cp-algo/tree/ascending_dfs.hpp

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• Last update: 2025-12-08 19:25:32+01:00
• Include: #include "cp-algo/tree/ascending_dfs.hpp"

Depends on

• cp-algo/graph/base.hpp
• cp-algo/graph/concepts.hpp
• cp-algo/graph/edge_types.hpp
• cp-algo/structures/stack_union.hpp
• cp-algo/util/big_alloc.hpp

Required by

• cp-algo/tree/diameter.hpp
• cp-algo/tree/hld.hpp

Verified with

• Minimum Diameter Spanning Tree (verify/graph/minimum_diameter_spanning_tree.test.cpp)
• Tree Diameter (verify/tree/diameter.test.cpp)
• Jump on Tree (verify/tree/jump.test.cpp)
• Lowest Common Ancestor (verify/tree/lca.test.cpp)

Code

#ifndef CP_ALGO_TREE_ASCENDING_DFS_HPP
#define CP_ALGO_TREE_ASCENDING_DFS_HPP

#include "../graph/base.hpp"
#include <cassert>
#include <vector>
#include <ranges>

namespace cp_algo::graph {
    // Generic ascending DFS that repeatedly peels leaves (degree 1).
    // `next(v)` must return the unique incident edge of `v` when degree[v] == 1.
    template<undirected_graph_type graph>
    void ascending_dfs(graph const& tree, auto &degree, auto &&next, auto &&callback, node_index root) {
        for (auto v : tree.nodes()) {
            while (degree[v] == 1) {
                edge_index ep = next(v);
                callback(v, ep);
                degree[v]--;
                v = tree.edge(ep).traverse(v);
                degree[v]--;
            }
        }
        callback(root, -1);
    }
    // XOR-based DFS that tracks the remaining incident edge via XOR.
    template<undirected_graph_type graph>
    big_vector<edge_index> xor_dfs(graph const& tree, auto &&callback, node_index root = 0) {
        big_vector<edge_index> neig_xor(tree.n());
        big_vector<int> degree(tree.n());
        for (auto v : tree.nodes()) {
            degree[v] = (int)std::ranges::distance(tree.outgoing(v));
        }
        degree[root] = 0;
        for (auto v : tree.nodes()) {
            for (auto e : tree.outgoing(v)) {
                neig_xor[v] ^= e;
            }
        }
        neig_xor[root] ^= edge_index(-1);
        ascending_dfs(tree, degree, [&](auto v) {
            edge_index ep = neig_xor[v];
            neig_xor[tree.edge(ep).traverse(v)] ^= ep;
            return ep;
        }, callback, root);

        return neig_xor; // parent edge for each node (root holds -1)
    }
    // DFS that uses a precomputed parent-edge array.
    template<undirected_graph_type graph>
    void parent_dfs(graph const& tree, auto const& parent, auto &&callback) {
        std::vector<int> degree(tree.n());
        node_index root = -1;
        for (auto [v, e] : parent | std::views::enumerate) {
            if (e != -1) {
                degree[v]++;
                degree[tree.edge(e).traverse(node_index(v))]++;
            } else {
                root = node_index(v);
            }
        }
        assert(root != -1);
        degree[root] = 0;
        ascending_dfs(tree, degree, [&](auto v) {
            return parent[v];
        }, callback, root);
    }
}
#endif // CP_ALGO_TREE_ASCENDING_DFS_HPP

#line 1 "cp-algo/tree/ascending_dfs.hpp"



#line 1 "cp-algo/graph/base.hpp"


#line 1 "cp-algo/graph/edge_types.hpp"


#include <iostream>
#include <cstdint>
namespace cp_algo::graph {
    using node_index = int;
    struct edge_base {
        int xor_nodes;

        edge_base() {}
        edge_base(node_index from, node_index to): xor_nodes(from ^ to) {}

