private static DiscreteDistribution Bivariate(BivariateContinuousDistribution distribution, DistributionsOperation operation)
{
if (operation == DistributionsOperation.PowerInv)
{
distribution = distribution.Rotate();
}
int samples = distribution.Samples;
double[] range = CommonRandomMath.GetRange(distribution.SupportMinLeft, distribution.SupportMaxLeft, distribution.SupportMinRight, distribution.SupportMaxRight, operation);
double[] rightAxis = CommonRandomMath.GenerateXAxis(distribution.SupportMinRight, distribution.SupportMaxRight, samples, out double rightStep);
double[] xAxis = CommonRandomMath.GenerateXAxis(range[0], range[1], samples, out double step);
double[] result = new double[samples];
switch (operation)
{
case DistributionsOperation.Add:
{
Parallel.For(0, xAxis.Length, i =>
{
double x = xAxis[i];
double sum = 0;
// Trap rule is useless because both normal and t-distributions are smoooth.
for (int j = 1; j < samples; j++)
{
double m = rightAxis[j];
sum += distribution.ProbabilityDensityFunction(x - m, m);
}
result[i] = sum * rightStep;
});
break;
}
case DistributionsOperation.Sub:
{
Parallel.For(0, xAxis.Length, i =>
{
double x = xAxis[i];
double sum = 0;
for (int j = 1; j < samples; j++)
{
double m = rightAxis[j];
sum += distribution.ProbabilityDensityFunction(x + m, m);
}
result[i] = sum * rightStep;
});
break;
}
case DistributionsOperation.Muliply:
{
Parallel.For(0, xAxis.Length, i =>
{
double x = xAxis[i];
double sum = 0;
for (int j = 1; j < samples; j++)
{
double m = rightAxis[j];
if (m != 0)
{
sum += distribution.ProbabilityDensityFunction(x / m, m) / Math.Abs(m);
}
}
result[i] = sum * rightStep;
});
break;
}
case DistributionsOperation.Divide:
{
Parallel.For(0, xAxis.Length, i =>
{
double x = xAxis[i];
double sum = 0;
for (int j = 1; j < samples; j++)
{
double m = rightAxis[j];
if (m != 0)
{
sum += distribution.ProbabilityDensityFunction(x * m, m) * Math.Abs(m);
}
}
result[i] = sum * rightStep;
});
break;
}
case DistributionsOperation.PowerInv:
{
Parallel.For(0, xAxis.Length, i =>
{
double m = 0;
double sum = 0;
double x = xAxis[i];
double d = 0;
double k = 0;
for (int j = 1; j < samples; j++)
{
m = rightAxis[j];
d = Math.Log(x, m);
k = Math.Abs(Math.Log(m) * x);
sum += distribution.ProbabilityDensityFunction(d, m) / k;
}
result[i] = sum * rightStep;
});
break;
}
case DistributionsOperation.Log:
{
Parallel.For(0, xAxis.Length, i =>
{
double m = 0;
double sum = 0;
double x = xAxis[i];
double d = 0;
double k = 0;
for (int j = 1; j < samples; j++)
{
m = rightAxis[j];
d = Math.Pow(m, x);
k = Math.Abs(Math.Log(m) * d);
sum += distribution.ProbabilityDensityFunction(d, m) * k;
}
result[i] = sum * rightStep;
});
break;
}
default:
{
throw new DistributionsInvalidOperationException();
}
}
return(new DiscreteDistribution(xAxis, result));
}
private static DiscreteDistribution DiscreteDistributionAndValue(DiscreteDistribution dpdf, double value, DistributionsOperation action)
{
int length = dpdf.InnerSamples;
double[] leftX = dpdf.XCoordinatesInternal;
double[] leftY = dpdf.YCoordinatesInternal;
double[] yCoordinates = new double[length];
double[] xCoordinates = new double[length];
switch (action)
{
case DistributionsOperation.Add:
{
for (int i = 0; i < length; i++)
{
yCoordinates[i] = leftY[i];
xCoordinates[i] = leftX[i] + value;
}
break;
}
case DistributionsOperation.Sub:
{
for (int i = 0; i < length; i++)
{
yCoordinates[i] = leftY[i];
xCoordinates[i] = leftX[i] - value;
}
break;
}
case DistributionsOperation.SubInv:
{
for (int i = 0; i < length; i++)
{
yCoordinates[length - i - 1] = leftY[i];
xCoordinates[length - i - 1] = value - leftX[i];
}
break;
}
case DistributionsOperation.Muliply:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.MultiplyRandomByZero);
}
if (value < 0)
{
for (int i = 0; i < length; i++)
{
yCoordinates[length - i - 1] = leftY[i] / Math.Abs(value);
