/*
    Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>

    All rights reserved. Use of this source code is governed by a
    BSD-style license that can be found in the LICENSE file.
*/




#pragma once

#include "numpy.h"

#if defined(__INTEL_COMPILER)
#  pragma warning(disable: 1682)
#elif defined(__GNUG__) || defined(__clang__)
#  pragma GCC diagnostic push
#  pragma GCC diagnostic ignored "-Wconversion"
#  pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#  ifdef __clang__


#    pragma GCC diagnostic ignored "-Wdeprecated"
#  endif
#  if __GNUC__ >= 7
#    pragma GCC diagnostic ignored "-Wint-in-bool-context"
#  endif
#endif

#if defined(_MSC_VER)
#  pragma warning(push)
#  pragma warning(disable: 4127)
#  pragma warning(disable: 4996)
#endif

#include <Eigen/Core>
#include <Eigen/SparseCore>




static_assert(EIGEN_VERSION_AT_LEAST(3,2,7), "Eigen support in pybind11 requires Eigen >= 3.2.7");

NAMESPACE_BEGIN(PYBIND11_NAMESPACE)


using EigenDStride = Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic>;
template <typename MatrixType> using EigenDRef = Eigen::Ref<MatrixType, 0, EigenDStride>;
template <typename MatrixType> using EigenDMap = Eigen::Map<MatrixType, 0, EigenDStride>;

NAMESPACE_BEGIN(detail)

#if EIGEN_VERSION_AT_LEAST(3,3,0)
using EigenIndex = Eigen::Index;
#else
using EigenIndex = EIGEN_DEFAULT_DENSE_INDEX_TYPE;
#endif


template <typename T> using is_eigen_dense_map = all_of<is_template_base_of<Eigen::DenseBase, T>, std::is_base_of<Eigen::MapBase<T, Eigen::ReadOnlyAccessors>, T>>;
template <typename T> using is_eigen_mutable_map = std::is_base_of<Eigen::MapBase<T, Eigen::WriteAccessors>, T>;
template <typename T> using is_eigen_dense_plain = all_of<negation<is_eigen_dense_map<T>>, is_template_base_of<Eigen::PlainObjectBase, T>>;
template <typename T> using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;




template <typename T> using is_eigen_other = all_of<
    is_template_base_of<Eigen::EigenBase, T>,
    negation<any_of<is_eigen_dense_map<T>, is_eigen_dense_plain<T>, is_eigen_sparse<T>>>
>;


template <bool EigenRowMajor> struct EigenConformable {
    bool conformable = false;
    EigenIndex rows = 0, cols = 0;
    EigenDStride stride{0, 0};
    bool negativestrides = false;

    EigenConformable(bool fits = false) : conformable{fits} {}

    EigenConformable(EigenIndex r, EigenIndex c,
            EigenIndex rstride, EigenIndex cstride) :
        conformable{true}, rows{r}, cols{c} {

        if (rstride < 0 || cstride < 0) {
            negativestrides = true;
        } else {
            stride = {EigenRowMajor ? rstride : cstride  ,
                      EigenRowMajor ? cstride : rstride   };
        }
    }

    EigenConformable(EigenIndex r, EigenIndex c, EigenIndex stride)
        : EigenConformable(r, c, r == 1 ? c*stride : stride, c == 1 ? r : r*stride) {}

    template <typename props> bool stride_compatible() const {


        return
            !negativestrides &&
            (props::inner_stride == Eigen::Dynamic || props::inner_stride == stride.inner() ||
                (EigenRowMajor ? cols : rows) == 1) &&
            (props::outer_stride == Eigen::Dynamic || props::outer_stride == stride.outer() ||
                (EigenRowMajor ? rows : cols) == 1);
    }
    operator bool() const { return conformable; }
};

template <typename Type> struct eigen_extract_stride { using type = Type; };
template <typename PlainObjectType, int MapOptions, typename StrideType>
struct eigen_extract_stride<Eigen::Map<PlainObjectType, MapOptions, StrideType>> { using type = StrideType; };
template <typename PlainObjectType, int Options, typename StrideType>
struct eigen_extract_stride<Eigen::Ref<PlainObjectType, Options, StrideType>> { using type = StrideType; };


