types::ndarray<
typename std::remove_cv<
typename std::remove_reference<
decltype(
std::declval<T>()
+
std::declval<typename utils::nested_container_value_type<F>::type>())
>::type
>::type,
1> append(types::ndarray<T,N> const& nto, F const& data) {
typename types::numpy_expr_to_ndarray<F>::type ndata(data);
long nsize = nto.size() + ndata.size();
types::ndarray<
typename std::remove_cv<
typename std::remove_reference<
decltype(
std::declval<T>()
+
std::declval<typename utils::nested_container_value_type<F>::type>())
>::type
>::type,
1> out(types::make_tuple(nsize), __builtin__::None);
size_t i=0;
auto out_back = std::copy(nto.fbegin(), nto.fend(), out.fbegin());
std::copy(ndata.fbegin(), ndata.fend(), out_back);
return out;
}
types::ndarray<T, N> _transpose(types::ndarray<T, N> const &a,
long const l[N])
{
auto shape = a.shape();
types::array<long, N> shp;
for (unsigned long i = 0; i < N; ++i)
shp[i] = shape[l[i]];
types::ndarray<T, N> new_array(shp, __builtin__::None);
types::array<long, N> new_strides;
new_strides[N - 1] = 1;
std::transform(new_strides.rbegin(), new_strides.rend() - 1, shp.rbegin(),
new_strides.rbegin() + 1, std::multiplies<long>());
types::array<long, N> old_strides;
old_strides[N - 1] = 1;
std::transform(old_strides.rbegin(), old_strides.rend() - 1,
shape.rbegin(), old_strides.rbegin() + 1,
std::multiplies<long>());
auto iter = a.buffer, iter_end = a.buffer + a.flat_size();
for (long i = 0; iter != iter_end; ++iter, ++i) {
long offset = 0;
for (unsigned long s = 0; s < N; s++)
offset += ((i / old_strides[l[s]]) % shape[l[s]]) * new_strides[s];
new_array.buffer[offset] = *iter;
}
return new_array;
}
types::none_type put(types::ndarray<T, N> &expr, long int ind, T const &v)
{
if (ind >= expr.flat_size() || ind < 0)
throw types::ValueError("indice out of bound");
*(expr.fbegin() + ind) = v;
return __builtin__::None;
}
types::ndarray<T,N> roll(types::ndarray<T,N> const& expr, long shift, long axis)
{
auto&& expr_shape = expr.shape();
while(shift<0) shift+=expr_shape[axis];
types::ndarray<T,N> out(expr_shape, __builtin__::None);
_roll(out.fbegin(), expr.fbegin(), shift, axis, expr_shape, utils::int_<N>());
return out;
}
types::ndarray<T, 1> repeat(types::ndarray<T, N> const &expr, int repeats)
{
types::ndarray<T, 1> out(
types::array<long, 1>{{expr.flat_size() * repeats}},
__builtin__::None);
auto out_iter = out.fbegin();
for (auto iter = expr.fbegin(), end = expr.fend(); iter != end; ++iter)
for (int i = 0; i < repeats; ++i)
*out_iter++ = *iter;
return out;
}
types::ndarray<decltype(std::declval<T0>() + std::declval<T1>()), 2>
outer(types::ndarray<T0, N0> const& a, types::ndarray<T1, N1> const& b)
{
types::ndarray<decltype(std::declval<T0>() + std::declval<T1>()), 2> out(types::array<long, 2>{{a.flat_size(), b.flat_size()}}, __builtin__::None);
auto iter = out.fbegin();
for(auto iter_a = a.fbegin(), end_a = a.fend(); iter_a != end_a; ++iter_a) {
auto val_a = *iter_a;
iter = std::transform(b.fbegin(), b.fend(), iter, [=](T1 val) { return val_a * val; });
}
return out;
}
types::none_type putmask(types::ndarray<T, pS> &expr, E const &mask,
F const &values)
{
auto amask = asarray(mask);
auto avalues = asarray(values);
auto iexpr = expr.fbegin();
auto n = avalues.flat_size();
for (long i = 0; i < expr.flat_size(); ++i)
if (*(amask.fbegin() + i))
*(iexpr + i) = *(avalues.fbegin() + i % n);
return __builtin__::None;
}
