private void oscFreq_Click(object sender, RoutedEventArgs e)
{
Pause();
PeriodicSourceBase source;
if (sender == osc1Freq)
{
source = oscPanel.Osc1.Source;
}
else
{
source = oscPanel.Osc2.Source;
}
MainMixer.ClearSources();
MainMixer.AddSource(source);
FrequencyFilter output = FrequencyFilter.Source;
var window = new FrequencyDialog();
window.ExportClicked += Window_ExportClicked;
window.ShowDialog();
void Window_ExportClicked(object sender, FreqEventArgs e)
{
window.ExportClicked -= Window_ExportClicked;
ExportFreqCharacteristics(e, source, output);
}
}
public IActionResult SingQuestion()
{
int Id = int.Parse(this.RouteData.Values["id"].ToString());
int? userId = HttpContext.Session.GetInt32("UserId");
var user = _dbContext.Users.First(a => a.Id == userId);
PropertyInfo info = user.GetType().GetProperty($"Answer{Id}");
var waveResampler = new Resampler(null);
Sound freqencyDetector = new Sound();
List <float> result = freqencyDetector.DetectFrequency(waveResampler);
float mainFrequency = FrequencyFilter.CalculateMainFreq(result);
if (Id == 19)
{
FrequencyClassificator FreqClass = new FrequencyClassificator(330);
UserAnswers.AddAnswer(FreqClass.Validate(mainFrequency));
info.SetValue(user, FreqClass.Validate(mainFrequency));
_dbContext.SaveChanges();
return(RedirectToAction("Question", new { Id = Id + 1 }));
}
else if (Id == 20)
{
FrequencyClassificator FreqClass = new FrequencyClassificator(440);
UserAnswers.AddAnswer(FreqClass.Validate(mainFrequency));
info.SetValue(user, FreqClass.Validate(mainFrequency));
_dbContext.SaveChanges();
return(RedirectToAction("YourResult"));
}
else
{
return(null);
}
}
public MainWindow()
{
InitializeComponent();
AForge.Point p = new AForge.Point();
AForge.Imaging.ComplexFilters.FrequencyFilter f = new FrequencyFilter();
}
public static IObservable <TSource> SetMaxFrequency <TSource>(this IObservable <TSource> source, double maxFrequency)
{
var filter = new FrequencyFilter(maxFrequency);
return(ChainNext <TSource, TSource>(source, obs => o => { if (filter.CheckLap())
{
obs.OnNext(o);
}
}));
}
public void ctor_2()
{
var filter = new FrequencyFilter(25);
Observable2.Interval(TimeSpan.FromMilliseconds(20))
.Do(_ => filter.CheckLap())
.Select(_ => filter.ArrangedFrequency)
.Subscribe(Console.WriteLine);
Thread.Sleep(3000);
}
public bool ProcessRecording(byte[] audioArray, int baseFreq)
{
var waveResampler = new Resampler(audioArray);
Sound freqencyDetector = new Sound();
List <float> result = freqencyDetector.DetectFrequency(waveResampler);
float mainFrequency = FrequencyFilter.CalculateMainFreq(result);
FrequencyClassificator FreqClass = new FrequencyClassificator(baseFreq);
bool answer = FreqClass.Validate(mainFrequency);
return(answer);
}
protected void AddFilterToChannel(FrequencyFilter filter, ChannelHandle channel)
{
if (channel.isRightChannel)
{
m_filtersRight.Add(filter);
m_channelIndicesRight.Add(channel.channelIndex);
}
else
{
m_filtersLeft.Add(filter);
m_channelIndicesLeft.Add(channel.channelIndex);
}
}
public void TestOnWideSequence()
{
var seq = new List <Point>();
seq.Add(new Point(0, 0));
seq.Add(new Point(1, 1));
seq.Add(new Point(2, 2));
seq.Add(new Point(3, 3));
FrequencyFilter filter = new FrequencyFilter();
var filtered = filter.Filter(seq).ToArray();
Assert.IsTrue(filtered.Length == 4);
}
public void TestOnNarrowSequence()
{
var seq = new List <Point>();
seq.Add(new Point(0, 0));
seq.Add(new Point(0.3, 0.3));
seq.Add(new Point(0.4, 0.5));
seq.Add(new Point(2, 2));
FrequencyFilter filter = new FrequencyFilter();
var filtered = filter.Filter(seq).ToArray();
Assert.IsTrue(filtered.Length == 2);
}
public void ctor_1()
{
var filter = new FrequencyFilter(25);
var meter = new FrequencyMeter();
Observable2.Interval(TimeSpan.FromMilliseconds(20))
.Where(_ => filter.CheckLap())
.Do(_ => meter.RecordLap())
.Subscribe(Console.WriteLine);
Thread.Sleep(3000);
Assert.IsTrue(meter.Frequency > 24);
Assert.IsTrue(meter.Frequency <= 25);
}
public Synthesizer(int sampleRate, int maximumInputs = 100)
{
inputs = new SynthesizerInput[maximumInputs];
