void Gaussian<T>::generate(VectorT& x) const
{
//generate a normalized gaussian distributed variable y
VectorT y(numDims());
for(int i=0;i<y.n;i++) y(i) = RandGaussian(0,1);
L.mul(y,x);
x += mu;
}
T Gaussian<T>::probability(const VectorT& x) const
{
int d = numDims();
T det=One;
for(int i=0;i<d;i++) det*=L(i,i);
T invc = Pow(2.0*Pi,0.5*T(d))*det;
VectorT x_mu,y;
x_mu.sub(x,mu);
y.resize(L.n);
LBackSubstitute(L,x_mu,y);
return Exp(-Half*y.normSquared())/invc;
}
const array::array_proxy array::operator()(const index &s0) const
{
index z = index(0);
if(isvector()){
switch(numDims(this->arr)) {
case 1: return gen_indexing(*this, s0, z, z, z);
case 2: return gen_indexing(*this, z, s0, z, z);
case 3: return gen_indexing(*this, z, z, s0, z);
case 4: return gen_indexing(*this, z, z, z, s0);
default: AF_THROW_ERR("ndims for Array is invalid", AF_ERR_SIZE);
}
}
else {
return gen_indexing(*this, s0, z, z, z, true);
}
}
// Assign values to an array
array::array_proxy&
af::array::array_proxy::operator=(const array &other)
{
unsigned nd = numDims(impl->parent_->get());
const dim4 this_dims = getDims(impl->parent_->get());
const dim4 other_dims = other.dims();
int dim = gforDim(impl->indices_);
af_array other_arr = other.get();
bool batch_assign = false;
bool is_reordered = false;
if (dim >= 0) {
//FIXME: Figure out a faster, cleaner way to do this
dim4 out_dims = seqToDims(impl->indices_, this_dims, false);
batch_assign = true;
for (int i = 0; i < AF_MAX_DIMS; i++) {
if (this->impl->indices_[i].isBatch) batch_assign &= (other_dims[i] == 1);
else batch_assign &= (other_dims[i] == out_dims[i]);
}
if (batch_assign) {
af_array out;
AF_THROW(af_tile(&out, other_arr,
out_dims[0] / other_dims[0],
out_dims[1] / other_dims[1],
out_dims[2] / other_dims[2],
out_dims[3] / other_dims[3]));
other_arr = out;
} else if (out_dims != other_dims) {
// HACK: This is a quick check to see if other has been reordered inside gfor
// TODO: Figure out if this breaks and implement a cleaner method
other_arr = gforReorder(other_arr, dim);
is_reordered = true;
}
}
af_array par_arr = 0;
if (impl->is_linear_) {
AF_THROW(af_flat(&par_arr, impl->parent_->get()));
nd = 1;
} else {
par_arr = impl->parent_->get();
}
af_array tmp = 0;
AF_THROW(af_assign_gen(&tmp, par_arr, nd, impl->indices_, other_arr));
af_array res = 0;
if (impl->is_linear_) {
AF_THROW(af_moddims(&res, tmp, this_dims.ndims(), this_dims.get()));
AF_THROW(af_release_array(par_arr));
AF_THROW(af_release_array(tmp));
} else {
res = tmp;
}
impl->parent_->set(res);
if (dim >= 0 && (is_reordered || batch_assign)) {
if (other_arr) AF_THROW(af_release_array(other_arr));
}
return *this;
}
unsigned array::numdims() const
{
return numDims(get());
}