        // Given one endpoint, return the other
        node_index traverse(node_index from) const {
            return xor_nodes ^ from;
        }

        static auto read(node_index v0 = 0) {
            node_index u, v;
            std::cin >> u >> v;
            u -= v0;
            v -= v0;
            return std::pair{u, edge_base(u, v)};
        }
    };

    struct weighted_edge: edge_base {
        int64_t w;

        weighted_edge() {}
        weighted_edge(node_index from, node_index to, int64_t w): edge_base(from, to), w(w) {}

        static auto read(node_index v0 = 0) {
            auto [u, e] = edge_base::read(v0);
            int64_t w;
            std::cin >> w;
            return std::pair{u, weighted_edge(u, e.traverse(u), w)};
        }
    };

    template<typename edge>
    concept edge_type = std::is_base_of_v<edge_base, edge>;
    template<typename edge>
    concept weighted_edge_type = std::is_base_of_v<weighted_edge, edge>;
}

#line 1 "cp-algo/graph/concepts.hpp"


#line 4 "cp-algo/graph/concepts.hpp"
#include <type_traits>

namespace cp_algo::graph {
    // Shared graph mode enum for all graph headers
    enum graph_mode { directed, undirected };
    // Traits: true for types that expose `edge_t` and static `mode`
    template<typename T, typename = void>
    struct graph_traits : std::false_type {};

    template<typename T>
    struct graph_traits<T, std::void_t<typename T::edge_t, decltype(T::mode)>> : std::true_type {
        using edge_t = typename T::edge_t;
        static constexpr auto mode = T::mode;
        static constexpr bool is_directed = mode == directed;
        static constexpr bool is_undirected = mode == undirected;
        static constexpr bool is_weighted = weighted_edge_type<edge_t>;
    };

    // Concepts
    template<typename G>
    concept graph_type = graph_traits<G>::value;

    template<typename G>
    concept digraph_type = graph_type<G> && graph_traits<G>::is_directed;

    template<typename G>
    concept undirected_graph_type = graph_type<G> && graph_traits<G>::is_undirected;

    template<typename G>
    concept weighted_graph_type = graph_type<G> && graph_traits<G>::is_weighted;

    template<typename G>
    concept weighted_digraph_type = digraph_type<G> && graph_traits<G>::is_weighted;

    template<typename G>
    concept weighted_undirected_graph_type = undirected_graph_type<G> && graph_traits<G>::is_weighted;
}

#line 1 "cp-algo/structures/stack_union.hpp"


#line 1 "cp-algo/util/big_alloc.hpp"



#include <map>
#include <deque>
#include <vector>
#include <string>
#include <cstddef>
#line 10 "cp-algo/util/big_alloc.hpp"

// Single macro to detect POSIX platforms (Linux, Unix, macOS)
#if defined(__linux__) || defined(__unix__) || (defined(__APPLE__) && defined(__MACH__))
#  define CP_ALGO_USE_MMAP 1
#  include <sys/mman.h>
#else
#  define CP_ALGO_USE_MMAP 0
#endif

namespace cp_algo {
    template <typename T, std::size_t Align = 32>
    class big_alloc {
        static_assert( Align >= alignof(void*), "Align must be at least pointer-size");
        static_assert(std::popcount(Align) == 1, "Align must be a power of two");
    public:
        using value_type = T;
        template <class U> struct rebind { using other = big_alloc<U, Align>; };
        constexpr bool operator==(const big_alloc&) const = default;
        constexpr bool operator!=(const big_alloc&) const = default;

        big_alloc() noexcept = default;
        template <typename U, std::size_t A>
        big_alloc(const big_alloc<U, A>&) noexcept {}

