List of usage examples for java.lang Math PI
double PI
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From source file:edu.indiana.d2i.datacatalog.dashboard.api.USStates.java
public static String getStates(String statesFilePath) throws ParserConfigurationException, IOException, SAXException { JSONObject statesFeatureCollection = new JSONObject(); statesFeatureCollection.put("type", "FeatureCollection"); JSONArray features = new JSONArray(); DocumentBuilderFactory documentBuilderFactory = DocumentBuilderFactory.newInstance(); try {/*from w ww .j av a 2s .co m*/ DocumentBuilder documentBuilder = documentBuilderFactory.newDocumentBuilder(); Document dom = documentBuilder.parse(new FileInputStream(new File(statesFilePath))); Element docElement = dom.getDocumentElement(); NodeList states = docElement.getElementsByTagName("state"); for (int i = 0; i < states.getLength(); i++) { Node state = states.item(i); JSONObject stateObj = new JSONObject(); stateObj.put("type", "Feature"); JSONObject geometry = new JSONObject(); geometry.put("type", "Polygon"); JSONArray coordinates = new JSONArray(); JSONArray coordinateSub = new JSONArray(); NodeList points = ((Element) state).getElementsByTagName("point"); for (int j = 0; j < points.getLength(); j++) { Node point = points.item(j); JSONArray pointObj = new JSONArray(); float lat = Float.parseFloat(((Element) point).getAttribute("lat")); float lng = Float.parseFloat(((Element) point).getAttribute("lng")); double trLng = lng * 20037508.34 / 180; double trLat = Math.log(Math.tan((90 + lat) * Math.PI / 360)) / (Math.PI / 180); pointObj.add(lng); pointObj.add(lat); coordinateSub.add(pointObj); } geometry.put("coordinates", coordinates); coordinates.add(coordinateSub); stateObj.put("geometry", geometry); JSONObject name = new JSONObject(); name.put("Name", ((Element) state).getAttribute("name")); name.put("colour", "#FFF901"); stateObj.put("properties", name); features.add(stateObj); } statesFeatureCollection.put("features", features); return statesFeatureCollection.toJSONString(); } catch (ParserConfigurationException e) { log.error("Error while processing states.xml.", e); throw e; } catch (FileNotFoundException e) { log.error("Error while processing states.xml.", e); throw e; } catch (SAXException e) { log.error("Error while processing states.xml.", e); throw e; } catch (IOException e) { log.error("Error while processing states.xml.", e); throw e; } }
From source file:endrov.nucAutoJH.FitGaussian.java
private static double[] fitGaussian2D_(EvPixels p, double sigmaInit, final double midxInit, final double midyInit) { //sigma00, sigma01, sigma11, mu_x, mu_y, c p = p.getReadOnly(EvPixelsType.DOUBLE); final double[] arrPixels = p.getArrayDouble(); final int w = p.getWidth(); final int h = p.getHeight(); int extent = (int) Math.round(3 * sigmaInit); extent = Math.max(extent, 2); final int sx = Math.max(0, (int) (midxInit - extent)); final int ex = Math.min(w, (int) (midxInit + extent + 1)); //+1 to the right? final int sy = Math.max(0, (int) (midyInit - extent)); final int ey = Math.min(h, (int) (midyInit + extent + 1)); double minIntensity = Double.MAX_VALUE; double maxIntensity = Double.MIN_VALUE; for (int y = sy; y < ey; y++) { int base = y * w; double dy2 = y - midyInit; dy2 = dy2 * dy2;/*w w w .jav a 2 s.c o m*/ for (int x = sx; x < ex; x++) { double dx2 = x - midxInit; dx2 = dx2 * dx2; double t = arrPixels[base + x]; //if(dx2+dy2<=extent*extent) { if (t < minIntensity) minIntensity = t; if (t > maxIntensity) maxIntensity = t; } } } //double[] weights=new double[]{1}; double[] startPoint = new double[] { sigmaInit, 0, sigmaInit, midxInit, midyInit, minIntensity, maxIntensity - minIntensity }; //double[] output=new double[startPoint.length]; try { MultivariateRealFunction func = new MultivariateRealFunction() { // opt.optimize( public double value(double[] arg) throws FunctionEvaluationException, IllegalArgumentException { double sigma00 = arg[0]; double sigma01 = arg[1]; double sigma11 = arg[2]; double mu0 = arg[3]; double mu1 = arg[4]; double C = arg[5]; double D = arg[6]; double sumError = 0; Matrix2d sigma = new Matrix2d(sigma00, sigma01, sigma01, sigma11); Matrix2d sigmaInv = new Matrix2d(); sigma.invert(sigmaInv); double sigmaDet = sigma.determinant(); double front = 1.0 / (2 * Math.PI * Math.sqrt(sigmaDet)); //System.out.println("front: "+front); //System.out.println("sigma inv "+sigmaInv); if (mu0 < sx || mu0 > ex) sumError += 1000000; if (mu1 < sy || mu1 > ey) sumError += 1000000; if (sigma00 < 1) sumError += 1000000; //if(sigma01<0) sumError+=1000000; if (sigma11 < 1) sumError += 1000000; if (D <= 0) sumError += 1000000; for (int y = sy; y < ey; y++) { int base = y * w; double dy2 = y - midyInit; dy2 = dy2 * dy2; for (int x = sx; x < ex; x++) { double dx2 = x - midxInit; dx2 = dx2 * dx2; double thisReal = arrPixels[base + x]; // if(dx2+dy2<=extent*extent) { // DoubleMatrix2D sigma=new DenseDoubleMatrix2D(new double[][]{{sigma00,sigma01},{sigma01,sigma11}}); //double sigmaDet=sigma00*sigma11-sigma01*sigma01; double dx0 = x - mu0; double dx1 = y - mu1; //http://en.wikipedia.org/wiki/Multivariate_normal_distribution Vector2d vX = new Vector2d(dx0, dx1); Vector2d op = new Vector2d(vX); sigmaInv.transform(op); double upper = -0.5 * op.dot(vX); double exp = Math.exp(upper); //System.out.println("front "+front+" "+exp+" C "+C+" thisreal"+thisReal+" upper "+upper); if (upper > -0.4) exp = 1; else exp = Math.max(0, 1 + upper + 0.4); /* if(exp<0.7) exp=0; else exp=1; */ double thisExpected = D * front * exp + C; double diff = thisExpected - thisReal; sumError += diff * diff; } } } //System.out.println(sigma00+"\t"+sigma01+"\t"+sigma11+"\tC"+C+"\tmu "+mu0+","+mu1+"\terr "+sumError); return sumError; // return new double[]{sumError}; } }; NelderMead opt = new NelderMead(); //LevenbergMarquardtOptimizer opt=new LevenbergMarquardtOptimizer(); opt.setMaxIterations(10000); RealPointValuePair pair = opt.optimize(func, GoalType.MINIMIZE, startPoint); int numit = opt.getIterations(); System.out.println("#it " + numit); System.out.println("err " + func.value(pair.getPointRef())); return pair.getPointRef(); // for(int i=0;i<startPoint.length;i++) // System.out.println("i: "+i+" "+output[i]); //, output, weights, startPoint); } /* catch (MaxIterationsExceededException e) { System.out.println("max it reached"); }*/ catch (Exception e) { e.printStackTrace(); } //Maybe this is a bad point? System.out.println("max it reached"); return startPoint; // return output; }
From source file:net.sourceforge.processdash.ui.lib.chart.DiscLegendAxis.java
/** * Converts a disc area to a coordinate in Java2D space on the legend axis. */// www . j av a 2 s .c om @Override public double valueToJava2D(double value, Rectangle2D area, RectangleEdge edge) { if (discItemDistributor == null) { // This should not happen since prior to using a legend axis, a DiscPlot // should set a DiscItemDistributor. return 0.0; } double discRadius = Math.sqrt(Math.abs(value) / Math.PI); double discDiameter = 2 * discRadius; double scaledDiameter = discDiameter * discItemDistributor.getScale(); double java2DValue = area.getMaxY() - scaledDiameter; return java2DValue; }
From source file:gedi.util.math.stat.distributions.PoissonBinomial.java
