private void OnAddItem()
{
var count = Items3.Count + 1;
Items3.Add(new SelectedItem(count.ToString(), $"备选 {count:d2}"));
}
public MainViewModel()
{
const int generatorSize = 100;
#region FirstPunct
double lamda1;
const double lamda2 = 3;
var rand = new Random();
var maxEx = 0.0;
var generatedNums1 = new List <double>();
var x11 = new List <double>();
var x12 = new List <double>();
var pi1 = new List <double>();
var Fx11 = new List <double>();
var Fx12 = new List <double>();
var histogramData = new int[10];
var teorProbability = new double[10];
for (var i = 0; i < generatorSize; i++)
{
generatedNums1.Add(rand.NextDouble());
}
double mu = 0.0;
foreach (var x in generatedNums1)
{
mu += x;
}
mu /= generatorSize;
avg1 = $" Average: {mu}";
disp1 = $" Dispersion: {Math.Pow(mu, 2.0)}";
lamda1 = 1 / mu;
foreach (var x in generatedNums1)
{
x11.Add(-Math.Log2(x) / lamda1);
x12.Add(-Math.Log2(x) / lamda2);
}
foreach (var num in x11)
{
if (maxEx < num)
{
maxEx = num;
}
Fx11.Add(1 - Math.Pow(Math.E, -lamda1 * num));
}
foreach (var num in x12)
{
Fx12.Add(1 - Math.Pow(Math.E, -lamda2 * num));
}
foreach (var x in x11)
{
if (x >= 0 && x < maxEx / 10)
{
histogramData[0]++;
}
if (x >= maxEx / 10 && x < 2 * maxEx / 10)
{
histogramData[1]++;
}
if (x >= 2 * maxEx / 10 && x < 3 * maxEx / 10)
{
histogramData[2]++;
}
if (x >= 3 * maxEx / 10 && x < 4 * maxEx / 10)
{
histogramData[3]++;
}
if (x >= 4 * maxEx / 10 && x < 5 * maxEx / 10)
{
histogramData[4]++;
}
if (x >= 5 * maxEx / 10 && x < 6 * maxEx / 10)
{
histogramData[5]++;
}
if (x >= 6 * maxEx / 10 && x < 7 * maxEx / 10)
{
histogramData[6]++;
}
if (x >= 7 * maxEx / 10 && x < 8 * maxEx / 10)
{
histogramData[7]++;
}
if (x >= 8 * maxEx / 10 && x < 9 * maxEx / 10)
{
histogramData[8]++;
}
if (x >= 9 * maxEx / 10 && x < 10 * maxEx / 10)
{
histogramData[9]++;
}
}
var hikv = 0.0;
for (var i = 0; i < 10; i++)
{
var x = (Math.Exp(-lamda1 * i * maxEx / 10 - Math.Exp(-lamda1 * i + 1 * maxEx / 10)));
pi1.Add(x);
}
for (var i = 0; i < pi1.Count; i++)
{
hikv += Math.Pow(histogramData[i] - pi1[i] * generatorSize, 2.0) / generatorSize * pi1[i];
}
hi1 = $" Hi^2: {hikv}";
#endregion
#region SecondPunct
double sigma1 = 2;
const double a1 = 3;
const double sigma2 = 4;
const double a2 = 5;
double sum;
var rand2 = new Random();
var maxNorm = 0.0;
var generatedList2 = new List <double>();
var muList = new List <double>();
var normalXList1 = new List <double>();
var normalXList2 = new List <double>();
var normalYList1 = new List <double>();
var normalYList2 = new List <double>();
var pi2 = new List <double>();
var histogramData2 = new int[10];
double mu2 = 0.0;
double sigma = 0.0;
for (var i = 0; i < generatorSize; i++)
{
sum = 0;
var randomed = rand2.NextDouble();
generatedList2.Add(randomed);
for (var j = 0; j < 12; j++)
{
sum += rand2.NextDouble();
}
muList.Add(sum - 6);
}
foreach (var x in generatedList2)
{
mu2 += x;
}
mu2 /= generatorSize;
foreach (var x in generatedList2)
{
sigma += Math.Pow(x - mu2, 2.0);
}
sigma /= (generatorSize - 1);
avg2 = $" Average: {mu2}";
disp2 = $" Dispersion: {sigma}";
foreach (var x in muList)
{
normalXList1.Add(sigma1 * x + a1);
}
foreach (var x in muList)
{
normalXList2.Add(sigma2 * x + a2);
}
foreach (var x in normalXList1)
{
normalYList1.Add(Math.Exp(-(x - a1)) / (2 * Math.Pow(sigma1, 2.0)) / (sigma1 * Math.Sqrt(2 * Math.PI)));
if (maxNorm < x)
{
maxNorm = x;
}
}
foreach (var x in normalXList2)
{
normalYList2.Add(Math.Exp(-(x - a2)) / (2 * Math.Pow(sigma2, 2.0)) / (sigma2 * Math.Sqrt(2 * Math.PI)));
}
foreach (var x in normalXList1)
{
if (x >= 0 && x < maxNorm / 10)
{
histogramData2[0]++;
}
if (x >= maxNorm / 10 && x < 2 * maxNorm / 10)
