public static void Predict(Matrix Model, int dims, string cliString)
{
var Re = new double[dims];
for (var j = 0; j < Re.Length; j++)
{
if (j >= cliString.Length)
{
break;
}
Re[j] = char.ToUpper(cliString[j]) / (double)128;
}
Console.WriteLine();
foreach (Vector it in Model)
{
int len = it.Axis.Length;
double dot = 0.0,
y;
for (int j = 0; j < len; j++)
{
dot += Re[j] * it.Axis[j].Im;
}
y = SigF.f(dot);
Console.WriteLine($"p({it.Id}|{cliString}) ~ {y}");
}
}
private static void DrawVector(Graphics g,
RectangleF r,
Complex[] F,
Color color)
{
float linf(float val, float from, float to)
{
return(val * (to / from));
}
var PixelOffsetMode = g.PixelOffsetMode;
if (F != null)
{
g.PixelOffsetMode = System.Drawing.Drawing2D.PixelOffsetMode.HighQuality;
var dots = new List <PointF>();
var pen = new Pen(color, 2f);
for (int i = 0; i < F.Length; i++)
{
var ampl = SigF.f((F[i].Im + F[i].Re) * 0.5) - 0.5;
// var ampl = ((F[i].Re + F[i].Im) / 2f);
//var ampl = Tanh.f((F[i].Re + F[i].Im) / 2f);
if (ampl < -1)
{
ampl = -1;
}
if (ampl > +1)
{
ampl = +1;
}
if (ampl < -1 || ampl > +1)
{
throw new IndexOutOfRangeException();
}
float m = r.Height / 2f;
float y
= linf(-(float)ampl, 1f, m) + m;
float x
= linf(i, F.Length - 1, r.Width);
dots.Add(new PointF(x, y));
}
PointF[] pts = dots.ToArray();
if (pts.Length > 1)
{
g.DrawCurve(
pen,
pts);
}
foreach (PointF p in pts)
{
float m = r.Height / 2f;
g.FillEllipse(pen.Brush, p.X - 3,
p.Y - 3, 7, 7);
}
pen.Dispose();
}
g.PixelOffsetMode = PixelOffsetMode;
}
public static float BinaryLogistic(Complex[] y, float[] X)
{
Debug.Assert(X != null);
Debug.Assert(y != null);
Debug.Assert(X.Length == y.Length);
float σ = 0.0f;
for (int j = 0; j < X.Length; j++)
{
σ += y[j].Re * X[j];
}
σ = (float)SigF.f(σ);
return(σ);
}
static double binaryLogistic(double[] X, double[] grads, Complex[] Y, double label, double lr)
{
if (Y == null)
{
return(0);
}
Debug.Assert(label >= -1 && label <= 1);
Debug.Assert(lr >= 0 && lr <= 1);
int len = X.Length;
double dot = 0.0;
for (int j = 0; j < len; j++)
{
dot += Y[j].Im * X[j];
}
var y = SigF.f(dot);
double diff = lr * (label - y);
if (double.IsNaN(diff) || double.IsInfinity(diff))
{
Console.WriteLine("NaN detected...");
return(diff);
}
if (grads != null)
{
Debug.Assert(grads.Length == len);
for (int j = 0; j < len; j++)
{
grads[j] += Y[j].Im * diff;
}
}
for (int j = 0; j < len; j++)
{
Y[j].Im += X[j] * diff;
}
return(y);
}
public static void onDrawMic(Surface2D Canvas, float phase, ISource wav)
{
int hz = wav?.Hz ?? 0;
var fft = wav?.Peek();
int samples = wav != null ?
fft.Length
: 0;
double h = samples != 0
? hz / (double)samples
: 0;
var duration = hz != 0
? Math.Round((double)samples / hz, 4)
: 0;
Canvas.TopLeft = $"{samples} @ {hz}Hz = {duration}s, {h}Hz";
Canvas.TopRight = $"{phase:N4}s";
Canvas.Fill(Color.Black);
if (fft == null)
{
return;
}
var X = Complex.InverseFFT(fft);
Canvas.Line((x, width) => Color.Green, (x, width) => {
int i = Surface2D.linear(x, width, X.Length);
return(SigF.f(X[i]) + 0.07);
});
Canvas.Line((x, width) => Color.FromArgb(173, 216, 230), (x, width) => {
int i = Surface2D.linear(x, width, samples / 7);
return(+(SigF.f(2 * fft[i].Magnitude) - 0.5));
}, true);
for (int s = 0; s < samples; s++)
{
fft[s].Scale(0.5f);
}
X = Complex.InverseFFT(fft);
Canvas.Line((x, width) => Color.White, (x, width) => {
int i = Surface2D.linear(x, width, samples / 7);
return(-(SigF.f(2 * fft[i].Magnitude) - 0.5));
}, true);
Canvas.Line((x, width) => Color.OrangeRed, (x, width) => {
int i = Surface2D.linear(x, width, X.Length);
return(SigF.f(X[i]) + 0.07);
});
Canvas.Line((x, width) => Color.DarkOrange, (x, width) => {
int i = Surface2D.linear(x, width, X.Length);
return(SigF.f(X[i]) - 1.07);
});
}
