public void setXY(double x, double y) {
// not validated
// x and y between -1 and 1
double sigmoidSteepness, sigmoidZero, baseLength;
double sensitivity =
1.1; // evaluated with set to 1.1: a sensitivity of 1 means the complete space of the button
// is used. 2 means only the middle part is used, making it more sensitive and more
// easy to get to extreme arousal (from a CHI perspective).
if (!down) {
p = x * sensitivity;
d = y * sensitivity;
baseLength = Math.max(Math.abs(p), Math.abs(d)); // MAX (P, D) base
// baseLength=Math.sqrt(Math.pow(p,2)+Math.pow(d,2))/Math.sqrt(2.0); //euclid P,D base
// now do the mapping to arousal.
// Arousal is controlled simple by using a Sigmoid function based on length of PD vector
sigmoidSteepness = 11;
sigmoidZero = 8;
a = 2 / (1 + Math.exp(-(sigmoidSteepness * baseLength - sigmoidZero))) - 1;
a_base = a;
// Arousal is controlled simply by using a quadratic function that has 0,0,0 as middle point,
// then drops to -1, then to 1 based MIN (P,D) length (mimics better original linear)
// sigmoidSteepness=6;
// sigmoidZero=0.35;
// a=sigmoidSteepness*Math.pow(Math.max(Math.abs(p),Math.abs(d))-sigmoidZero, 2)-1;
p = (p > 1 ? 1 : (p < -1 ? -1 : p));
d = (d > 1 ? 1 : (d < -1 ? -1 : d));
a = (a > 1 ? 1 : (a < -1 ? -1 : a));
} else {
double tmp_p, tmp_d;
tmp_p = x * sensitivity;
tmp_d = y * sensitivity;
baseLength = Math.max(Math.abs(tmp_p), Math.abs(tmp_d)); // MAX (P, D) base
// baseLength=Math.sqrt(Math.pow(p,2)+Math.pow(d,2))/Math.sqrt(2.0); //euclid P,D base
// now do the mapping to arousal.
// Arousal is controlled simple by using a Sigmoid function based on length of PD vector
sigmoidSteepness = 11;
sigmoidZero = 8;
// a=a_base-(d-tmp_d)+2/(1+Math.exp(-(sigmoidSteepness*baseLength-sigmoidZero)))-1;
a = tmp_d;
// Arousal is controlled simply by using a quadratic function that has 0,0,0 as middle point,
// then drops to -1, then to 1 based MIN (P,D) length (mimics better original linear)
// sigmoidSteepness=6;
// sigmoidZero=0.35;
// a=sigmoidSteepness*Math.pow(Math.max(Math.abs(p),Math.abs(d))-sigmoidZero, 2)-1;
// p=(p>1?1:(p<-1?-1:p));
// d=(d>1?1:(d<-1?-1:d));
a = (a > 1 ? 1 : (a < -1 ? -1 : a));
}
}
protected void plotScatterDiagram() {
// plot sample as one dimensional scatter plot and Gaussian
double xmax = 5.;
double xmin = -5.;
DatanGraphics.openWorkstation(getClass().getName(), "E3Min_1.ps");
DatanGraphics.setFormat(0., 0.);
DatanGraphics.setWindowInComputingCoordinates(xmin, xmax, 0., .5);
DatanGraphics.setViewportInWorldCoordinates(-.15, .9, .16, .86);
DatanGraphics.setWindowInWorldCoordinates(-.414, 1., 0., 1.);
DatanGraphics.setBigClippingWindow();
DatanGraphics.chooseColor(2);
DatanGraphics.drawFrame();
DatanGraphics.drawScaleX("y");
DatanGraphics.drawScaleY("f(y)");
DatanGraphics.drawBoundary();
double xpl[] = new double[2];
double ypl[] = new double[2];
// plot scatter diagram
DatanGraphics.chooseColor(1);
for (int i = 0; i < y.length; i++) {
xpl[0] = y[i];
xpl[1] = y[i];
ypl[0] = 0.;
ypl[0] = .1;
DatanGraphics.drawPolyline(xpl, ypl);
}
// draw Gaussian corresponding to solution
int npl = 100;
xpl = new double[npl];
ypl = new double[npl];
double fact = 1. / (Math.sqrt(2. * Math.PI) * x.getElement(1));
double dpl = (xmax - xmin) / (double) (npl - 1);
for (int i = 0; i < npl; i++) {
xpl[i] = xmin + (double) i * dpl;
ypl[i] = fact * Math.exp(-.5 * Math.pow((xpl[i] - x.getElement(0)) / x.getElement(1), 2.));
}
DatanGraphics.chooseColor(5);
DatanGraphics.drawPolyline(xpl, ypl);
// draw caption
String sn = "N = " + nny;
numForm.setMaximumFractionDigits(3);
numForm.setMinimumFractionDigits(3);
String sx1 = ", x_1# = " + numForm.format(x.getElement(0));
String sx2 = ", x_2# = " + numForm.format(x.getElement(1));
String sdx1 = ", &D@x_1# = " + numForm.format(Math.sqrt(cx.getElement(0, 0)));
String sdx2 = ", &D@x_2# = " + numForm.format(Math.sqrt(cx.getElement(1, 1)));
caption = sn + sx1 + sx2 + sdx1 + sdx2;
DatanGraphics.setBigClippingWindow();
DatanGraphics.chooseColor(2);
DatanGraphics.drawCaption(1., caption);
DatanGraphics.closeWorkstation();
}
public IntensityFeatureScaleSpacePyramidApp(Class<T> imageType, Class<D> derivType) {
super(1);
this.imageType = imageType;
addAlgorithm(
0,
"Hessian Det",
new WrapperHessianBlobIntensity<T, D>(HessianBlobIntensity.Type.DETERMINANT, derivType));
addAlgorithm(
0,
"Laplacian",
new WrapperHessianBlobIntensity<T, D>(HessianBlobIntensity.Type.TRACE, derivType));
addAlgorithm(
0,
"Harris",
new WrapperGradientCornerIntensity<T, D>(
FactoryIntensityPointAlg.harris(2, 0.4f, false, derivType)));
addAlgorithm(
0,
"Shi Tomasi",
new WrapperGradientCornerIntensity<T, D>(
FactoryIntensityPointAlg.shiTomasi(2, false, derivType)));
addAlgorithm(
0,
"FAST 12",
new WrapperFastCornerIntensity<T, D>(FactoryIntensityPointAlg.fast12(5, 11, imageType)));
addAlgorithm(0, "KitRos", new WrapperKitRosCornerIntensity<T, D>(derivType));
addAlgorithm(
0,
"Median",
new WrapperMedianCornerIntensity<T, D>(FactoryBlurFilter.median(imageType, 2), imageType));
setMainGUI(gui);
double scales[] = new double[25];
for (int i = 0; i < scales.length; i++) {
scales[i] = Math.exp(i * 0.15);
}
pyramid = new ScaleSpacePyramid<T>(imageType, scales);
anyDerivative =
GImageDerivativeOps.createDerivatives(imageType, FactoryImageGenerator.create(derivType));
}
public void gradedResponsePersonParameter() {
double[] a = new double[NITEM]; // read canned data
a[0] = 0.85;
a[1] = 1.00;
a[2] = 0.90;
a[3] = 1.10;
a[4] = 1.40;
double[][] cpt = {
{1.72, 0.00, -1.72},
{1.20, 0.20, -1.50},
{2.10, 1.10, -0.70},
{-0.60, -0.80, -1.20},
{1.40, 0.70, -1.70}
};
double[] u = {3.0, 2.0, 3.0, 4.0, 3.0};
double theta = 0.4; // initial value of theta
int trall = -1; // set traces
int trmle = -1;
String yn = JOptionPane.showInputDialog("Trace all? Y/N");
if (yn.equalsIgnoreCase("y")) {
trall = 0;
trmle = 0;
} else {
String ynmle = JOptionPane.showInputDialog("Trace MLE? Y/N");
if (ynmle.equalsIgnoreCase("y")) {
trmle = 0;
} else {
// normal processing
} // end if (ynmle ...
