public void GetChars_method_should_return_positive_values(
[Values("Hello", "world", "my", "dear", "friend!")] string test)
{
//arrange
var complex = new ComplexSample();
//act
var result = complex.GetChars(test);
//assert
Assert.IsTrue(result.Sum() >= 0 || result.Sum() < 0);
}
static void Main(string[] args)
{
// Define the default EduHub Directory if non-standard environment (ie. testing)
// EduHubContext.DefaultEduHubDirectory = @"E:\eduHub";
// Simple Sample
SimpleSample.Run();
// Navigation Sample
NavigationSample.Run();
// Complex Sample (May only run successfully when AKC and AR datasets are manually added to Service C)
ComplexSample.Run();
// Write-Back Sample
// WriteBackSample.Run();
}
public override void Receive(ComplexSample newSample)
{
//Add the new sample to the buffer
mBuffer[mBufferPointer] = newSample;
//Increment & Adjust the buffer pointer for circular wrap around
mBufferPointer++;
if (mBufferPointer >= mBufferSize)
{
mBufferPointer = 0;
}
//Convolution - multiply filter coefficients by the circular buffer
//samples to calculate a new filtered value
double leftAccumulator = 0;
double rightAccumulator = 0;
//Start with the center tap value
leftAccumulator += mCoefficients[mCenterCoefficient] *
mBuffer[mIndexMap[mBufferPointer][mCenterCoefficientMapIndex]].Left;
rightAccumulator += mCoefficients[mCenterCoefficient] *
mBuffer[mIndexMap[mBufferPointer][mCenterCoefficientMapIndex]].Right;
//For the remaining coefficients, add the symmetric samples, oldest and newest
//first, then multiply by the single coefficient
for (int x = 0; x < mCenterCoefficient; x++)
{
leftAccumulator += mCoefficients[x] *
(mBuffer[mIndexMap[mBufferPointer][x]].Left +
mBuffer[mIndexMap[mBufferPointer][x + mCenterCoefficient]].Left);
rightAccumulator += mCoefficients[x] *
(mBuffer[mIndexMap[mBufferPointer][x]].Right +
mBuffer[mIndexMap[mBufferPointer][x + mCenterCoefficient]].Right);
}
//We're almost finished ... apply gain, cast the doubles to floats and
//send it on it's merry way
Send(new ComplexSample((float)(leftAccumulator * mGain),
(float)(rightAccumulator * mGain)));
}
public override void Receive(ComplexSample newSample)
{
//Add the new sample to the buffer
mBuffer[mBufferPointer] = newSample;
//Increment & Adjust the buffer pointer for circular wrap around
mBufferPointer++;
if (mBufferPointer >= mBufferSize)
{
mBufferPointer = 0;
}
//Convolution - multiply filter coefficients by the circular buffer
//samples to calculate a new filtered value
double leftAccumulator = 0;
double rightAccumulator = 0;
//Start with the center tap value
leftAccumulator += mCoefficients[mCenterCoefficient] *
mBuffer[mIndexMap[mBufferPointer][mCenterCoefficientMapIndex]].Left;
rightAccumulator += mCoefficients[mCenterCoefficient] *
mBuffer[mIndexMap[mBufferPointer][mCenterCoefficientMapIndex]].Right;
//For the remaining coefficients, add the symmetric samples, oldest and newest
//first, then multiply by the single coefficient
for (int x = 0; x < mCenterCoefficient; x++)
{
leftAccumulator += mCoefficients[x] *
(mBuffer[mIndexMap[mBufferPointer][x]].Left +
mBuffer[mIndexMap[mBufferPointer][x + mCenterCoefficient]].Left);
rightAccumulator += mCoefficients[x] *
(mBuffer[mIndexMap[mBufferPointer][x]].Right +
mBuffer[mIndexMap[mBufferPointer][x + mCenterCoefficient]].Right);
}
//We're almost finished ... apply gain, cast the doubles to floats and
//send it on it's merry way
Send(new ComplexSample((float)(leftAccumulator * mGain),
(float)(rightAccumulator * mGain)));
}
