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Cleaned up code, removing outdated methods and fixing minor issues. #41

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34 changes: 32 additions & 2 deletions FCWTAPI/CWTOutput.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,8 @@ public class CWTOutput

public CWTOutput(double[][] real, double[][] imag)
{
RealArray = FCWTAPI.ToTwoDArray(real);
ImagArray = FCWTAPI.ToTwoDArray(imag);
RealArray = ToTwoDArray(real);
ImagArray = ToTwoDArray(imag);
Columns = RealArray.GetLength(1);
Rows = RealArray.GetLength(0);
}
Expand Down Expand Up @@ -54,5 +54,35 @@ public CWTOutput(double[][] real, double[][] imag)
}
return output;
}
public static double[,] ToTwoDArray(double[][] jaggedTwoD)
{
int arrayCount = jaggedTwoD.Length;
int arrayLength = jaggedTwoD[0].Length;
double[,] twodOutput = new double[arrayCount, arrayLength];
for (int i = 0; i < arrayCount; i++)
{
if (i > 0)
{
if (jaggedTwoD[i].Length != jaggedTwoD[i - 1].Length)
{
arrayLength = jaggedTwoD[i].Length + 1;
}
}
try
{
for (int j = 0; j < arrayLength; j++)
{
twodOutput[i, j] = jaggedTwoD[i][j];
}
}
catch (IndexOutOfRangeException)
{
string rowError = String.Format("Invalid array length in row {0}", i);
throw new IndexOutOfRangeException(rowError);
}

}
return twodOutput;
}
}
}
214 changes: 1 addition & 213 deletions FCWTAPI/FCWTAPI.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -107,219 +107,7 @@ private static float ToFloat(double value)
private static float[] GenerateOutputArray(int size, int noctave, int nvoice)
{
return new float[size * noctave * nvoice * 2];
}
/// <summary>
/// Moves the 1D array to a 2D jagged array.
/// </summary>
/// <param name="array1D"></param>
/// <param name="size"></param>
/// <param name="noctave"></param>
/// <param name="nvoice"></param>
/// <returns></returns>
public static float[][] FixOutputArray(float[] array1D, int size, int noctave, int nvoice)
{
// From the original fCWT library code
int numberCols = noctave * nvoice * 2;
int numberRows = size;
// Creates the final with freq as higher dim
float[][] fixedResults = new float[numberCols][];
for(int i = 0; i < numberCols; i += 2)
{
float[] imagtemp = new float[size];
float[] realtemp = new float[size];
for (int j = 0; j < numberRows; j++)
{
if(j % 2 == 0)
{
realtemp[j] = array1D[j];
}
else
{
imagtemp[j] = array1D[j];
}
}
fixedResults[i] = realtemp;
fixedResults[i + 1] = imagtemp;
}
return fixedResults;
}

//First element corresponds to the first jagged array dimension (voices), second element corresponds to the second dim (timepoints)

/// <summary>
/// Converts jagged 2D arrays to formal 2D arrays
/// The first dimension of the resulting 2D array corresponds to the voices
/// The second dimension corresponds to the time points of the input signal
/// </summary>
/// <param name="jaggedTwoD">2D jagged array to be converted</param>
/// <returns></returns>
/// <exception cref="IndexOutOfRangeException"></exception>
public static float[,] ToTwoDArray(float[][] jaggedTwoD)
{

int arrayCount = jaggedTwoD.Length;
int arrayLength = jaggedTwoD[0].Length;
float[,] twodOutput = new float[arrayCount, arrayLength];
for (int i = 0; i < arrayCount; i++)
{
if(i > 0)
{
if (jaggedTwoD[i].Length != jaggedTwoD[i - 1].Length)
{
arrayLength = jaggedTwoD[i].Length + 1;
}
}
try
{
for (int j = 0; j < arrayLength; j++)
{
twodOutput[i, j] = jaggedTwoD[i][j];
}
}
catch(IndexOutOfRangeException)
{
string rowError = String.Format("Invalid array length in row {0}", i);
throw new IndexOutOfRangeException(rowError);
}

}
return twodOutput;
}
public static double[,] ToTwoDArray(double[][] jaggedTwoD)
{
int arrayCount = jaggedTwoD.Length;
int arrayLength = jaggedTwoD[0].Length;
double[,] twodOutput = new double[arrayCount, arrayLength];
for (int i = 0; i < arrayCount; i++)
{
if (i > 0)
{
if (jaggedTwoD[i].Length != jaggedTwoD[i - 1].Length)
{
arrayLength = jaggedTwoD[i].Length + 1;
}
}
try
{
for (int j = 0; j < arrayLength; j++)
{
twodOutput[i, j] = jaggedTwoD[i][j];
}
}
catch (IndexOutOfRangeException)
{
string rowError = String.Format("Invalid array length in row {0}", i);
throw new IndexOutOfRangeException(rowError);
}

