List of usage examples for org.apache.commons.math3.stat.descriptive.summary Sum Sum
public Sum()
From source file:com.itemanalysis.psychometrics.factoranalysis.PrincipalComponentsMethod.java
public double estimateParameters() { EigenDecomposition eigen = new EigenDecomposition(R); RealMatrix eigenVectors = eigen.getV().getSubMatrix(0, nVariables - 1, 0, nFactors - 1); double[] ev = new double[nFactors]; for (int i = 0; i < nFactors; i++) { ev[i] = Math.sqrt(eigen.getRealEigenvalue(i)); }// w w w .j a v a 2 s. c o m DiagonalMatrix evMatrix = new DiagonalMatrix(ev);//USE Apache version of Diagonal matrix when upgrade to version 3.2 RealMatrix LOAD = eigenVectors.multiply(evMatrix); //rotate factor loadings if (rotationMethod != RotationMethod.NONE) { GPArotation gpa = new GPArotation(); RotationResults results = gpa.rotate(LOAD, rotationMethod); LOAD = results.getFactorLoadings(); } Sum[] colSums = new Sum[nFactors]; Sum[] colSumsSquares = new Sum[nFactors]; for (int j = 0; j < nFactors; j++) { colSums[j] = new Sum(); colSumsSquares[j] = new Sum(); } factorLoading = new double[nVariables][nFactors]; communality = new double[nVariables]; uniqueness = new double[nVariables]; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { factorLoading[i][j] = LOAD.getEntry(i, j); colSums[j].increment(factorLoading[i][j]); colSumsSquares[j].increment(Math.pow(factorLoading[i][j], 2)); communality[i] += Math.pow(factorLoading[i][j], 2); } } //check sign of factor double sign = 1.0; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { if (colSums[j].getResult() < 0) { sign = -1.0; } else { sign = 1.0; } factorLoading[i][j] = factorLoading[i][j] * sign; } uniqueness[i] = 1.0 - communality[i]; } double totSumOfSquares = 0.0; sumsOfSquares = new double[nFactors]; proportionOfExplainedVariance = new double[nFactors]; proportionOfVariance = new double[nFactors]; for (int j = 0; j < nFactors; j++) { sumsOfSquares[j] = colSumsSquares[j].getResult(); totSumOfSquares += sumsOfSquares[j]; } for (int j = 0; j < nFactors; j++) { proportionOfExplainedVariance[j] = sumsOfSquares[j] / totSumOfSquares; proportionOfVariance[j] = sumsOfSquares[j] / nVariables; } return 0.0; }
From source file:com.itemanalysis.psychometrics.factoranalysis.GeneralizedLeastSquaresMethod.java
private void computeFactorLoadings(double[] x) { uniqueness = x;/*w w w . ja va 2s.c o m*/ communality = new double[nVariables]; for (int i = 0; i < nVariables; i++) { R.setEntry(i, i, 1.0 - x[i]); } EigenDecomposition E = new EigenDecomposition(R); RealMatrix L = E.getV().getSubMatrix(0, nVariables - 1, 0, nFactors - 1); double[] ev = new double[nFactors]; for (int i = 0; i < nFactors; i++) { ev[i] = Math.sqrt(E.getRealEigenvalue(i)); } DiagonalMatrix M = new DiagonalMatrix(ev); RealMatrix LOAD = L.multiply(M); //rotate factor loadings if (rotationMethod != RotationMethod.NONE) { GPArotation gpa = new GPArotation(); RotationResults results = gpa.rotate(LOAD, rotationMethod); LOAD = results.getFactorLoadings(); } Sum[] colSums = new Sum[nFactors]; Sum[] colSumsSquares = new Sum[nFactors]; for (int j = 0; j < nFactors; j++) { colSums[j] = new Sum(); colSumsSquares[j] = new Sum(); } factorLoading = new double[nVariables][nFactors]; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { factorLoading[i][j] = LOAD.getEntry(i, j); colSums[j].increment(factorLoading[i][j]); colSumsSquares[j].increment(Math.pow(factorLoading[i][j], 2)); communality[i] += Math.pow(factorLoading[i][j], 2); } } //check sign of factor double sign = 1.0; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { if (colSums[j].getResult() < 0) { sign = -1.0; } else { sign = 1.0; } factorLoading[i][j] = factorLoading[i][j] * sign; } } double totSumOfSquares = 0.0; sumsOfSquares = new double[nFactors]; proportionOfExplainedVariance = new double[nFactors]; proportionOfVariance = new double[nFactors]; for (int j = 0; j < nFactors; j++) { sumsOfSquares[j] = colSumsSquares[j].getResult(); totSumOfSquares += sumsOfSquares[j]; } for (int j = 0; j < nFactors; j++) { proportionOfExplainedVariance[j] = sumsOfSquares[j] / totSumOfSquares; proportionOfVariance[j] = sumsOfSquares[j] / nVariables; } }
