Examples of transpose()

Examples of jpianotrain.staff.Note.transpose()

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        log.debug("Playing: "+o);
        nt=(Note)o;
        if (nt.getPitch()>=pit) {
          pit=nt.getPitch();
        } else {
          nt.transpose(12);
        }
        n[i]=nt;
      }
      MidiThread mt=MidiThread.getInstance();
      if (mt==null) {
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Examples of kodkod.engine.bool.BooleanMatrix.transpose()

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    final BooleanMatrix child = unaryExpr.expression().accept(this);
    final ExprOperator op = unaryExpr.op();

    switch(op) {
    case TRANSPOSE           : ret = child.transpose(); break;
    case CLOSURE             : ret = child.closure(); break;
    case REFLEXIVE_CLOSURE  : ret = child.closure().or(visit((ConstantExpression)Expression.IDEN)); break;
    default :
      throw new IllegalArgumentException("Unknown operator: " + op);
    }
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Examples of net.sourceforge.processdash.data.util.ResultSet.transpose()

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        if (parameters.get("h0") == null)
            parameters.put("h0", "Project/Task");
        ResultSet tableData = ResultSet.get(getDataRepository(), parameters,
            getPrefix(), getPSPProperties());
        if (parameters.get("transpose") != null)
            tableData = tableData.transpose();

        return tableData;
    }

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Examples of no.uib.cipr.matrix.DenseMatrix.transpose()

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    sparse.set(dense);

    for (Matrix m : Lists.newArrayList(dense, sparse)) {
      log.info("starting " + m.getClass());
      Matrix t = new DenseMatrix(m);
      t.transpose();
      Matrix o = new DenseMatrix(dense.numRows(), dense.numColumns());
      log.info("warming up " + m.getClass() + " " + o.getClass());
      for (int i = 0; i < 10; i++)
        m.mult(t, o);
      log.info("starting " + m.getClass() + " " + o.getClass());
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Examples of no.uib.cipr.matrix.Matrix.transpose()

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    sparse.set(dense);

    for (Matrix m : Lists.newArrayList(dense, sparse)) {
      log.info("starting " + m.getClass());
      Matrix t = new DenseMatrix(m);
      t.transpose();
      Matrix o = new DenseMatrix(dense.numRows(), dense.numColumns());
      log.info("warming up " + m.getClass() + " " + o.getClass());
      for (int i = 0; i < 10; i++)
        m.mult(t, o);
      log.info("starting " + m.getClass() + " " + o.getClass());
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Examples of org.apache.commons.math.linear.RealMatrix.transpose()

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    private void checkAEqualUSVt(RealMatrix matrix) {
        BiDiagonalTransformer transformer = new BiDiagonalTransformer(matrix);
        RealMatrix u = transformer.getU();
        RealMatrix b = transformer.getB();
        RealMatrix v = transformer.getV();
        double norm = u.multiply(b).multiply(v.transpose()).subtract(matrix).getNorm();
        Assert.assertEquals(0, norm, 1.0e-14);
    }

    @Test
    public void testUOrthogonal() {
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Examples of org.apache.commons.math.linear.RealMatrix.transpose()

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                }
            }
        }

        // Compute and return Hat matrix
        return Q.multiply(augI).multiply(Q.transpose());
    }

    /**
     * <p>Returns the sum of squared deviations of Y from its mean.</p>
     *
 
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Examples of org.apache.commons.math.linear.RealMatrix.transpose()

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    @Override
    protected RealMatrix calculateBetaVariance() {
        int p = X.getColumnDimension();
        RealMatrix Raug = qr.getR().getSubMatrix(0, p - 1 , 0, p - 1);
        RealMatrix Rinv = new LUDecompositionImpl(Raug).getSolver().getInverse();
        return Rinv.multiply(Rinv.transpose());
    }

}
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Examples of org.apache.commons.math.linear.RealMatrixImpl.transpose()

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                double[] bi = bData[i];
                for (int j = 0; j < b.getColumnDimension(); ++j) {
                    bi[j] = 1.0 + 0.1 * ++counter;
                }
            }
            RealMatrix bbt = b.multiply(b.transpose());
            covariance = new RealMatrixImpl(mean.length, mean.length);
            double[][] covData = covariance.getDataRef();
            for (int i = 0; i < covariance.getRowDimension(); ++i) {
                covData[i][i] = bbt.getEntry(i, i);
                for (int j = 0; j < covariance.getColumnDimension(); ++j) {
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Examples of org.apache.commons.math3.linear.Array2DRowRealMatrix.transpose()

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            for (int i = 0; i < n; i++) {
                for (int j = 0; j < k; j++) {
                    final RealMatrix vec
                        = new Array2DRowRealMatrix(MathArrays.ebeSubtract(data[i], newMeans[j]));
                    final RealMatrix dataCov
                        = vec.multiply(vec.transpose()).scalarMultiply(gamma[i][j]);
                    newCovMats[j] = newCovMats[j].add(dataCov);
                }
            }

            // Converting to arrays for use by fitted model
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