Change method names to follow accepted convention

Issue #370

src/AnalysisPrograms/Audio2InputForConvCNN.cs

@@ -666,7 +666,7 @@ public static AudioToSonogramResult GenerateSpectrogramImages(FileInfo sourceRec
 
             ////LoggedConsole.WriteLine("LCN: FramesPerSecond (Prior to LCN) = {0}", sonogram.FramesPerSecond);
             ////LoggedConsole.WriteLine("LCN: Neighbourhood of {0} seconds = {1} frames", neighbourhoodSeconds, neighbourhoodFrames);
-            sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLCN(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
+            sonogram.Data = NoiseRemoval_Briggs.NoiseReductionByLcn(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
 
             // draw amplitude spectrogram unannotated
             FileInfo outputImage1 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".amplitd.bmp"));

src/AnalysisPrograms/OscillationsGeneric.cs

@@ -184,7 +184,7 @@ public static void Main(Arguments arguments)
             // LocalContrastNormalisation over frequency bins is better and faster.
             int neighbourhood = 15;
             double contrastLevel = 0.5;
-            sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLCN(sonogram.Data, neighbourhood, contrastLevel);
+            sonogram.Data = NoiseRemoval_Briggs.NoiseReductionByLcn(sonogram.Data, neighbourhood, contrastLevel);
 
             // ###############################################################
             // lowering the sensitivity threshold increases the number of hits.

src/AnalysisPrograms/SURFAnalysis.cs

@@ -385,7 +385,7 @@ public static AudioToSonogramResult GenerateSpectrogramImages(FileInfo sourceRec
 
             //LoggedConsole.WriteLine("LCN: FramesPerSecond (Prior to LCN) = {0}", sonogram.FramesPerSecond);
             //LoggedConsole.WriteLine("LCN: Neighbourhood of {0} seconds = {1} frames", neighbourhoodSeconds, neighbourhoodFrames);
-            sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLCN(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
+            sonogram.Data = NoiseRemoval_Briggs.NoiseReductionByLcn(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
 
             // draw amplitude spectrogram unannotated
             FileInfo outputImage1 = new FileInfo(Path.Combine(opDir.FullName, sourceName + ".amplitd.png"));

src/AnalysisPrograms/SpectrogramGenerator/SpectrogramGenerator.Core.cs

@@ -559,7 +559,7 @@ public static Image<Rgb24> GetLcnSpectrogram(
             //spectrogram.Data =
             //    NoiseRemoval_Briggs.NoiseReduction_byLowestPercentileSubtraction(spectrogram.Data, lowPercentile);
             spectrogram.Data =
-                NoiseRemoval_Briggs.NoiseReduction_byLCN(spectrogram.Data, neighbourhoodFrames, lcnContrastLevel);
+                NoiseRemoval_Briggs.NoiseReductionByLcn(spectrogram.Data, neighbourhoodFrames, lcnContrastLevel);
 
             //spectrogram.Data =
             //            NoiseRemoval_Briggs.NoiseReduction_byLCNDivision(spectrogram.Data, lowPercent: 20, neighbourhoodFrames, lcnContrastLevel);

