/**
* @brief Gets a random double that follows the gaussian distribution.
*/
double rand_double_gaussian (void)
{
double theta, rsq;
theta = rand_double_range( 0., 2.*M_PI );
rsq = rand_double_exponential( 0.5 );
return (sqrt(rsq) * cos(theta));
}
void randomvals_int (t_randomvals *x, t_atom_long value)
{
t_rand_gen *gen = &x->gen;
double *means = x->means;
double *devs = x->devs;
double *weights = x->weights;
double *lo_bounds = x->lo_bounds;
double *hi_bounds = x->hi_bounds;
double randval, mean, dev, lo_bound, hi_bound;
long i;
long num_params = x->num_params;
if (value >= 2)
{
// Summed windowed gaussians random distribution
// Choose a mean and dev pair based on weighting
randval = rand_double_n(gen, weights[num_params - 1]);
for (i = 0; i < num_params - 1; i++)
if (randval < weights[i])
break;
// Generate a windowed gaussian number (between 0 and 1) using a fast implementation
mean = means[i];
dev = devs[i];
lo_bound = lo_bounds[i];
hi_bound = hi_bounds[i];
randval = ltqnorm(0.5 + 0.5 * rand_double_range(gen, lo_bound, hi_bound)) * dev + mean;
if (randval > 1.)
randval = 1.;
if (randval < 0.)
randval = 0.;
}
else
{
// Generate a flat distribution random number between 0 and 1
randval = rand_double(gen);
}
outlet_float(x->the_outlet, randval);
}
/**
* @brief Gets an int in range [low,high].
*/
int rand_int_range( int low, int high )
{
return (int)round( rand_double_range( (double)low, (double)high ) );
}
void randomvals_perform64 (t_randomvals *x, t_object *dsp64, double **ins, long numins, double **outs, long numouts, long vec_size, long flags, void *userparam)
{
// Set pointers
double *in = ins[0];
double *out = outs[0];
t_rand_gen *gen = &x->gen;
double *means = x->means;
double *devs = x->devs;
double *weights = x->weights;
double *lo_bounds = x->lo_bounds;
double *hi_bounds = x->hi_bounds;
double randval, mean, dev, lo_bound, hi_bound;
long test, i;
long num_params = x->num_params;
while (vec_size--)
{
test = *in++;
if (test >= 1)
{
if (test >= 2)
{
// Summed windowed gaussians random distribution
// Choose a mean and dev pair based on weighting
randval = rand_double_n(gen, weights[num_params - 1]);
for (i = 0; i < num_params - 1; i++)
if (randval < weights[i])
break;
// Generate a windowed gaussian number (between 0 and 1) using a fast implementation
mean = means[i];
dev = devs[i];
lo_bound = lo_bounds[i];
hi_bound = hi_bounds[i];
randval = ltqnorm(0.5 + 0.5 * rand_double_range(gen, lo_bound, hi_bound)) * dev + mean;
if (randval > 1.)
randval = 1.;
if (randval < 0.)
randval = 0.;
}
else
{
// Generate a flat distribution random number between 0 and 1
randval = rand_double(gen);
}
}
else
{
// Output zeros
randval = 0;
}
*out++ = randval;
}
}
t_int *randomvals_perform (t_int *w)
{
// Set pointers
float *in = (float *) w[1];
float *out = (float *) w[2];
long vec_size = w[3];
t_randomvals *x = (t_randomvals *) w[4];
t_rand_gen *gen = &x->gen;
double *means = x->means;
double *devs = x->devs;
double *weights = x->weights;
double *lo_bounds = x->lo_bounds;
double *hi_bounds = x->hi_bounds;
double randval, mean, dev, lo_bound, hi_bound;
long test, i;
long num_params = x->num_params;
while (vec_size--)
{
test = *in++;
if (test >= 1)
{
if (test >= 2)
{
// Summed windowed gaussians random distribution
// Choose a mean and dev pair based on weighting
randval = rand_double_n(gen, weights[num_params - 1]);
for (i = 0; i < num_params - 1; i++)
if (randval < weights[i])
break;
// Generate a windowed gaussian number (between 0 and 1) using a fast implementation
mean = means[i];
dev = devs[i];
lo_bound = lo_bounds[i];
hi_bound = hi_bounds[i];
randval = ltqnorm(0.5 + 0.5 * rand_double_range(gen, lo_bound, hi_bound)) * dev + mean;
if (randval > 1.)
randval = 1.;
if (randval < 0.)
randval = 0.;
}
else
{
// Generate a flat distribution random number between 0 and 1
randval = rand_double(gen);
}
}
else
{
// Output zeros
randval = 0;
}
*out++ = randval;
}
return w + 5;
}