xCoordinates[length - i - 1] = leftX[i] * value;
}
}
else
{
for (int i = 0; i < length; i++)
{
yCoordinates[i] = leftY[i] / Math.Abs(value);
xCoordinates[i] = leftX[i] * value;
}
}
break;
}
case DistributionsOperation.Divide:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.DivisionByZero);
}
if (value < 0)
{
for (int i = 0; i < length; i++)
{
yCoordinates[length - i - 1] = leftY[i] * Math.Abs(value);
xCoordinates[length - i - 1] = leftX[i] / value;
}
}
else
{
for (int i = 0; i < length; i++)
{
yCoordinates[i] = leftY[i] * Math.Abs(value);
xCoordinates[i] = leftX[i] / value;
}
}
break;
}
default:
{
throw new NotImplementedException();
}
}
return(new DiscreteDistribution(xCoordinates, yCoordinates));
}
private static DiscreteDistribution[] Swap(DiscreteDistribution dpdfLeft, DiscreteDistribution dpdfRight, DistributionsOperation action, out DistributionsOperation newAction)
{
double stepX = dpdfLeft.Step;
double stepY = dpdfRight.Step;
switch (action)
{
case DistributionsOperation.Add:
{
newAction = action;
if (stepX < stepY)
{
return(new DiscreteDistribution[] { dpdfRight, dpdfLeft });
}
else
{
return(new DiscreteDistribution[] { dpdfLeft, dpdfRight });
}
}
case DistributionsOperation.Sub:
{
if (stepX < stepY)
{
newAction = DistributionsOperation.Add;
return(new DiscreteDistribution[] { Multiply(dpdfRight, -1), dpdfLeft });
}
else
{
newAction = action;
return(new DiscreteDistribution[] { dpdfLeft, dpdfRight });
}
}
case DistributionsOperation.Muliply:
{
newAction = action;
// When one of distributions crossing Oy we need to exact locate them to eliminate 1/0 error on numerical integration
if (dpdfRight.MinX <= 0 && dpdfRight.MaxX >= 0 && !(dpdfLeft.MinX <= 0 && dpdfLeft.MaxX >= 0))
{
return(new DiscreteDistribution[] { dpdfRight, dpdfLeft });
}
else if (dpdfLeft.MinX <= 0 && dpdfLeft.MaxX >= 0 && !(dpdfRight.MinX <= 0 && dpdfRight.MaxX >= 0))
{
return(new DiscreteDistribution[] { dpdfLeft, dpdfRight });
}
else
{
if (stepX < stepY)
{
return(new DiscreteDistribution[] { dpdfRight, dpdfLeft });
}
else
{
return(new DiscreteDistribution[] { dpdfLeft, dpdfRight });
}
}
}
default:
{
newAction = action;
return(new DiscreteDistribution[] { dpdfLeft, dpdfRight });
}
}
}
private static DiscreteDistribution TwoDiscreteDistributions(DiscreteDistribution dpdfLeft, DiscreteDistribution dpdfRight, DistributionsOperation action)
{
var exchange = Swap(dpdfLeft, dpdfRight, action, out DistributionsOperation newAction);
action = newAction;
dpdfLeft = exchange[0];
dpdfRight = exchange[1];
int lengthLeft = dpdfLeft.InnerSamples;
int lengthRight = dpdfRight.InnerSamples;
double stepRight = dpdfRight.Step;
double stepLeft = dpdfLeft.Step;
double leftMinX = dpdfLeft.MinX;
double leftMaxX = dpdfLeft.MaxX;
double[] leftX = dpdfLeft.XCoordinatesInternal;
double[] leftY = dpdfLeft.YCoordinatesInternal;
double[] rightX = dpdfRight.XCoordinatesInternal;
double[] rightY = dpdfRight.YCoordinatesInternal;
double[] yCoordinates = new double[lengthRight];
double[] range = CommonRandomMath.GetRange(dpdfLeft.InnerMinX, dpdfLeft.InnerMaxX, dpdfRight.InnerMinX, dpdfRight.InnerMaxX, action);
double[] xCoordinates = CommonRandomMath.GenerateXAxis(range[0], range[1], lengthRight, out double stepX0);
switch (action)
{
case DistributionsOperation.Add:
{
List <int> operations = new List <int>();
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double x = xCoordinates[i];
double sum = 0;
double y = 0;
double r = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
r = y * GetYByX(x - m, leftY, leftMinX, leftMaxX, stepLeft, lengthLeft);
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
yCoordinates[i] = sum * stepRight;
});
break;
}
case DistributionsOperation.Sub:
{
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double x = xCoordinates[i];
double sum = 0;
double r = 0;
double y = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