        [[nodiscard]] T* allocate(std::size_t n) {
            std::size_t padded = round_up(n * sizeof(T));
            std::size_t align = std::max<std::size_t>(alignof(T),  Align);
#if CP_ALGO_USE_MMAP
            if (padded >= MEGABYTE) {
                void* raw = mmap(nullptr, padded,
                                PROT_READ | PROT_WRITE,
                                MAP_PRIVATE | MAP_ANONYMOUS, -1, 0);
                madvise(raw, padded, MADV_HUGEPAGE);
                madvise(raw, padded, MADV_POPULATE_WRITE);
                return static_cast<T*>(raw);
            }
#endif
            return static_cast<T*>(::operator new(padded, std::align_val_t(align)));
        }

        void deallocate(T* p, std::size_t n) noexcept {
            if (!p) return;
            std::size_t padded = round_up(n * sizeof(T));
            std::size_t align  = std::max<std::size_t>(alignof(T),  Align);
    #if CP_ALGO_USE_MMAP
            if (padded >= MEGABYTE) { munmap(p, padded); return; }
    #endif
            ::operator delete(p, padded, std::align_val_t(align));
        }

    private:
        static constexpr std::size_t MEGABYTE = 1 << 20;
        static constexpr std::size_t round_up(std::size_t x) noexcept {
            return (x + Align - 1) / Align * Align;
        }
    };

    template<typename T>
    using big_vector = std::vector<T, big_alloc<T>>;
    template<typename T>
    using big_basic_string = std::basic_string<T, std::char_traits<T>, big_alloc<T>>;
    template<typename T>
    using big_deque = std::deque<T, big_alloc<T>>;
    template<typename Key, typename Value, typename Compare = std::less<Key>>
    using big_map = std::map<Key, Value, Compare, big_alloc<std::pair<const Key, Value>>>;
    using big_string = big_basic_string<char>;
}

#line 5 "cp-algo/structures/stack_union.hpp"
#include <iterator>
#include <ranges>
namespace cp_algo::structures {
    template<class datatype>
    struct stack_union {
        stack_union(int n = 0): head(n), next(1), data(1) {}

        void push(int v, datatype const& vdata) {
            next.push_back(head[v]);
            head[v] = (int)std::size(next) - 1;
            data.push_back(vdata);
        }
        template<typename... Args>
        void emplace(int v, Args&&... vdata) {
            next.push_back(head[v]);
            head[v] = (int)std::size(next) - 1;
            data.emplace_back(std::forward<Args>(vdata)...);
        }

        void reserve(int m) {
            data.reserve(m);
            next.reserve(m);
        }

        size_t size() const {return std::size(head);}
        size_t nodes() const {return std::size(data);}

        template<typename Su>
        struct _iterator {
            using value_type = std::conditional_t<std::is_const_v<Su>, const datatype, datatype>;
            using difference_type = std::ptrdiff_t;

            Su* su = nullptr;
            int sv = 0;

            value_type& operator*() const { return su->data[sv]; }
            _iterator& operator++() { 
                sv = su->next[sv];
                return *this; 
            }
            _iterator operator++(int) { auto tmp = *this; ++*this; return tmp; }
            friend bool operator==(_iterator const& it, std::default_sentinel_t) { 
                return it.sv == 0;
            }
        };

        using iterator = _iterator<stack_union<datatype>>;
        using const_iterator = _iterator<const stack_union<datatype>>;

        auto operator[](this auto&& self, int v) {
            using Iter = _iterator<std::remove_reference_t<decltype(self)>>;
            return std::ranges::subrange(Iter{&self, self.head[v]}, std::default_sentinel);
        }

        big_vector<int> head, next;
        big_vector<datatype> data;
    };
}

#line 7 "cp-algo/graph/base.hpp"
namespace cp_algo::graph {
    using edge_index = int;
    template<edge_type _edge_t = edge_base, graph_mode _mode = undirected>
    struct graph {
        using edge_t = _edge_t;
        static constexpr auto mode = _mode;
        using incidence_list = structures::stack_union<edge_index>;
        graph(int n, int v0 = 0): v0(v0), adj(n) {}

