added random sampling without replacement

src/AnalysisPrograms/MahnooshSandpit.cs

@@ -34,7 +34,7 @@ public void Execute(Arguments arguments)
         {
             LoggedConsole.WriteLine("feature learning process");
 
-            var inputDir = @"D:\Mahnoosh\Liz\"; //@"M:\Postdoc\Liz\"; //@"C:\Users\kholghim\Mahnoosh\UnsupervisedFeatureLearning\"; //
+            var inputDir = @"D:\Mahnoosh\Liz\"; //@"C:\Users\kholghim\Mahnoosh\Liz\"; // @"C:\Users\kholghim\Mahnoosh\UnsupervisedFeatureLearning\"; // @"M:\Postdoc\Liz\"; //
             var resultDir = Path.Combine(inputDir, "FeatureLearning");
             var inputPath = Path.Combine(inputDir, "TrainSet"); //PatchSamplingSegments //PatchSampling
             var trainSetPath = Path.Combine(inputDir, "TrainSet");
@@ -934,23 +934,23 @@ public class Arguments : SubCommandBase
         {
             public override Task<int> Execute(CommandLineApplication app)
             {
-                //var instance = new MahnooshSandpit();
-                //instance.Execute(this);
+                var instance = new MahnooshSandpit();
+                instance.Execute(this);
                 //GenerateSpectrograms();
-                ExtractClusteringFeatures();
+                //ExtractClusteringFeatures();
 
                 return this.Ok();
             }
         }
 
         public static void ExtractClusteringFeatures()
         {
-            LoggedConsole.WriteLine("feature extraction process");
-            var inputDir = @"D:\Mahnoosh\Liz\"; //@"M:\Postdoc\Liz\"; //@"C:\Users\kholghim\Mahnoosh\UnsupervisedFeatureLearning\"; //
+            LoggedConsole.WriteLine("feature extraction process...");
+            var inputDir = @"D:\Mahnoosh\Liz\"; //@"C:\Users\kholghim\Mahnoosh\UnsupervisedFeatureLearning\"; //@"M:\Postdoc\Liz\"; //
             var resultDir = Path.Combine(inputDir, "FeatureLearning");
-            var trainSetPath = Path.Combine(inputDir, "TrainSet");
+            //var trainSetPath = Path.Combine(inputDir, "TrainSet");
             var testSetPath = Path.Combine(inputDir, "TestSet");
-            var configPath = @"D:\Mahnoosh\Liz\AnalysisConfigFiles\FeatureLearningConfig.yml"; // @"C:\Work\GitHub\audio-analysis\src\AnalysisConfigFiles\FeatureLearningConfig.yml"; //
+            var configPath = @"D:\Mahnoosh\Liz\AnalysisConfigFiles\FeatureLearningConfig.yml"; //@"C:\Work\GitHub\audio-analysis\src\AnalysisConfigFiles\FeatureLearningConfig.yml"; //  
             var centroidsPath = Path.Combine(resultDir, "ClusterCentroids0.csv");
 
             var configFile = configPath.ToFileInfo();

src/AudioAnalysisTools/DSP/FeatureLearning.cs

@@ -111,11 +111,28 @@ public static class FeatureLearning
 
                     // Second: selecting random patches from each freq band matrix and add them to the corresponding patch list
                     int count = 0;
+
+                    // file counter
+                    //int no = 0;
+
                     while (count < allSubmatrices.Count)
                     {
                         randomPatchLists[$"randomPatch{count.ToString()}"].Add(PatchSampling
                             .GetPatches(allSubmatrices.ToArray()[count], patchWidth, patchHeight, numRandomPatches,
                                 PatchSampling.SamplingMethod.Random).ToMatrix());
+                         /*
+
+                        //  take the total number of frames out of each second minute paper
+                        if (no / 2 == 0)
+                        {
+                            int rows = allSubmatrices.ToArray()[count].GetLength(0);
+                            int columns = allSubmatrices.ToArray()[count].GetLength(1);
+                            randomPatchLists[$"randomPatch{count.ToString()}"].Add(PatchSampling
+                                .GetPatches(allSubmatrices.ToArray()[count], patchWidth, patchHeight, (rows / patchHeight) * (columns / patchWidth),
+                                    PatchSampling.SamplingMethod.Sequential).ToMatrix());
+                            no++;
+                        }
+                        */
                         count++;
                     }
                 }

src/AudioAnalysisTools/DSP/PatchSampling.cs

@@ -6,6 +6,7 @@ namespace AudioAnalysisTools.DSP
 {
     using System;
     using System.Collections.Generic;
+    using System.Linq;
     using Accord.Math;
     using TowseyLibrary;
 
@@ -348,21 +349,37 @@ private static List<double[]> GetSequentialPatches(double[,] matrix, int patchWi
         /// </summary>
         private static List<double[]> GetRandomPatches(double[,] matrix, int patchWidth, int patchHeight, int numberOfPatches)
         {
+            // Note: to make the method more flexible in terms of selecting a random patch with any height and width,
+            // first a random number generator is defined for both patchHeight and patchWidth.
+            // However, the possibility of selecting duplicates especially when selecting too many random numbers from
+            // a range (e.g., 1000 out of 1440) is high with a a random generator.
+            // Since, we are mostly interested in full-band patches, i.e., patchWidth = (maxFreqBin - minFreqBin + 1) / numFreqBand,
+            // it is important to select non-duplicate patchHeights. Hence, instead of a random generator for patchHeight,
+            // a better solution is to make a sequence of numbers to be selected, shuffle them, and
+            // finally, a first n (number of required patches) numbers could be selected.
+
+            int rows = matrix.GetLength(0);
+            int columns = matrix.GetLength(1);
+
             int seed = 100;
             Random randomNumber = new Random(seed);
+
+            // not sure whether it is better to use new Guid() instead of randomNumber.Next()
+            var randomRowNumbers = Enumerable.Range(0, rows - patchHeight).OrderBy(x => randomNumber.Next()).Take(numberOfPatches).ToList();
             List<double[]> patches = new List<double[]>();
 
-            int rows = matrix.GetLength(0);
-            int columns = matrix.GetLength(1);
-            for (int i = 0; i < numberOfPatches; i++)
+            for (int i = 0; i < randomRowNumbers.Count; i++) //for (int i = 0; i < numberOfPatches; i++)
             {
                 // selecting a random number from the height of the matrix
-                int rowRandomNumber = randomNumber.Next(0, rows - patchHeight);
+                //int rowRandomNumber = randomNumber.Next(0, rows - patchHeight);
 
                 // selecting a random number from the width of the matrix
                 int columnRandomNumber = randomNumber.Next(0, columns - patchWidth);
-                double[,] submatrix = MatrixTools.Submatrix(matrix, rowRandomNumber, columnRandomNumber,
-                    rowRandomNumber + patchHeight - 1, columnRandomNumber + patchWidth - 1);
+
+                double[,] submatrix = MatrixTools.Submatrix(matrix, randomRowNumbers[i], columnRandomNumber,
+                    randomRowNumbers[i] + patchHeight - 1, columnRandomNumber + patchWidth - 1);
+
+                //double[,] submatrix = MatrixTools.Submatrix(matrix, rowRandomNumber, columnRandomNumber, rowRandomNumber + patchHeight - 1, columnRandomNumber + patchWidth - 1);
 
                 // convert a matrix to a vector by concatenating columns and
                 // store it to the array of vectors