types::ndarray<T, M> reshape(types::ndarray<T, N> const &expr,
types::array<long, M> const &new_shape)
{
auto where = std::find(new_shape.begin(), new_shape.end(), -1);
if (where != new_shape.end()) {
auto auto_shape = new_shape;
auto_shape[where - new_shape.begin()] =
expr.flat_size() / std::accumulate(new_shape.begin(),
new_shape.end(), -1L,
std::multiplies<long>());
return expr.reshape(auto_shape);
} else
return expr.reshape(new_shape);
}
typename std::enable_if<types::is_numexpr_arg<F>::value,
types::none_type>::type
put(types::ndarray<T, N> &expr, F const &ind, E const &v)
{
auto vind = asarray(ind);
auto vv = asarray(v);
for (long i = 0; i < ind.flat_size(); ++i) {
auto val = *(vind.fbegin() + i);
if (val >= expr.flat_size() || val < 0)
throw types::ValueError("indice out of bound");
*(expr.fbegin() + val) = *(vv.fbegin() + i % vv.flat_size());
}
return __builtin__::None;
}
types::ndarray<T,1> resize(types::ndarray<T,N> const& expr, int new_shape)
{
types::ndarray<T,1> out(types::array<long, N> {{new_shape}}, __builtin__::None);
auto n = expr.size();
if(n < new_shape) {
auto iter = std::copy(expr.fbegin(), expr.fend(), out.fbegin());
for(size_t i = 1; i < new_shape / n; ++i)
iter = std::copy(out.fbegin(), out.fbegin() + n, iter);
std::copy(out.fbegin(), out.fbegin() + new_shape % n, iter);
}
else
std::copy(expr.fbegin(), expr.fbegin() + new_shape, out.fbegin());
return out;
}
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::ndarray<T, types::array<long, std::tuple_size<pS>::value>>
rot90(types::ndarray<T, pS> const &expr, int k)
{
auto constexpr N = std::tuple_size<pS>::value;
if (k % 4 == 0)
return copy(expr);
types::array<long, N> shape = sutils::array(expr.shape());
if (k % 4 != 2)
std::swap(shape[0], shape[1]);
types::ndarray<T, types::array<long, N>> out(shape, __builtin__::None);
if (k % 4 == 1) {
for (int i = 0; i < shape[1]; ++i)
for (int j = 0; j < shape[0]; ++j)
out[shape[0] - 1 - j][i] = expr[i][j];
} else if (k % 4 == 2) {
for (int i = 0; i < shape[1]; ++i)
for (int j = 0; j < shape[0]; ++j)
out[shape[0] - 1 - j][shape[1] - 1 - i] = expr[j][i];
} else {
for (int i = 0; i < shape[1]; ++i)
for (int j = 0; j < shape[0]; ++j)
out[j][shape[1] - 1 - i] = expr[i][j];
}
return out;
}
types::ndarray<long, N> argsort(types::ndarray<T,N> const& a) {
size_t last_axis = a.shape[N-1];
size_t n = a.flat_size();
types::ndarray<long, N> indices(a.shape, __builtin__::None);
for(long j=0, * iter_indices = indices.buffer, *end_indices = indices.buffer + n;
iter_indices != end_indices;
iter_indices += last_axis, j+=last_axis)
{
// fill with the original indices
std::iota(iter_indices, iter_indices + last_axis, 0L);
// sort the index using the value from a
std::sort(iter_indices, iter_indices + last_axis,
[&a,j](long i1, long i2) {return *(a.fbegin() + j + i1) < *(a.fbegin() + j + i2);});
}
return indices;
}
types::ndarray<T, 1>
flatten(types::ndarray<T,N> const& a) {
long n = a.size();
T *buffer = new T[n];
std::copy(a.buffer, a.buffer + n, buffer);
long shape[1] = {n};
return types::ndarray<T, 1>(buffer, shape);
}
typename types::numpy_expr_to_ndarray<F>::type take(types::ndarray<T,N> const & expr, F const& indices)
{
typename types::numpy_expr_to_ndarray<F>::type out = asarray(indices);
auto expr_iter = expr.fbegin();
for(auto out_iter = out.fbegin(), out_end = out.fend(); out_iter != out_end; ++out_iter)
*out_iter = *(expr_iter + *out_iter);
