oms3.dsl.cosu.Morris Maven / Gradle / Ivy
/*
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package oms3.dsl.cosu;
import java.util.ArrayList;
import java.util.List;
public class Morris {
/**
* @param args
*/
public static void main(String[] args) {
int k = 4; // No. of factors
int p = 6; // No. of levels per factor (even)
int t = 8; // No. of trajectories
double[][] range_array = {{0, 4}, {2, 3}, {4, 5}, {1, 5}};
Matrix range = new Matrix(range_array);
// Create samples for Morris method
double x[] = new double[k];
double y_f[] = new double[k];
double y_s[] = new double[k];
double El_Ef[][] = new double[t][k];
double Mat_array[][] = new double[k + 1][k];
double w_array[][] = new double[k + 1][1];
Matrix Mat = new Matrix(Mat_array);
Matrix w = new Matrix(w_array);
Matrix[] Mat_store = new Matrix[t];
for (int i = 0; i < t; i++) {
Mat_store[i] = new Matrix(Mat_array);
}
List values = new ArrayList();
int u = 0, a = 0, r = 0;
double inc = (double) 1 / (p - 1);
double delta = p * inc / 2;
double temp = 0;
do {
values.add(temp);
temp = temp + inc;
} while (temp <= 1);
do {
for (int j = 0; j < k; j++) {
Mat.data[0][j] = values.get((int) (Math.floor(p * Math.random())));
}
int q[] = permutation(k);
for (int j = 0; j < k; j++) {
for (int i = 0; i < Mat.N; i++) {
Mat.data[j + 1][i] = Mat.data[j][i];
}
double mat_cal = Mat.data[j + 1][q[j]] + delta;
Mat.data[j+1][q[j]] = (mat_cal > 1) ? (mat_cal - 2 * delta) : mat_cal;
}
// Check to not repeat trajectories
int add = 1;
if (a > 0) {
for (int i = 0; i < a; i++) {
if (Mat.eq(Mat_store[i]) == true) {
add--;
}
}
}
if (add == 1) {
Mat_store[a] = Mat.copy();
a++;
}
} while (a < t);
// scale trajectories to real factor ranges
double scale[] = new double[range.M];
for (int i = 0; i < range.M; i++) {
scale[i] = range.data[i][1] - range.data[i][0];
}
for (int i = 0; i < w.M; i++) {
for (int j = 0; j < w.N; j++) {
w.data[i][j] = 1;
}
}
Matrix w_temp = new Matrix(new double[w.M][range.M]);
Matrix w_temp2 = new Matrix(new double[w.M][scale.length]);
for (int i = 0; i < w.M; i++) {
for (int j = 0; j < range.M; j++) {
w_temp.data[i][j] = w.data[i][0] * range.data[j][0];
w_temp2.data[i][j] = w.data[i][0] * scale[j];
}
}
for (int i = 0; i <= t - 1; i++) {
Mat_store[i] = w_temp.plus(Mat_store[i].timesbyelement(w_temp2));
}
// Calculation Mean & Standard deviation of elementary effect
for (int i = 0; i < t; i++) {
for (int j = 0; j < k; j++) {
for (int l = 0; l <= Mat_store[i].N - 1; l++) {
x[l] = Mat_store[i].data[j][l];
}
y_f[j] = equation(x);
for (int l = 0; l < Mat_store[i].N; l++) {
x[l] = Mat_store[i].data[j + 1][l];
}
y_s[j] = equation(x);
for (int l = 0; l < Mat_store[i].N; l++) {
if (Mat_store[i].data[j][l] != Mat_store[i].data[j + 1][l]) {
u = l;
break;
}
}
El_Ef[r][u] = (y_s[j] - y_f[j]) / delta;
}
r++;
}
double Mean[] = new double[k];
double Std[] = new double[k];
for (int l = 0; l < k; l++) {
double tmp = 0;
for (int i = 0; i © 2015 - 2024 Weber Informatics LLC | Privacy Policy