} // end if (yn ... else
System.out.println("All= " + trall + " MLE= " + trmle + " Max Cycles= " + MAXIT);
double fds = 0.0; // first derivative sum
double sds = 0.0; // second derivative sum
System.out.println("Initial Theta= " + theta);
for (int nit = 1; nit <= MAXIT; nit++) {
System.out.println("MLE Iteration= " + nit);
for (int i = 0; i <= NITEM - 1; i++) {
double term4 = 0.0;
for (int k = 0; k <= MRC - 1; k++) {
double k1 = k + 1.0; // casting
if (u[i] == k1) {
char ptsflg = 'n';
// calc p's and w's
int km1 = k - 1;
double pstrkm1 = 1.0;
double wkm1 = 0.0;
double devkm1 = 0.0; // initialize
if (km1 != -1) {
devkm1 = cpt[i][km1] + a[i] * theta;
pstrkm1 = 1.0 / (1.0 + Math.exp(-devkm1));
wkm1 = pstrkm1 * (1.0 - pstrkm1);
} else {
// normal processing
} // end if (km1 ...
double pstrk = 0.0;
double wk = 0.0;
double dev = 0.0; // initialize
if (k != MRC - 1) {
dev = cpt[i][k] + a[i] * theta;
pstrk = 1.0 / (1.0 + Math.exp(-dev));
wk = pstrk * (1.0 - pstrk);
} else {
// normal processing
} // end if (k ...
double pk = pstrkm1 - pstrk;
if (trall == 0) {
System.out.println("Item(" + (i + 1) + ")" + " U(I)= " + u[i]);
System.out.println(
"K-1="
+ k
+ " Dev(K-1)= "
+ devkm1
+ " Pstar(K-1)= "
+ pstrkm1
+ " W(K-1)= "
+ wkm1);
System.out.println(
"K=" + (k + 1) + " Dev(K)= " + dev + " Pstar(K)= " + pstrk + " W(K)= " + wk);
} else {
// normal processing
} // end if (trall ...
if (pk < 0.0001 || pk > 0.9999) {
ptsflg = 'y';
break; // exit for (int k ...
} else {
// normal processing
} // end if (pk ...
// calc first and second derivative terms
// first derivative
double fterm = (wkm1 - wk) / pk;
fds += fterm;
if (trall == 0) {
System.out.println("Fterm= " + fterm + " First Derivative Sum= " + fds);
} else {
// normal processing
} // end if (trall ...
// second derivative
double term1 = -wk * (1.0 - 2.0 * pstrk) / pk;
double term2 = wkm1 * (1.0 - 2.0 * pstrkm1) / pk;
double term3 = -(wkm1 - wk) * (wkm1 - wk) / (pk * pk);
term4 += term1 + term2 + term3;
sds += a[i] * a[i] * term4;
if (trall == 0) {
System.out.println("Term1= " + term1 + " Term2= " + term2 + " Term3= " + term3);
System.out.println("Term4= " + term4 + " Second Derivative Sum= " + sds);
} else {
// normal processing
} // end if (trall ...
} else {
// normal processing
} // end if (u[i] ...
} // end for (int k ... (BASIC 230)
} // end for (int i ... (BASIC 240)
double delta = fds / sds;
theta -= delta;
if (trall == 0 || trmle == 0) {
System.out.println("Theta= " + theta + " Delta= " + delta);
} else {
// normal processing
} // end if (trall ...
if (Math.abs(delta) < 0.05) {
break; // exit for (nit ...
} else {
// normal processing
} // end if (Math.abs ...
if (nit == MAXIT) {
System.out.println("Maximum Cycles Reached");
} else {
// normal processing
} // end if (nit ...
} // end for (int nit ... (BASIC 280)
System.out.println("Theta Estimate= " + theta);
System.exit(0); // last line
} // end public static ...
public void gradedResponseItemParameters() {
double[] pstr = new double[MRC + 1]; // for BASIC 1200
double[] w = new double[MRC + 1]; // for BASIC 1200
double[] pk = new double[MRC];
double[] pobs = new double[MRC];
double[] sfd = new double[MRC];
double[] t = new double[MRC];
double[] pdelta = new double[MRC];
double[] b = new double[MBC];
double[] bk = new double[MRC];
double[][] mtrx = new double[MRC][MRC];
double[][] tk = new double[MRC][MRC];
// read canned data
double a = 1.0; // initial value of common slope
double[] theta = new double[MAXGPS];
theta[0] = -3.0;
theta[1] = -2.0;
theta[2] = -1.0;
theta[3] = 0.0;
theta[4] = 1.0;
theta[5] = 2.0;
theta[6] = 3.0;
double[] f = {1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0};
double[][] r = {
{691.0, 242.0, 61.0, 6.0},
{500.0, 341.0, 136.0, 23.0},
{309.0, 382.0, 242.0, 67.0},
{159.0, 341.0, 341.0, 159.0},
{67.0, 242.0, 382.0, 309.0},
{23.0, 136.0, 341.0, 500.0},
{6.0, 61.0, 242.0, 691.0},
};
double[] cpt = new double[MBC];
cpt[0] = 1.8;
cpt[1] = 0.0;
cpt[2] = -1.8;
int trall = -1; // establish trace of program
int trmle = -1;
String yn = JOptionPane.showInputDialog("Trace all? Y/N");
if (yn.equalsIgnoreCase("y")) {
trall = 0;
trmle = 0;
} else {
String ynmle = JOptionPane.showInputDialog("Trace MLE terms? Y/N");
if (ynmle.equalsIgnoreCase("y")) {
trmle = 0;
} else {
// normal processing
} // end if (ynmle ...