return out;
}
types::list<types::ndarray<T, N>> split(types::ndarray<T, N> const &a,
long nb_split)
{
if (a.flat_size() % nb_split != 0)
throw types::ValueError(
"array split does not result in an equal division");
return array_split(a, nb_split);
}
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;
}
decltype(std::declval<T>() + 1.) median(types::ndarray<T, N> const &arr)
{
size_t n = arr.flat_size();
T *tmp = new T[n];
std::copy(arr.buffer, arr.buffer + n, tmp);
std::sort(tmp, tmp + n);
auto out = (tmp[n / 2] + tmp[(n - 1) / 2]) / double(2);
delete[] tmp;
return out;
}
types::none_type place(types::ndarray<T, N> &expr,
types::ndarray<Tp, Np> const &mask, F const &values)
{
auto first = expr.fend();
auto viter = values.begin(), vend = values.end();
auto miter = mask.fbegin();
for (auto iter = expr.fbegin(), end = expr.fend(); iter != end;
++iter, ++miter) {
if (*miter) {
if (first == expr.fend())
first = iter;
if (viter != vend) {
*iter = *viter;
++viter;
} else
*iter = *first;
}
}
return __builtin__::None;
}
types::ndarray<T,2> diag(types::ndarray<T,1> const &a, long k=0) {
long n = a.size() + std::abs(k);
types::ndarray<T,2> out(types::make_tuple(n,n), 0);
if(k>=0)
for(long i=0,j =k ; i< n and j<n ;++i,++j)
out[i][j] = a[i];
else
for(long i=-k,j =0 ; i< n and j<n ;++i,++j)
out[i][j] = a[j];
return out;
}
types::ndarray<T, N> roll(types::ndarray<T, N> const &expr, long shift)
{
while (shift < 0)
shift += expr.flat_size();
shift %= expr.flat_size();
types::ndarray<T, N> out(expr.shape(), __builtin__::None);
std::copy(expr.fbegin(), expr.fend() - shift,
std::copy(expr.fend() - shift, expr.fend(), out.fbegin()));
return out;
}
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;
}
}
types::ndarray<T,2> tril(types::ndarray<T,2> const& expr, int k = 0)
{
auto&& expr_shape = expr.shape();
types::ndarray<T,2> out(expr_shape, __builtin__::None);
for(int i=0; i<expr_shape[0]; ++i) {
auto out_i = out[i];
auto expr_i = expr[i];
for(long j=0 ; j<expr_shape[1]; ++j)
if( j - i <= k)
out_i[j] = expr_i[j];
else
out_i[j] = 0;
}
return out;
}
types::ndarray<T,M> resize(types::ndarray<T,N> const& expr, types::array<long, M> const& new_shape)
{
auto where = std::find(new_shape.begin(), new_shape.end(), -1);
if(where != new_shape.end()) {
types::array<long, M> auto_shape(new_shape);
auto_shape[where - new_shape.begin()] = expr.size() / std::accumulate(new_shape.begin(), new_shape.end(), -1L, std::multiplies<long>());
return resize(expr, auto_shape);
}
types::ndarray<T,M> out(new_shape, __builtin__::None);
auto nshape = out.size();
auto n = expr.size();
if(n < nshape) {
auto iter = std::copy(expr.fbegin(), expr.fend(), out.fbegin());
for(size_t i = 1; i < nshape / n; ++i) {
iter = std::copy(out.fbegin(), out.fbegin() + n, iter);
}
std::copy(out.fbegin(), out.fbegin() + nshape % n, iter);
}
else
std::copy(expr.fbegin(), expr.fbegin() + nshape, out.fbegin());
return out;
}
T item(types::ndarray<T, N> const& expr, long i)
{
if(i<0) i += expr.size();
return *(expr.fbegin() + i);
}
types::ndarray<T, 1> flatten(types::ndarray<T, N> const &a)
{
return {a.mem, types::array<long, 1>{{a.flat_size()}}};
}
types::str tostring(types::ndarray<T, N> const &expr)
{
return types::str(reinterpret_cast<const char *>(expr.buffer),
expr.flat_size() * sizeof(T));
}
types::none_type fill(types::ndarray<T, N> &e, F f)
{
std::fill(e.fbegin(), e.fend(), f);
return __builtin__::None;
}