本文整理汇总了Java中org.ejml.data.Complex64F类的典型用法代码示例。如果您正苦于以下问题:Java Complex64F类的具体用法?Java Complex64F怎么用?Java Complex64F使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
Complex64F类属于org.ejml.data包,在下文中一共展示了Complex64F类的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: computeSolutions
import org.ejml.data.Complex64F; //导入依赖的package包/类
/**
* <p>
* Find the polynomial roots and for each root compute the Fundamental matrix.
* Given the two matrices it will compute an alpha such that the determinant is zero.<br>
*
* det(&alpha*F1 + (1-α)*F2 ) = 0
* </p>
*/
public void computeSolutions( FastQueue<DenseMatrix64F> solutions )
{
if( !rootFinder.process(poly))
return;
List<Complex64F> zeros = rootFinder.getRoots();
for( Complex64F c : zeros ) {
if( !c.isReal() && Math.abs(c.imaginary) > 1e-10 )
continue;
DenseMatrix64F F = solutions.grow();
double a = c.real;
double b = 1-c.real;
for( int i = 0; i < 9; i++ ) {
F.data[i] = a*F1.data[i] + b*F2.data[i];
}
// det(F) = 0 is already enforced, but for essential matrices it needs to enforce
// that the first two singular values are zero and the last one is zero
if( !computeFundamental && !projectOntoEssential(F) ) {
solutions.removeTail();
}
}
}
示例2: process
import org.ejml.data.Complex64F; //导入依赖的package包/类
/**
* Computes the essential matrix from point correspondences.
*
* @param points Input: List of points correspondences in normalized image coordinates
* @param solutions Output: Storage for the found solutions. .
* @return true for success or false if a fault has been detected
*/
public boolean process( List<AssociatedPair> points , FastQueue<DenseMatrix64F> solutions ) {
if( points.size() != 5 )
throw new IllegalArgumentException("Exactly 5 points are required, not "+points.size());
solutions.reset();
// Computes the 4-vector span which contains E. See equations 7-9
computeSpan(points);
// Construct a linear system based on the 10 constraint equations. See equations 5,6, and 10 .
helper.setNullSpace(X,Y,Z,W);
helper.setupA1(A1);
helper.setupA2(A2);
// instead of Gauss-Jordan elimination LU decomposition is used to solve the system
solver.setA(A1);
solver.solve(A2, C);
// construct the z-polynomial matrix. Equations 11-14
helper.setDeterminantVectors(C);
helper.extractPolynomial(poly.getCoefficients());
if( !findRoots.process(poly) )
return false;
for( Complex64F c : findRoots.getRoots() ) {
if( !c.isReal() )
continue;
solveForXandY(c.real);
DenseMatrix64F E = solutions.grow();
for( int i = 0; i < 9; i++ ) {
E.data[i] = x*X[i] + y*Y[i] + z*Z[i] + W[i];
}
}
return true;
}
示例3: magsqr
import org.ejml.data.Complex64F; //导入依赖的package包/类
public static double magsqr(Complex64F v){
return (v.real*v.real + v.imaginary*v.imaginary);
}
示例4: process
import org.ejml.data.Complex64F; //导入依赖的package包/类
/**
* @inheritDoc
*/
@Override
public boolean process( Point2D_F64 obs1 , Point2D_F64 obs2, Point2D_F64 obs3,
double length23 , double length13 , double length12 ) {
double cos12 = computeCosine(obs1,obs2);
double cos13 = computeCosine(obs1,obs3);
double cos23 = computeCosine(obs2,obs3);
double a = length23, b = length13, c = length12;
// divide out numbers before multiplying them. less overflow/underflow that way
double a2_div_b2 = (a/b)*(a/b);
