gonum.org/v1/gonum v0.17.0: stat.Mean, stat.Variance

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.Mean
  - gonum.org/v1/gonum/stat.Variance

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:sha256:50b774bcdd1f7eb7e65b8661d5585ee0c2bb6ef1222d337edf2c91e2060a5f25","contract":["stat.Mean calculates the unweighted arithmetic mean of a slice of float64 values","stat.Mean calculates the weighted arithmetic mean when weights are specified","stat.Mean panics when the length of weights does not match the length of values","stat.Variance calculates the unbiased sample variance of unweighted data","stat.Variance calculates the weighted sample variance when weights are specified","stat.Variance panics when the length of weights does not match the length of values"],"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.Mean","gonum.org/v1/gonum/stat.Variance"]},"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.Mean","gonum.org/v1/gonum/stat.Variance"],"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 dataset
	values := []float64{2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0}

	// Compute unweighted mean and variance
	mean := stat.Mean(values, nil)
	variance := stat.Variance(values, nil)

	fmt.Printf("Unweighted Mean: %.2f\n", mean)
	fmt.Printf("Unweighted Variance: %.4f\n", variance)

	// Weighted data
	weightedVals := []float64{10.0, 20.0, 30.0}
	weights := []float64{1.0, 2.0, 1.0}

	weightedMean := stat.Mean(weightedVals, weights)
	weightedVariance := stat.Variance(weightedVals, weights)

	fmt.Printf("Weighted Mean: %.2f\n", weightedMean)
	fmt.Printf("Weighted Variance: %.4f\n", weightedVariance)
}

{
  "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.Mean",
    "gonum.org/v1/gonum/stat.Variance"
  ]
}

package main

import (
	"fmt"
	"math"
	"os"

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

func main() {
	// Assertion 1: stat.Mean calculates the unweighted arithmetic mean of a slice of float64 values
	vals := []float64{2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0}
	unweightedMean := stat.Mean(vals, nil)
	expectedMean := 5.0
	if math.Abs(unweightedMean-expectedMean) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Mean unweighted mismatch: got %f, want %f\n", unweightedMean, expectedMean)
		os.Exit(1)
	}

	// Assertion 2: stat.Mean calculates the weighted arithmetic mean when weights are specified
	weightedVals := []float64{10.0, 20.0, 30.0}
	weights := []float64{1.0, 2.0, 1.0}
	weightedMean := stat.Mean(weightedVals, weights)
	expectedWeightedMean := 20.0
	if math.Abs(weightedMean-expectedWeightedMean) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Mean weighted mismatch: got %f, want %f\n", weightedMean, expectedWeightedMean)
		os.Exit(1)
	}

	// Assertion 3: stat.Mean panics when the length of weights does not match the length of values
	meanPanicked := false
	func() {
		defer func() {
			if r := recover(); r != nil {
				meanPanicked = true
			}
		}()
		stat.Mean([]float64{1.0, 2.0}, []float64{1.0})
	}()
	if !meanPanicked {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Mean did not panic on mismatched slice lengths\n")
		os.Exit(1)
	}

	// Assertion 4: stat.Variance calculates the unbiased sample variance of unweighted data
	unweightedVar := stat.Variance(vals, nil)
	expectedVar := 32.0 / 7.0
	if math.Abs(unweightedVar-expectedVar) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Variance unweighted mismatch: got %f, want %f\n", unweightedVar, expectedVar)
		os.Exit(1)
	}

	// Assertion 5: stat.Variance calculates the weighted sample variance when weights are specified
	weightedVar := stat.Variance(weightedVals, weights)
	expectedWeightedVar := 200.0 / 3.0
	if math.Abs(weightedVar-expectedWeightedVar) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Variance weighted mismatch: got %f, want %f\n", weightedVar, expectedWeightedVar)
		os.Exit(1)
	}

	// Assertion 6: stat.Variance panics when the length of weights does not match the length of values
	varPanicked := false
	func() {
		defer func() {
			if r := recover(); r != nil {
				varPanicked = true
			}
		}()
		stat.Variance([]float64{1.0, 2.0}, []float64{1.0})
	}()
	if !varPanicked {
		fmt.Fprintf(os.Stderr, "FAIL: stat.Variance did not panic on mismatched slice lengths\n")
		os.Exit(1)
	}

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