src/AudioAnalysisTools/DSP/NoiseRemoval_Briggs.cs

@@ -21,7 +21,7 @@ public static class NoiseRemoval_Briggs
         /// Same method as above except take square root of the cell energy divided by the noise.
         /// Taking the square root has the effect of reducing image contrast.
         /// </summary>
-        public static double[,] NoiseReduction_byDivisionAndSqrRoot(double[,] matrix, int percentileThreshold)
+        public static double[,] NoiseReductionByDivisionAndSqrRoot(double[,] matrix, int percentileThreshold)
         {
             double[] profile = NoiseProfile.GetNoiseProfile_fromLowestPercentileFrames(matrix, percentileThreshold);
             profile = DataTools.filterMovingAverage(profile, 3);
@@ -63,7 +63,7 @@ public static class NoiseRemoval_Briggs
         /// <param name="matrix">the passed amplitude or energy spectrogram.</param>
         /// <param name="percentileThreshold">Must be an integer percent.</param>
         /// <returns>Spectrogram data matrix with noise subtracted.</returns>
-        public static double[,] NoiseReduction_byLowestPercentileSubtraction(double[,] matrix, int percentileThreshold)
+        public static double[,] NoiseReductionByLowestPercentileSubtraction(double[,] matrix, int percentileThreshold)
         {
             double[] profile = NoiseProfile.GetNoiseProfile_fromLowestPercentileFrames(matrix, percentileThreshold);
             profile = DataTools.filterMovingAverage(profile, 3);
@@ -99,7 +99,7 @@ public static class NoiseRemoval_Briggs
         /// A low contrastLevel = 0.1 give more grey image.
         /// A high contrastLevel = 1.0 give mostly white high contrast image.
         /// </summary>
-        public static double[,] NoiseReduction_byLCN(double[,] matrix, int lowPercent, int neighbourhood, double contrastLevel)
+        public static double[,] NoiseReductionByLcn(double[,] matrix, int lowPercent, int neighbourhood, double contrastLevel)
         {
             double[] noiseProfile = NoiseProfile.GetNoiseProfile_BinWiseFromLowestPercentileCells(matrix, lowPercent);
             noiseProfile = DataTools.filterMovingAverage(noiseProfile, 5);
@@ -139,7 +139,7 @@ public static class NoiseRemoval_Briggs
         /// </summary>
         /// <param name="neighbourhood">suitable vaues are odd numbers 9 - 59.</param>
         /// <param name="contrastLevel">Suitable values are 0.1 to 1.0.</param>
-        public static double[,] NoiseReduction_byLCN(double[,] matrix, int neighbourhood, double contrastLevel)
+        public static double[,] NoiseReductionByLcn(double[,] matrix, int neighbourhood, double contrastLevel)
         {
             int rowCount = matrix.GetLength(0);
             int colCount = matrix.GetLength(1);
@@ -253,7 +253,7 @@ public static double[] CalculateLocalVariance2(double[,] matrix, int colId, int
 
         public static double[,] BriggsNoiseFilterAndGetMask(double[,] matrix, int percentileThreshold, double binaryThreshold)
         {
-            double[,] m = NoiseReduction_byDivision(matrix, percentileThreshold);
+            double[,] m = NoiseReductionByDivision(matrix, percentileThreshold);
 
             // smooth and truncate
             m = ImageTools.WienerFilter(m, 7); //Briggs uses 17
@@ -280,7 +280,7 @@ public static double[] CalculateLocalVariance2(double[,] matrix, int colId, int
         /// Then divide cell energy by the profile value.
         /// This method was adapted from a paper by Briggs.
         /// </summary>
-        public static double[,] NoiseReduction_byDivision(double[,] matrix, int percentileThreshold)
+        public static double[,] NoiseReductionByDivision(double[,] matrix, int percentileThreshold)
         {
             double[] profile = NoiseProfile.GetNoiseProfile_fromLowestPercentileFrames(matrix, percentileThreshold);
             profile = DataTools.filterMovingAverage(profile, 3);
@@ -321,7 +321,7 @@ public static Image BriggsNoiseFilterAndGetSonograms(
             int nyquist,
             int herzInterval)
         {
-            double[,] m = NoiseReduction_byDivisionAndSqrRoot(matrix, percentileThreshold);
+            double[,] m = NoiseReductionByDivisionAndSqrRoot(matrix, percentileThreshold);
 
             var images = new List<Image<Rgb24>>();
 

src/AudioAnalysisTools/DSP/SNR.cs

@@ -1004,8 +1004,8 @@ public static Tuple<double[,], double[]> NoiseReduce(double[,] m, NoiseReduction
                     break;
                 case NoiseReductionType.BriggsPercentile:
                     // Briggs filters twice
-                    m = NoiseRemoval_Briggs.NoiseReduction_byDivisionAndSqrRoot(m, (int)parameter);
-                    m = NoiseRemoval_Briggs.NoiseReduction_byDivisionAndSqrRoot(m, (int)parameter);
+                    m = NoiseRemoval_Briggs.NoiseReductionByDivisionAndSqrRoot(m, (int)parameter);
+                    m = NoiseRemoval_Briggs.NoiseReductionByDivisionAndSqrRoot(m, (int)parameter);
                     break;
                 case NoiseReductionType.Binary:
                     {