code cleanup as per comments on last commit

turbidity/main.go

@@ -2,6 +2,8 @@ package main
 
 import (
 	"fmt"
+	"log"
+	"math"
 
 	"gonum.org/v1/plot"
 	"gonum.org/v1/plot/plotter"
@@ -11,62 +13,65 @@ import (
 	"gocv.io/x/gocv"
 )
 
-func main() {
+const (
-	n_images := 6
+	nImages  = 6
-	n_samples := 10
+	nSamples = 10
+)
 
-	// Load template
+func main() {
+	nImages := 6
+	nSamples := 10
+
+	// Load template and standard image.
 	template := gocv.IMRead("template.jpg", gocv.IMReadGrayScale)
 	standard := gocv.IMRead("standard.jpg", gocv.IMReadGrayScale)
 
-	images := make([][]gocv.Mat, n_images)
+	imgs := make([][]gocv.Mat, nImages)
 
-	//Load images
+	// Load test images.
-	for i := 0; i < n_images; i++ {
+	for i := range imgs {
-		images[i] = make([]gocv.Mat, n_samples)
+		imgs[i] = make([]gocv.Mat, nSamples)
-		for j := 0; j < n_samples; j++ {
+		for j := range imgs[i] {
-			images[i][j] = gocv.IMRead(fmt.Sprintf("images/t-%v/000%v.jpg", i, j), gocv.IMReadGrayScale)
+			imgs[i][j] = gocv.IMRead(fmt.Sprintf("images/t-%v/000%v.jpg", i, j), gocv.IMReadGrayScale)
 		}
 	}
 
-	// Create turbidity sensor
+	// Create turbidity sensor.
 	ts := TurbiditySensor{template: template, standard: standard, k1: 90, k2: 90, scale: 5.0, alpha: 1.0}
 
-	var final_result Results
+	var finalRes Results
-	final_result.New(n_images)
+	finalRes.New(nImages)
 
-	// Score each image by calculating the average score from camera burst
+	// Score each image by calculating the average score from camera burst.
-	for i := range images {
+	for i := range imgs {
-
-		//Evaluate camera burst
-		sample_result, err := ts.Evaluate(n_samples, images[i])
 
+		// Evaluate camera burst.
+		sample_result, err := ts.Evaluate(imgs[i])
 		if err != nil {
-			fmt.Println(err)
+			log.Fatalf("Evaluation Failed: %v", err)
 		}
 
-		// Append the average result from camera burst
+		// Add the average result from camera burst.
-		final_result.Append(Average(sample_result.saturation), Average(sample_result.contrast), float64((i+1)*10), i)
+		finalRes.Update(average(sample_result.saturation), average(sample_result.contrast), float64(i*10), i)
 	}
 
-	// Plot the final results
+	// Plot the final results.
-	err := PlotResults(final_result.turbidity, Normalize(final_result.saturation), Normalize(final_result.contrast))
+	err := plotResults(finalRes.turbidity, normalize(finalRes.saturation), normalize(finalRes.contrast))
-
-	fmt.Println(final_result.saturation)
-	fmt.Println(final_result.contrast)
-
 	if err != nil {
-		fmt.Println(err)
+		log.Fatalf("Plotting Failed: %v", err)
 	}
+
+	log.Printf("Saturation: %v", finalRes.saturation)
+	log.Printf("Contrast: %v", finalRes.contrast)
 }
 
-// PLOTTING FUNCTIONS
+// Plotting Functions.
 
-// Normalize values in a slice between 0 and 1
+// Normalize values in a slice between 0 and 1.
-func Normalize(slice []float64) []float64 {
+func normalize(slice []float64) []float64 {
 
-	max := -1e10
+	max := -math.MaxFloat64
-	min := 1e10
+	min := math.MaxFloat64
 
 	out := make([]float64, len(slice))
 
@@ -90,8 +95,8 @@ func Normalize(slice []float64) []float64 {
 	return out
 }
 
-// Return the average of a slice
+// Return the average of a slice.
-func Average(slice []float64) float64 {
+func average(slice []float64) float64 {
 
 	out := 0.0
 
@@ -102,7 +107,7 @@ func Average(slice []float64) float64 {
 	return out / float64(len(slice))
 }
 
-func PlotResults(x, saturation, contrast []float64) error {
+func plotResults(x, saturation, contrast []float64) error {
 
 	err := plotToFile(
 		"Results",
@@ -117,7 +122,7 @@ func PlotResults(x, saturation, contrast []float64) error {
 	)
 
 	if err != nil {
-		return fmt.Errorf("Could not plot results: %v", err)
+		return fmt.Errorf("Could not plot results: %w", err)
 	}
 
 	return nil
@@ -127,16 +132,13 @@ func PlotResults(x, saturation, contrast []float64) error {
 // provided draw function, and then saves to a PNG file with filename of name.
 func plotToFile(name, xTitle, yTitle string, draw func(*plot.Plot) error) error {
 	p := plot.New()
-
 	p.Title.Text = name
 	p.X.Label.Text = xTitle
 	p.Y.Label.Text = yTitle
-
 	err := draw(p)
 	if err != nil {
 		return fmt.Errorf("could not draw plot contents: %w", err)
 	}
-
 	if err := p.Save(15*vg.Centimeter, 15*vg.Centimeter, "plots/"+name+".png"); err != nil {
 		return fmt.Errorf("could not save plot: %w", err)
 	}
@@ -145,9 +147,7 @@ func plotToFile(name, xTitle, yTitle string, draw func(*plot.Plot) error) error
 