From source file:com.itemanalysis.psychometrics.factoranalysis.MINRESmethod.java
private void computeFactorLoadings(double[] x) { uniqueness = x;/*from w w w . ja v a 2 s . c o m*/ communality = new double[nVariables]; double[] sqrtPsi = new double[nVariables]; double[] invSqrtPsi = new double[nVariables]; for (int i = 0; i < nVariables; i++) { sqrtPsi[i] = Math.sqrt(x[i]); invSqrtPsi[i] = 1.0 / Math.sqrt(x[i]); } DiagonalMatrix diagPsi = new DiagonalMatrix(x); DiagonalMatrix diagSqtPsi = new DiagonalMatrix(sqrtPsi); DiagonalMatrix diagInvSqrtPsi = new DiagonalMatrix(invSqrtPsi); RealMatrix Sstar = diagInvSqrtPsi.multiply(R2).multiply(diagInvSqrtPsi); EigenDecomposition E = new EigenDecomposition(Sstar); RealMatrix L = E.getV().getSubMatrix(0, nVariables - 1, 0, nFactors - 1); double[] ev = new double[nFactors]; for (int i = 0; i < nFactors; i++) { ev[i] = Math.sqrt(Math.max(E.getRealEigenvalue(i) - 1, 0)); } DiagonalMatrix M = new DiagonalMatrix(ev); RealMatrix LOAD2 = L.multiply(M); RealMatrix LOAD = diagSqtPsi.multiply(LOAD2); //rotate factor loadings if (rotationMethod != RotationMethod.NONE) { GPArotation gpa = new GPArotation(); RotationResults results = gpa.rotate(LOAD, rotationMethod); LOAD = results.getFactorLoadings(); } Sum[] colSums = new Sum[nFactors]; Sum[] colSumsSquares = new Sum[nFactors]; for (int j = 0; j < nFactors; j++) { colSums[j] = new Sum(); colSumsSquares[j] = new Sum(); } factorLoading = new double[nVariables][nFactors]; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { factorLoading[i][j] = LOAD.getEntry(i, j); colSums[j].increment(factorLoading[i][j]); colSumsSquares[j].increment(Math.pow(factorLoading[i][j], 2)); communality[i] += Math.pow(factorLoading[i][j], 2); } } //check sign of factor double sign = 1.0; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { if (colSums[j].getResult() < 0) { sign = -1.0; } else { sign = 1.0; } factorLoading[i][j] = factorLoading[i][j] * sign; } } double totSumOfSquares = 0.0; sumsOfSquares = new double[nFactors]; proportionOfExplainedVariance = new double[nFactors]; proportionOfVariance = new double[nFactors]; for (int j = 0; j < nFactors; j++) { sumsOfSquares[j] = colSumsSquares[j].getResult(); totSumOfSquares += sumsOfSquares[j]; } for (int j = 0; j < nFactors; j++) { proportionOfExplainedVariance[j] = sumsOfSquares[j] / totSumOfSquares; proportionOfVariance[j] = sumsOfSquares[j] / nVariables; } }
From source file:com.itemanalysis.psychometrics.factoranalysis.MaximumLikelihoodMethod.java
private void computeFactorLoadings(double[] x) { uniqueness = x;//w w w.ja v a2s . c o m communality = new double[nVariables]; double[] sqrtPsi = new double[nVariables]; double[] invSqrtPsi = new double[nVariables]; for (int i = 0; i < nVariables; i++) { sqrtPsi[i] = Math.sqrt(x[i]); invSqrtPsi[i] = 1.0 / Math.sqrt(x[i]); } DiagonalMatrix diagPsi = new DiagonalMatrix(x); DiagonalMatrix diagSqtPsi = new DiagonalMatrix(sqrtPsi); DiagonalMatrix diagInvSqrtPsi = new DiagonalMatrix(invSqrtPsi); RealMatrix Sstar = diagInvSqrtPsi.multiply(R).multiply(diagInvSqrtPsi); EigenDecomposition E = new EigenDecomposition(Sstar); RealMatrix L = E.getV().getSubMatrix(0, nVariables - 1, 0, nFactors - 1); double[] ev = new double[nFactors]; for (int i = 0; i < nFactors; i++) { ev[i] = Math.sqrt(Math.max(E.getRealEigenvalue(i) - 1, 0)); } DiagonalMatrix M = new DiagonalMatrix(ev); RealMatrix LOAD2 = L.multiply(M); RealMatrix LOAD = diagSqtPsi.multiply(LOAD2); //rotate factor loadings if (rotationMethod != RotationMethod.NONE) { GPArotation gpa = new GPArotation(); RotationResults results = gpa.rotate(LOAD, rotationMethod); LOAD = results.getFactorLoadings(); } Sum[] colSums = new Sum[nFactors]; Sum[] colSumsSquares = new Sum[nFactors]; for (int j = 0; j < nFactors; j++) { colSums[j] = new Sum(); colSumsSquares[j] = new Sum(); } factorLoading = new double[nVariables][nFactors]; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { factorLoading[i][j] = LOAD.getEntry(i, j); colSums[j].increment(factorLoading[i][j]); colSumsSquares[j].increment(Math.pow(factorLoading[i][j], 2)); communality[i] += Math.pow(factorLoading[i][j], 