private void preprocess() { int n = pp.length; m = n + 1;/*from w w w . ja va 2 s .co m*/ int nextPowerOf2 = Integer.highestOneBit(m); if (nextPowerOf2 != m) nextPowerOf2 <<= 1; m = nextPowerOf2; n = m - 1; int ins = 0; int start = 0; for (int i = 1; i < pp.length; i++) { if (Math.abs(pp[i] - pp[start]) > 1E-10) { if (i - start > 1) { double p = pp[start]; pp[ins++] = -(i - start); pp[ins++] = p; } else { pp[ins++] = pp[i - 1]; } start = i; } } if (pp.length - start > 1) { double p = pp[start]; pp[ins++] = -(pp.length - start); pp[ins++] = p; } else { pp[ins++] = pp[pp.length - 1]; } double delta = 2 * Math.PI / m; z = new Complex[m]; z[0] = new Complex(1, 0); for (int i = 1; i <= Math.ceil(n / 2.0); i++) { double tt = i * delta; // for(int j=0;j<pp.length;j++) // { // double pj=j<opp.length?opp[j]:0; // double ax=1-pj+pj*Math.cos(tt); // double bx=pj*Math.sin(tt); // double tmp1=Math.sqrt(ax*ax+bx*bx); // double tmp2=Math.atan2(bx,ax); //atan2(x,y) // c1o+=Math.log(tmp1); // c2o+=tmp2; // } double c1 = 0.00; double c2 = 0.00; for (int j = 0; j < ins; j++) { double pj = pp[j]; double f = 1; if (pj < 0) { f = -pj; pj = pp[++j]; } double ax = 1 - pj + pj * Math.cos(tt); double bx = pj * Math.sin(tt); double tmp1 = Math.sqrt(ax * ax + bx * bx); double tmp2 = Math.atan2(bx, ax); //atan2(x,y) c1 += Math.log(tmp1) * f; c2 += tmp2 * f; } z[i] = new Complex(Math.exp(c1) * Math.cos(c2), Math.exp(c1) * Math.sin(c2)); z[z.length - i] = z[i].conjugate(); } FastFourierTransformer fft = new FastFourierTransformer(DftNormalization.STANDARD); z = fft.transform(z, TransformType.FORWARD); }
From source file:AsymptoticFreedom.GraphViewPanel.java
public JFreeChart getResultChart() { // XY ?//from ww w . j ava 2 s . c o m int quark_size = ViewPanel.quark_list.size(); if (quark_size < 2) return new JFreeChart(new XYPlot()); // XY Dataset XYSeriesCollection data = new XYSeriesCollection(); //System.out.println(series.get(0).getY(30)); for (XYSeries s : series) { data.addSeries(s); } final JFreeChart chart = ChartFactory.createXYLineChart("Potential", "Distance", "Potential", data, PlotOrientation.VERTICAL, true, true, false); chart.setTitle("Potential of quarks"); // ? XYPlot plot = (XYPlot) chart.getPlot(); //plot.addRangeMarker(new ValueMarker(15,Color.RED,new BasicStroke(2.0f))); for (int i = 0; i < quark_size; i++) { for (int j = i + 1; j < quark_size; j++) { Quark quark1 = ViewPanel.quark_list.get(i); Quark quark2 = ViewPanel.quark_list.get(j); double distance = quark1.pos.distance(quark2.pos); double value = quark1.calculatePotential(quark2); String anno_title = String.format("V_ %c-%c", quark1.color.charAt(0), quark2.color.charAt(0)); //System.out.println(anno_title); XYPointerAnnotation pointer = new XYPointerAnnotation(anno_title, distance, value, 3.0 * Math.PI / 4.0); plot.addAnnotation(pointer); } } plot.getRangeAxis().setRange(-500, 4000); return chart; }
From source file:endrov.typeLineageAutoNucJH.FitGaussian.java
private static double[] fitGaussian2D_(EvPixels p, double sigmaInit, final double midxInit, final double midyInit) { //sigma00, sigma01, sigma11, mu_x, mu_y, c p = p.getReadOnly(EvPixelsType.DOUBLE); final double[] arrPixels = p.getArrayDouble(); final int w = p.getWidth(); final int h = p.getHeight(); int extent = (int) Math.round(3 * sigmaInit); extent = Math.max(extent, 2); final int sx = Math.max(0, (int) (midxInit - extent)); final int ex = Math.min(w, (int) (midxInit + extent + 1)); //+1 to the right? final int sy = Math.max(0, (int) (midyInit - extent)); final int ey = Math.min(h, (int) (midyInit + extent + 1)); double minIntensity = Double.MAX_VALUE; double maxIntensity = -Double.MAX_VALUE; for (int y = sy; y < ey; y++) { int base = y * w; double dy2 = y - midyInit; dy2 = dy2 * dy2;// ww w . j av a2s . co m for (int x = sx; x < ex; x++) { double dx2 = x - midxInit; dx2 = dx2 * dx2; double t = arrPixels[base + x]; //if(dx2+dy2<=extent*extent) { if (t < minIntensity) minIntensity = t; if (t > maxIntensity) maxIntensity = t; } } } //double[] weights=new double[]{1}; double[] startPoint = new double[] { sigmaInit, 0, sigmaInit, midxInit, midyInit, minIntensity, maxIntensity - minIntensity }; //double[] output=new double[startPoint.length]; try { MultivariateRealFunction func = new MultivariateRealFunction() { // opt.optimize( public double value(double[] arg) throws FunctionEvaluationException, IllegalArgumentException { double sigma00 = arg[0]; double sigma01 = arg[1]; double sigma11 = arg[2]; double mu0 = arg[3]; double mu1 = arg[4]; double C = arg[5]; double D = arg[6]; double sumError = 0; Matrix2d sigma = new Matrix2d(sigma00, sigma01, sigma01, sigma11); Matrix2d sigmaInv = new Matrix2d(); sigma.invert(sigmaInv); double sigmaDet = sigma.determinant(); double front = 1.0 / (2 * Math.PI * Math.sqrt(sigmaDet)); //System.out.println("front: "+front); //System.out.println("sigma inv "+sigmaInv); if (mu0 < sx || mu0 > ex) sumError += 1000000; if (mu1 < sy || mu1 > ey) sumError += 1000000; if (sigma00 < 1) sumError += 1000000; //if(sigma01<0) sumError+=1000000; if (sigma11 < 1) sumError += 1000000; if (D <= 0) sumError += 1000000; for (int y = sy; y < ey; y++) { int base = y * w; double dy2 = y - midyInit; dy2 = dy2 * dy2; for (int x = sx; x < ex; x++) { double dx2 = x - midxInit; dx2 = dx2 * dx2; double thisReal = arrPixels[base + x]; // if(dx2+dy2<=extent*extent) { // DoubleMatrix2D sigma=new DenseDoubleMatrix2D(new double[][]{{sigma00,sigma01},{sigma01,sigma11}}); //double sigmaDet=sigma00*sigma11-sigma01*sigma01; double dx0 = x - mu0; double dx1 = y - mu1; //http://en.wikipedia.org/wiki/Multivariate_normal_distribution Vector2d vX = new Vector2d(dx0, dx1); Vector2d op = new Vector2d(vX); sigmaInv.transform(op); double upper = -0.5 * op.dot(vX); double exp = Math.exp(upper); //System.out.println("front "+front+" "+exp+" C "+C+" thisreal"+thisReal+" upper "+upper); if (upper > -0.4) exp = 1; else exp = Math.max(0, 1 + upper + 0.4); /* if(exp<0.7) exp=0; else exp=1; */ double thisExpected = D * front * exp + C; double diff = thisExpected - thisReal; sumError += diff * diff; } } } //System.out.println(sigma00+"\t"+sigma01+"\t"+sigma11+"\tC"+C+"\tmu "+mu0+","+mu1+"\terr "+sumError); return sumError; // return new double[]{sumError}; } }; NelderMead opt = new NelderMead(); //LevenbergMarquardtOptimizer opt=new LevenbergMarquardtOptimizer(); opt.setMaxIterations(10000); RealPointValuePair pair = opt.optimize(func, GoalType.MINIMIZE, startPoint); int numit = opt.getIterations(); System.out.println("#it " + numit); System.out.println("err " + func.value(pair.getPointRef())); return pair.getPointRef(); // for(int i=0;i<startPoint.length;i++) // System.out.println("i: "+i+" "+output[i]); //, output, weights, startPoint); } /* catch (MaxIterationsExceededException e) { System.out.println("max it reached"); }*/ catch (Exception e) { e.printStackTrace(); } //Maybe this is a bad point? System.out.println("max it reached"); return startPoint; // return output; }
From source file:Float11.java
static public double atan2(double y, double x) { // if x=y=0/*from w w w .j a va 2 s .c o m*/ if (y == 0. && x == 0.) return 0.; // if x>0 atan(y/x) if (x > 0.) return atan(y / x); // if x<0 sign(y)*(pi - atan(|y/x|)) if (x < 0.) { if (y < 0.) return -(Math.PI - atan(y / x)); else return Math.PI - atan(-y / x); } // if x=0 y!=0 sign(y)*pi/2 if (y < 0.) return -Math.PI / 2.; else return Math.PI / 2.; }
From source file:BooksDemo.java