}
return twodOutput;
}

/// <summary>
/// Used to split the imaginary and the real arrays when using a complex wavelet, i.e. the morlet.
/// </summary>
/// <param name="combinedArray"></param>
/// <param name="realArray"></param>
/// <param name="imaginaryArray"></param>
public static void SplitIntoRealAndImaginary(float[][] combinedArray, out float[][] realArray, out float[][] imaginaryArray)
{
// every other row is the opposite
int rowNumber = combinedArray.GetLength(0);
int colNumber = combinedArray[0].Length;
// row number will always be even when using a complex wavelet

realArray = new float[colNumber / 2][];
imaginaryArray = new float[colNumber / 2][];

int realIndexer = 0;
int imagIndexer = 0;
int combinedIndexer = 0;
while (combinedIndexer < colNumber)
{
int colLength = combinedArray[combinedIndexer].Length;
if (combinedIndexer % 2 == 0)
{
realArray[realIndexer] = new float[colLength];
realArray[realIndexer] = combinedArray[combinedIndexer];
realIndexer++;
}
else
{
imaginaryArray[imagIndexer] = new float[colLength];
imaginaryArray[imagIndexer] = combinedArray[combinedIndexer];
imagIndexer++;
}
combinedIndexer++;
}
}
/// <summary>
/// Calculates the phase of the continuous wavelet transform output using a morlet wavelet.
/// </summary>
/// <param name="realArray"></param><summary>The real part of the complex morlet CWT.</summary>
/// <param name="imagArray"></param><summary>The imaginary part of the complex morlet CWT. </summary>
/// <returns></returns>
/// <exception cref="ArgumentException"></exception>
public static float[][] CalculatePhase(float[][] realArray, float[][] imagArray)
{
int realRows = realArray.GetLength(0);
int imagRows = imagArray.GetLength(0);

int realCols = realArray[0].Length;
if(realRows != imagRows)
{
throw new ArgumentException("Real and imaginary arrays have unequal lengths");
}

float[][] phaseArray = new float[realRows][];

for(int i = 0; i < realRows; i++)
{
float[] temp = new float[realCols];
for(int j =0; j < realCols; j++)
{
float val = imagArray[i][j] / realArray[i][j];
double v = (Math.Atan((double)val));
temp[j] = 1F / (float)v;
}
phaseArray[i] = temp;
}
return phaseArray;
}
/// <summary>
/// Calculates the modulus of the complex morlet continuous wavelet transform.
/// </summary>
/// <param name="realArray"></param>
/// <param name="imagArray"></param>
/// <returns></returns>
/// <exception cref="ArgumentException"></exception>
public static float[][] CalculateModulus(float[][] realArray, float[][] imagArray)
{
int realRows = realArray.GetLength(0);
int imagRows = imagArray.GetLength(0);

int realCols = realArray[0].Length;
if (realRows != imagRows)
{
throw new ArgumentException("Real and imaginary arrays have unequal lengths");
}

float[][] modArray = new float[realRows][];

for (int i = 0; i < realRows; i++)
{
float[] temp = new float[realCols];
for (int j = 0; j < realCols; j++)
{
float val = realArray[i][j]*realArray[i][j] + imagArray[i][j]*imagArray[i][j];
temp[j] = (float)Math.Sqrt((double)val);
}
modArray[i] = temp;
}
return modArray;
}