        graph transpose() const {
            static_assert(mode == directed, "transpose is only defined for directed graphs");
            graph<edge_t, mode> gt(n(), v0);
            for(auto v: nodes()) {
                for(auto e: outgoing(v)) {
                    gt.add_edge(edge(e).traverse(v), edge(e));
                }
            }
            return gt;
        }
        edge_index add_edge(node_index u, edge_t e) {
            edge_index idx = (edge_index)size(E);
            E.push_back(e);
            adj.push(u, idx);
            if constexpr (mode == undirected) {
                adj.push(e.traverse(u), idx);
            }
            return idx;
        }
        edge_index add_edge(node_index u, auto... Args) {
            return add_edge(u, edge_t(u, Args...));
        }
        void read_edges(node_index m) {
            adj.reserve(mode == undirected ? 2 * m : m);
            for(edge_index i = 0; i < m; i++) {
                auto [u, e] = edge_t::read(v0);
                add_edge(u, e);
            }
        }
        auto outgoing(node_index v) const {return adj[v];}
        auto edges() const {return E | std::views::all;}
        auto nodes() const {return std::views::iota(node_index(0), n());}
        auto edge_indices() const {return std::views::iota(edge_index(0), m());}
        auto&& incidence_lists(this auto&& self) {return self.adj;}
        auto&& edge(this auto&& self, edge_index e) {return self.E[e];}
        node_index n() const {return (node_index)incidence_lists().size();}
        edge_index m() const {return (edge_index)edges().size();}
    private:
        node_index v0;
        big_vector<edge_t> E;
        incidence_list adj;
    };
    // aliases for most standard cases
    template<edge_type edge_t = edge_base>
    using digraph = graph<edge_t, directed>;
    template<weighted_edge_type edge_t = weighted_edge, graph_mode mode = undirected>
    using weighted_graph = graph<edge_t, mode>;
    template<weighted_edge_type edge_t = weighted_edge>
    using weighted_digraph = digraph<edge_t>;
}

#line 5 "cp-algo/tree/ascending_dfs.hpp"
#include <cassert>
#line 8 "cp-algo/tree/ascending_dfs.hpp"

namespace cp_algo::graph {
    // Generic ascending DFS that repeatedly peels leaves (degree 1).
    // `next(v)` must return the unique incident edge of `v` when degree[v] == 1.
    template<undirected_graph_type graph>
    void ascending_dfs(graph const& tree, auto &degree, auto &&next, auto &&callback, node_index root) {
        for (auto v : tree.nodes()) {
            while (degree[v] == 1) {
                edge_index ep = next(v);
                callback(v, ep);
                degree[v]--;
                v = tree.edge(ep).traverse(v);
                degree[v]--;
            }
        }
        callback(root, -1);
    }
    // XOR-based DFS that tracks the remaining incident edge via XOR.
    template<undirected_graph_type graph>
    big_vector<edge_index> xor_dfs(graph const& tree, auto &&callback, node_index root = 0) {
        big_vector<edge_index> neig_xor(tree.n());
        big_vector<int> degree(tree.n());
        for (auto v : tree.nodes()) {
            degree[v] = (int)std::ranges::distance(tree.outgoing(v));
        }
        degree[root] = 0;
        for (auto v : tree.nodes()) {
            for (auto e : tree.outgoing(v)) {
                neig_xor[v] ^= e;
            }
        }
        neig_xor[root] ^= edge_index(-1);
        ascending_dfs(tree, degree, [&](auto v) {
            edge_index ep = neig_xor[v];
            neig_xor[tree.edge(ep).traverse(v)] ^= ep;
            return ep;
        }, callback, root);

        return neig_xor; // parent edge for each node (root holds -1)
    }
    // DFS that uses a precomputed parent-edge array.
    template<undirected_graph_type graph>
    void parent_dfs(graph const& tree, auto const& parent, auto &&callback) {
        std::vector<int> degree(tree.n());
        node_index root = -1;
        for (auto [v, e] : parent | std::views::enumerate) {
            if (e != -1) {
                degree[v]++;
                degree[tree.edge(e).traverse(node_index(v))]++;
            } else {
                root = node_index(v);
            }
        }
        assert(root != -1);
        degree[root] = 0;
        ascending_dfs(tree, degree, [&](auto v) {
            return parent[v];
        }, callback, root);
    }
}

