Exemple #1
0
/* Subroutine */ int zlarnv_(integer *idist, integer *iseed, integer *n, 
	doublecomplex *x)
{
    /* System generated locals */
    integer i__1, i__2, i__3, i__4, i__5;
    doublereal d__1, d__2;
    doublecomplex z__1, z__2, z__3;

    /* Builtin functions */
    double log(doublereal), sqrt(doublereal);
    void z_exp(doublecomplex *, doublecomplex *);

    /* Local variables */
    integer i__;
    doublereal u[128];
    integer il, iv;
    extern /* Subroutine */ int dlaruv_(integer *, integer *, doublereal *);


/*  -- LAPACK auxiliary routine (version 3.2) -- */
/*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/*     November 2006 */

/*     .. Scalar Arguments .. */
/*     .. */
/*     .. Array Arguments .. */
/*     .. */

/*  Purpose */
/*  ======= */

/*  ZLARNV returns a vector of n random complex numbers from a uniform or */
/*  normal distribution. */

/*  Arguments */
/*  ========= */

/*  IDIST   (input) INTEGER */
/*          Specifies the distribution of the random numbers: */
/*          = 1:  real and imaginary parts each uniform (0,1) */
/*          = 2:  real and imaginary parts each uniform (-1,1) */
/*          = 3:  real and imaginary parts each normal (0,1) */
/*          = 4:  uniformly distributed on the disc abs(z) < 1 */
/*          = 5:  uniformly distributed on the circle abs(z) = 1 */

/*  ISEED   (input/output) INTEGER array, dimension (4) */
/*          On entry, the seed of the random number generator; the array */
/*          elements must be between 0 and 4095, and ISEED(4) must be */
/*          odd. */
/*          On exit, the seed is updated. */

/*  N       (input) INTEGER */
/*          The number of random numbers to be generated. */

/*  X       (output) COMPLEX*16 array, dimension (N) */
/*          The generated random numbers. */

/*  Further Details */
/*  =============== */

/*  This routine calls the auxiliary routine DLARUV to generate random */
/*  real numbers from a uniform (0,1) distribution, in batches of up to */
/*  128 using vectorisable code. The Box-Muller method is used to */
/*  transform numbers from a uniform to a normal distribution. */

/*  ===================================================================== */

/*     .. Parameters .. */
/*     .. */
/*     .. Local Scalars .. */
/*     .. */
/*     .. Local Arrays .. */
/*     .. */
/*     .. Intrinsic Functions .. */
/*     .. */
/*     .. External Subroutines .. */
/*     .. */
/*     .. Executable Statements .. */

    /* Parameter adjustments */
    --x;
    --iseed;

    /* Function Body */
    i__1 = *n;
    for (iv = 1; iv <= i__1; iv += 64) {
/* Computing MIN */
	i__2 = 64, i__3 = *n - iv + 1;
	il = min(i__2,i__3);

/*        Call DLARUV to generate 2*IL real numbers from a uniform (0,1) */
/*        distribution (2*IL <= LV) */

	i__2 = il << 1;
	dlaruv_(&iseed[1], &i__2, u);

	if (*idist == 1) {

/*           Copy generated numbers */

	    i__2 = il;
	    for (i__ = 1; i__ <= i__2; ++i__) {
		i__3 = iv + i__ - 1;
		i__4 = (i__ << 1) - 2;
		i__5 = (i__ << 1) - 1;
		z__1.r = u[i__4], z__1.i = u[i__5];
		x[i__3].r = z__1.r, x[i__3].i = z__1.i;
/* L10: */
	    }
	} else if (*idist == 2) {

/*           Convert generated numbers to uniform (-1,1) distribution */

	    i__2 = il;
	    for (i__ = 1; i__ <= i__2; ++i__) {
		i__3 = iv + i__ - 1;
		d__1 = u[(i__ << 1) - 2] * 2. - 1.;
		d__2 = u[(i__ << 1) - 1] * 2. - 1.;
		z__1.r = d__1, z__1.i = d__2;
		x[i__3].r = z__1.r, x[i__3].i = z__1.i;
/* L20: */
	    }
	} else if (*idist == 3) {

/*           Convert generated numbers to normal (0,1) distribution */

	    i__2 = il;
	    for (i__ = 1; i__ <= i__2; ++i__) {
		i__3 = iv + i__ - 1;
		d__1 = sqrt(log(u[(i__ << 1) - 2]) * -2.);
		d__2 = u[(i__ << 1) - 1] * 6.2831853071795864769252867663;
		z__3.r = 0., z__3.i = d__2;
		z_exp(&z__2, &z__3);
		z__1.r = d__1 * z__2.r, z__1.i = d__1 * z__2.i;
		x[i__3].r = z__1.r, x[i__3].i = z__1.i;
/* L30: */
	    }
	} else if (*idist == 4) {

