types::ndarray<T,N - 1>
prod(types::ndarray<T,N> const& array, long axis)
{
if(axis<0 || axis >=long(N))
throw types::ValueError("axis out of bounds");
auto shape = array.shape;
if(axis==0)
{
types::array<long, N> shp;
shp[0] = 1;
std::copy(shape.begin() + 1, shape.end(), shp.begin() + 1);
types::ndarray<T,N> out(shp, 1);
return std::accumulate(array.begin(), array.end(), *out.begin(), proxy::multiply());
}
else
{
types::array<long, N-1> shp;
std::copy(shape.begin(), shape.end() - 1, shp.begin());
types::ndarray<T,N-1> prody(shp, __builtin__::None);
std::transform(array.begin(), array.end(), prody.begin(), [=](types::ndarray<T,N-1> const& other) {return prod(other, axis-1);});
return prody;
}
}
types::ndarray<T,N - 1 >
max(types::ndarray<T,N> const& array, long axis)
{
if(axis<0 || axis >=long(N))
throw types::ValueError("axis out of bounds");
auto shape = array.shape;
if(axis==0)
{
types::array<long, N> shp;
shp[0] = 1;
std::copy(shape.begin() + 1, shape.end(), shp.begin() + 1);
types::ndarray<T,N> out(shp, std::numeric_limits<T>::lowest());
return std::accumulate(array.begin(), array.end(), *out.begin(), numpy::proxy::maximum());
}
else
{
types::array<long, N-1> shp;
std::copy(shape.begin(), shape.end() - 1, shp.begin());
types::ndarray<T,N-1> maxy(shp, __builtin__::None);
std::transform(array.begin(), array.end(), maxy.begin(), [=](types::ndarray<T,N-1> const& other) {return max(other, axis-1);});
return maxy;
}
}
typename std::enable_if<types::is_iterable<I>::value,
types::list<types::ndarray<T, N>>>::type
array_split(types::ndarray<T, N> const &a, I const &split_mask)
{
long sz = std::distance(a.begin(), a.end());
types::list<types::ndarray<T, N>> out(1 + split_mask.flat_size());
long index = 0;
auto inserter = out.begin();
for (auto next_index : split_mask) {
*inserter++ = a[types::contiguous_slice(index, next_index)];
index = next_index;
}
*inserter = a[types::contiguous_slice(index, sz)];
return out;
}
types::ndarray<typename types::numpy_type<dtype>::type,N> cumprod(types::ndarray<T,N> const& expr, long axis, dtype d = dtype()) {
if(axis<0 || axis >=long(N))
throw types::ValueError("axis out of bounds");
auto shape = expr.shape;
types::ndarray<typename types::numpy_type<dtype>::type,N> cumprody(shape, __builtin__::None);
if(axis==0) {
std::copy(expr.buffer, expr.buffer + shape[N-1], cumprody.buffer);
std::transform(cumprody.begin(), cumprody.end()-1, expr.begin() + 1, cumprody.begin() + 1, std::multiplies<types::ndarray<T,N-1>>());
}
else {
std::transform(expr.begin(), expr.end(), cumprody.begin(), [=](types::ndarray<T,N-1> const& e) { return cumprod(e, axis-1, d); });
}
return cumprody;
}
types::list<types::ndarray<T, N>> array_split(types::ndarray<T, N> const &a,
long nb_split)
{
long sz = std::distance(a.begin(), a.end());
long n = (sz + nb_split - 1) / nb_split;
long end = n * nb_split;
long nb_full_split = nb_split;
if (end != sz)
nb_full_split -= (end - sz);
types::list<types::ndarray<T, N>> out(nb_split);
long index = 0;
for (long i = 0; i < nb_full_split; ++i, index += n)
out[i] = a[types::contiguous_slice(index, index + n)];
for (long i = nb_full_split; i < nb_split; ++i, index += (n - 1))
out[i] = a[types::contiguous_slice(index, index + n - 1)];
return out;
}