#ifndef CP_ALGO_TREE_ASCENDING_DFS_HPP
#define CP_ALGO_TREE_ASCENDING_DFS_HPP
#include "../graph/base.hpp"
#include <cassert>
#include <vector>
#include <ranges>
namespace cp_algo::graph{template<undirected_graph_type graph>void ascending_dfs(graph const&tree,auto&degree,auto&&next,auto&&callback,node_index root){for(auto v:tree.nodes()){while(degree[v]==1){edge_index ep=next(v);callback(v,ep);degree[v]--;v=tree.edge(ep).traverse(v);degree[v]--;}}callback(root,-1);}template<undirected_graph_type graph>big_vector<edge_index>xor_dfs(graph const&tree,auto&&callback,node_index root=0){big_vector<edge_index>neig_xor(tree.n());big_vector<int>degree(tree.n());for(auto v:tree.nodes()){degree[v]=(int)std::ranges::distance(tree.outgoing(v));}degree[root]=0;for(auto v:tree.nodes()){for(auto e:tree.outgoing(v)){neig_xor[v]^=e;}}neig_xor[root]^=edge_index(-1);ascending_dfs(tree,degree,[&](auto v){edge_index ep=neig_xor[v];neig_xor[tree.edge(ep).traverse(v)]^=ep;return ep;},callback,root);return neig_xor;}template<undirected_graph_type graph>void parent_dfs(graph const&tree,auto const&parent,auto&&callback){std::vector<int>degree(tree.n());node_index root=-1;for(auto[v,e]:parent|std::views::enumerate){if(e!=-1){degree[v]++;degree[tree.edge(e).traverse(node_index(v))]++;}else{root=node_index(v);}}assert(root!=-1);degree[root]=0;ascending_dfs(tree,degree,[&](auto v){return parent[v];},callback,root);}}
#endif