r = y * GetYByX(x + m, leftY, leftMinX, leftMaxX, stepLeft, lengthLeft);
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
yCoordinates[i] = sum * stepRight;
});
break;
}
case DistributionsOperation.Muliply:
{
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double sum = 0;
double x = xCoordinates[i];
double k = 0;
double r = 0;
double y = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
k = Math.Abs(m);
if (k != 0)
{
r = y * GetYByX(x / m, leftY, leftMinX, leftMaxX, stepLeft, lengthLeft) / k;
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
}
yCoordinates[i] = sum * stepRight;
});
// in case when both of distributions cross Oy it is inf in zero
if (dpdfLeft.MinX <= 0 && dpdfLeft.MaxX >= 0 && dpdfRight.MinX <= 0 && dpdfRight.MaxX >= 0)
{
for (int i = 0; i < lengthRight - 1; i++)
{
if (xCoordinates[i] <= 0 && xCoordinates[i + 1] > 0)
{
yCoordinates[i] = double.PositiveInfinity;
break;
}
}
}
break;
}
case DistributionsOperation.Divide:
{
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double sum = 0;
double x = xCoordinates[i];
double k = 0;
double r = 0;
double y = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
k = Math.Abs(m);
if (k != 0)
{
r = y * GetYByX(x * m, leftY, leftMinX, leftMaxX, stepLeft, lengthLeft) * k;
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
}
yCoordinates[i] = sum * stepRight;
});
break;
}
case DistributionsOperation.PowerInv:
{
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double sum = 0;
double x = xCoordinates[i];
double k = 0;
double r = 0;
double y = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
k = Math.Abs(Math.Log(m) * x);
if (k != 0)
{
r = y * GetYByX(Math.Log(x, m), leftY, leftMinX, leftMaxX, stepLeft, lengthLeft) / k;
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
}
yCoordinates[i] = sum * stepRight;
});
break;
}
case DistributionsOperation.Log:
{
Parallel.For(0, lengthRight, i =>
{
double m = 0;
double sum = 0;
double x = xCoordinates[i];
double d = 0;
double k = 0;
double r = 0;
double y = 0;
for (int j = 0; j < lengthRight; j++)
{
m = rightX[j];
y = rightY[j];
d = Math.Pow(m, x);
k = Math.Abs(Math.Log(m) * d);
if (k != 0)
{
r = y * GetYByX(d, leftY, leftMinX, leftMaxX, stepLeft, lengthLeft) * k;
if (j == 0 || j == lengthRight - 1)
{
r /= 2;
}
sum += r;
}
}
yCoordinates[i] = sum * stepRight;
});
break;
}
default:
{
throw new NotImplementedException();
}
}
var result = new DiscreteDistribution(xCoordinates, yCoordinates);
return(result);
}
private static DiscreteDistribution Operation(BaseDistribution dpdf, double value, DistributionsOperation action)
{
int length = dpdf.InnerSamples;
double[] yCoordinates = new double[length];
double[] xCoordinates;
switch (action)
{
case DistributionsOperation.DivideInv:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.DivisionOfZero);
}
if ((dpdf.InnerMinX < 0 && dpdf.InnerMaxX > 0) || dpdf.InnerMinX == 0 || dpdf.InnerMaxX == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.DivisionByZeroCrossingRandom);
}
double r1 = value / dpdf.InnerMinX;
double r2 = value / dpdf.InnerMaxX;
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double z = xCoordinates[i];
double d = value / z;
double k = Math.Abs(value) / Math.Pow(z, 2);
yCoordinates[i] = dpdf.InnerGetPDFYbyX(d) * k;
}
break;
}
case DistributionsOperation.Power:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfRandomInZeroPower);
}
if (value < 0 && ((dpdf.InnerMinX < 0 && dpdf.InnerMaxX > 0) || dpdf.InnerMinX == 0 || dpdf.InnerMaxX == 0))
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfZeroCrossingRandomInNegativePower);
}
bool evenPower = Math.Abs(value % 2) == 0;
bool naturalPower = value - (int)value == 0;
if (dpdf.InnerMinX < 0 && !naturalPower)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfNotPositiveRandomInIrrationalPower);
}