 // plotterXY provides a plotter.XYs type value based on the given x and y data.
 func plotterXY(x, y []float64) plotter.XYs {
-
 	xy := make(plotter.XYs, len(x))
-
 	for i := range x {
 		xy[i].X = x[i]
 		xy[i].Y = y[i]

turbidity/results.go

@@ -1,5 +1,6 @@
 package main
 
+// struct to hold the results of the turbidity sensor.
 type Results struct {
 	turbidity  []float64
 	saturation []float64
@@ -12,7 +13,8 @@ func (r *Results) New(n int) {
 	r.contrast = make([]float64, n)
 }
 
-func (r *Results) Append(saturation, contrast, turbidity float64, index int) {
+// Update results to add new values at specified index.
+func (r *Results) Update(saturation, contrast, turbidity float64, index int) {
 	r.saturation[index] = saturation
 	r.contrast[index] = contrast
 	r.turbidity[index] = turbidity

turbidity/turbidity.go

@@ -1,6 +1,7 @@
 package main
 
 import (
+	"errors"
 	"fmt"
 	"image"
 	"math"
@@ -8,97 +9,93 @@ import (
 	"gocv.io/x/gocv"
 )
 
-// TURBIDITY SENSOR
+// Turbidity Sensor.
 type TurbiditySensor struct {
 	template, standard gocv.Mat
 	k1, k2             int //block size
 	alpha, scale       float64
 }
 
-// Given a slice of test images of size n, return the sharpness and contrast scores
+// Given a slice of test images, return the sharpness and contrast scores.
-func (ts TurbiditySensor) Evaluate(n int, images []gocv.Mat) (Results, error) {
+func (ts TurbiditySensor) Evaluate(imgs []gocv.Mat) (Results, error) {
 
 	var result Results
-	result.New(n)
+	result.New(len(imgs))
 
-	for i := range images {
+	for i := range imgs {
-
-		// Transform image
-		marker, err := ts.Transform(images[i])
 
+		// Transform image.
+		marker, err := ts.Transform(imgs[i])
 		if err != nil {
-			return result, fmt.Errorf("Image %v: %v", i, err)
+			return result, fmt.Errorf("Image %v: %w", i, err)
 		}
 
-		// Apply sobel filter
+		// Apply sobel filter.
 		edge := ts.Sobel(marker, ts.scale)
 
-		// Evaluate
+		// Evaluate image.
 		out, err := ts.EvaluateImage(marker, edge, ts.k1, ts.k2, ts.alpha)
-
 		if err != nil {
 			return result, err
 		}
 
-		result.Append(out[0], out[1], float64((i+1)*10), i)
+		result.Update(out[0], out[1], float64(i*10), i)
 	}
 
 	return result, nil
 }
 
-// Evaluate image sharpness and contrast using blocks of size k1 by k2. Return a slice of the respective scores
+// Evaluate image sharpness and contrast using blocks of size k1 by k2. Return a slice of the respective scores.
 func (ts TurbiditySensor) EvaluateImage(img, edge gocv.Mat, k1, k2 int, alpha float64) ([]float64, error) {
 
-	// Slice to store results
+	// Slice to store results.
 	result := make([]float64, 2) // [0.0, 0.0]
 
 	if img.Rows()%k1 != 0 || img.Cols()%k2 != 0 {
-		return result, fmt.Errorf("Dimensions not compatible (%v, %v)", k1, k2)
+		return nil, fmt.Errorf("Dimensions not compatible (%v, %v)", k1, k2)
 	}
 
-	l_step := int(img.Rows() / k1)
+	lStep := int(img.Rows() / k1)
-	k_step := int(img.Cols() / k2)
+	kStep := int(img.Cols() / k2)
 
-	for l := 0; l < img.Rows(); l = l + l_step {
+	for l := 0; l < img.Rows(); l = l + lStep {
-		for k := 0; k < img.Cols(); k = k + k_step {
+		for k := 0; k < img.Cols(); k = k + kStep {
-
-			//EME
-			err := ts.EvaluateBlock(edge, l, k, l+l_step, k+k_step, result, "EME", alpha)
 
+			// Enhancement Measure Estimation (EME), provides a measure of the sharpness.
+			err := ts.EvaluateBlock(edge, l, k, l+lStep, k+kStep, result, "EME", alpha)
 			if err != nil {
-				return result, err
+				return nil, err
 			}
 