/*           Convert generated numbers to complex numbers uniformly */
/*           distributed on the unit disk */

	    i__2 = il;
	    for (i__ = 1; i__ <= i__2; ++i__) {
		i__3 = iv + i__ - 1;
		d__1 = sqrt(u[(i__ << 1) - 2]);
		d__2 = u[(i__ << 1) - 1] * 6.2831853071795864769252867663;
		z__3.r = 0., z__3.i = d__2;
		z_exp(&z__2, &z__3);
		z__1.r = d__1 * z__2.r, z__1.i = d__1 * z__2.i;
		x[i__3].r = z__1.r, x[i__3].i = z__1.i;
/* L40: */
	    }
	} else if (*idist == 5) {

/*           Convert generated numbers to complex numbers uniformly */
/*           distributed on the unit circle */

	    i__2 = il;
	    for (i__ = 1; i__ <= i__2; ++i__) {
		i__3 = iv + i__ - 1;
		d__1 = u[(i__ << 1) - 1] * 6.2831853071795864769252867663;
		z__2.r = 0., z__2.i = d__1;
		z_exp(&z__1, &z__2);
		x[i__3].r = z__1.r, x[i__3].i = z__1.i;
/* L50: */
	    }
	}
/* L60: */
    }
    return 0;

/*     End of ZLARNV */

} /* zlarnv_ */
Exemple #2
0
/* Subroutine */ int dlarnv_(integer *idist, integer *iseed, integer *n,
                             doublereal *x)
{
    /* System generated locals */
    integer i__1, i__2, i__3;

    /* Builtin functions */
    double log(doublereal), sqrt(doublereal), cos(doublereal);

    /* Local variables */
    integer i__;
    doublereal u[128];
    integer il, iv, il2;
    extern /* Subroutine */ int dlaruv_(integer *, integer *, doublereal *);


    /*  -- LAPACK auxiliary routine (version 3.2) -- */
    /*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
    /*     November 2006 */

    /*     .. Scalar Arguments .. */
    /*     .. */
    /*     .. Array Arguments .. */
    /*     .. */

    /*  Purpose */
    /*  ======= */

    /*  DLARNV returns a vector of n random real numbers from a uniform or */
    /*  normal distribution. */

    /*  Arguments */
    /*  ========= */

    /*  IDIST   (input) INTEGER */
    /*          Specifies the distribution of the random numbers: */
    /*          = 1:  uniform (0,1) */
    /*          = 2:  uniform (-1,1) */
    /*          = 3:  normal (0,1) */

    /*  ISEED   (input/output) INTEGER array, dimension (4) */
    /*          On entry, the seed of the random number generator; the array */
    /*          elements must be between 0 and 4095, and ISEED(4) must be */
    /*          odd. */
    /*          On exit, the seed is updated. */

    /*  N       (input) INTEGER */
    /*          The number of random numbers to be generated. */

    /*  X       (output) DOUBLE PRECISION array, dimension (N) */
    /*          The generated random numbers. */

    /*  Further Details */
    /*  =============== */

    /*  This routine calls the auxiliary routine DLARUV to generate random */
    /*  real numbers from a uniform (0,1) distribution, in batches of up to */
    /*  128 using vectorisable code. The Box-Muller method is used to */
    /*  transform numbers from a uniform to a normal distribution. */

    /*  ===================================================================== */

    /*     .. Parameters .. */
    /*     .. */
    /*     .. Local Scalars .. */
    /*     .. */
    /*     .. Local Arrays .. */
    /*     .. */
    /*     .. Intrinsic Functions .. */
    /*     .. */
    /*     .. External Subroutines .. */
    /*     .. */
    /*     .. Executable Statements .. */

    /* Parameter adjustments */
    --x;
    --iseed;

    /* Function Body */
    i__1 = *n;
    for (iv = 1; iv <= i__1; iv += 64) {
        /* Computing MIN */
        i__2 = 64, i__3 = *n - iv + 1;
        il = min(i__2,i__3);
        if (*idist == 3) {
            il2 = il << 1;
        } else {
            il2 = il;
        }