2); } } //check sign of factor double sign = 1.0; for (int i = 0; i < nVariables; i++) { for (int j = 0; j < nFactors; j++) { if (colSums[j].getResult() < 0) { sign = -1.0; } else { sign = 1.0; } factorLoading[i][j] = factorLoading[i][j] * sign; } } double totSumOfSquares = 0.0; sumsOfSquares = new double[nFactors]; proportionOfExplainedVariance = new double[nFactors]; proportionOfVariance = new double[nFactors]; for (int j = 0; j < nFactors; j++) { sumsOfSquares[j] = colSumsSquares[j].getResult(); totSumOfSquares += sumsOfSquares[j]; } for (int j = 0; j < nFactors; j++) { proportionOfExplainedVariance[j] = sumsOfSquares[j] / totSumOfSquares; proportionOfVariance[j] = sumsOfSquares[j] / nVariables; } }
From source file:fiji.plugin.trackmate.action.brownianmotion.WalkerMethodEstimator.java
private double[] getHistogramML(double[] pm) { double[] histMl = new double[histBinNumber]; Sum sum = new Sum(); for (int b = 0; b < histMl.length; b++) { double outersum = 0; for (int k = minTrackLength; k <= maxTrackLength; k++) { double sumpm = sum.evaluate(pm); double innersum = 0; for (int m = 0; m < pm.length; m++) { innersum += (probMSD((b + 1) * deltaB, k, (m + 1) * deltaR) * deltaB * pm[m]) / sumpm; }/* w w w. ja v a 2 s.c om*/ outersum += Nk[k] * innersum; } histMl[b] = outersum; } return histMl; }
From source file:de.biomedical_imaging.ij.nanotrackj.WalkerMethodEstimator.java
private double[] getHistogramML(double[] pm) { double[] histMl = new double[histBinNumber]; Sum sum = new Sum(); for (int b = 0; b < histMl.length; b++) { double outersum = 0; for (int k = kMin; k <= kMax; k++) { double sumpm = sum.evaluate(pm); double innersum = 0; for (int m = 0; m < pm.length; m++) { innersum += (probMSD((b + 1) * deltaB, k, (m + 1) * deltaR) * deltaB * pm[m]) / sumpm; }/*from w w w .j a va2 s .c om*/ outersum += Nk[k] * innersum; } histMl[b] = outersum; } return histMl; }
From source file:de.biomedical_imaging.ij.nanotrackj.WalkerMethodEstimator.java
/** * //from w w w .jav a2 s. c o m * @return Histogram [i][j]: i = bin, j = density */ public double[][] estimate() { double[] dens = new double[binNumber]; java.util.Arrays.fill(dens, 1.0 / binNumber); Sum sum = new Sum(); //IJ.log(""+dens[2]); lastChiSquared = getChiSquared(dens); double changeChiSquared = Double.MAX_VALUE; IJ.showStatus("Size Distribution Estimation by Walker's Method"); while (changeChiSquared > 0.01) { IJ.showProgress((int) ((1 - changeChiSquared) * 100), 99); for (int m = 0; m < dens.length; m++) { double sumpm = sum.evaluate(dens); double help2 = 0; for (int k = 0; k < data.length; k++) { double help1 = 0; double prob = probMSD(data[k][0], data[k][1], (m + 1) * deltaR); for (int l = 0; l < dens.length; l++) { double prob2 = probMSD(data[k][0], data[k][1], (l + 1) * deltaR); help1 += prob2 * dens[l] / sumpm; } help2 = help2 + prob / help1; } dens[m] = dens[m] * 1.0 / data.length * help2; } double newChiSquared = getChiSquared(dens); changeChiSquared = Math.abs(newChiSquared - lastChiSquared) / lastChiSquared; lastChiSquared = newChiSquared; } IJ.showProgress(99, 99); //Normalize double sumdens = sum.evaluate(dens); double[][] densxy = new double[dens.length][2]; for (int i = 0; i < dens.length; i++) { densxy[i][0] = binSizeInnm * (i + 1) * 2.0; //To Diamter in [nm] dens[i] = dens[i] / sumdens; //Normalize densxy[i][1] = dens[i]; } return densxy; }
From source file:com.udojava.evalex.Expression.java
/** * Creates a new expression instance from an expression string with a given * default match context./* ww w . j a v a 2 s . co m*/ * * @param expression The expression. E.g. <code>"2.4*sin(3)/(2-4)"</code> or * <code>"sin(y)>0 & max(z, 3)>3"</code> */ public Expression(String expression, LinkedList<String> hist, Variables vars) { this.history = hist; this.expression = expression; mainVars = vars; addOperator(new Operator("+", 20, true, "Addition") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.ARRAY) { MyComplex vo = new MyComplex(v1.list); vo.list.add(v2); return vo; } return v1.add(v2); } }); addOperator(new Operator("-", 20, true, "Subtraction") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.ARRAY) { MyComplex