} // end if (yn ... else
System.out.println("All= " + trall + " MLE= " + trmle + " Max Cycles= " + MAXIT);
int iflag = -1;
for (int nit = 1; nit <= MAXIT; nit++) {
// clear sums, vectors, and matrix
for (int rr = 0; rr <= MRC - 1; rr++) { // rr for r
sfd[rr] = 0.0;
for (int c = 0; c <= MRC - 1; c++) {
mtrx[rr][c] = 0.0;
} // end for (int c ...
} // end for (int rr ...
System.out.println("MLE Iteration= " + nit);
for (int g = 0; g <= MAXGPS - 1; g++) {
System.out.println("Ability Level= " + (g + 1));
// calc p star
pstr[0] = 1.0;
w[0] = 0.0;
pstr[MRC] = 0.0;
w[MRC] = 0.0;
if (trall == 0) {
System.out.println("Boundard Curve Pstar's");
} else {
// normal processing
} // end if (trall ...
for (int y = 0; y <= MBC - 1; y++) {
double dev = cpt[y] + a * theta[g];
pstr[y + 1] = 1.0 / (1.0 + Math.exp(-dev));
w[y + 1] = pstr[y + 1] * (1.0 - pstr[y + 1]);
if (trall == 0) {
System.out.println(
"Intercept("
+ (y + 1)
+ ")= "
+ cpt[y]
+ " A= "
+ a
+ " Theta("
+ (g + 1)
+ ")= "
+ theta[g]);
System.out.println(
"Dev= "
+ dev
+ " Pstar("
+ (y + 1)
+ ")= "
+ pstr[y + 1]
+ " W("
+ (y + 1)
+ ")= "
+ w[y + 1]);
} else {
// normal processing
} // end if (trall ...
} // end for (int y ... (BASIC 1280)
// calc p observed
if (trall == 0) {
System.out.println("Pk and P observed");
} else {
// normal processing
}
for (int k = 0; k <= MRC - 1; k++) {
if (k == 0) {
pk[k] = 1.0 - pstr[k + 1];
} else if (k == MRC - 1) {
pk[MRC - 1] = pstr[MRC - 1];
} else {
pk[k] = pstr[k] - pstr[k + 1];
} // end if (k ...
pobs[k] = r[g][k] / f[g];
if (trall == 0) {
System.out.println("K= " + (k + 1) + " PK= " + pk[k] + " PObs= " + pobs[k]);
} else {
// normal processing
} // end if (trall ...
} // end for (int k ... (BASIC 1360)
// calculate first derivative terms for intercepts
if (trall == 0) {
System.out.println("Intercept Terms");
} else {
// normal processing
} // end if (trall ...
for (int y = 0; y <= MBC - 1; y++) {
double term1 = -pobs[y] / pk[y] + pobs[y + 1] / pk[y + 1];
double term2 = f[g] * w[y + 1] * term1;
sfd[y] += term2;
if (trall == 0) {
System.out.println(
"Y= "
+ (y + 1)
+ " Term1= "
+ term1
+ " Term2= "
+ term2
+ " First Derivative= "
+ sfd[y]);
} else {
// normal processing
} // end if (trall ...
} // end for (int y ... (BASIC 1460)
// calculate first derivative terms for slope
double sumls = 0.0;
if (trall == 0) {
System.out.println("Common Slope Terms");
} else {
// normal processing
} // end if (trall ...
for (int k = 0; k <= MRC - 1; k++) {
double term1 = w[k] - w[k + 1];
double term2 = (pobs[k] / pk[k]) * term1;
sumls += term2;
if (trall == 0) {
System.out.println(
"K= " + (k + 1) + " Term1= " + term1 + " Term2= " + term2 + " SumLS= " + sumls);
} else {
// normal processing
} // end if (trall ...
} // end for (int k ... (BASIC 1560)
double term3 = f[g] * theta[g] * sumls;
sfd[MRC - 1] = sfd[MRC - 1] + term3;
if (trall == 0) {
System.out.println("Term3= " + term3 + " First Derivative Term= " + sfd[MRC - 1]);
} else {
// normal processing
} // end if (trall ...
// calculate intercept terms for information matrix
if (trall == 0) {
System.out.println("Intercept Terms in Information Matrix");
} else {
// normal processing
} // end if (trall ...
for (int rr = 0; rr <= MBC - 1; rr++) { // rr for r
for (int c = 0; c <= MBC - 1; c++) {
if (rr == c) { // diagonal intercept term
double term1 = 1 / pk[c] + 1 / pk[c + 1];
double term2 = f[g] * w[c + 1] * w[c + 1] * term1;
mtrx[rr][c] += term2;
if (trall == 0) {
System.out.println(
"R= "
+ (rr + 1)
+ " C= "
+ (c + 1)
+ " Term1= "
+ term1
+ " Term2= "
+ term2);
System.out.println("Matrix Element= " + mtrx[rr][c]);
} else {
// normal processing
} // end if (trall ...
} else {
double term1 = f[g] * w[rr + 1] * w[c + 1];
double term2 = -term1 * (1.0 / pk[c]); // switched
if (rr > c) {
term2 = -term1 * (1.0 / pk[rr]);
} else {
// normal processing
} // end if (rr ...
mtrx[rr][c] += term2;
if (Math.abs(rr - c) > 1) {
mtrx[rr][c] = 0.0;
} else {
// normal processing
} // end if (Math.abs ...
if (trall == 0) {
System.out.println(
"R= "
+ (rr + 1)
+ " C= "
+ (c + 1)
+ " Term1= "
+ term1
+ " Term2= "
+ term2);
System.out.println("Matrix Element= " + mtrx[rr][c]);
} else {
// normal processing
} // end if (trall ...
} // end if (rr ...