-			//AMEE
+			// AMEE, provides a measure of the contrast.
-			err = ts.EvaluateBlock(img, l, k, l+l_step, k+k_step, result, "AMEE", alpha)
+			err = ts.EvaluateBlock(img, l, k, l+lStep, k+kStep, result, "AMEE", alpha)
-
 			if err != nil {
-				return result, err
+				return nil, err
 			}
 		}
 	}
 
-	// EME
+	// EME.
-	result[0] = 2.0 / (float64(k1) * float64(k1)) * result[0]
+	result[0] = 2.0 / (float64(k1) * float64(k2)) * result[0]
 
-	// AMEE
+	// AMEE.
-	result[1] = -1.0 / (float64(k1) * float64(k1)) * result[1]
+	result[1] = -1.0 / (float64(k1) * float64(k2)) * result[1]
 
 	return result, nil
 }
 
-// Evaluate a block within and image and add to to the result slice
+// Evaluate a block within an image and add to to the result slice.
 func (ts TurbiditySensor) EvaluateBlock(img gocv.Mat, l1, k1, l2, k2 int, result []float64, operation string, alpha float64) error {
 
-	max := -1e10
+	max := -math.MaxFloat64
-	min := 1e10
+	min := math.MaxFloat64
 
 	for i := l1; i < l2; i++ {
 		for j := k1; j < k2; j++ {
 
 			value := float64(img.GetUCharAt(i, j))
 
-			// Check max/min conditions, zero values are ignored
+			// Check max/min conditions, zero values are ignored.
 			if value > max && value != 0.0 {
 				max = value
 			}
@@ -108,17 +105,13 @@ func (ts TurbiditySensor) EvaluateBlock(img gocv.Mat, l1, k1, l2, k2 int, result
 		}
 	}
 
-	// Blocks which have no information are ignored
+	// Blocks which have no information are ignored.
-	if max != -1e10 && min != 1e10 && max != min {
+	if max != -math.MaxFloat64 && min != math.MaxFloat64 && max != min {
 		if operation == "EME" {
-
 			result[0] += math.Log(max / min)
-
 		} else if operation == "AMEE" {
-
 			contrast := (max + min) / (max - min)
 			result[1] += math.Pow(alpha*(contrast), alpha) * math.Log(contrast)
-
 		} else {
 			return fmt.Errorf("Invalid operation: %v", operation)
 		}
@@ -126,54 +119,50 @@ func (ts TurbiditySensor) EvaluateBlock(img gocv.Mat, l1, k1, l2, k2 int, result
 	return nil
 }
 
-// Search image for matching template. Returns the transformed image  which best match the template
+// Search image for matching template. Returns the transformed image  which best match the template.
 func (ts TurbiditySensor) Transform(img gocv.Mat) (gocv.Mat, error) {
-
 	out := gocv.NewMat()
 	mask := gocv.NewMat()
-
 	corners_img := gocv.NewMat()
 	corners_template := gocv.NewMat()
 
-	// Find corners in image
+	// Find corners in image.
 	if !gocv.FindChessboardCorners(img, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) {
-
+		// Apply default if transformation fails.
-		// Apply default if transformation fails
 		// fmt.Println("Corner detection failed applying standard transformation")
-
 		if !gocv.FindChessboardCorners(ts.standard, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) {
-			return out, fmt.Errorf("Could not find corners in default image")
+			return out, errors.New("Could not find corners in default image")
 		}
 	}
 
-	// Find corners in template
+	// Find corners in template.
 	if !gocv.FindChessboardCorners(ts.template, image.Pt(3, 3), &corners_template, gocv.CalibCBNormalizeImage) {
-		return out, fmt.Errorf("Could not find corners in template")
+		return out, errors.New("Could not find corners in template")
 	}
 
-	// Find and apply transformation
+	// Find and apply transformation.
 	H := gocv.FindHomography(corners_img, &corners_template, gocv.HomograpyMethodRANSAC, 3.0, &mask, 2000, 0.995)
 	gocv.WarpPerspective(img, &out, H, image.Pt(ts.template.Rows(), ts.template.Cols()))
 
 	return out, nil
 }
 
-// Apply sobel filter to an image with a given scale and return the result
+// Apply sobel filter to an image with a given scale and return the result.
 func (ts TurbiditySensor) Sobel(img gocv.Mat, scale float64) gocv.Mat {
 
 	dx := gocv.NewMat()
 	dy := gocv.NewMat()
 	sobel := gocv.NewMat()
 
-	// Apply filter
+	// Apply filter.
 	gocv.Sobel(img, &dx, gocv.MatTypeCV64F, 0, 1, 3, scale, 0.0, gocv.BorderConstant)
 	gocv.Sobel(img, &dy, gocv.MatTypeCV64F, 1, 0, 3, scale, 0.0, gocv.BorderConstant)
 
-	// Convert to unsigned
+	// Convert to unsigned.
 	gocv.ConvertScaleAbs(dx, &dx, 1.0, 0.0)
 	gocv.ConvertScaleAbs(dy, &dy, 1.0, 0.0)
 
-	// Add x and y components
+	// Add x and y components.
 	gocv.AddWeighted(dx, 0.5, dy, 0.5, 0, &sobel)
 
 	return sobel