vo = new MyComplex(v1.list); vo.list.removeIf(o -> o.equals(v2)); return vo; } return v1.subtract(v2); } }); addOperator(new Operator("*", 30, true, "Real number multiplication") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return v1.multiply(v2); } }); addOperator(new Operator("/", 30, true, "Real number division") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return v1.divide(v2); } }); addOperator(new Operator("%", 30, true, "Remainder of integer division") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { double r = v1.real % v2.real; return new MyComplex(r); } }); addOperator( new Operator("^", 40, false, "Exponentation. See: https://en.wikipedia.org/wiki/Exponentiation") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return v1.pow(v2); } }); addOperator(new Operator("&&", 4, false, "Logical AND. Evaluates to 1 if both operands are not 0") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { boolean b1 = (v1.real == 0.0 && v2.real == 0.0); return new MyComplex(b1 ? 1 : 0); } }); addOperator(new Operator("||", 2, false, "Logical OR. Evaluates to 0 if both operands are 0") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { boolean b1 = (v1.real == 0.0 && v2.real == 0.0); return new MyComplex(b1 ? 0 : 1); } }); addOperator(new Operator(">", 10, false, "Greater than. See: See: https://en.wikipedia.org/wiki/Inequality_(mathematics)") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real > v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() > v2.abs() ? 1 : 0); } } }); addOperator(new Operator(">=", 10, false, "Greater or equal") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real >= v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() >= v2.abs() ? 1 : 0); } } }); addOperator(new Operator("<", 10, false, "Less than. See: https://en.wikipedia.org/wiki/Inequality_(mathematics)") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real < v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() < v2.abs() ? 1 : 0); } } }); addOperator(new Operator("<=", 10, false, "less or equal") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real <= v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() <= v2.abs() ? 1 : 0); } } }); addOperator(new Operator("->", 7, false, "Set variable v to new value ") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1 instanceof PitDecimal) { PitDecimal target = (PitDecimal) v1; String s = target.getVarToken(); setVariable(s, v2); return v2; } throw new ExpressionException("LHS not variable"); } }); addOperator(new Operator("=", 7, false, "Equality") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real == v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() == v2.abs() ? 1 : 0); } } }); addOperator(new Operator("!=", 7, false, "Inequality. See: https://en.wikipedia.org/wiki/Inequality_(mathematics)") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { if (v1.type == ValueType.REAL && v2.type == ValueType.REAL) { return new MyComplex(v1.real != v2.real ? 1 : 0); } else { return new MyComplex(v1.abs() != v2.abs() ? 1 : 0); } } }); addOperator( new Operator("or", 7, false, "Bitwise OR. See: https://en.wikipedia.org/wiki/Logical_disjunction") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return new MyComplex((long) v1.real | (long) v2.real); } }); addOperator(new Operator("and", 7, false, "Bitwise AND. See: https://en.wikipedia.org/wiki/Logical_conjunction") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return new MyComplex((long) v1.real & (long) v2.real); } }); addOperator(new Operator("xor", 7, false, "Bitwise XOR, See: https://en.wikipedia.org/wiki/Exclusive_or") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return new MyComplex((long) v1.real ^ (long) v2.real); } }); addOperator(new Operator("!", 50, true, "Factorial. See https://en.wikipedia.org/wiki/Factorial") { public BigInteger factorial(long n) { BigInteger factorial = BigInteger.ONE; for (long i = 1; i <= n; i++) { factorial = factorial.multiply(BigInteger.valueOf(i)); } return factorial; } @Override public MyComplex eval(MyComplex v1, MyComplex v2) { BigInteger fact = factorial((long) v1.real); return