#line 1 "cp-algo/tree/ascending_dfs.hpp"
#line 1 "cp-algo/graph/base.hpp"
#line 1 "cp-algo/graph/edge_types.hpp"
#include <iostream>
#include <cstdint>
namespace cp_algo::graph{using node_index=int;struct edge_base{int xor_nodes;edge_base(){}edge_base(node_index from,node_index to):xor_nodes(from^to){}node_index traverse(node_index from)const{return xor_nodes^from;}static auto read(node_index v0=0){node_index u,v;std::cin>>u>>v;u-=v0;v-=v0;return std::pair{u,edge_base(u,v)};}};struct weighted_edge:edge_base{int64_t w;weighted_edge(){}weighted_edge(node_index from,node_index to,int64_t w):edge_base(from,to),w(w){}static auto read(node_index v0=0){auto[u,e]=edge_base::read(v0);int64_t w;std::cin>>w;return std::pair{u,weighted_edge(u,e.traverse(u),w)};}};template<typename edge>concept edge_type=std::is_base_of_v<edge_base,edge>;template<typename edge>concept weighted_edge_type=std::is_base_of_v<weighted_edge,edge>;}
#line 1 "cp-algo/graph/concepts.hpp"
#line 4 "cp-algo/graph/concepts.hpp"
#include <type_traits>
namespace cp_algo::graph{enum graph_mode{directed,undirected};template<typename T,typename=void>struct graph_traits:std::false_type{};template<typename T>struct graph_traits<T,std::void_t<typename T::edge_t,decltype(T::mode)>>:std::true_type{using edge_t=typename T::edge_t;static constexpr auto mode=T::mode;static constexpr bool is_directed=mode==directed;static constexpr bool is_undirected=mode==undirected;static constexpr bool is_weighted=weighted_edge_type<edge_t>;};template<typename G>concept graph_type=graph_traits<G>::value;template<typename G>concept digraph_type=graph_type<G>&&graph_traits<G>::is_directed;template<typename G>concept undirected_graph_type=graph_type<G>&&graph_traits<G>::is_undirected;template<typename G>concept weighted_graph_type=graph_type<G>&&graph_traits<G>::is_weighted;template<typename G>concept weighted_digraph_type=digraph_type<G>&&graph_traits<G>::is_weighted;template<typename G>concept weighted_undirected_graph_type=undirected_graph_type<G>&&graph_traits<G>::is_weighted;}
#line 1 "cp-algo/structures/stack_union.hpp"
#line 1 "cp-algo/util/big_alloc.hpp"
#include <map>
#include <deque>
#include <vector>
#include <string>
#include <cstddef>
#line 10 "cp-algo/util/big_alloc.hpp"
#if defined(__linux__) || defined(__unix__) || (defined(__APPLE__) && defined(__MACH__))
#  define CP_ALGO_USE_MMAP 1
#  include <sys/mman.h>
#else
#  define CP_ALGO_USE_MMAP 0
#endif
namespace cp_algo{template<typename T,std::size_t Align=32>class big_alloc{static_assert(Align>=alignof(void*),"Align must be at least pointer-size");static_assert(std::popcount(Align)==1,"Align must be a power of two");public:using value_type=T;template<class U>struct rebind{using other=big_alloc<U,Align>;};constexpr bool operator==(const big_alloc&)const=default;constexpr bool operator!=(const big_alloc&)const=default;big_alloc()noexcept=default;template<typename U,std::size_t A>big_alloc(const big_alloc<U,A>&)noexcept{}[[nodiscard]]T*allocate(std::size_t n){std::size_t padded=round_up(n*sizeof(T));std::size_t align=std::max<std::size_t>(alignof(T),Align);
#if CP_ALGO_USE_MMAP
if(padded>=MEGABYTE){void*raw=mmap(nullptr,padded,PROT_READ|PROT_WRITE,MAP_PRIVATE|MAP_ANONYMOUS,-1,0);madvise(raw,padded,MADV_HUGEPAGE);madvise(raw,padded,MADV_POPULATE_WRITE);return static_cast<T*>(raw);}
#endif
return static_cast<T*>(::operator new(padded,std::align_val_t(align)));}void deallocate(T*p,std::size_t n)noexcept{if(!p)return;std::size_t padded=round_up(n*sizeof(T));std::size_t align=std::max<std::size_t>(alignof(T),Align);
#if CP_ALGO_USE_MMAP
if(padded>=MEGABYTE){munmap(p,padded);return;}
#endif
::operator delete(p,padded,std::align_val_t(align));}private:static constexpr std::size_t MEGABYTE=1<<20;static constexpr std::size_t round_up(std::size_t x)noexcept{return(x+Align-1)/Align*Align;}};template<typename T>using big_vector=std::vector<T,big_alloc<T>>;template<typename T>using big_basic_string=std::basic_string<T,std::char_traits<T>,big_alloc<T>>;template<typename T>using big_deque=std::deque<T,big_alloc<T>>;template<typename Key,typename Value,typename Compare=std::less<Key>>using big_map=std::map<Key,Value,Compare,big_alloc<std::pair<const Key,Value>>>;using big_string=big_basic_string<char>;}
#line 5 "cp-algo/structures/stack_union.hpp"
#include <iterator>
#include <ranges>
