#include "blaswrap.h"
#include "f2c.h"

/* Subroutine */ int claesy_(complex *a, complex *b, complex *c__, complex *
	rt1, complex *rt2, complex *evscal, complex *cs1, complex *sn1)
{
/*  -- LAPACK auxiliary routine (version 3.1) --   
       Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..   
       November 2006   


    Purpose   
    =======   

    CLAESY computes the eigendecomposition of a 2-by-2 symmetric matrix   
       ( ( A, B );( B, C ) )   
    provided the norm of the matrix of eigenvectors is larger than   
    some threshold value.   

    RT1 is the eigenvalue of larger absolute value, and RT2 of   
    smaller absolute value.  If the eigenvectors are computed, then   
    on return ( CS1, SN1 ) is the unit eigenvector for RT1, hence   

    [  CS1     SN1   ] . [ A  B ] . [ CS1    -SN1   ] = [ RT1  0  ]   
    [ -SN1     CS1   ]   [ B  C ]   [ SN1     CS1   ]   [  0  RT2 ]   

    Arguments   
    =========   

    A       (input) COMPLEX   
            The ( 1, 1 ) element of input matrix.   

    B       (input) COMPLEX   
            The ( 1, 2 ) element of input matrix.  The ( 2, 1 ) element   
            is also given by B, since the 2-by-2 matrix is symmetric.   

    C       (input) COMPLEX   
            The ( 2, 2 ) element of input matrix.   

    RT1     (output) COMPLEX   
            The eigenvalue of larger modulus.   

    RT2     (output) COMPLEX   
            The eigenvalue of smaller modulus.   

    EVSCAL  (output) COMPLEX   
            The complex value by which the eigenvector matrix was scaled   
            to make it orthonormal.  If EVSCAL is zero, the eigenvectors   
            were not computed.  This means one of two things:  the 2-by-2   
            matrix could not be diagonalized, or the norm of the matrix   
            of eigenvectors before scaling was larger than the threshold   
            value THRESH (set below).   

    CS1     (output) COMPLEX   
    SN1     (output) COMPLEX   
            If EVSCAL .NE. 0,  ( CS1, SN1 ) is the unit right eigenvector   
            for RT1.   

   =====================================================================   



       Special case:  The matrix is actually diagonal.   
       To avoid divide by zero later, we treat this case separately. */
    /* Table of constant values */
    static complex c_b1 = {1.f,0.f};
    static integer c__2 = 2;
    
    /* System generated locals */
    real r__1, r__2;
    complex q__1, q__2, q__3, q__4, q__5, q__6, q__7;
    /* Builtin functions */
    double c_abs(complex *);
    void pow_ci(complex *, complex *, integer *), c_sqrt(complex *, complex *)
	    , c_div(complex *, complex *, complex *);
    /* Local variables */
    static complex s, t;
    static real z__;
    static complex tmp;
    static real babs, tabs, evnorm;



    if (c_abs(b) == 0.f) {
	rt1->r = a->r, rt1->i = a->i;
	rt2->r = c__->r, rt2->i = c__->i;
	if (c_abs(rt1) < c_abs(rt2)) {
	    tmp.r = rt1->r, tmp.i = rt1->i;
	    rt1->r = rt2->r, rt1->i = rt2->i;
	    rt2->r = tmp.r, rt2->i = tmp.i;
	    cs1->r = 0.f, cs1->i = 0.f;
	    sn1->r = 1.f, sn1->i = 0.f;
	} else {
	    cs1->r = 1.f, cs1->i = 0.f;
	    sn1->r = 0.f, sn1->i = 0.f;
	}
    } else {