double r1 = Math.Pow(dpdf.InnerMinX, value);
double r2 = Math.Pow(dpdf.InnerMaxX, value);
if (dpdf.InnerMinX < 0 && dpdf.InnerMaxX > 0 && evenPower)
{
r2 = Math.Max(r1, r2);
r1 = 0;
}
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double d = Math.Sign(xCoordinates[i]) * Math.Pow(Math.Abs(xCoordinates[i]), 1d / value);
double k = Math.Abs(Math.Pow(Math.Abs(xCoordinates[i]), (1d - value) / value) / value);
yCoordinates[i] = dpdf.InnerGetPDFYbyX(d) * k;
if (evenPower)
{
yCoordinates[i] += dpdf.InnerGetPDFYbyX(-d) * k;
}
}
break;
}
case DistributionsOperation.PowerInv:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfZeroInRandomPower);
}
else if (value < 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfNegativeInRandomPower);
}
else if (value == 1)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfOneInRandomPower);
}
double r1 = Math.Pow(value, dpdf.InnerMinX);
double r2 = Math.Pow(value, dpdf.InnerMaxX);
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double d = Math.Log(xCoordinates[i], value);
double k = Math.Abs(Math.Log(value) * xCoordinates[i]);
yCoordinates[i] = dpdf.InnerGetPDFYbyX(d) / k;
}
break;
}
case DistributionsOperation.Log:
{
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithZeroBase);
}
else if (value < 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithNegativeBase);
}
else if (value == 1)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithOneBase);
}
if (dpdf.InnerMinX <= 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmOfNotPositiveRandom);
}
double r1 = Math.Log(dpdf.InnerMinX, value);
double r2 = Math.Log(dpdf.InnerMaxX, value);
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double d = Math.Pow(value, xCoordinates[i]);
double k = Math.Abs(Math.Log(value) * d);
yCoordinates[i] = dpdf.InnerGetPDFYbyX(d) * k;
}
break;
}
case DistributionsOperation.LogInv:
{
if (dpdf.InnerMinX <= 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithNotPositiveRandomBase);
}
if ((dpdf.InnerMinX < 1 && dpdf.InnerMaxX > 1) || dpdf.InnerMinX == 1 || dpdf.InnerMaxX == 1)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithOneCrossingRandomBase);
}
if (value == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmOfZeroValue);
}
if (value < 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmOfNegativeValue);
}
double r1 = Math.Log(value, dpdf.InnerMaxX);
double r2 = Math.Log(value, dpdf.InnerMinX);
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double d = Math.Pow(value, 1d / xCoordinates[i]);
double k = Math.Abs((d * Math.Log(value)) / Math.Pow(xCoordinates[i], 2));
yCoordinates[i] = dpdf.InnerGetPDFYbyX(d) * k;
}
break;
}
case DistributionsOperation.Abs:
{
double r1 = Math.Abs(dpdf.InnerMinX);
double r2 = Math.Abs(dpdf.InnerMaxX);
if (dpdf.InnerMinX <= 0 && dpdf.InnerMaxX >= 0)
{
r2 = Math.Max(r1, r2);
r1 = 0;
}
xCoordinates = GenerateXAxis(r1, r2, length, out _);
for (int i = 0; i < length; i++)
{
double zPow = xCoordinates[i];
yCoordinates[i] = dpdf.InnerGetPDFYbyX(zPow) + dpdf.InnerGetPDFYbyX(-zPow);
}
break;
}
case DistributionsOperation.Sin:
{
double r1 = -1;
double r2 = 1;
xCoordinates = GenerateXAxis(r1, r2, length, out _);
// Max asin [-PI/2, PI/2]
int minJ = (int)(dpdf.MinX / (2 * Math.PI)) - 1;
int maxJ = (int)(dpdf.MaxX / (2 * Math.PI)) + 1;
for (int i = 0; i < length; i++)
{
double z = xCoordinates[i];
double arcsin = Math.Asin(z);
double k = 1d / Math.Sqrt(1 - Math.Pow(z, 2));
for (double j = minJ; j <= maxJ; j++)
{
double v = dpdf.InnerGetPDFYbyX((Math.PI * 2 * j) - (Math.PI + arcsin)) +
dpdf.InnerGetPDFYbyX((Math.PI * 2 * j) + arcsin);
if (v != 0)
{
yCoordinates[i] += k * v;
}
}
}
break;
}
case DistributionsOperation.Cos:
{
// https://mathoverflow.net/questions/35260/resultant-probability-distribution-when-taking-the-cosine-of-gaussian-distribute
// TODO: Verify for trigonometric functions work properly. And remove range?