namespace cp_algo::structures{template<class datatype>struct stack_union{stack_union(int n=0):head(n),next(1),data(1){}void push(int v,datatype const&vdata){next.push_back(head[v]);head[v]=(int)std::size(next)-1;data.push_back(vdata);}template<typename... Args>void emplace(int v,Args&&... vdata){next.push_back(head[v]);head[v]=(int)std::size(next)-1;data.emplace_back(std::forward<Args>(vdata)...);}void reserve(int m){data.reserve(m);next.reserve(m);}size_t size()const{return std::size(head);}size_t nodes()const{return std::size(data);}template<typename Su>struct _iterator{using value_type=std::conditional_t<std::is_const_v<Su>,const datatype,datatype>;using difference_type=std::ptrdiff_t;Su*su=nullptr;int sv=0;value_type&operator*()const{return su->data[sv];}_iterator&operator++(){sv=su->next[sv];return*this;}_iterator operator++(int){auto tmp=*this;++*this;return tmp;}friend bool operator==(_iterator const&it,std::default_sentinel_t){return it.sv==0;}};using iterator=_iterator<stack_union<datatype>>;using const_iterator=_iterator<const stack_union<datatype>>;auto operator[](this auto&&self,int v){using Iter=_iterator<std::remove_reference_t<decltype(self)>>;return std::ranges::subrange(Iter{&self,self.head[v]},std::default_sentinel);}big_vector<int>head,next;big_vector<datatype>data;};}
#line 7 "cp-algo/graph/base.hpp"
namespace cp_algo::graph{using edge_index=int;template<edge_type _edge_t=edge_base,graph_mode _mode=undirected>struct graph{using edge_t=_edge_t;static constexpr auto mode=_mode;using incidence_list=structures::stack_union<edge_index>;graph(int n,int v0=0):v0(v0),adj(n){}graph transpose()const{static_assert(mode==directed,"transpose is only defined for directed graphs");graph<edge_t,mode>gt(n(),v0);for(auto v:nodes()){for(auto e:outgoing(v)){gt.add_edge(edge(e).traverse(v),edge(e));}}return gt;}edge_index add_edge(node_index u,edge_t e){edge_index idx=(edge_index)size(E);E.push_back(e);adj.push(u,idx);if constexpr(mode==undirected){adj.push(e.traverse(u),idx);}return idx;}edge_index add_edge(node_index u,auto... Args){return add_edge(u,edge_t(u,Args...));}void read_edges(node_index m){adj.reserve(mode==undirected?2*m:m);for(edge_index i=0;i<m;i++){auto[u,e]=edge_t::read(v0);add_edge(u,e);}}auto outgoing(node_index v)const{return adj[v];}auto edges()const{return E|std::views::all;}auto nodes()const{return std::views::iota(node_index(0),n());}auto edge_indices()const{return std::views::iota(edge_index(0),m());}auto&&incidence_lists(this auto&&self){return self.adj;}auto&&edge(this auto&&self,edge_index e){return self.E[e];}node_index n()const{return(node_index)incidence_lists().size();}edge_index m()const{return(edge_index)edges().size();}private:node_index v0;big_vector<edge_t>E;incidence_list adj;};template<edge_type edge_t=edge_base>using digraph=graph<edge_t,directed>;template<weighted_edge_type edge_t=weighted_edge,graph_mode mode=undirected>using weighted_graph=graph<edge_t,mode>;template<weighted_edge_type edge_t=weighted_edge>using weighted_digraph=digraph<edge_t>;}
#line 5 "cp-algo/tree/ascending_dfs.hpp"
#include <cassert>
#line 8 "cp-algo/tree/ascending_dfs.hpp"
namespace cp_algo::graph{template<undirected_graph_type graph>void ascending_dfs(graph const&tree,auto&degree,auto&&next,auto&&callback,node_index root){for(auto v:tree.nodes()){while(degree[v]==1){edge_index ep=next(v);callback(v,ep);degree[v]--;v=tree.edge(ep).traverse(v);degree[v]--;}}callback(root,-1);}template<undirected_graph_type graph>big_vector<edge_index>xor_dfs(graph const&tree,auto&&callback,node_index root=0){big_vector<edge_index>neig_xor(tree.n());big_vector<int>degree(tree.n());for(auto v:tree.nodes()){degree[v]=(int)std::ranges::distance(tree.outgoing(v));}degree[root]=0;for(auto v:tree.nodes()){for(auto e:tree.outgoing(v)){neig_xor[v]^=e;}}neig_xor[root]^=edge_index(-1);ascending_dfs(tree,degree,[&](auto v){edge_index ep=neig_xor[v];neig_xor[tree.edge(ep).traverse(v)]^=ep;return ep;},callback,root);return neig_xor;}template<undirected_graph_type graph>void parent_dfs(graph const&tree,auto const&parent,auto&&callback){std::vector<int>degree(tree.n());node_index root=-1;for(auto[v,e]:parent|std::views::enumerate){if(e!=-1){degree[v]++;degree[tree.edge(e).traverse(node_index(v))]++;}else{root=node_index(v);}}assert(root!=-1);degree[root]=0;ascending_dfs(tree,degree,[&](auto v){return parent[v];},callback,root);}}

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