refactor: improve comments and variable names for clarity.

shazam/fft.go

@@ -4,20 +4,20 @@ import (
 	"math"
 )
 
-// Fft performs the Fast Fourier Transform on the input signal.
+// FFT computes the Fast Fourier Transform (FFT) of the input data,
+// converting the signal from the time domain to the frequency domain.
+// For better understanding, refer to this video: https://www.youtube.com/watch?v=spUNpyF58BY
 func FFT(input []float64) []complex128 {
-	// Convert input to complex128
 	complexArray := make([]complex128, len(input))
 	for i, v := range input {
 		complexArray[i] = complex(v, 0)
 	}
 
 	fftResult := make([]complex128, len(complexArray))
-	copy(fftResult, complexArray) // Copy input to result buffer
+	copy(fftResult, complexArray)
 	return recursiveFFT(fftResult)
 }
 
-// recursiveFFT performs the recursive FFT algorithm.
 func recursiveFFT(complexArray []complex128) []complex128 {
 	N := len(complexArray)
 	if N <= 1 {

shazam/fingerprint.go

@@ -11,7 +11,6 @@ const (
 )
 
 // Fingerprint generates fingerprints from a list of peaks and stores them in an array.
-// The fingerprints are encoded using a 32-bit integer format and stored in an array.
 // Each fingerprint consists of an address and a couple.
 // The address is a hash. The couple contains the anchor time and the song ID.
 func Fingerprint(peaks []Peak, songID uint32) map[uint32]models.Couple {

shazam/image.go

@@ -11,11 +11,9 @@ import (
 
 // ConvertSpectrogramToImage converts a spectrogram to a heat map image
 func SpectrogramToImage(spectrogram [][]complex128, outputPath string) error {
-	// Determine dimensions of the spectrogram
 	numWindows := len(spectrogram)
 	numFreqBins := len(spectrogram[0])
 
-	// Create a new grayscale image
 	img := image.NewGray(image.Rect(0, 0, numFreqBins, numWindows))
 
 	// Scale the values in the spectrogram to the range [0, 255]
@@ -38,7 +36,6 @@ func SpectrogramToImage(spectrogram [][]complex128, outputPath string) error {
 		}
 	}
 
-	// Save the image to a PNG file
 	file, err := os.Create(outputPath)
 	if err != nil {
 		return err

shazam/spectrogram.go

@@ -14,19 +14,18 @@ const (
 	hopSize     = freqBinSize / 32
 )
 
-func Spectrogram(samples []float64, sampleRate int) ([][]complex128, error) {
+func Spectrogram(sample []float64, sampleRate int) ([][]complex128, error) {
 	lpf := NewLowPassFilter(maxFreq, float64(sampleRate))
-	filteredSamples := lpf.Filter(samples)
+	filteredSample := lpf.Filter(sample)
 
-	downsampledSamples, err := Downsample(filteredSamples, sampleRate, sampleRate/dspRatio)
+	downsampledSample, err := Downsample(filteredSample, sampleRate, sampleRate/dspRatio)
 	if err != nil {
-		return nil, fmt.Errorf("couldn't downsample audio samples: %v", err)
+		return nil, fmt.Errorf("couldn't downsample audio sample: %v", err)
 	}
 
-	numOfWindows := len(downsampledSamples) / (freqBinSize - hopSize)
+	numOfWindows := len(downsampledSample) / (freqBinSize - hopSize)
 	spectrogram := make([][]complex128, numOfWindows)
 
-	// Apply Hamming window function
 	window := make([]float64, freqBinSize)
 	for i := range window {
 		window[i] = 0.54 - 0.46*math.Cos(2*math.Pi*float64(i)/(float64(freqBinSize)-1))
@@ -36,12 +35,12 @@ func Spectrogram(samples []float64, sampleRate int) ([][]complex128, error) {
 	for i := 0; i < numOfWindows; i++ {
 		start := i * hopSize
 		end := start + freqBinSize
-		if end > len(downsampledSamples) {
+		if end > len(downsampledSample) {
-			end = len(downsampledSamples)
+			end = len(downsampledSample)
 		}
 
 		bin := make([]float64, freqBinSize)
-		copy(bin, downsampledSamples[start:end])
+		copy(bin, downsampledSample[start:end])
 
 		// Apply Hamming window
 		for j := range window {