new MyComplex(fact, BigInteger.ZERO); } }); addOperator(new Operator("~", 8, false, "Bitwise negation") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { BigInteger bi = v2.toBigIntegerReal(); int c = bi.bitLength(); if (c == 0) { return new MyComplex(1); } for (int s = 0; s < c; s++) { bi = bi.flipBit(s); } return new MyComplex(bi); } }); addOperator(new Operator("shl", 8, false, "Left Bit shift") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return new MyComplex((long) v1.real << (long) v2.real); } }); addOperator(new Operator("shr", 8, false, "Right bit shift") { @Override public MyComplex eval(MyComplex v1, MyComplex v2) { return new MyComplex((long) v1.real >>> (long) v2.real); } }); addFunction(new Function("NOT", 1, "evaluates to 0 if argument != 0") { @Override public MyComplex eval(List<MyComplex> parameters) { boolean zero = parameters.get(0).abs() == 0; return new MyComplex(zero ? 1 : 0); } }); addFunction(new Function("RND", 2, "Give random number in the range between first and second argument") { @Override public MyComplex eval(List<MyComplex> parameters) { double low = parameters.get(0).real; double high = parameters.get(1).real; return new MyComplex(low + Math.random() * (high - low)); } }); MersenneTwister mers = new MersenneTwister(System.nanoTime()); addFunction(new Function("MRS", 0, "Mersenne twister random generator") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(mers.nextDouble()); } }); addFunction(new Function("BIN", 2, "Binomial Coefficient 'n choose k'") { @Override public MyComplex eval(List<MyComplex> parameters) { int n = (int) parameters.get(0).real; int k = (int) parameters.get(1).real; double d = CombinatoricsUtils.binomialCoefficientDouble(n, k); return new MyComplex(d); } }); addFunction(new Function("STIR", 2, "Stirling number of 2nd kind: http://mathworld.wolfram.com/StirlingNumberoftheSecondKind.html") { @Override public MyComplex eval(List<MyComplex> parameters) { int n = (int) parameters.get(0).real; int k = (int) parameters.get(1).real; double d = CombinatoricsUtils.stirlingS2(n, k); return new MyComplex(d); } }); addFunction(new Function("SIN", 1, "Sine function") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).sin(); } }); addFunction(new Function("COS", 1, "Cosine function") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).cos(); } }); addFunction(new Function("TAN", 1, "Tangent") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).tan(); } }); addFunction(new Function("ASIN", 1, "Reverse Sine") { // added by av @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).asin(); } }); addFunction(new Function("ACOS", 1, "Reverse Cosine") { // added by av @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).acos(); } }); addFunction(new Function("ATAN", 1, "Reverse Tangent") { // added by av @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).atan(); } }); addFunction(new Function("SINH", 1, "Hyperbolic Sine") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).sinh(); } }); addFunction(new Function("COSH", 1, "Hyperbolic Cosine") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).cosh(); } }); addFunction(new Function("TANH", 1, "Hyperbolic Tangent") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).tanh(); } }); addFunction(new Function("RAD", 1, "Transform degree to radian") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.toRadians(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("DEG", 1, "Transform radian to degree") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.toDegrees(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("MAX", -1, "Find the biggest value in a list") { @Override public MyComplex eval(List<MyComplex> parameters) { MyComplex save = new MyComplex(Double.MIN_VALUE); if (parameters.size() == 0) { throw new ExpressionException("MAX requires at least one parameter"); } // if (parameters.get(0).type == ValueType.ARRAY) // parameters = parameters.get(0).list; if (parameters.get(0).type == ValueType.COMPLEX) { for (MyComplex parameter : parameters) { if (parameter.abs() > save.abs()) { save = parameter; } } save.type = ValueType.COMPLEX; } else { for (MyComplex parameter : parameters) { if (parameter.real > save.real) { save = parameter; } } save.type = ValueType.REAL; } return save; } }); /////////////////////////////////////////////////////// addFunction(new Function("IF", 3, "Conditional: give param3 if param1 is 0, otherwise param2") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.get(0).real == 0.0) { return parameters.get(2); } return parameters.get(1); } }); addFunction(new Function("PERC", 2, "Get param1 percent of param2") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).divide(new MyComplex(100)).multiply(parameters.get(1)); } }); addFunction(new Function("PER", 2, "How many percent is param1 of param2") { @Override public MyComplex eval(List<MyComplex> parameters) { return parameters.get(0).multiply(new MyComplex(100)).divide(parameters.get(1)); } }); addFunction(new Function("H", 1, "Evaluate _history element") { @Override public MyComplex eval(List<MyComplex> parameters) { int i = (int) parameters.get(0).real; Expression ex = new Expression(history.get(i), history, mainVars); return ex.eval(); } }); addFunction(new Function("MERS", 1, "Calculate Mersenne Number") { @Override public MyComplex eval(List<MyComplex> parameters) { MyComplex p = parameters.get(0); return new MyComplex(2).pow(p).subtract(new MyComplex(1)); } }); addFunction(new Function("GCD", 2, "Find greatest common divisor of 2 values") { @Override public MyComplex eval(List<MyComplex> parameters) { double a = parameters.get(0).real; double b = parameters.get(1).real; long r = ArithmeticUtils.gcd((long) a, (long) b); return new MyComplex(r); } }); addFunction(new Function("LCM", 2, "Find least common multiple of 2 values") { @Override public MyComplex eval(List<MyComplex> parameters) { double a = parameters.get(0).real; double b = parameters.get(1).real; long r = ArithmeticUtils.lcm((long) a, (long) b); return new MyComplex(r); } }); addFunction(new Function("AMEAN", -1, "Arithmetic mean of a set of values") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.size() == 0) { throw new ExpressionException("MEAN requires at least one parameter"); } Mean m = new Mean(); double[] d = MyComplex.getRealArray(parameters); double d2 = m.evaluate(d); return new MyComplex(d2); } }); // addFunction(new Function("BYT", -1, // "Value from sequence of bytes") // { // @Override // public MyComplex eval (List<MyComplex> parameters) // { // if (parameters.size() == 0) // { // return MyComplex.ZERO; // } // BigInteger res = BigInteger.ZERO; // for (MyComplex parameter : parameters) // { // if (parameter.intValue() < 0 || parameter.intValue() > 255) // { // throw new ExpressionException("not a byte value"); // } // res = res.shiftLeft(8); // res = res.or(parameter.toBigInteger()); // } // return new MyComplex(res, BigInteger.ZERO); // } // }); addFunction(new Function("SEQ", 3, "Generate Sequence p1=start, p2=step, p3=count") { @Override public MyComplex eval(List<MyComplex> parameters) { double start = parameters.get(0).real; ArrayList<MyComplex> arr = new ArrayList<>(); for (int s = 0; s < (int) (parameters.get(2).real); s++) { arr.add(new MyComplex(start)); start += parameters.get(1).real; } return new MyComplex(arr); } }); addFunction(new Function("PROD", -1, "Product of real values") { @Override public MyComplex eval(List<MyComplex> parameters) { Product p = new Product(); double[] d = MyComplex.getRealArray(parameters); return new MyComplex(p.evaluate(d)); } }); addFunction(new Function("SUM", -1, "Sum of values") { @Override public MyComplex eval(List<MyComplex> parameters) { Sum p = new Sum(); double[] d = MyComplex.getRealArray(parameters); return new MyComplex(p.evaluate(d)); } }); addFunction(new Function("ANG", 1, "Angle phi of complex number in radians") { @Override public MyComplex eval(List<MyComplex> parameters) { double b = parameters.get(0).angle(); return new MyComplex(b); } }); addFunction(new Function("IM", 1, "Get imaginary part") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(parameters.get(0).imaginary); } }); addFunction(new Function("RE", 1, "Get real part") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(parameters.get(0).real); } }); addFunction(new