_ = GetTrigonometricRange(-1, 1, dpdf);
double r1 = -1;
double r2 = 1;
xCoordinates = GenerateXAxis(r1, r2, length, out _);
// Max acos [0, PI]
int minJ = (int)(dpdf.MinX / (2 * Math.PI)) - 1;
int maxJ = (int)(dpdf.MaxX / (2 * Math.PI)) + 1;
for (int i = 0; i < length; i++)
{
double z = xCoordinates[i];
double acos = Math.Acos(z);
double k = 1d / Math.Sqrt(1 - Math.Pow(z, 2));
for (double j = minJ; j <= maxJ; j++)
{
double v = dpdf.InnerGetPDFYbyX((2 * (j + 1) * Math.PI) - acos) +
dpdf.InnerGetPDFYbyX((2 * j * Math.PI) + acos);
if (v != 0)
{
yCoordinates[i] += k * v;
}
}
}
break;
}
case DistributionsOperation.Tan:
{
if (dpdf.MaxX - dpdf.MinX >= Math.PI ||
dpdf.MinX % Math.PI <= -Math.PI / 2 ||
dpdf.MaxX % Math.PI >= Math.PI / 2)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.TangentOfValueCrossingAsymptote);
}
double r1 = Math.Tan(dpdf.MinX);
double r2 = Math.Tan(dpdf.MaxX);
xCoordinates = GenerateXAxis(r1, r2, length, out _);
int j = dpdf.Mean < 0 ? (int)(dpdf.MinX / Math.PI) : (int)(dpdf.MaxX / Math.PI);
for (int i = 0; i < length; i++)
{
double z = xCoordinates[i];
double atan = Math.Atan(z);
double k = 1d / (Math.Pow(z, 2) + 1);
double v = dpdf.InnerGetPDFYbyX((-Math.PI / 2d) + (Math.PI * j)) +
dpdf.InnerGetPDFYbyX(atan + (j * Math.PI));
if (v != 0)
{
yCoordinates[i] = k * v;
}
}
break;
}
default:
{
throw new NotImplementedException();
}
}
return(new DiscreteDistribution(xCoordinates, yCoordinates));
}
public static double[] GetRange(double min1, double max1, double min2, double max2, DistributionsOperation action)
{
double[] allBounds = new double[4];
allBounds[0] = min1;
allBounds[1] = max1;
allBounds[2] = min2;
allBounds[3] = max2;
double[] result = new double[2];
switch (action)
{
case DistributionsOperation.Add:
{
result[0] = min1 + min2;
result[1] = max1 + max2;
break;
}
case DistributionsOperation.Sub:
{
result[0] = min1 - max2;
result[1] = max1 - min2;
break;
}
case DistributionsOperation.Muliply:
{
double[] variants = new double[4];
variants[0] = min1 * min2;
variants[1] = min1 * max2;
variants[2] = max1 * min2;
variants[3] = max1 * max2;
result[0] = variants.Min();
result[1] = variants.Max();
break;
}
case DistributionsOperation.Divide:
{
if (min2 == 0 || max2 == 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.DivisionByZeroCrossingRandom);
}
if (min2 < 0 && max2 > 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.DivisionByZeroCrossingRandom);
}
double[] variants = new double[4];
variants[0] = min1 / min2;
variants[1] = min1 / max2;
variants[2] = max1 / min2;
variants[3] = max1 / max2;
result[0] = variants.Min();
result[1] = variants.Max();
break;
}
case DistributionsOperation.PowerInv:
{
if (min2 < 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.ExponentialOfNotPositiveRandomInIrrationalPower);
}
double[] variants = new double[4];
variants[0] = Math.Pow(min2, min1);
variants[1] = Math.Pow(max2, min1);
variants[2] = Math.Pow(min2, max1);
variants[3] = Math.Pow(max2, max1);
result[0] = variants.Min();
result[1] = variants.Max();
break;
}
case DistributionsOperation.Log:
{
if (min1 <= 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmOfNotPositiveRandom);
}
if (min2 <= 0)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithNotPositiveRandomBase);
}
if ((min2 < 1 && max2 > 1) || min2 == 1 || max2 == 1)
{
throw new DistributionsInvalidOperationException(DistributionsInvalidOperationExceptionType.LogarithmWithOneCrossingRandomBase);
}
double[] variants = new double[4];
variants[0] = Math.Log(min1, min2);
variants[1] = Math.Log(max1, min2);
variants[2] = Math.Log(min1, max2);
variants[3] = Math.Log(max1, max2);
result[0] = variants.Min();
result[1] = variants.Max();
break;
}
default:
{
throw new NotImplementedException();
}
}
return(result);
}