/*        Compute the eigenvalues and eigenvectors.   
          The characteristic equation is   
             lambda **2 - (A+C) lambda + (A*C - B*B)   
          and we solve it using the quadratic formula. */

	q__2.r = a->r + c__->r, q__2.i = a->i + c__->i;
	q__1.r = q__2.r * .5f, q__1.i = q__2.i * .5f;
	s.r = q__1.r, s.i = q__1.i;
	q__2.r = a->r - c__->r, q__2.i = a->i - c__->i;
	q__1.r = q__2.r * .5f, q__1.i = q__2.i * .5f;
	t.r = q__1.r, t.i = q__1.i;

/*        Take the square root carefully to avoid over/under flow. */

	babs = c_abs(b);
	tabs = c_abs(&t);
	z__ = dmax(babs,tabs);
	if (z__ > 0.f) {
	    q__5.r = t.r / z__, q__5.i = t.i / z__;
	    pow_ci(&q__4, &q__5, &c__2);
	    q__7.r = b->r / z__, q__7.i = b->i / z__;
	    pow_ci(&q__6, &q__7, &c__2);
	    q__3.r = q__4.r + q__6.r, q__3.i = q__4.i + q__6.i;
	    c_sqrt(&q__2, &q__3);
	    q__1.r = z__ * q__2.r, q__1.i = z__ * q__2.i;
	    t.r = q__1.r, t.i = q__1.i;
	}

/*        Compute the two eigenvalues.  RT1 and RT2 are exchanged   
          if necessary so that RT1 will have the greater magnitude. */

	q__1.r = s.r + t.r, q__1.i = s.i + t.i;
	rt1->r = q__1.r, rt1->i = q__1.i;
	q__1.r = s.r - t.r, q__1.i = s.i - t.i;
	rt2->r = q__1.r, rt2->i = q__1.i;
	if (c_abs(rt1) < c_abs(rt2)) {
	    tmp.r = rt1->r, tmp.i = rt1->i;
	    rt1->r = rt2->r, rt1->i = rt2->i;
	    rt2->r = tmp.r, rt2->i = tmp.i;
	}

/*        Choose CS1 = 1 and SN1 to satisfy the first equation, then   
          scale the components of this eigenvector so that the matrix   
          of eigenvectors X satisfies  X * X' = I .  (No scaling is   
          done if the norm of the eigenvalue matrix is less than THRESH.) */

	q__2.r = rt1->r - a->r, q__2.i = rt1->i - a->i;
	c_div(&q__1, &q__2, b);
	sn1->r = q__1.r, sn1->i = q__1.i;
	tabs = c_abs(sn1);
	if (tabs > 1.f) {
/* Computing 2nd power */
	    r__2 = 1.f / tabs;
	    r__1 = r__2 * r__2;
	    q__5.r = sn1->r / tabs, q__5.i = sn1->i / tabs;
	    pow_ci(&q__4, &q__5, &c__2);
	    q__3.r = r__1 + q__4.r, q__3.i = q__4.i;
	    c_sqrt(&q__2, &q__3);
	    q__1.r = tabs * q__2.r, q__1.i = tabs * q__2.i;
	    t.r = q__1.r, t.i = q__1.i;
	} else {
	    q__3.r = sn1->r * sn1->r - sn1->i * sn1->i, q__3.i = sn1->r * 
		    sn1->i + sn1->i * sn1->r;
	    q__2.r = q__3.r + 1.f, q__2.i = q__3.i + 0.f;
	    c_sqrt(&q__1, &q__2);
	    t.r = q__1.r, t.i = q__1.i;
	}
	evnorm = c_abs(&t);
	if (evnorm >= .1f) {
	    c_div(&q__1, &c_b1, &t);
	    evscal->r = q__1.r, evscal->i = q__1.i;
	    cs1->r = evscal->r, cs1->i = evscal->i;
	    q__1.r = sn1->r * evscal->r - sn1->i * evscal->i, q__1.i = sn1->r 
		    * evscal->i + sn1->i * evscal->r;
	    sn1->r = q__1.r, sn1->i = q__1.i;
	} else {
	    evscal->r = 0.f, evscal->i = 0.f;
	}
    }
    return 0;

/*     End of CLAESY */

} /* claesy_ */