{
histogramData2[1]++;
}
if (x >= 2 * maxNorm / 10 && x < 3 * maxNorm / 10)
{
histogramData2[2]++;
}
if (x >= 3 * maxNorm / 10 && x < 4 * maxNorm / 10)
{
histogramData2[3]++;
}
if (x >= 4 * maxNorm / 10 && x < 5 * maxNorm / 10)
{
histogramData2[4]++;
}
if (x >= 5 * maxNorm / 10 && x < 6 * maxNorm / 10)
{
histogramData2[5]++;
}
if (x >= 6 * maxNorm / 10 && x < 7 * maxNorm / 10)
{
histogramData2[6]++;
}
if (x >= 7 * maxNorm / 10 && x < 8 * maxNorm / 10)
{
histogramData2[7]++;
}
if (x >= 8 * maxNorm / 10 && x < 9 * maxNorm / 10)
{
histogramData2[8]++;
}
if (x >= 9 * maxNorm / 10 && x < 10 * maxNorm / 10)
{
histogramData2[9]++;
}
}
var hikv2 = 0.0;
for (var i = 0; i < 10; i++)
{
var x = Math.Pow(a1, i) / factorial_Recursion(i) * Math.Exp(-a1);
pi2.Add(x);
}
for (var i = 0; i < pi1.Count; i++)
{
hikv2 += Math.Pow(histogramData2[i] - pi2[i] * generatorSize, 2.0) / generatorSize * pi2[i];
}
hi2 = $" Hi^2: {hikv2}";
#endregion
#region ThirdPunct
var a = Math.Pow(5, 13);
var c = Math.Pow(2, 31);
var max = 0.0;
var rand3 = new Random().NextDouble();
var z = new List <double>();
var x1 = new List <double>();
avg3 = $" Average: {rand3}";
disp3 = $" Dispersion: {Math.Pow(rand3,2.0)}";
var histogramData3 = new int[10];
for (var i = 0; i < generatorSize; i++)
{
if (i == 0)
{
z.Add(a * rand3 % c);
}
else
{
z.Add(a * z[i - 1] % c);
}
}
foreach (var y in z)
{
var temp = y / c;
if (max < temp)
{
max = temp;
}
x1.Add(temp);
}
foreach (var x in x1)
{
if (x >= 0 && x < max / 10)
{
histogramData3[0]++;
}
if (x >= max / 10 && x < 2 * max / 10)
{
histogramData3[1]++;
}
if (x >= 2 * max / 10 && x < 3 * max / 10)
{
histogramData3[2]++;
}
if (x >= 3 * max / 10 && x < 4 * max / 10)
{
histogramData3[3]++;
}
if (x >= 4 * max / 10 && x < 5 * max / 10)
{
histogramData3[4]++;
}
if (x >= 5 * max / 10 && x < 6 * max / 10)
{
histogramData3[5]++;
}
if (x >= 6 * max / 10 && x < 7 * max / 10)
{
histogramData3[6]++;
}
if (x >= 7 * max / 10 && x < 8 * max / 10)
{
histogramData3[7]++;
}
if (x >= 8 * max / 10 && x < 9 * max / 10)
{
histogramData3[8]++;
}
if (x >= 9 * max / 10 && x < 10 * max / 10)
{
histogramData3[9]++;
}
}
var hikv3 = 0.0;
for (var i = 0; i < 10; i++)
{
var chisl = Math.Pow(histogramData3[i] - 0.1 * generatorSize, 2);
var znam = 0.1 * generatorSize;
hikv3 += chisl / znam;
}
hi3 = $" Hi^2: {hikv3}";
#endregion
#region Graph
Title_ex1 = "Expotential (lamda = 2)";
Title_ex2 = "Expotential (lamda = 3)";
Title_ex3 = "Normal (sigma = 2, a = 3)";
Title_ex4 = "Normal (sigma = 4, a = 5)";
Histogram1_title = "Histogram for expotential distribution law";
Histogram2_title = "Histogram for normal distribution law";
Histogram3_title = "Histogram for uniform distribution law";
#region Expot
for (var i = 0; i < x11.Count; i++)
{
Points1.Add(new DataPoint(x11[i], Fx11[i]));
}
for (var i = 0; i < x12.Count; i++)
{
Points2.Add(new DataPoint(x12[i], Fx12[i]));
}
#region Histogram
for (var i = 0; i < histogramData.Length; i++)
{
Items1.Add(new ColumnItem {
Value = histogramData[i], CategoryIndex = i
});
}
#endregion
#endregion
#region Normal
for (var i = 0; i < normalXList1.Count; i++)
{
Points3.Add(new DataPoint(normalXList1[i], normalYList1[i]));
}
for (var i = 0; i < normalXList2.Count; i++)
{
Points4.Add(new DataPoint(normalXList2[i], normalYList2[i]));
}
#region Histogram
for (var i = 0; i < histogramData2.Length; i++)
{
Items2.Add(new ColumnItem {
Value = histogramData2[i], CategoryIndex = i
});
}
#endregion
#endregion
#region Third
for (var i = 0; i < histogramData3.Length; i++)
{
Items3.Add(new ColumnItem {
Value = histogramData3[i], CategoryIndex = i
});
}
#endregion
#endregion
}