cnf ran: reorganize powermanagement helpers (#160)

This moves the powermanagement stats file to be a package under ran and adds unit tests for it. Additionally, the metric collections helpers have been moved to their own package under powermanagement.

tests/cnf/ran/internal/stats/stats.go

@@ -0,0 +1,58 @@
+package stats
+
+import (
+	"fmt"
+	"math"
+	"slices"
+)
+
+// Mean computes the arithmetic mean of the input array.
+func Mean(input []float64) (float64, error) {
+	if len(input) < 1 {
+		return math.NaN(), fmt.Errorf("input array must have at least 1 element")
+	}
+
+	sum := 0.0
+	for _, x := range input {
+		sum += x
+	}
+
+	return sum / float64(len(input)), nil
+}
+
+// StdDev computes the population standard deviation of the input array.
+func StdDev(input []float64) (float64, error) {
+	if len(input) < 1 {
+		return math.NaN(), fmt.Errorf("input array must have at least 1 element")
+	}
+
+	mean, _ := Mean(input)
+
+	sum := 0.0
+	for _, x := range input {
+		sum += (x - mean) * (x - mean)
+	}
+
+	return math.Sqrt(sum / float64(len(input))), nil
+}
+
+// Median computes the median value of the input array.
+func Median(input []float64) (float64, error) {
+	if len(input) < 1 {
+		return math.NaN(), fmt.Errorf("input array must have at least 1 element")
+	}
+
+	numElements := len(input)
+
+	// sort a copy of the input array
+	inputCopy := make([]float64, numElements)
+	copy(inputCopy, input)
+
+	slices.Sort(inputCopy)
+
+	if numElements%2 == 1 {
+		return inputCopy[numElements/2], nil
+	}
+
+	return (inputCopy[numElements/2] + inputCopy[numElements/2-1]) / 2, nil
+}

tests/cnf/ran/internal/stats/stats_test.go

@@ -0,0 +1,95 @@
+package stats
+
+import (
+	"fmt"
+	"math"
+	"testing"
+
+	"github.com/stretchr/testify/assert"
+)
+
+const epsilon float64 = 1e-9
+
+func TestMean(t *testing.T) {
+	testCases := []struct {
+		input          []float64
+		expectedOutput float64
+		expectedError  error
+	}{
+		{
+			input:          []float64{1, 2, 3, 4, 5},
+			expectedOutput: 3,
+			expectedError:  nil,
+		},
+		{
+			input:          []float64{},
+			expectedOutput: math.NaN(),
+			expectedError:  fmt.Errorf("input array must have at least 1 element"),
+		},
+	}
+
+	for _, testCase := range testCases {
+		output, err := Mean(testCase.input)
+		assert.Equal(t, testCase.expectedError, err)
+
+		if testCase.expectedError == nil {
+			assert.InDelta(t, testCase.expectedOutput, output, epsilon)
+		}
+	}
+}
+
+func TestStdDev(t *testing.T) {
+	testCases := []struct {
+		input          []float64
+		expectedOutput float64
+		expectedError  error
+	}{
+		{
+			input:          []float64{1, 2, 3, 4, 5},
+			expectedOutput: math.Sqrt2,
+			expectedError:  nil,
+		},
+		{
+			input:          []float64{},
+			expectedOutput: math.NaN(),
+			expectedError:  fmt.Errorf("input array must have at least 1 element"),
+		},
+	}
+
+	for _, testCase := range testCases {
+		output, err := StdDev(testCase.input)
+		assert.Equal(t, testCase.expectedError, err)
+
+		if testCase.expectedError == nil {
+			assert.InDelta(t, testCase.expectedOutput, output, epsilon)
+		}
+	}
+}
+
+func TestMedian(t *testing.T) {
+	testCases := []struct {
+		input          []float64
+		expectedOutput float64
+		expectedError  error
+	}{
+		{
+			input:          []float64{1, 2, 3, 4, 5},
+			expectedOutput: 3,
+			expectedError:  nil,
+		},
+		{
+			input:          []float64{},
+			expectedOutput: math.NaN(),
+			expectedError:  fmt.Errorf("input array must have at least 1 element"),
+		},
+	}
+
+	for _, testCase := range testCases {
+		output, err := Median(testCase.input)
+		assert.Equal(t, testCase.expectedError, err)
+
+		if testCase.expectedError == nil {
+			assert.InDelta(t, testCase.expectedOutput, output, epsilon)
+		}
+	}
+}