} // end for (int c ... (BASIC 1730)
} // end for (int rr ... (BASIC 1730)
// calculate slope terms for information matrix
if (trall == 0) {
System.out.println("Slope Terms in Information Matrix");
} else {
// normal processing
} // end if (trall ...
int rr = MRC - 1; // rr for r
for (int c = 0; c <= MRC - 1; c++) {
if (trall == 0) {
System.out.println("R= " + (rr + 1) + " C= " + (c + 1));
} else {
// normal processing
} // end if (trall ...
double term1 = 0.0; // initialize
double term2 = 0.0;
if (c != MRC - 1) {
term1 = (w[c] - w[c + 1]) / pk[c] - (w[c + 1] - w[c + 2]) / pk[c + 1];
term2 = -f[g] * w[c + 1] * theta[g] * term1;
} else {
term2 = 0.0;
for (int k = 0; k <= MRC - 1; k++) {
term1 = (w[k] - w[k + 1]) * (w[k] - w[k + 1]) * 1.0 / pk[k];
term2 += term1;
if (trall == 0) {
System.out.println("K= " + (k + 1) + " Term1= " + term1 + " Term2= " + term2);
} else {
// normal processing
} // end if (trall ...
} // end for (int k ...
term2 = term2 * f[g] * theta[g] * theta[g];
} // end if (c ...
mtrx[rr][c] += term2;
if (trall == 0) {
System.out.println(
"Term1= " + term1 + " Term2= " + term2 + " Matrix Element= " + mtrx[rr][c]);
} else {
// normal processing
} // end if (trall ...
} // end for (int c ... (BASIC 1930)
// put slope row derivatives in last column
for (int c = 0; c <= MRC - 1; c++) {
mtrx[c][rr] = mtrx[rr][c];
} // end for (int c ...
if (trall == 0) {
System.out.println("Information Matrix");
} else {
// normal processing
} // end if (trall ...
for (int row = 0; row <= MRC - 1; row++) { // row for r
for (int c = 0; c <= MRC - 1; c++) {
if (trall == 0) {
System.out.println(
"R= " + (row + 1) + " C= " + (c + 1) + " Matrix Element= " + mtrx[row][c]);
} else {
// normal processing
} // end if (trall ...
} // end for (int c ...
} // end for (int r ...
} // end for (int g ... (BASIC 270)
// invert information matrix
for (int kk = 0; kk <= MRC - 1; kk++) {
if (mtrx[0][0] <= 0.000001) {
System.out.println("The matrix is singular, " + "very near singular, or indefinite");
iflag = 0;
break; // exit for (int kk ...
} else {
double sr = Math.sqrt(mtrx[0][0]); // sr for r
for (int ik = 0; ik <= MBC - 1; ik++) {
t[ik] = mtrx[ik + 1][0] / sr;
} // end for (ik ...
t[MRC - 1] = 1.0 / sr;
for (int jk = 0; jk <= MBC - 1; jk++) {
for (int ik = 0; ik <= MBC - 1; ik++) {
mtrx[ik][jk] = mtrx[ik + 1][jk + 1] - t[ik] * t[jk];
} // end for (ik ...
} // end for (jk ... (BASIC 2170)
for (int ik = 0; ik <= MRC - 1; ik++) {
mtrx[ik][MRC - 1] = -t[ik] * t[MRC - 1];
} // end for (ik ...
for (int jk = 0; jk <= MBC - 1; jk++) {
mtrx[MRC - 1][jk] = mtrx[jk][MRC - 1];
} // end for (jk ...
} // end if (mtrx ...
} // end for (int kk ... (BASIC 2195)
for (int jk = 0; jk <= MRC - 1; jk++) {
for (int ik = 0; ik <= MRC - 1; ik++) {
mtrx[ik][jk] = -mtrx[ik][jk];
} // end for (ik ...
} // end for (jk ...
if (trall == 0) {
for (int jk = 0; jk <= MRC - 1; jk++) {
for (int ik = 0; ik <= MRC - 1; ik++) {
System.out.println(
"Row= "
+ (jk + 1)
+ " Col= "
+ (ik + 1)
+ " Inversion Elementmt= "
+ mtrx[jk][ik]);
} // end for (ik ...
} // end for (jk ...
} else {
// normal processing
} // end if (trall ...
// BASIC 290
char converg = 'y';
if (iflag == 0) {
break; // exit for (int nit ...
} else {
// calculate change vector and obtain new estimates
for (int jk = 0; jk <= MRC - 1; jk++) {
pdelta[jk] = 0.0;
} // end for (jk ...
for (int jk = 0; jk <= MRC - 1; jk++) {
for (int ik = 0; ik <= MRC - 1; ik++) {
pdelta[jk] += mtrx[jk][ik] * sfd[ik];
} // end for (ik ...
if (trall == 0 || trmle == 0) {
System.out.println("Delta Parameter(" + (jk + 1) + ")= " + pdelta[jk]);
} else {
// normal processing
} // end if (trall ...
} // end for (jk ...
// may need big delta protection here
// obtain new item parameter vlaues
for (int ik = 0; ik <= MBC - 1; ik++) {
cpt[ik] += pdelta[ik];
if (trall == 0 || trmle == 0) {
System.out.println("Intercept(" + (ik + 1) + ")= " + cpt[ik]);
} else {
// normal processing
} // end if (trall ...
} // end for (ik ...
a += pdelta[MRC - 1];
if (trall == 0 || trmle == 0) {
System.out.println("Common Slope= " + a);
} else {
// normal processing
} // end if (trall ...
// calculate convergence criterion
for (int k = 0; k <= MRC - 1; k++) {
if (Math.abs(pdelta[k]) > 0.05) {
converg = 'n';
break; // exit for (k ...
} else {
// normal processing
} // end if (Math.abs ...
} // end for (k ...
} // end if (iflag ...
if (converg == 'y') {
System.out.println("Converg=y"); // new line
break; // exit for (nit ...
} else {
// normal processing
} // end if (converg ...
if (nit == MAXIT) {
System.out.println("Reached Maximum Cycles");
} else {
// normal processing
} // end if (nit ...
} // end for (int nit ... (BASIC 330)
if (iflag != 0) {
// print item parameter estimates
for (int y = 0; y <= MBC - 1; y++) {
b[y] = -cpt[y] / a;
System.out.println(
"Intercept(" + (y + 1) + ")= " + cpt[y] + "Boundary Curve B(" + (y + 1) + ")= " + b[y]);
} // end for (int y ...
System.out.println("Common Slope= " + a);
for (int k = 0; k <= MRC - 1; k++) {
if (k == 0) {
bk[k] = b[0];
} else if (k == MRC - 1) {
bk[k] = b[MBC - 1];
} else {
bk[k] = (b[k] + b[k - 1]) / 2.0;
}
System.out.println("Response Category(" + (k + 1) + ") Difficulty= " + bk[k]);
} // end for (k ...
System.out.println("Item Discrimination= " + a);
} else {
// normal processing
} // end if (iflag ...
