static inline real isotropicRandomR(dsfmt_t* dsfmtState, real scaleRad1, real scaleRad2,
real Mass1, real Mass2)
{
// Rejection sampling radius generation
real RHO_MAX = 3/(4*M_PI) * (Mass1/(mw_pow(scaleRad1,3)) + Mass2/(mw_pow(scaleRad2,3)));
mwbool GOOD_RADIUS = 0;
// Arbitrarily define sample range to be [0, 5(a1 + a2)
real r;
while (GOOD_RADIUS != 1)
{
r = mwXrandom(dsfmtState,0.0, 3*(scaleRad1 + scaleRad2));
real u = (real)mwXrandom(dsfmtState,0.0,1.0);
real val = 3/(4*M_PI)*(Mass1/(mw_pow(scaleRad1,3)) *mw_pow(1 + mw_pow(r,2)/mw_pow(scaleRad1,2),-5/2) +
Mass2/(mw_pow(scaleRad2,3))*mw_pow(1 + mw_pow(r,2)/mw_pow(scaleRad2,2),-5/2));
if (val/RHO_MAX > u)
{
GOOD_RADIUS = 1;
}
}
return r;
}
/* The estimate formula has the unfortunate property of being negative
for small n. This will be the most negative. Add this as an extra
boost to prevent negative flops estimates.
*/
static real worstFlops(real cQ, real d, real f)
{
real a = mw_pow(2.0, 3.0 - 3.0 * d / cQ);
real b = (cQ - d) * mw_log(8.0);
real c = cQ * mw_log(mw_pow(8.0, 1.0 - d / cQ));
return -a * sqr(f) * (cQ + b - c) / (M_E * mw_log(8.0));
}
real propability_match(int n, int k, real pobs){
real result;
result = choose(n, k);
result *= mw_pow(pobs, (real)k);
result *= mw_pow((1-pobs), (real)(n-k));
result = mw_log(result);
return result;
}
static inline real isotropicRandomV(real r, real scaleRad1, real scaleRad2, real Mass1, real Mass2)
{
real val;
val = mw_sqrt(Mass1/mw_sqrt(mw_pow(r,2) + mw_pow(scaleRad1,2))
+ Mass2/mw_sqrt(mw_pow(r,2) + mw_pow(scaleRad2,2)));
return val;
}
/* generatePlummer: generate Plummer model initial conditions for test
* runs, scaled to units such that M = -4E = G = 1 (Henon, Heggie,
* etc). See Aarseth, SJ, Henon, M, & Wielen, R (1974) Astr & Ap, 37,
* 183.
*/
static int nbGenerateIsotropicCore(lua_State* luaSt,
dsfmt_t* prng,
unsigned int nbody,
real mass1,
real mass2,
mwbool ignore,
mwvector rShift,
mwvector vShift,
real radiusScale1,
real radiusScale2)
{
unsigned int i;
int table;
Body b;
real r, velScale;
real mass = mass1 + mass2;
real radiusScale = mw_sqrt(mw_pow(radiusScale1,2) + mw_pow(radiusScale2,2));
memset(&b, 0, sizeof(b));
velScale = mw_sqrt(mass / radiusScale); /* and recip. speed scale */
b.bodynode.type = BODY(ignore); /* Same for all in the model */
b.bodynode.mass = mass / nbody; /* Mass per particle */
lua_createtable(luaSt, nbody, 0);
table = lua_gettop(luaSt);
for (i = 0; i < nbody; ++i)
{
do
{
r = isotropicRandomR(prng, radiusScale1, radiusScale2, mass1, mass2);
/* FIXME: We should avoid the divide by 0.0 by multiplying
* the original random number by 0.9999.. but I'm too lazy
* to change the tests. Same with other models */
}
while (isinf(r));
b.bodynode.pos = isotropicBodyPosition(prng, rShift, r);
b.vel = isotropicBodyVelocity(prng, r, vShift, velScale, radiusScale1, radiusScale2, mass1, mass2);
assert(nbPositionValid(b.bodynode.pos));
pushBody(luaSt, &b);
// printf("Body %d is pushed. \n",i);
lua_rawseti(luaSt, table, i + 1);
}
return 1;
}
/* For using a combination of light and dark models to generate timestep */
static real plummerTimestepIntegral(real smalla, real biga, real Md, real step)
{
/* Calculate the enclosed mass of the big sphere within the little sphere's scale length */
real encMass, val, r;
encMass = 0.0;
for (r = 0.0; r <= smalla; r += step)
{
val = sqr(r) / mw_pow(sqr(r) + sqr(biga), 2.5);
encMass += val * step;
}
encMass *= 3.0 * Md * sqr(biga);
return encMass;
}