Function("POL", 2, "Make complex number from polar coords. angle is first arg") { @Override public MyComplex eval(List<MyComplex> parameters) { double angle = parameters.get(0).real; double len = parameters.get(1).real; Complex c = ComplexUtils.polar2Complex(len, angle); return new MyComplex(c); } }); addFunction(new Function("GMEAN", -1, "Geometric mean of a set of values") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.size() == 0) { throw new ExpressionException("MEAN requires at least one parameter"); } GeometricMean m = new GeometricMean(); double[] d = MyComplex.getRealArray(parameters); double d2 = m.evaluate(d); return new MyComplex(d2); } }); addFunction(new Function("HMEAN", -1, "Harmonic mean of a set of values") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.size() == 0) { throw new ExpressionException("MEAN requires at least one parameter"); } MyComplex res = new MyComplex(0); int num = 0; for (MyComplex parameter : parameters) { res = res.add(new MyComplex(1).divide(parameter)); num++; } res = new MyComplex(res.abs()); return new MyComplex(num).divide(res); } }); addFunction(new Function("VAR", -1, "Variance of a set of values") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.size() == 0) { throw new ExpressionException("MEAN requires at least one parameter"); } double[] arr = new double[parameters.size()]; for (int s = 0; s < parameters.size(); s++) { arr[s] = parameters.get(s).real; } return new MyComplex(variance(arr)); } }); addFunction(new Function("NPR", 1, "Next prime number greater or equal the argument") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(nextPrime((int) parameters.get(0).real)); } }); addFunction(new Function("NSWP", 1, "Swap nibbles") { @Override public MyComplex eval(List<MyComplex> parameters) { BigInteger bi = parameters.get(0).toBigIntegerReal(); String s = bi.toString(16); s = new StringBuilder(s).reverse().toString(); return new MyComplex(new BigInteger(s, 16), BigInteger.ZERO); } }); addFunction(new Function("BSWP", 1, "Swap bytes") { @Override public MyComplex eval(List<MyComplex> parameters) { BigInteger bi = parameters.get(0).toBigIntegerReal(); String s = bi.toString(16); while (s.length() % 4 != 0) { s = s + "0"; } if (bi.intValue() < 256) { s = "00" + s; } s = Misc.reverseHex(s); return new MyComplex(new BigInteger(s, 16), BigInteger.ZERO); } }); addFunction(new Function("PYT", 2, "Pythagoras's result = sqrt(param1^2+param2^2) https://en.wikipedia.org/wiki/Pythagorean_theorem") { @Override public MyComplex eval(List<MyComplex> par) { double a = par.get(0).real; double b = par.get(1).real; return new MyComplex(Math.sqrt(a * a + b * b)); } }); addFunction(new Function("FIB", 1, "Fibonacci number") { // --Commented out by Inspection (2/19/2017 7:46 PM):private final Operator exp = operators.get("^"); @Override public MyComplex eval(List<MyComplex> par) { return Misc.iterativeFibonacci((int) par.get(0).real); } }); /////////////////////////////////////////////// addFunction(new Function("MIN", -1, "Find the smallest in a list of values") { @Override public MyComplex eval(List<MyComplex> parameters) { MyComplex save = new MyComplex(Double.MAX_VALUE); if (parameters.size() == 0) { throw new ExpressionException("MAX requires at least one parameter"); } if (parameters.get(0).type == ValueType.COMPLEX) { for (MyComplex parameter : parameters) { if (parameter.abs() < save.abs()) { save = parameter; } } save.type = ValueType.COMPLEX; } else { for (MyComplex parameter : parameters) { if (parameter.real < save.real) { save = parameter; } } save.type = ValueType.REAL; } return save; } }); addFunction(new Function("ABS", 1, "Get absolute value of a number") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(parameters.get(0).abs()); } }); addFunction(new Function("LN", 1, "Logarithm base e of the argument") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.log(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("LOG", 1, "Logarithm base 10 of the argument") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.log10(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("FLOOR", 