System.exit(0); // last line
} // end public static ...
/** Translation durchfuehren */
public void process() {
int i, j, k;
int ch, len;
float f1;
double d1, d2, d3, d4, d5;
long progOff, progLen, lo;
// io
AudioFile reInF = null;
AudioFile imInF = null;
AudioFile reOutF = null;
AudioFile imOutF = null;
AudioFileDescr reInStream = null;
AudioFileDescr imInStream = null;
AudioFileDescr reOutStream = null;
AudioFileDescr imOutStream = null;
FloatFile reFloatF[] = null;
FloatFile imFloatF[] = null;
File reTempFile[] = null;
File imTempFile[] = null;
int outChanNum;
float[][] reInBuf; // [ch][i]
float[][] imInBuf; // [ch][i]
float[][] reOutBuf = null; // [ch][i]
float[][] imOutBuf = null; // [ch][i]
float[] convBuf1, convBuf2;
boolean complex;
PathField ggOutput;
// Synthesize
Param ampRef = new Param(1.0, Param.ABS_AMP); // transform-Referenz
float gain; // gain abs amp
float dryGain, wetGain;
float inGain;
float maxAmp = 0.0f;
Param peakGain;
int inLength, inOff;
int pre;
int post;
int length;
int framesRead, framesWritten, outLength;
boolean polarIn, polarOut;
// phase unwrapping
double[] phi;
int[] wrap;
double[] carry;
Param lenRef;
topLevel:
try {
complex = pr.bool[PR_HASIMINPUT] || pr.bool[PR_HASIMOUTPUT];
polarIn = pr.intg[PR_OPERATOR] == OP_POLAR2RECT;
polarOut = pr.intg[PR_OPERATOR] == OP_RECT2POLAR;
if ((polarIn || polarOut) && !complex) throw new IOException(ERR_NOTCOMPLEX);
// ---- open input ----
reInF = AudioFile.openAsRead(new File(pr.text[PR_REINPUTFILE]));
reInStream = reInF.getDescr();
inLength = (int) reInStream.length;
reInBuf = new float[reInStream.channels][8192];
imInBuf = new float[reInStream.channels][8192];
if (pr.bool[PR_HASIMINPUT]) {
imInF = AudioFile.openAsRead(new File(pr.text[PR_IMINPUTFILE]));
imInStream = imInF.getDescr();
if (imInStream.channels != reInStream.channels) throw new IOException(ERR_COMPLEX);
inLength = (int) Math.min(inLength, imInStream.length);
}
lenRef = new Param(AudioFileDescr.samplesToMillis(reInStream, inLength), Param.ABS_MS);
d1 =
AudioFileDescr.millisToSamples(
reInStream, (Param.transform(pr.para[PR_OFFSET], Param.ABS_MS, lenRef, null).value));
j = (int) (d1 >= 0.0 ? (d1 + 0.5) : (d1 - 0.5)); // correct rounding for negative values!
length =
(int)
(AudioFileDescr.millisToSamples(
reInStream,
(Param.transform(pr.para[PR_LENGTH], Param.ABS_MS, lenRef, null)).value)
+ 0.5);
// System.err.println( "offset = "+j );
if (j >= 0) {
inOff = Math.min(j, inLength);
if (!pr.bool[PR_REVERSE]) {
reInF.seekFrame(inOff);
if (pr.bool[PR_HASIMINPUT]) {
imInF.seekFrame(inOff);
}
}
inLength -= inOff;
pre = 0;
} else {
inOff = 0;
pre = Math.min(-j, length);
}
inLength = Math.min(inLength, length - pre);
post = length - pre - inLength;
if (pr.bool[PR_REVERSE]) {
i = pre;
pre = post;
post = i;
inOff += inLength;
}
// .... check running ....
if (!threadRunning) break topLevel;
// for( op = 0; op < 2; op++ ) {
// System.out.println( op +": pre "+pre[op]+" / len "+inLength[op]+" / post "+post[op] );
// }
// System.out.println( "tot "+length[0]);
outLength = length;
outChanNum = reInStream.channels;
// ---- open output ----
ggOutput = (PathField) gui.getItemObj(GG_REOUTPUTFILE);
if (ggOutput == null) throw new IOException(ERR_MISSINGPROP);
reOutStream = new AudioFileDescr(reInStream);
ggOutput.fillStream(reOutStream);
reOutStream.channels = outChanNum;
// well, more sophisticated code would
// move and truncate the markers...
if ((pre == 0) /* && (post == 0) */) {
reInF.readMarkers();
reOutStream.setProperty(
AudioFileDescr.KEY_MARKERS, reInStream.getProperty(AudioFileDescr.KEY_MARKERS));
}
reOutF = AudioFile.openAsWrite(reOutStream);
reOutBuf = new float[outChanNum][8192];
imOutBuf = new float[outChanNum][8192];
if (pr.bool[PR_HASIMOUTPUT]) {
imOutStream = new AudioFileDescr(reInStream);
ggOutput.fillStream(imOutStream);
imOutStream.channels = outChanNum;
imOutStream.file = new File(pr.text[PR_IMOUTPUTFILE]);
imOutF = AudioFile.openAsWrite(imOutStream);
}
// .... check running ....
if (!threadRunning) break topLevel;
// ---- Further inits ----
phi = new double[outChanNum];
wrap = new int[outChanNum];
carry = new double[outChanNum];
for (ch = 0; ch < outChanNum; ch++) {
phi[ch] = 0.0;
wrap[ch] = 0;
carry[ch] = Double.NEGATIVE_INFINITY;
}
progOff = 0; // read, transform, write
progLen = (long) outLength * 3;
wetGain = (float) (Param.transform(pr.para[PR_WETMIX], Param.ABS_AMP, ampRef, null)).value;
dryGain = (float) (Param.transform(pr.para[PR_DRYMIX], Param.ABS_AMP, ampRef, null)).value;
if (pr.bool[PR_DRYINVERT]) {
dryGain = -dryGain;
}
inGain = (float) (Param.transform(pr.para[PR_INPUTGAIN], Param.ABS_AMP, ampRef, null)).value;
if (pr.bool[PR_INVERT]) {
inGain = -inGain;
}
// normalization requires temp files
if (pr.intg[PR_GAINTYPE] == GAIN_UNITY) {
reTempFile = new File[outChanNum];
reFloatF = new FloatFile[outChanNum];
for (ch = 0;
ch < outChanNum;
ch++) { // first zero them because an exception might be thrown
reTempFile[ch] = null;
reFloatF[ch] = null;
}
for (ch = 0; ch < outChanNum; ch++) {
reTempFile[ch] = IOUtil.createTempFile();
reFloatF[ch] = new FloatFile(reTempFile[ch], GenericFile.MODE_OUTPUT);
}
if (pr.bool[PR_HASIMOUTPUT]) {
imTempFile = new File[outChanNum];
imFloatF = new FloatFile[outChanNum];
for (ch = 0;
ch < outChanNum;
ch++) { // first zero them because an exception might be thrown
imTempFile[ch] = null;
imFloatF[ch] = null;
}
for (ch = 0; ch < outChanNum; ch++) {
imTempFile[ch] = IOUtil.createTempFile();
imFloatF[ch] = new FloatFile(imTempFile[ch], GenericFile.MODE_OUTPUT);
}
}
progLen += outLength;
} else {
gain = (float) (Param.transform(pr.para[PR_GAIN], Param.ABS_AMP, ampRef, null)).value;
wetGain *= gain;
dryGain *= gain;
}
// .... check running ....
