cern.colt.matrix.linalg.LUDecompositionQuick Java Examples
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cern.colt.matrix.linalg.LUDecompositionQuick.
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Example #1
Source File: TestMatrix2D.java From database with GNU General Public License v2.0 | 4 votes |
/** */ public static void doubleTest23(int runs, int size, double nonZeroFraction, boolean dense) { System.out.println("\n\n"); System.out.println("initializing..."); DoubleMatrix2D A, LU, I, Inv; DoubleMatrix1D b, solved; double mean = 5.0; double stdDev = 3.0; cern.jet.random.Normal random = new cern.jet.random.Normal(mean, stdDev, new cern.jet.random.engine.MersenneTwister()); System.out.println("sampling..."); double value = 2; if (dense) A = Factory2D.dense.sample(size,size, value, nonZeroFraction); else A = Factory2D.sparse.sample(size,size, value, nonZeroFraction); b = A.like1D(size).assign(1); //A.assign(random); //A.assign(F.rint); // round System.out.println("generating invertible matrix..."); Property.generateNonSingular(A); //I = Factory2D.identity(size); LU = A.like(); solved = b.like(); //Inv = Factory2D.make(size,size); LUDecompositionQuick lu = new LUDecompositionQuick(); System.out.println("benchmarking assignment..."); cern.colt.Timer timer = new cern.colt.Timer().start(); LU.assign(A); solved.assign(b); timer.stop().display(); LU.assign(A); lu.decompose(LU); System.out.println("benchmarking LU..."); timer.reset().start(); for (int i=runs; --i >=0; ) { solved.assign(b); //Inv.assign(I); //lu.decompose(LU); lu.solve(solved); //lu.solve(Inv); } timer.stop().display(); //System.out.println("A="+A); //System.out.println("LU="+LU); //System.out.println("U="+lu.getU()); //System.out.println("L="+lu.getL()); System.out.println("done."); }
Example #2
Source File: TestMatrix2D.java From jAudioGIT with GNU Lesser General Public License v2.1 | 4 votes |
/** */ public static void doubleTest23(int runs, int size, double nonZeroFraction, boolean dense) { System.out.println("\n\n"); System.out.println("initializing..."); DoubleMatrix2D A, LU, I, Inv; DoubleMatrix1D b, solved; double mean = 5.0; double stdDev = 3.0; cern.jet.random.Normal random = new cern.jet.random.Normal(mean, stdDev, new cern.jet.random.engine.MersenneTwister()); System.out.println("sampling..."); double value = 2; if (dense) A = Factory2D.dense.sample(size,size, value, nonZeroFraction); else A = Factory2D.sparse.sample(size,size, value, nonZeroFraction); b = A.like1D(size).assign(1); //A.assign(random); //A.assign(F.rint); // round System.out.println("generating invertible matrix..."); Property.generateNonSingular(A); //I = Factory2D.identity(size); LU = A.like(); solved = b.like(); //Inv = Factory2D.make(size,size); LUDecompositionQuick lu = new LUDecompositionQuick(); System.out.println("benchmarking assignment..."); cern.colt.Timer timer = new cern.colt.Timer().start(); LU.assign(A); solved.assign(b); timer.stop().display(); LU.assign(A); lu.decompose(LU); System.out.println("benchmarking LU..."); timer.reset().start(); for (int i=runs; --i >=0; ) { solved.assign(b); //Inv.assign(I); //lu.decompose(LU); lu.solve(solved); //lu.solve(Inv); } timer.stop().display(); //System.out.println("A="+A); //System.out.println("LU="+LU); //System.out.println("U="+lu.getU()); //System.out.println("L="+lu.getL()); System.out.println("done."); }