template <typename Type_> struct EigenProps {
    using Type = Type_;
    using Scalar = typename Type::Scalar;
    using StrideType = typename eigen_extract_stride<Type>::type;
    static constexpr EigenIndex
        rows = Type::RowsAtCompileTime,
        cols = Type::ColsAtCompileTime,
        size = Type::SizeAtCompileTime;
    static constexpr bool
        row_major = Type::IsRowMajor,
        vector = Type::IsVectorAtCompileTime,
        fixed_rows = rows != Eigen::Dynamic,
        fixed_cols = cols != Eigen::Dynamic,
        fixed = size != Eigen::Dynamic,
        dynamic = !fixed_rows && !fixed_cols;

    template <EigenIndex i, EigenIndex ifzero> using if_zero = std::integral_constant<EigenIndex, i == 0 ? ifzero : i>;
    static constexpr EigenIndex inner_stride = if_zero<StrideType::InnerStrideAtCompileTime, 1>::value,
                                outer_stride = if_zero<StrideType::OuterStrideAtCompileTime,
                                                       vector ? size : row_major ? cols : rows>::value;
    static constexpr bool dynamic_stride = inner_stride == Eigen::Dynamic && outer_stride == Eigen::Dynamic;
    static constexpr bool requires_row_major = !dynamic_stride && !vector && (row_major ? inner_stride : outer_stride) == 1;
    static constexpr bool requires_col_major = !dynamic_stride && !vector && (row_major ? outer_stride : inner_stride) == 1;




    static EigenConformable<row_major> conformable(const array &a) {
        const auto dims = a.ndim();
        if (dims < 1 || dims > 2)
            return false;

        if (dims == 2) {

            EigenIndex
                np_rows = a.shape(0),
                np_cols = a.shape(1),
                np_rstride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar)),
                np_cstride = a.strides(1) / static_cast<ssize_t>(sizeof(Scalar));
            if ((fixed_rows && np_rows != rows) || (fixed_cols && np_cols != cols))
                return false;

            return {np_rows, np_cols, np_rstride, np_cstride};
        }



        const EigenIndex n = a.shape(0),
              stride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar));

        if (vector) {
            if (fixed && size != n)
                return false;
            return {rows == 1 ? 1 : n, cols == 1 ? 1 : n, stride};
        }
        else if (fixed) {

            return false;
        }
        else if (fixed_cols) {


            if (cols != n) return false;
            return {1, n, stride};
        }
        else {

            if (fixed_rows && rows != n) return false;
            return {n, 1, stride};
        }
    }

    static constexpr bool show_writeable = is_eigen_dense_map<Type>::value && is_eigen_mutable_map<Type>::value;
    static constexpr bool show_order = is_eigen_dense_map<Type>::value;
    static constexpr bool show_c_contiguous = show_order && requires_row_major;
    static constexpr bool show_f_contiguous = !show_c_contiguous && show_order && requires_col_major;

    static constexpr auto descriptor =
        _("numpy.ndarray[") + npy_format_descriptor<Scalar>::name +
        _("[")  + _<fixed_rows>(_<(size_t) rows>(), _("m")) +
        _(", ") + _<fixed_cols>(_<(size_t) cols>(), _("n")) +
        _("]") +