if (!threadRunning) break topLevel;
// ----==================== the real stuff ====================----
framesRead = 0;
framesWritten = 0;
while (threadRunning && (framesWritten < outLength)) {
// ---- choose chunk len ----
len = Math.min(8192, outLength - framesWritten);
if (pre > 0) {
len = Math.min(len, pre);
} else if (inLength > 0) {
len = Math.min(len, inLength);
} else {
len = Math.min(len, post);
}
// ---- read input chunks ----
if (pre > 0) {
Util.clear(reInBuf);
if (complex) {
Util.clear(imInBuf);
}
pre -= len;
} else if (inLength > 0) {
if (pr.bool[PR_REVERSE]) { // ---- read reversed ----
reInF.seekFrame(inOff - framesRead - len);
reInF.readFrames(reInBuf, 0, len);
for (ch = 0; ch < reInStream.channels; ch++) {
convBuf1 = reInBuf[ch];
for (i = 0, j = len - 1; i < j; i++, j--) {
f1 = convBuf1[j];
convBuf1[j] = convBuf1[i];
convBuf1[i] = f1;
}
}
if (pr.bool[PR_HASIMINPUT]) {
imInF.seekFrame(inOff - framesRead - len);
imInF.readFrames(imInBuf, 0, len);
for (ch = 0; ch < imInStream.channels; ch++) {
convBuf1 = imInBuf[ch];
for (i = 0, j = len - 1; i < j; i++, j--) {
f1 = convBuf1[j];
convBuf1[j] = convBuf1[i];
convBuf1[i] = f1;
}
}
} else if (complex) {
Util.clear(imInBuf);
}
} else { // ---- read normal ----
reInF.readFrames(reInBuf, 0, len);
if (pr.bool[PR_HASIMINPUT]) {
imInF.readFrames(imInBuf, 0, len);
} else if (complex) {
Util.clear(imInBuf);
}
}
inLength -= len;
framesRead += len;
} else {
Util.clear(reInBuf);
if (complex) {
Util.clear(imInBuf);
}
post -= len;
}
progOff += len;
// .... progress ....
setProgression((float) progOff / (float) progLen);
// .... check running ....
if (!threadRunning) break topLevel;
// ---- save dry signal ----
for (ch = 0; ch < outChanNum; ch++) {
convBuf1 = reInBuf[ch];
convBuf2 = reOutBuf[ch];
for (i = 0; i < len; i++) {
convBuf2[i] = convBuf1[i] * dryGain;
}
if (complex) {
convBuf1 = imInBuf[ch];
convBuf2 = imOutBuf[ch];
for (i = 0; i < len; i++) {
convBuf2[i] = convBuf1[i] * dryGain;
}
}
}
// ---- rectify + apply input gain ----
for (ch = 0; ch < reInStream.channels; ch++) {
convBuf1 = reInBuf[ch];
convBuf2 = imInBuf[ch];
// ---- rectify ----
if (pr.bool[PR_RECTIFY]) {
if (complex) {
if (polarIn) {
for (i = 0; i < len; i++) {
convBuf2[i] = 0.0f;
}
} else {
for (i = 0; i < len; i++) {
d1 = convBuf1[i];
d2 = convBuf2[i];
convBuf1[i] = (float) Math.sqrt(d1 * d1 + d2 * d2);
convBuf2[i] = 0.0f;
}
}
} else {
for (i = 0; i < len; i++) {
convBuf1[i] = Math.abs(convBuf1[i]);
}
}
}
// ---- apply input gain ----
Util.mult(convBuf1, 0, len, inGain);
if (complex & !polarIn) {
Util.mult(convBuf2, 0, len, inGain);
}
}
// ---- heart of the dragon ----
for (ch = 0; ch < outChanNum; ch++) {
convBuf1 = reInBuf[ch];
convBuf2 = imInBuf[ch];
switch (pr.intg[PR_OPERATOR]) {
case OP_NONE: // ================ None ================
for (i = 0; i < len; i++) {
reOutBuf[ch][i] += wetGain * convBuf1[i];
}
if (complex) {
for (i = 0; i < len; i++) {
imOutBuf[ch][i] += wetGain * convBuf2[i];
}
}
break;
case OP_SIN: // ================ Cosinus ================
if (complex) {
for (i = 0; i < len; i++) {
reOutBuf[ch][i] += wetGain * (float) Math.sin(convBuf1[i] * Math.PI);
imOutBuf[ch][i] += wetGain * (float) Math.sin(convBuf2[i] * Math.PI);
}
} else {
for (i = 0; i < len; i++) {
reOutBuf[ch][i] += wetGain * (float) Math.sin(convBuf1[i] * Math.PI);
}
}
break;
case OP_SQR: // ================ Square ================
if (complex) {
for (i = 0; i < len; i++) {
reOutBuf[ch][i] +=
wetGain * (convBuf1[i] * convBuf1[i] - convBuf2[i] * convBuf2[i]);
imOutBuf[ch][i] -= wetGain * (convBuf1[i] * convBuf2[i] * 2);
}
} else {
for (i = 0; i < len; i++) {
reOutBuf[ch][i] += wetGain * (convBuf1[i] * convBuf1[i]);
}
}
break;
case OP_SQRT: // ================ Square root ================
if (complex) {
d3 = phi[ch];
k = wrap[ch];
d4 = k * Constants.PI2;
for (i = 0; i < len; i++) {
d1 =
wetGain
* Math.pow(convBuf1[i] * convBuf1[i] + convBuf2[i] * convBuf2[i], 0.25);
d2 = Math.atan2(convBuf2[i], convBuf1[i]);
if (d2 - d3 > Math.PI) {
k--;
d4 = k * Constants.PI2;
} else if (d3 - d2 > Math.PI) {
k++;
d4 = k * Constants.PI2;
}
d2 += d4;
d3 = d2;
d2 /= 2;
reOutBuf[ch][i] += (float) (d1 * Math.cos(d2));
imOutBuf[ch][i] += (float) (d1 * Math.sin(d2));
}
phi[ch] = d3;
wrap[ch] = k;
} else {
for (i = 0; i < len; i++) {
f1 = convBuf1[i];
if (f1 > 0) {
reOutBuf[ch][i] += wetGain * (float) Math.sqrt(f1);