        /*        Call DLARUV to generate IL2 numbers from a uniform (0,1) */
        /*        distribution (IL2 <= LV) */

        dlaruv_(&iseed[1], &il2, u);

        if (*idist == 1) {

            /*           Copy generated numbers */

            i__2 = il;
            for (i__ = 1; i__ <= i__2; ++i__) {
                x[iv + i__ - 1] = u[i__ - 1];
                /* L10: */
            }
        } else if (*idist == 2) {

            /*           Convert generated numbers to uniform (-1,1) distribution */

            i__2 = il;
            for (i__ = 1; i__ <= i__2; ++i__) {
                x[iv + i__ - 1] = u[i__ - 1] * 2. - 1.;
                /* L20: */
            }
        } else if (*idist == 3) {

            /*           Convert generated numbers to normal (0,1) distribution */

            i__2 = il;
            for (i__ = 1; i__ <= i__2; ++i__) {
                x[iv + i__ - 1] = sqrt(log(u[(i__ << 1) - 2]) * -2.) * cos(u[(
                                      i__ << 1) - 1] * 6.2831853071795864769252867663);
                /* L30: */
            }
        }
        /* L40: */
    }
    return 0;

    /*     End of DLARNV */

} /* dlarnv_ */
Exemple #3
0
/* Subroutine */ int dlarnv_(integer *idist, integer *iseed, integer *n, 
	doublereal *x)
{
/*  -- LAPACK auxiliary routine (version 2.0) --   
       Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,   
       Courant Institute, Argonne National Lab, and Rice University   
       September 30, 1994   


    Purpose   
    =======   

    DLARNV returns a vector of n random real numbers from a uniform or   
    normal distribution.   

    Arguments   
    =========   

    IDIST   (input) INTEGER   
            Specifies the distribution of the random numbers:   
            = 1:  uniform (0,1)   
            = 2:  uniform (-1,1)   
            = 3:  normal (0,1)   

    ISEED   (input/output) INTEGER array, dimension (4)   
            On entry, the seed of the random number generator; the array 
  
            elements must be between 0 and 4095, and ISEED(4) must be   
            odd.   
            On exit, the seed is updated.   

    N       (input) INTEGER   
            The number of random numbers to be generated.   

    X       (output) DOUBLE PRECISION array, dimension (N)   
            The generated random numbers.   

    Further Details   
    ===============   

    This routine calls the auxiliary routine DLARUV to generate random   
    real numbers from a uniform (0,1) distribution, in batches of up to   
    128 using vectorisable code. The Box-Muller method is used to   
    transform numbers from a uniform to a normal distribution.   

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


    
   Parameter adjustments   
       Function Body */
    /* System generated locals */
    integer i__1, i__2, i__3;
    /* Builtin functions */
    double log(doublereal), sqrt(doublereal), cos(doublereal);
    /* Local variables */
    static integer i;
    static doublereal u[128];
    static integer il, iv;
    extern /* Subroutine */ int dlaruv_(integer *, integer *, doublereal *);
    static integer il2;


#define U(I) u[(I)]
#define X(I) x[(I)-1]
#define ISEED(I) iseed[(I)-1]


    i__1 = *n;
    for (iv = 1; iv <= *n; iv += 64) {
/* Computing MIN */
	i__2 = 64, i__3 = *n - iv + 1;
	il = min(i__2,i__3);
	if (*idist == 3) {
	    il2 = il << 1;
	} else {
	    il2 = il;
	}

/*        Call DLARUV to generate IL2 numbers from a uniform (0,1)   
          distribution (IL2 <= LV) */

	dlaruv_(&ISEED(1), &il2, u);

	if (*idist == 1) {

/*           Copy generated numbers */

	    i__2 = il;
	    for (i = 1; i <= il; ++i) {
		X(iv + i - 1) = U(i - 1);
/* L10: */
	    }
	} else if (*idist == 2) {

/*           Convert generated numbers to uniform (-1,1) distribut
ion */

	    i__2 = il;
	    for (i = 1; i <= il; ++i) {
		X(iv + i - 1) = U(i - 1) * 2. - 1.;
/* L20: */
	    }
	} else if (*idist == 3) {

/*           Convert generated numbers to normal (0,1) distributio
n */

	    i__2 = il;
	    for (i = 1; i <= il; ++i) {
		X(iv + i - 1) = sqrt(log(U((i << 1) - 2)) * -2.) * cos(U((i <<
			 1) - 1) * 6.2831853071795864769252867663);
/* L30: */
	    }
	}
/* L40: */
    }
    return 0;

/*     End of DLARNV */

} /* dlarnv_ */