gonum.org/v1/gonum v0.17.0: stat.Correlation

Clean-room public code sample — generation instructions

Write a brand-new, minimal, self-contained code sample in this clean-room directory.
Do not copy, paraphrase, or reference any existing project source. Work only from this spec.

A csx.json manifest scaffold already exists. Do not recreate it from memory. Preserve its case.goal, packages and symbols; fill its empty case.contract with exact assertions and correct its environment, commands and verifierAdapter for the files you generate.

Goal: verify pkg:golang/gonum.org/v1/gonum@v0.17.0
Kind: HOW

Use EXACTLY these public packages and versions:
  - pkg:golang/gonum.org/v1/gonum@v0.17.0
Demonstrate these symbols/APIs:
  - gonum.org/v1/gonum/stat.Correlation

Rules:
  - One focused purpose; the smallest project that proves the goal.
  - Include a contract test (test/contract.*) that runs OFFLINE and exits 0 exactly when the goal behavior works.
  - Pin every dependency with a lockfile so resolution is reproducible.
  - No secrets, credentials, or tokens. No real URLs (only example.com or localhost). No absolute paths.
  - No personal names, emails, company names, or project identifiers of any kind.
  - No binaries and no generated output (node_modules, dist, target, venv, .git, .env).
  - Keep it under 200 files and 256KB packed.

{"case":{"caseId":"case:sha256:924b8f2c96a4d6d1dc39e9b541f2639f13bbbb6d90153f25a22b4fa124c7acdb","contract":["stat.Correlation calculates the unweighted Pearson correlation between two float64 slices","stat.Correlation returns -1 for perfectly negatively correlated float64 slices","stat.Correlation calculates the weighted Pearson correlation when weights are specified","stat.Correlation panics when the lengths of the two slices do not match","stat.Correlation panics when the length of weights does not match the slice length"],"goal":"verify pkg:golang/gonum.org/v1/gonum@v0.17.0","kind":"HOW","packages":["pkg:golang/gonum.org/v1/gonum@v0.17.0"],"schemaVersion":1,"symbols":["gonum.org/v1/gonum/stat.Correlation"]},"contractCommand":["go","run","./test"],"environment":{"arch":"x64","distro":"ubuntu","ecosystem":"golang","libc":"glibc","libcVersion":"2.39","os":"linux","osVersionBucket":"24","packageManager":"go","schemaVersion":1},"license":"MIT-0","packages":["pkg:golang/gonum.org/v1/gonum@v0.17.0"],"schemaVersion":1,"subject":"pkg:golang/gonum.org/v1/gonum@v0.17.0","symbols":["gonum.org/v1/gonum/stat.Correlation"],"verifierAdapter":"golang@1"}

module example.com/sample

go 1.26.6

require gonum.org/v1/gonum v0.17.0

gonum.org/v1/gonum v0.17.0 h1:VbpOemQlsSMrYmn7T2OUvQ4dqxQXU+ouZFQsZOx50z4=
gonum.org/v1/gonum v0.17.0/go.mod h1:El3tOrEuMpv2UdMrbNlKEh9vd86bmQ6vqIcDwxEOc1E=

package main

import (
	"fmt"

	"gonum.org/v1/gonum/stat"
)

func main() {
	// Sample datasets
	x := []float64{1.0, 2.0, 3.0, 4.0, 5.0}
	y := []float64{2.0, 4.0, 6.0, 8.0, 10.0}

	// Compute unweighted Pearson correlation (perfect positive correlation: 1.0)
	corr := stat.Correlation(x, y, nil)
	fmt.Printf("Unweighted Correlation: %.4f\n", corr)

	// Weighted correlation
	weights := []float64{1.0, 2.0, 3.0, 2.0, 1.0}
	weightedCorr := stat.Correlation(x, y, weights)
	fmt.Printf("Weighted Correlation: %.4f\n", weightedCorr)
}

{
  "schemaVersion": 1,
  "goal": "verify pkg:golang/gonum.org/v1/gonum@v0.17.0",
  "kind": "HOW",
  "packages": [
    "pkg:golang/gonum.org/v1/gonum@v0.17.0"
  ],
  "symbols": [
    "gonum.org/v1/gonum/stat.Correlation"
  ]
}

package main

import (
	"fmt"
	"math"
	"os"

	"gonum.org/v1/gonum/stat"
)

func main() {
	// Assertion 1: stat.Correlation calculates the unweighted Pearson correlation between two float64 slices
	x := []float64{1.0, 2.0, 3.0, 4.0, 5.0}
	y := []float64{2.0, 4.0, 6.0, 8.0, 10.0}
	rPos := stat.Correlation(x, y, nil)
	if math.Abs(rPos-1.0) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Correlation positive mismatch: got %f, want 1.0\n", rPos)
		os.Exit(1)
	}

	// Assertion 2: stat.Correlation returns -1 for perfectly negatively correlated float64 slices
	yNeg := []float64{10.0, 8.0, 6.0, 4.0, 2.0}
	rNeg := stat.Correlation(x, yNeg, nil)
	if math.Abs(rNeg-(-1.0)) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Correlation negative mismatch: got %f, want -1.0\n", rNeg)
		os.Exit(1)
	}

	// Assertion 3: stat.Correlation calculates the weighted Pearson correlation when weights are specified
	wX := []float64{1.0, 2.0, 3.0}
	wY := []float64{1.0, 3.0, 2.0}
	weights := []float64{1.0, 2.0, 1.0}
	rWeighted := stat.Correlation(wX, wY, weights)
	expectedWeighted := 1.0 / math.Sqrt(5.5)
	if math.Abs(rWeighted-expectedWeighted) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Correlation weighted mismatch: got %f, want %f\n", rWeighted, expectedWeighted)
		os.Exit(1)
	}

	// Assertion 4: stat.Correlation panics when the lengths of the two slices do not match
	mismatchPanicked := false
	func() {
		defer func() {
			if r := recover(); r != nil {
				mismatchPanicked = true
			}
		}()
		stat.Correlation([]float64{1.0, 2.0}, []float64{1.0}, nil)
	}()
	if !mismatchPanicked {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Correlation did not panic on mismatched slice lengths\n")
		os.Exit(1)
	}

	// Assertion 5: stat.Correlation panics when the length of weights does not match the slice length
	weightPanicked := false
	func() {
		defer func() {
			if r := recover(); r != nil {
				weightPanicked = true
			}
		}()
		stat.Correlation([]float64{1.0, 2.0}, []float64{1.0, 2.0}, []float64{1.0})
	}()
	if !weightPanicked {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Correlation did not panic on mismatched weights length\n")
		os.Exit(1)
	}

	fmt.Println("All gonum stat.Correlation contract assertions passed.")
}