} // else undefiniert
}
}
break;
case OP_RECT2POLARW: // ================ Rect->Polar (wrapped) ================
for (i = 0; i < len; i++) {
d1 = wetGain * Math.sqrt(convBuf1[i] * convBuf1[i] + convBuf2[i] * convBuf2[i]);
d2 = Math.atan2(convBuf2[i], convBuf1[i]);
reOutBuf[ch][i] += (float) d1;
imOutBuf[ch][i] += (float) d2;
}
break;
case OP_RECT2POLAR: // ================ Rect->Polar ================
d3 = phi[ch];
k = wrap[ch];
d4 = k * Constants.PI2;
for (i = 0; i < len; i++) {
d1 = wetGain * Math.sqrt(convBuf1[i] * convBuf1[i] + convBuf2[i] * convBuf2[i]);
d2 = Math.atan2(convBuf2[i], convBuf1[i]);
if (d2 - d3 > Math.PI) {
k--;
d4 = k * Constants.PI2;
} else if (d3 - d2 > Math.PI) {
k++;
d4 = k * Constants.PI2;
}
d2 += d4;
reOutBuf[ch][i] += (float) d1;
imOutBuf[ch][i] += (float) d2;
d3 = d2;
}
phi[ch] = d3;
wrap[ch] = k;
break;
case OP_POLAR2RECT: // ================ Polar->Rect ================
for (i = 0; i < len; i++) {
f1 = wetGain * convBuf1[i];
reOutBuf[ch][i] += f1 * (float) Math.cos(convBuf2[i]);
imOutBuf[ch][i] += f1 * (float) Math.sin(convBuf2[i]);
}
break;
case OP_LOG: // ================ Log ================
if (complex) {
d3 = phi[ch];
k = wrap[ch];
d4 = k * Constants.PI2;
d5 = carry[ch];
for (i = 0; i < len; i++) {
d1 = Math.sqrt(convBuf1[i] * convBuf1[i] + convBuf2[i] * convBuf2[i]);
d2 = Math.atan2(convBuf2[i], convBuf1[i]);
if (d2 - d3 > Math.PI) {
k--;
d4 = k * Constants.PI2;
} else if (d3 - d2 > Math.PI) {
k++;
d4 = k * Constants.PI2;
}
if (d1 > 0.0) {
d5 = Math.log(d1);
}
d2 += d4;
reOutBuf[ch][i] += (float) d5;
imOutBuf[ch][i] += (float) d2;
d3 = d2;
}
phi[ch] = d3;
wrap[ch] = k;
carry[ch] = d5;
} else {
for (i = 0; i < len; i++) {
f1 = convBuf1[i];
if (f1 > 0) {
reOutBuf[ch][i] += wetGain * (float) Math.log(f1);
} // else undefiniert
}
}
break;
case OP_EXP: // ================ Exp ================
if (complex) {
for (i = 0; i < len; i++) {
d1 = wetGain * Math.exp(convBuf1[i]);
reOutBuf[ch][i] += (float) (d1 * Math.cos(convBuf2[i]));
imOutBuf[ch][i] += (float) (d1 * Math.sin(convBuf2[i]));
}
} else {
for (i = 0; i < len; i++) {
reOutBuf[ch][i] += wetGain * (float) Math.exp(convBuf1[i]);
}
}
break;
case OP_NOT: // ================ NOT ================
for (i = 0; i < len; i++) {
lo = ~((long) (convBuf1[i] * 2147483647.0));
reOutBuf[ch][i] += wetGain * (float) ((lo & 0xFFFFFFFFL) / 2147483647.0);
}
if (complex) {
for (i = 0; i < len; i++) {
lo = ~((long) (convBuf2[i] * 2147483647.0));
imOutBuf[ch][i] += wetGain * (float) ((lo & 0xFFFFFFFFL) / 2147483647.0);
}
}
break;
}
} // for outChan
progOff += len;
// .... progress ....
setProgression((float) progOff / (float) progLen);
// .... check running ....
if (!threadRunning) break topLevel;
// ---- write output chunk ----
if (reFloatF != null) {
for (ch = 0; ch < outChanNum; ch++) {
reFloatF[ch].writeFloats(reOutBuf[ch], 0, len);
if (pr.bool[PR_HASIMOUTPUT]) {
imFloatF[ch].writeFloats(imOutBuf[ch], 0, len);
}
}
} else {
reOutF.writeFrames(reOutBuf, 0, len);
if (pr.bool[PR_HASIMOUTPUT]) {
imOutF.writeFrames(imOutBuf, 0, len);
}
}
// check max amp
for (ch = 0; ch < outChanNum; ch++) {
convBuf1 = reOutBuf[ch];
for (i = 0; i < len; i++) {
f1 = Math.abs(convBuf1[i]);
if (f1 > maxAmp) {
maxAmp = f1;
}
}
if (pr.bool[PR_HASIMOUTPUT]) {
convBuf1 = imOutBuf[ch];
for (i = 0; i < len; i++) {
f1 = Math.abs(convBuf1[i]);
if (f1 > maxAmp) {
maxAmp = f1;
}
}
}
}
progOff += len;
framesWritten += len;
// .... progress ....
setProgression((float) progOff / (float) progLen);
} // while not framesWritten
// ----==================== normalize output ====================----
if (pr.intg[PR_GAINTYPE] == GAIN_UNITY) {
peakGain = new Param(maxAmp, Param.ABS_AMP);
gain =
(float)
(Param.transform(
pr.para[PR_GAIN],
Param.ABS_AMP,
new Param(1.0 / peakGain.value, peakGain.unit),
null))
.value;
f1 = pr.bool[PR_HASIMOUTPUT] ? ((1.0f + getProgression()) / 2) : 1.0f;
normalizeAudioFile(reFloatF, reOutF, reOutBuf, gain, f1);
if (pr.bool[PR_HASIMOUTPUT]) {
normalizeAudioFile(imFloatF, imOutF, imOutBuf, gain, 1.0f);
}
maxAmp *= gain;
for (ch = 0; ch < outChanNum; ch++) {
reFloatF[ch].cleanUp();
reFloatF[ch] = null;
reTempFile[ch].delete();
reTempFile[ch] = null;
if (pr.bool[PR_HASIMOUTPUT]) {
imFloatF[ch].cleanUp();
imFloatF[ch] = null;
imTempFile[ch].delete();
imTempFile[ch] = null;
}
}
}
// .... check running ....