}

}
}
27 changes: 0 additions & 27 deletions FCWTAPI/GaussianSmoothing.cs
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Expand Up @@ -105,33 +105,6 @@ public class GaussianSmoothing
}
return dim2Smoothing;
}
public static double[,] EllipticGaussianConvolution(double[,] inputData, double frequencyDeviation, double timeDeviation)
{
if (inputData.GetLength(0) < (frequencyDeviation * 6 + 1) || inputData.GetLength(1) < (timeDeviation * 6 + 1))
{
throw new ArgumentException("Matrix may not be smaller than the convoluting Gaussian kernel");
}
double[,] frequencyKernel = CalculateNormalized1DSampleKernel(frequencyDeviation);
double[,] timeKernel = CalculateNormalized1DSampleKernel(timeDeviation);
// Calculates the 1D kernel to be used for smoothing
double[,] frequencySmoothing = new double[inputData.GetLength(0), inputData.GetLength(1)];
double[,] timeSmoothing = new double[inputData.GetLength(0), inputData.GetLength(1)];
// x-direction smoothing
for (int i = 0; i < inputData.GetLength(0); i++)
{
// Calculates each point in the x direction
for (int j = 0; j < inputData.GetLength(1); j++)
frequencySmoothing[i, j] = ProcessPoint(inputData, i, j, frequencyKernel, 0);
}
//y-direction smoothing
for (int i = 0; i < inputData.GetLength(0); i++)
{
//Calculates each point in the y direction from the x smoothed array res 1
for (int j = 0; j < inputData.GetLength(1); j++)
timeSmoothing[i, j] = ProcessPoint(frequencySmoothing, i, j, timeKernel, 1);
}
return timeSmoothing;
}
/// <summary>
/// Performs 2D Gaussian smoothing using an elliptic Gaussian kernel
/// </summary>
Expand Down
77 changes: 0 additions & 77 deletions TestFCWTAPI/FCWTAPITests.cs
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Expand Up @@ -38,83 +38,6 @@ public static void TestConvertDoubleToFloat()
Assert.AreEqual((float)testArray[1], fArray[1]);
}
[Test]
public static void TestFixOutputArray()
{
float[] testArray = new float[]
{1F, 2F, 3F,
4F, 5F, 6F,
7F, 8F, 9F,
10F, 11F, 12F};

float[][] outputArray = FCWTAPI.FixOutputArray(testArray, 3, 1, 2);
Assert.AreEqual(4, outputArray.GetLength(0));
}


[Test]
public static void TestToTwoDArray()
{
float[][] testJagged2d = new float[][]
{
new float[] {1, 2, 3, 4, 5, 6},
new float[] {7, 8, 9, 10, 11, 12 },
new float[] {11, 12, 13, 14, 15, 16}
};
float[,] test2DArray = FCWTAPI.ToTwoDArray(testJagged2d);
Assert.AreEqual(3, test2DArray.GetLength(0));
Assert.AreEqual(6, test2DArray.GetLength(1));
Assert.AreEqual(testJagged2d[0][4], test2DArray[0, 4]);
Assert.AreEqual(testJagged2d[2][2], test2DArray[2, 2]);
float[][] badJaggedArray1 = new float[][]
{
new float[] {1, 2, 3, 4, 5, 6, 22},
new float[] {7, 8, 9, 10, 11, 12 },
new float[] {11, 12, 13, 14, 15, 16}
};
Assert.Throws<IndexOutOfRangeException>(() => FCWTAPI.ToTwoDArray(badJaggedArray1));
float[][] badJaggedArray2 = new float[][]
{
new float[] {1, 2, 3, 4, 5, 6},
new float[] {7, 8, 9, 10, 11, 12, 22 },
new float[] {11, 12, 13, 14, 15, 16}
};
Assert.Throws<IndexOutOfRangeException>(() => FCWTAPI.ToTwoDArray(badJaggedArray2));
float[][] badJaggedArray3 = new float[][]
{
new float[] {1, 2, 3, 4, 5, 6},
new float[] {7, 8, 9, 10, 11, 12 },
new float[] {11, 12, 13, 14, 15, 16, 22}
};
Assert.Throws<IndexOutOfRangeException>(() => FCWTAPI.ToTwoDArray(badJaggedArray3));
}
[Test]
public static void TestCalculatePhase()
{
float[][] testArray = new float[][]
{
new float[] {1F, 1.2F, 1.3F, 1.4F },
new float[] {1.5F, 1.6F, 1.7F, 1.8F }
};

float[][] phaseArray = FCWTAPI.CalculatePhase(testArray, testArray);

Assert.AreEqual(1.273, phaseArray[0][0], 0.001);
}
[Test]
public static void TestCalculateModulus()
{
float[][] testArray = new float[][]
{
new float[] {1F, 2F, 3F, 4F },
new float[] {5F, 6F, 7F, 8F }
};

float[][] modArray = FCWTAPI.CalculateModulus(testArray, testArray);
Console.WriteLine(string.Join("; ", modArray[0].AsEnumerable()));
Assert.AreEqual(1.41421, modArray[0][0], 0.001);

}
[Test]
public void TestAPIResults()
{
float[] input = Enumerable.Range(0, 1000).Select(i => (float)Math.Cos(0.5 * Math.PI * (double)i)).ToArray();
Expand Down
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