        _<show_writeable>(", flags.writeable", "") +
        _<show_c_contiguous>(", flags.c_contiguous", "") +
        _<show_f_contiguous>(", flags.f_contiguous", "") +
        _("]");
};



template <typename props> handle eigen_array_cast(typename props::Type const &src, handle base = handle(), bool writeable = true) {
    constexpr ssize_t elem_size = sizeof(typename props::Scalar);
    array a;
    if (props::vector)
        a = array({ src.size() }, { elem_size * src.innerStride() }, src.data(), base);
    else
        a = array({ src.rows(), src.cols() }, { elem_size * src.rowStride(), elem_size * src.colStride() },
                  src.data(), base);

    if (!writeable)
        array_proxy(a.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;

    return a.release();
}





template <typename props, typename Type>
handle eigen_ref_array(Type &src, handle parent = none()) {


    return eigen_array_cast<props>(src, parent, !std::is_const<Type>::value);
}





template <typename props, typename Type, typename = enable_if_t<is_eigen_dense_plain<Type>::value>>
handle eigen_encapsulate(Type *src) {
    capsule base(src, [](void *o) { delete static_cast<Type *>(o); });
    return eigen_ref_array<props>(*src, base);
}



template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_plain<Type>::value>> {
    using Scalar = typename Type::Scalar;
    using props = EigenProps<Type>;

    bool load(handle src, bool convert) {

        if (!convert && !isinstance<array_t<Scalar>>(src))
            return false;


        auto buf = array::ensure(src);

        if (!buf)
            return false;

        auto dims = buf.ndim();
        if (dims < 1 || dims > 2)
            return false;

        auto fits = props::conformable(buf);
        if (!fits)
            return false;


        value = Type(fits.rows, fits.cols);
        auto ref = reinterpret_steal<array>(eigen_ref_array<props>(value));
        if (dims == 1) ref = ref.squeeze();
        else if (ref.ndim() == 1) buf = buf.squeeze();

        int result = detail::npy_api::get().PyArray_CopyInto_(ref.ptr(), buf.ptr());

        if (result < 0) {
            PyErr_Clear();
            return false;
        }

        return true;
    }

private:


    template <typename CType>
    static handle cast_impl(CType *src, return_value_policy policy, handle parent) {
        switch (policy) {
            case return_value_policy::take_ownership:
            case return_value_policy::automatic:
                return eigen_encapsulate<props>(src);
            case return_value_policy::move:
                return eigen_encapsulate<props>(new CType(std::move(*src)));
            case return_value_policy::copy:
                return eigen_array_cast<props>(*src);
            case return_value_policy::reference:
            case return_value_policy::automatic_reference:
                return eigen_ref_array<props>(*src);
            case return_value_policy::reference_internal:
                return eigen_ref_array<props>(*src, parent);
            default:
                throw cast_error("unhandled return_value_policy: should not happen!");
        };
    }

public:


    static handle cast(Type &&src, return_value_policy  , handle parent) {
        return cast_impl(&src, return_value_policy::move, parent);
    }

    static handle cast(const Type &&src, return_value_policy  , handle parent) {
        return cast_impl(&src, return_value_policy::move, parent);
    }

    static handle cast(Type &src, return_value_policy policy, handle parent) {
        if (policy == return_value_policy::automatic || policy == return_value_policy::automatic_reference)
            policy = return_value_policy::copy;
        return cast_impl(&src, policy, parent);
    }

    static handle cast(const Type &src, return_value_policy policy, handle parent) {
        if (policy == return_value_policy::automatic || policy == return_value_policy::automatic_reference)
            policy = return_value_policy::copy;
        return cast(&src, policy, parent);
    }

    static handle cast(Type *src, return_value_policy policy, handle parent) {
        return cast_impl(src, policy, parent);
    }

    static handle cast(const Type *src, return_value_policy policy, handle parent) {
        return cast_impl(src, policy, parent);
    }

    static constexpr auto name = props::descriptor;

    operator Type*() { return &value; }
    operator Type&() { return value; }
    operator Type&&() && { return std::move(value); }
    template <typename T> using cast_op_type = movable_cast_op_type<T>;

private:
    Type value;
};


template <typename MapType> struct eigen_map_caster {
private:
    using props = EigenProps<MapType>;

public:







    static handle cast(const MapType &src, return_value_policy policy, handle parent) {
        switch (policy) {
            case return_value_policy::copy:
                return eigen_array_cast<props>(src);
            case return_value_policy::reference_internal:
                return eigen_array_cast<props>(src, parent, is_eigen_mutable_map<MapType>::value);
            case return_value_policy::reference:
            case return_value_policy::automatic:
            case return_value_policy::automatic_reference:
                return eigen_array_cast<props>(src, none(), is_eigen_mutable_map<MapType>::value);
            default:

                pybind11_fail("Invalid return_value_policy for Eigen Map/Ref/Block type");
        }
    }

    static constexpr auto name = props::descriptor;




    bool load(handle, bool) = delete;
    operator MapType() = delete;
    template <typename> using cast_op_type = MapType;
};


template <typename Type> struct type_caster<Type, enable_if_t<is_eigen_dense_map<Type>::value>>
    : eigen_map_caster<Type> {};



template <typename PlainObjectType, typename StrideType>
struct type_caster<
    Eigen::Ref<PlainObjectType, 0, StrideType>,
    enable_if_t<is_eigen_dense_map<Eigen::Ref<PlainObjectType, 0, StrideType>>::value>
> : public eigen_map_caster<Eigen::Ref<PlainObjectType, 0, StrideType>> {
private:
    using Type = Eigen::Ref<PlainObjectType, 0, StrideType>;
    using props = EigenProps<Type>;
    using Scalar = typename props::Scalar;
    using MapType = Eigen::Map<PlainObjectType, 0, StrideType>;
    using Array = array_t<Scalar, array::forcecast |
                ((props::row_major ? props::inner_stride : props::outer_stride) == 1 ? array::c_style :
                 (props::row_major ? props::outer_stride : props::inner_stride) == 1 ? array::f_style : 0)>;
    static constexpr bool need_writeable = is_eigen_mutable_map<Type>::value;

    std::unique_ptr<MapType> map;
    std::unique_ptr<Type> ref;






    Array copy_or_ref;
public:
    bool load(handle src, bool convert) {


        bool need_copy = !isinstance<Array>(src);

        EigenConformable<props::row_major> fits;
        if (!need_copy) {


            Array aref = reinterpret_borrow<Array>(src);

            if (aref && (!need_writeable || aref.writeable())) {
                fits = props::conformable(aref);
                if (!fits) return false;
                if (!fits.template stride_compatible<props>())
                    need_copy = true;
                else
                    copy_or_ref = std::move(aref);
            }
            else {
                need_copy = true;
            }
        }

        if (need_copy) {



            if (!convert || need_writeable) return false;

            Array copy = Array::ensure(src);
            if (!copy) return false;
            fits = props::conformable(copy);
            if (!fits || !fits.template stride_compatible<props>())
                return false;
            copy_or_ref = std::move(copy);
            loader_life_support::add_patient(copy_or_ref);
        }

        ref.reset();
        map.reset(new MapType(data(copy_or_ref), fits.rows, fits.cols, make_stride(fits.stride.outer(), fits.stride.inner())));
        ref.reset(new Type(*map));

        return true;
    }

    operator Type*() { return ref.get(); }
    operator Type&() { return *ref; }
    template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;

private:
    template <typename T = Type, enable_if_t<is_eigen_mutable_map<T>::value, int> = 0>
    Scalar *data(Array &a) { return a.mutable_data(); }

    template <typename T = Type, enable_if_t<!is_eigen_mutable_map<T>::value, int> = 0>
    const Scalar *data(Array &a) { return a.data(); }



    template <typename S> using stride_ctor_default = bool_constant<
        S::InnerStrideAtCompileTime != Eigen::Dynamic && S::OuterStrideAtCompileTime != Eigen::Dynamic &&
        std::is_default_constructible<S>::value>;


    template <typename S> using stride_ctor_dual = bool_constant<
        !stride_ctor_default<S>::value && std::is_constructible<S, EigenIndex, EigenIndex>::value>;