double c2_div_b2 = (c/b)*(c/b);
double a2_m_c2_div_b2 = a2_div_b2 - c2_div_b2;
double a2_p_c2_div_b2 = a2_div_b2 + c2_div_b2;
poly.c[0] = -4*a2_div_b2*pow2(cos12) + pow2(a2_m_c2_div_b2 + 1);
poly.c[1] = 4*(-a2_m_c2_div_b2*(1 + a2_m_c2_div_b2)*cos13 + 2*a2_div_b2*pow2(cos12)*cos13 - (1-a2_p_c2_div_b2)*cos23*cos12);
poly.c[2] = 2*(pow2(a2_m_c2_div_b2) - 1 + 2*pow2(a2_m_c2_div_b2)*pow2(cos13) + 2*(1-c2_div_b2)*pow2(cos23) - 4*a2_p_c2_div_b2*cos12*cos13*cos23 + 2*(1-a2_div_b2)*pow2(cos12));
poly.c[3] = 4*(a2_m_c2_div_b2*(1-a2_m_c2_div_b2)*cos13 - (1 - a2_p_c2_div_b2)*cos23*cos12 + 2*c2_div_b2*pow2(cos23)*cos13);
poly.c[4] = -4*c2_div_b2*cos23*cos23 + pow2(a2_m_c2_div_b2 - 1);
// solve for real roots
solutions.reset();
if( !rootFinder.process(poly) )
return false;
List<Complex64F> roots = rootFinder.getRoots();
for( Complex64F r : roots ) {
if( !r.isReal() ) {
continue;
}
double v = r.real;
double u = ((-1 + a2_div_b2 - c2_div_b2)*v*v - 2*(a2_div_b2 - c2_div_b2)*cos13*v + 1 + a2_div_b2 - c2_div_b2)/
(2*(cos12 - v*cos23));
// compute the distance of each point
PointDistance3 s = solutions.grow();
s.dist1 = Math.sqrt(a*a/(u*u + v*v - 2*u*v*cos23));
s.dist2 = s.dist1*u;
s.dist3 = s.dist1*v;
}
return solutions.size() != 0;
}
示例5: process
import org.ejml.data.Complex64F; //导入依赖的package包/类
/**
* @inheritDoc
*/
public boolean process( Point2D_F64 obs1 , Point2D_F64 obs2, Point2D_F64 obs3,
double length23 , double length13 , double length12 ) {
solutions.reset();
cos12 = computeCosine(obs1,obs2); // cos(gama)
cos13 = computeCosine(obs1,obs3); // cos(beta)
cos23 = computeCosine(obs2,obs3); // cos(alpha)
double a = length23, b = length13, c = length12;
double a2_d_b2 = (a/b)*(a/b);
double c2_d_b2 = (c/b)*(c/b);
a2=a*a; b2=b*b; c2 = c*c;
// poly.c[0] = a2*(a2*pow2(sin13) - b2*pow2(sin23));
// poly.c[1] = b2*(b2-c2)*pow2(sin23) + a2*(a2 + 2*c2)*pow2(sin13) + 2*a2*b2*(-1 + cos23*cos13*cos12);
// poly.c[2] = b2*(b2-a2)*pow2(sin12) + c2*(c2 + 2*a2)*pow2(sin13) + 2*b2*c2*(-1 + cos23*cos13*cos12);
// poly.c[3] = c2*(c2*pow2(sin13) - b2*pow2(sin12) );
// Auto generated code + hand simplification. See P3PFinsterwalder.py I prefer it over the equations found
// in the paper (commented out above) since it does not require sin(theta).
poly.c[0] = a2*(a2*(1 - pow2(cos13)) + b2*(pow2(cos23) - 1));
poly.c[1] = 2*a2*b2*(cos12*cos13*cos23 - 1) + a2*(a2 + 2*c2)*(1 - pow2(cos13)) + b2*(b2 - c2)*( 1 - pow2(cos23));
poly.c[2] = 2*c2*b2*(cos12*cos13*cos23 - 1) + c2*(c2 + 2*a2)*(1 - pow2(cos13)) + b2*(b2 - a2)*( 1 - pow2(cos12));
poly.c[3] = c2*(b2*(pow2(cos12) - 1) + c2*( 1 - pow2(cos13)));
if( poly.computeDegree() < 0 )
return false;
if( !rootFinder.process(poly) )
return false;
// search for real roots
Complex64F root = null;
for( Complex64F r : rootFinder.getRoots() ) {
if( r.isReal() ) {
root = r;
break;
}
}
if( root == null )
return false;
double lambda = root.real;
double A = 1 + lambda;
double B = -cos23;
double C = 1 - a2_d_b2 - lambda*c2_d_b2;
double D = -lambda*cos12;
double E = (a2_d_b2 + lambda*c2_d_b2)*cos13;
double F = -a2_d_b2 + lambda*(1-c2_d_b2);
p = Math.sqrt(B*B - A*C);
q = Math.signum(B*E - C*D)*Math.sqrt(E*E - C*F);
computeU((-B+p)/C,(-E+q)/C);
computeU((-B-p)/C,(-E-q)/C);
return true;
}