private void rotateBook() { if (!isBookShowingFront()) { rotator1.setMinimumAngle((float) Math.PI * 1.0f); rotator1.setMaximumAngle(0.0f);//from ww w . ja va2 s.co m } else { rotator1.setMinimumAngle(0.0f); rotator1.setMaximumAngle((float) Math.PI * 1.0f); } front = !front; rotor1Alpha.setStartTime(System.currentTimeMillis()); }
From source file:com.qaant.threadModels.TWhaley.java
private void wWhaley() { tipoEjercicio = AMERICAN;/*from www . j ava 2s . c om*/ // q=(tipoContrato==STOCK) ? dividendRate:rate; //q: si es una accion q es el dividendo, si es un futuro q se toma la rate para descontar el valor futr a presente //Se hace este reemplazo para poder usar la misma form en STOCK y FUTURO double xx; switch (tipoContrato) { case STOCK: q = dividendRate; b = rate; break; case FUTURES: q = rate; b = 0; break; } double vlt2 = volatModel * volatModel; double VltSqrDayYear = volatModel * sqrDayYear; double h = 1 - z; //descuento para valor presente double alfa = 2 * rate / vlt2; double beta = 2 * (b - q) / vlt2; double lambda = (-(beta - 1) + cpFlag * Math.sqrt((beta - 1) * (beta - 1) + 4 * alfa / h)) / 2; double eex = Math.exp(-q * dayYear);//descuento por dividendos double s1 = strike; double zz = 1 / Math.sqrt(2 * Math.PI); double zerror = 1; do { double d1 = (Math.log(s1 / strike) + ((rate - q) + vlt2 / 2) * dayYear) / VltSqrDayYear; xx = (1 - eex * new NormalDistribution().cumulativeProbability(cpFlag * d1)); double corr = s1 / lambda * xx; QBlackScholes option = new QBlackScholes(tipoContrato, s1, volatModel, dividendRate, callPut, strike, daysToExpiration, rate, 0); double mBlackScholes = option.getPrima(); double rhs = mBlackScholes + cpFlag * corr; double lhs = cpFlag * (s1 - strike); zerror = lhs - rhs; double nd1 = zz * Math.exp(-0.5 * d1 * d1); //standard normal prob? double slope = cpFlag * (1 - 1 / lambda) * xx + 1 / lambda * (eex * nd1) * 1 / VltSqrDayYear; s1 = s1 - zerror / slope; } while (Math.abs(zerror) > 0.000001); double a = cpFlag * s1 / lambda * xx; switch (callPut) { case CALL: //Call if (underlyingValue >= s1) { prima = underlyingValue - strike; } else { prima += a * Math.pow((underlyingValue / s1), lambda); } break; case PUT: //Put if (underlyingValue <= s1) { prima = strike - underlyingValue; } else { prima += a * Math.pow((underlyingValue / s1), lambda); } //prima=10.1; break; } }
From source file:Main.java
public void paint(Graphics g, JComponent c) { JLabel label = (JLabel) c; String text = label.getText(); Icon icon = (label.isEnabled()) ? label.getIcon() : label.getDisabledIcon(); if ((icon == null) && (text == null)) { return;/* w w w. j av a2 s. com*/ } FontMetrics fm = g.getFontMetrics(); paintViewInsets = c.getInsets(paintViewInsets); paintViewR.x = paintViewInsets.left; paintViewR.y = paintViewInsets.top; // Use inverted height & width paintViewR.height = c.getWidth() - (paintViewInsets.left + paintViewInsets.right); paintViewR.width = c.getHeight() - (paintViewInsets.top + paintViewInsets.bottom); paintIconR.x = paintIconR.y = paintIconR.width = paintIconR.height = 0; paintTextR.x = paintTextR.y = paintTextR.width = paintTextR.height = 0; String clippedText = layoutCL(label, fm, text, icon, paintViewR, paintIconR, paintTextR); Graphics2D g2 = (Graphics2D) g; AffineTransform tr = g2.getTransform(); if (clockwise) { g2.rotate(Math.PI / 2); g2.translate(0, -c.getWidth()); } else { g2.rotate(-Math.PI / 2); g2.translate(-c.getHeight(), 0); } if (icon != null) { icon.paintIcon(c, g, paintIconR.x, paintIconR.y); } if (text != null) { int textX = paintTextR.x; int textY = paintTextR.y + fm.getAscent(); if (label.isEnabled()) { paintEnabledText(label, g, clippedText, textX, textY); } else { paintDisabledText(label, g, clippedText, textX, textY); } } g2.setTransform(tr); }