    template <typename S> using stride_ctor_outer = bool_constant<
        !any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value &&
        S::OuterStrideAtCompileTime == Eigen::Dynamic && S::InnerStrideAtCompileTime != Eigen::Dynamic &&
        std::is_constructible<S, EigenIndex>::value>;
    template <typename S> using stride_ctor_inner = bool_constant<
        !any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value &&
        S::InnerStrideAtCompileTime == Eigen::Dynamic && S::OuterStrideAtCompileTime != Eigen::Dynamic &&
        std::is_constructible<S, EigenIndex>::value>;

    template <typename S = StrideType, enable_if_t<stride_ctor_default<S>::value, int> = 0>
    static S make_stride(EigenIndex, EigenIndex) { return S(); }
    template <typename S = StrideType, enable_if_t<stride_ctor_dual<S>::value, int> = 0>
    static S make_stride(EigenIndex outer, EigenIndex inner) { return S(outer, inner); }
    template <typename S = StrideType, enable_if_t<stride_ctor_outer<S>::value, int> = 0>
    static S make_stride(EigenIndex outer, EigenIndex) { return S(outer); }
    template <typename S = StrideType, enable_if_t<stride_ctor_inner<S>::value, int> = 0>
    static S make_stride(EigenIndex, EigenIndex inner) { return S(inner); }

};





template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_other<Type>::value>> {
protected:
    using Matrix = Eigen::Matrix<typename Type::Scalar, Type::RowsAtCompileTime, Type::ColsAtCompileTime>;
    using props = EigenProps<Matrix>;
public:
    static handle cast(const Type &src, return_value_policy  , handle  ) {
        handle h = eigen_encapsulate<props>(new Matrix(src));
        return h;
    }
    static handle cast(const Type *src, return_value_policy policy, handle parent) { return cast(*src, policy, parent); }

    static constexpr auto name = props::descriptor;




    bool load(handle, bool) = delete;
    operator Type() = delete;
    template <typename> using cast_op_type = Type;
};

template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_sparse<Type>::value>> {
    typedef typename Type::Scalar Scalar;
    typedef remove_reference_t<decltype(*std::declval<Type>().outerIndexPtr())> StorageIndex;
    typedef typename Type::Index Index;
    static constexpr bool rowMajor = Type::IsRowMajor;

    bool load(handle src, bool) {
        if (!src)
            return false;

        auto obj = reinterpret_borrow<object>(src);
        object sparse_module = module::import("scipy.sparse");
        object matrix_type = sparse_module.attr(
            rowMajor ? "csr_matrix" : "csc_matrix");

        if (!obj.get_type().is(matrix_type)) {
            try {
                obj = matrix_type(obj);
            } catch (const error_already_set &) {
                return false;
            }
        }

        auto values = array_t<Scalar>((object) obj.attr("data"));
        auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
        auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
        auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
        auto nnz = obj.attr("nnz").cast<Index>();

        if (!values || !innerIndices || !outerIndices)
            return false;

        value = Eigen::MappedSparseMatrix<Scalar, Type::Flags, StorageIndex>(
            shape[0].cast<Index>(), shape[1].cast<Index>(), nnz,
            outerIndices.mutable_data(), innerIndices.mutable_data(), values.mutable_data());

        return true;
    }

    static handle cast(const Type &src, return_value_policy  , handle  ) {
        const_cast<Type&>(src).makeCompressed();

        object matrix_type = module::import("scipy.sparse").attr(
            rowMajor ? "csr_matrix" : "csc_matrix");

        array data(src.nonZeros(), src.valuePtr());
        array outerIndices((rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
        array innerIndices(src.nonZeros(), src.innerIndexPtr());

        return matrix_type(
            std::make_tuple(data, innerIndices, outerIndices),
            std::make_pair(src.rows(), src.cols())
        ).release();
    }

    PYBIND11_TYPE_CASTER(Type, _<(Type::IsRowMajor) != 0>("scipy.sparse.csr_matrix[", "scipy.sparse.csc_matrix[")
            + npy_format_descriptor<Scalar>::name + _("]"));
};

NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

#if defined(__GNUG__) || defined(__clang__)
#  pragma GCC diagnostic pop
#elif defined(_MSC_VER)
#  pragma warning(pop)
#endif