1, "Rounds DOWN to nearest Integer") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.floor(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("CEIL", 1, "Rounds UP to nearest Integer") { @Override public MyComplex eval(List<MyComplex> parameters) { double d = Math.ceil(parameters.get(0).real); return new MyComplex(d); } }); addFunction(new Function("ROU", 1, "Rounds to nearest Integer") { @Override public MyComplex eval(List<MyComplex> parameters) { int d = (int) (parameters.get(0).real + 0.5); return new MyComplex(d); } }); addFunction(new Function("SQRT", 1, "Square root") { @Override public MyComplex eval(List<MyComplex> parameters) { MyComplex p = parameters.get(0); if (p.type == ValueType.REAL) { return new MyComplex(Math.sqrt(p.real)); } return p.sqrt(); } }); addFunction(new Function("ARR", -1, "Create array") { @Override public MyComplex eval(List<MyComplex> parameters) { return new MyComplex(parameters); } }); addFunction(new Function("POLY", -1, "Treat array as Polynom") { @Override public MyComplex eval(List<MyComplex> parameters) { double[] d = MyComplex.getRealArray(parameters); PolynomialFunction p = new PolynomialFunction(d); return new MyComplex(p); } }); addFunction(new Function("DRVE", -1, "Make derivative of polynomial") { @Override public MyComplex eval(List<MyComplex> parameters) { PolynomialFunction p; if (parameters.get(0).isPoly()) { p = new PolynomialFunction(parameters.get(0).getRealArray()); } else { double[] d = MyComplex.getRealArray(parameters); p = new PolynomialFunction(d); } return new MyComplex(p.polynomialDerivative()); } }); addFunction(new Function("ADRVE", -1, "Make antiderivative of polynomial. Constant is always zero") { @Override public MyComplex eval(List<MyComplex> parameters) { PolynomialFunction p; if (parameters.get(0).isPoly()) { p = new PolynomialFunction(parameters.get(0).getRealArray()); } else { double[] d = MyComplex.getRealArray(parameters); p = new PolynomialFunction(d); } return new MyComplex(Misc.antiDerive(p)); } }); addFunction(new Function("PVAL", 2, "Compute value of polynom for the given argument.") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.get(0).isPoly()) { PolynomialFunction p = new PolynomialFunction(parameters.get(0).getRealArray()); double v = p.value(parameters.get(1).real); return new MyComplex(v); } throw new ExpressionException("first arg must be polynomial"); } }); addFunction(new Function("INTGR", 3, "Numerical integration") { @Override public MyComplex eval(List<MyComplex> parameters) { if (parameters.get(0).isPoly()) { PolynomialFunction p = new PolynomialFunction(parameters.get(0).getRealArray()); double start = parameters.get(1).real; double end = parameters.get(2).real; SimpsonIntegrator si = new SimpsonIntegrator(); double d = si.integrate(1000, p, start, end); return new MyComplex(d); } throw new ExpressionException("first arg must be polynomial"); } }); }
From source file:org.apereo.portal.events.aggr.JpaStatisticalSummaryTest.java
@Ignore @Test// www . j a v a 2 s. com public void testSummaryStatisticsJson() throws Exception { final SecondMoment secondMoment = new SecondMoment(); final Sum sum = new Sum(); final SumOfSquares sumsq = new SumOfSquares(); final Min min = new Min(); final Max max = new Max(); final SumOfLogs sumLog = new SumOfLogs(); final Random r = new Random(0); for (int i = 0; i < 10; i++) { final int nextInt = r.nextInt(100000000); secondMoment.increment(nextInt); sum.increment(nextInt); sumsq.increment(nextInt); min.increment(nextInt); max.increment(nextInt); sumLog.increment(nextInt); } testStorelessUnivariateStatistic(secondMoment, 7.513432791665536E15); testStorelessUnivariateStatistic(sum, 6.01312177E8); testStorelessUnivariateStatistic(sumsq, 4.3671066212513456E16); testStorelessUnivariateStatistic(min, 2116447.0); testStorelessUnivariateStatistic(max, 8.5505948E7); testStorelessUnivariateStatistic(sumLog, 175.91713800250577); }
From source file:org.apereo.portal.events.aggr.stat.JpaStatisticalSummary.java
private Sum _getSum() { if (this.sum == null) { this.sum = new Sum(); }/* w w w .j a va2 s . c om*/ return this.sum; }