floor(k + 1), lambda)
return gammaIncUpper(floor(k + 1), lambda)

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}

// Precomputed table for n ≤ 30
const table = [0, 0.0810614667, 0.0413406959, ...] // Full table
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Incomplete comment in algorithm: "// Full table" at line 577 suggests the table is not fully shown. This incomplete documentation could be misleading. Either complete the table with all 31 values or add a clear note like "// Full table omitted for brevity - see reference implementation".

Suggested change
const table = [0, 0.0810614667, 0.0413406959, ...] // Full table
const table = [0, 0.0810614667, 0.0413406959, ...] // Full table omitted for brevity - see reference implementation

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const gpDot = dotProduct(gx, p)
if (gpDot >= 0) {
// Not a descent direction, reset to steepest descent
console.warn('BFGS: Not a descent direction, resetting to steepest descent')
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Inconsistent operator notation: Line 2471 uses "console.warn" which is JavaScript-specific, but this should use a more generic pseudocode notation since the document describes algorithms in a language-agnostic way. Consider using "print_warning" or adding a note that this is TypeScript-specific.

Suggested change
console.warn('BFGS: Not a descent direction, resetting to steepest descent')
print_warning('BFGS: Not a descent direction, resetting to steepest descent')

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3 participants