SynthesizerInput input;
for (int i = 0; i < maximumInputs; i++)
{
input = new SynthesizerInput();
inputs[i] = input;
mixer.AddSource(input.Envelope);
}
Format = new AudioFormat(sampleRate, 1, 32);
FrequencyFilter = new FrequencyFilter(mixer);
FrequencyFilter.Disable();
}
public void TestFilteringLastPoint()
{
List <Point> unfiltered = new List <Point>();
unfiltered.Add(new Point(0, 0));
unfiltered.Add(new Point(1, 0.1));
unfiltered.Add(new Point(-1, 0.2));
unfiltered.Add(new Point(0.5, 0.22));
unfiltered.Add(new Point(0.4, 0.23));
unfiltered.Add(new Point(2, 0));
FrequencyFilter filter = new FrequencyFilter();
filter.SetScreenRect(new Rect(0, 0, 2, 10));
var filtered = filter.Filter(unfiltered);
Assert.IsTrue(filtered[filtered.Count - 1] == new Point(2, 0));
}
private async void ExportFreqCharacteristics(FreqEventArgs e, PeriodicSourceBase source, FrequencyFilter output)
{
SaveFileDialog sfd = new SaveFileDialog();
sfd.Filter = "CSV File|*.csv";
var now = DateTime.Now;
sfd.FileName = $"{now.Month}-{now.Day} {now.Hour}-{now.Minute}-{now.Second}.csv";
if (sfd.ShowDialog() ?? false)
{
List <(double, double)> exportingData = new List <(double, double)>();
progressOverlay.Visibility = Visibility.Visible;
await Task.Run(() =>
{
TimeSpan currentTime = TimeSpan.Zero;
int size = (int)(source.Format.SampleRate * 1);
for (double current = e.From; e.To >= current; current += e.Step)
{
source.SetFrequency((float)current);
var sourceData = source.Next(size);
var outputData = output.Next(size);
var sourceAv = sourceData.Average(f => Math.Abs(f));
var outputAv = outputData.Average(f => Math.Abs(f));
var gain = 20 * Math.Log10(outputAv / sourceAv);
exportingData.Add((current, gain));
currentTime += TimeSpan.FromSeconds(0.1);
}
});
using (var sw = new StreamWriter(sfd.FileName))
{
foreach (var pair in exportingData)
{
sw.WriteLine($"{pair.Item1}, {pair.Item2}");
}
}
progressOverlay.Visibility = Visibility.Hidden;
}
}
public FFTWindow(string file)
{
InitializeComponent();
if (string.IsNullOrEmpty(file))
{
MessageBox.Show("Did not specify file, nerd");
this.Close();
}
else
{
try
{
Bitmap myBmp = new Bitmap(file);
if (myBmp.Width < 1000)
{
imgFFT.Height = myBmp.Height;
imgFFT.Width = myBmp.Width;
imgFFT2.Height = myBmp.Height;
imgFFT2.Width = myBmp.Width;
this.Width = 2 * myBmp.Width;
}
else
{
imgFFT.Height = myBmp.Height / 2;
imgFFT.Width = myBmp.Width / 2;
imgFFT2.Height = myBmp.Height / 2;
imgFFT2.Width = myBmp.Width / 2;
this.Width = myBmp.Width;
}
Bitmap tmp = ResizeImage(myBmp, 1024, 1024); //rozmiar do potegi 2
Bitmap grayScaleBP = ToGrayscale(tmp); // do skali szarosci oraz 8bpp
ComplexImage complexImage = ComplexImage.FromBitmap(grayScaleBP); //obraz zespolony
complexImage.ForwardFourierTransform(); //przeprowadzenie forward fourier transform
Bitmap fourierImage1 = complexImage.ToBitmap(); //obraz modulu
fourierImage1 = ResizeImage(fourierImage1, myBmp.Width, myBmp.Height);
imgFFT.Source = BitmapToImageSource(fourierImage1);
FrequencyFilter filter = new FrequencyFilter(new IntRange(20, 128)); //filtr częstotl
filter.Apply(complexImage);
complexImage.BackwardFourierTransform(); //wsteczna transformacja
Bitmap fourierImage2 = complexImage.ToBitmap(); //konwersja obrazu zesp do bitmapy
fourierImage2 = ResizeImage(fourierImage2, myBmp.Width, myBmp.Height);
imgFFT2.Source = BitmapToImageSource(fourierImage2);
grayScaleBP.Dispose();
//clone.Dispose();
myBmp.Dispose();
fourierImage1.Dispose();
fourierImage2.Dispose();
}
catch
{
MessageBox.Show("Wrong file, nerd");
this.Close();
}
}
}
// Frequency filter
private void frequencyFilterFourierItem_Click( object sender, System.EventArgs e )
{
FrequencyFilterForm form = new FrequencyFilterForm( );
form.InputRange = new IntRange( 0, width >> 1 );
form.OutputRange = new IntRange( 0, width >> 1 );
if ( form.ShowDialog( ) == DialogResult.OK )
{
backup = (ComplexImage) image.Clone( );
// create and apply filter
FrequencyFilter filter = new FrequencyFilter( form.OutputRange );
filter.Apply( image );
UpdateNewImage( );
}
}