if (!threadRunning) break topLevel;
// ---- Finish ----
reOutF.close();
reOutF = null;
reOutStream = null;
if (imOutF != null) {
imOutF.close();
imOutF = null;
imOutStream = null;
}
reInF.close();
reInF = null;
reInStream = null;
if (pr.bool[PR_HASIMINPUT]) {
imInF.close();
imInF = null;
imInStream = null;
}
reOutBuf = null;
imOutBuf = null;
reInBuf = null;
imInBuf = null;
// inform about clipping/ low level
handleClipping(maxAmp);
} catch (IOException e1) {
setError(e1);
} catch (OutOfMemoryError e2) {
reOutBuf = null;
imOutBuf = null;
reInBuf = null;
imInBuf = null;
convBuf1 = null;
convBuf2 = null;
System.gc();
setError(new Exception(ERR_MEMORY));
}
// ---- cleanup (topLevel) ----
convBuf1 = null;
convBuf2 = null;
if (reInF != null) {
reInF.cleanUp();
reInF = null;
}
if (imInF != null) {
imInF.cleanUp();
imInF = null;
}
if (reOutF != null) {
reOutF.cleanUp();
reOutF = null;
}
if (imOutF != null) {
imOutF.cleanUp();
imOutF = null;
}
if (reFloatF != null) {
for (ch = 0; ch < reFloatF.length; ch++) {
if (reFloatF[ch] != null) {
reFloatF[ch].cleanUp();
reFloatF[ch] = null;
}
if (reTempFile[ch] != null) {
reTempFile[ch].delete();
reTempFile[ch] = null;
}
}
}
if (imFloatF != null) {
for (ch = 0; ch < imFloatF.length; ch++) {
if (imFloatF[ch] != null) {
imFloatF[ch].cleanUp();
imFloatF[ch] = null;
}
if (imTempFile[ch] != null) {
imTempFile[ch].delete();
imTempFile[ch] = null;
}
}
}
} // process()
protected void compute() {
n = (int) ni[0].parseInput();
t0 = ni[1].parseInput();
deltat = ni[2].parseInput();
x1 = ni[3].parseInput();
x2 = ni[4].parseInput();
sigma = ni[5].parseInput();
// generate data points
t = new DatanVector(n);
y = new DatanVector(n);
dy = new DatanVector(n);
rand = DatanRandom.standardNormal(n);
for (int i = 0; i < n; i++) {
t.setElement(i, t0 + (double) i * deltat);
y.setElement(i, x1 * Math.pow(t.getElement(i), x2) + sigma * rand[i]);
dy.setElement(i, sigma);
}
// find 1st approximation of unknowns by method of log-log plot
tlog = new double[n];
ylog = new double[n];
dellog = new double[n];
int npos = 0;
for (int i = 0; i < n; i++) {
if (t.getElement(i) > 0. && y.getElement(i) > 0.) {
tlog[npos] = Math.log(t.getElement(i));
ylog[npos] = Math.log(y.getElement(i));
dellog[npos] = 1.;
npos++;
}
}
DatanVector vtlog = new DatanVector(npos);
DatanVector vylog = new DatanVector(npos);
DatanVector vdellog = new DatanVector(npos);
for (int j = 0; j < npos; j++) {
vtlog.setElement(j, tlog[j]);
vylog.setElement(j, ylog[j]);
vdellog.setElement(j, dellog[j]);
}
LsqPol lp = new LsqPol(vtlog, vylog, vdellog, 2);
x = lp.getResult();
x.setElement(0, Math.exp(x.getElement(0)));
df.writeLine(" x = " + x.toString());
// perform fit
int[] list = {1, 1};
powerlaw = new Powerlaw();
LsqNon ln = new LsqNon(t, y, dy, x, list, powerlaw);
x = ln.getResult();
x1 = x.getElement(0);
x2 = x.getElement(1);
cov = ln.getCovarianceMatrix();
delx1 = Math.sqrt(cov.getElement(0, 0));
delx2 = Math.sqrt(cov.getElement(1, 1));
rho = cov.getElement(1, 0) / (delx1 * delx2);
m = ln.getChiSquare();
p = 1. - StatFunct.cumulativeChiSquared(m, n - 1);
// curve of fitted exponential
xpl = new double[1001];
ypl = new double[1001];
dpl = (double) (n - 1) * deltat / 1000.;
for (int i = 0; i < 1001; i++) {
xpl[i] = t0 + (double) i * dpl;
ypl[i] = x1 * Math.pow(xpl[i], x2);
}
// prepare data points for plotting
datx = new double[n];
daty = new double[n];
datsx = new double[n];
datsy = new double[n];
datrho = new double[n];
for (int i = 0; i < n; i++) {
datx[i] = t.getElement(i);
daty[i] = y.getElement(i);
datsx[i] = 0.;
datsy[i] = dy.getElement(i);
datrho[i] = 0.;
}
// display data and fitted curve
caption =
"x_1#="
+ String.format(Locale.US, "%5.2f", x1)
+ ", x_2#="
+ String.format(Locale.US, "%5.2f", x2)
+ ", &D@x_1#="
+ String.format(Locale.US, "%5.2f", delx1)
+ ", &D@x_2#="
+ String.format(Locale.US, "%5.2f", delx2)
+ ", &r@="
+ String.format(Locale.US, "%5.2f", rho)
+ ", M="
+ String.format(Locale.US, "%5.2f", m)
+ ", P="
+ String.format(Locale.US, "%6.4f", p);
new GraphicsWithDataPointsAndPolyline(
getClass().getName(),
"",
xpl,
ypl,
1,
.3,
datx,
daty,
datsx,
datsy,
datrho,
"t",
"y",
caption);
}
public double evaluate_1(double x) {
return (2 * x / x * x + 1)
- 0.4 * Math.exp(0.4 * x) * Math.cos(Math.PI * x)
+ Math.PI * Math.exp(0.4 * x) * Math.sin(Math.PI * x);
}
public double evaluate(double x) {
return Math.log(x * x + 1) - Math.exp(0.4 * x) * Math.cos(Math.PI * x);
}
public static double exp10(double val) {
return Math.exp(val / LOG10SCALE);
}
