Merge remote-tracking branch 'upstream/fixgraph' into fixgraph

This commit is contained in:
Filip Hlásek 2020-08-02 23:25:48 -07:00
commit f1b909c8da
12 changed files with 693 additions and 528 deletions

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@ -39,6 +39,7 @@ add_subdirectory(probability)
add_subdirectory(data_structures) add_subdirectory(data_structures)
add_subdirectory(machine_learning) add_subdirectory(machine_learning)
add_subdirectory(numerical_methods) add_subdirectory(numerical_methods)
add_subdirectory(graph)
cmake_policy(SET CMP0054 NEW) cmake_policy(SET CMP0054 NEW)
cmake_policy(SET CMP0057 NEW) cmake_policy(SET CMP0057 NEW)

20
graph/CMakeLists.txt Normal file
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@ -0,0 +1,20 @@
# If necessary, use the RELATIVE flag, otherwise each source file may be listed
# with full pathname. RELATIVE may makes it easier to extract an executable name
# automatically.
file( GLOB APP_SOURCES RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.cpp )
# file( GLOB APP_SOURCES ${CMAKE_SOURCE_DIR}/*.c )
# AUX_SOURCE_DIRECTORY(${CMAKE_CURRENT_SOURCE_DIR} APP_SOURCES)
foreach( testsourcefile ${APP_SOURCES} )
# I used a simple string replace, to cut off .cpp.
string( REPLACE ".cpp" "" testname ${testsourcefile} )
add_executable( ${testname} ${testsourcefile} )
set_target_properties(${testname} PROPERTIES
LINKER_LANGUAGE CXX
)
if(OpenMP_CXX_FOUND)
target_link_libraries(${testname} OpenMP::OpenMP_CXX)
endif()
install(TARGETS ${testname} DESTINATION "bin/graph")
endforeach( testsourcefile ${APP_SOURCES} )

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@ -1,62 +1,196 @@
/**
*
* \file
* \brief [Breadth First Search Algorithm
* (Breadth First Search)](https://en.wikipedia.org/wiki/Breadth-first_search)
*
* \author [Ayaan Khan](http://github.com/ayaankhan98)
*
* \details
* Breadth First Search also quoted as BFS is a Graph Traversal Algorithm.
* Time Complexity O(|V| + |E|) where V are the number of vertices and E
* are the number of edges in the graph.
*
* Applications of Breadth First Search are
*
* 1. Finding shortest path between two vertices say u and v, with path
* length measured by number of edges (an advantage over depth first
* search algorithm)
* 2. Ford-Fulkerson Method for computing the maximum flow in a flow network.
* 3. Testing bipartiteness of a graph.
* 4. Cheney's Algorithm, Copying garbage collection.
*
* And there are many more...
*
* <h4>working</h4>
* In the implementation below we first created a graph using the adjacency
* list representation of graph.
* Breadth First Search Works as follows
* it requires a vertex as a start vertex, Start vertex is that vertex
* from where you want to start traversing the graph.
* we maintain a bool array or a vector to keep track of the vertices
* which we have visited so that we do not traverse the visited vertices
* again and again and eventually fall into an infinite loop. Along with this
* boolen array we use a Queue.
*
* 1. First we mark the start vertex as visited.
* 2. Push this visited vertex in the Queue.
* 3. while the queue is not empty we repeat the following steps
*
* 1. Take out an element from the front of queue
* 2. start exploring the adjacency list of this vertex
* if element in the adjacency list is not visited then we
* push that element into the queue and mark this as visited
*
*/
#include <algorithm>
#include <cassert>
#include <iostream> #include <iostream>
using namespace std; #include <queue>
class graph { #include <vector>
int v;
list<int> *adj;
public: /**
graph(int v); * \namespace graph
void addedge(int src, int dest); * \brief Graph algorithms
void printgraph(); */
void bfs(int s); namespace graph {
}; /**
graph::graph(int v) { * \brief
this->v = v; * Adds and edge between two vertices of graph say u and v in this
this->adj = new list<int>[v]; * case.
*
* @param adj Adjacency list representation of graph
* @param u first vertex
* @param v second vertex
*
*/
void addEdge(std::vector<std::vector<int>> *adj, int u, int v) {
/**
* Here we are considering directed graph that's the
* reason we are adding v to the adjacency list representation of u
* but not adding u to the adjacency list representation of v
*
* in case of a un-directed graph you can un comment the statement below.
*/
(*adj)[u - 1].push_back(v - 1);
// adj[v - 1].push_back(u -1);
} }
void graph::addedge(int src, int dest) {
src--; /**
dest--; * \brief
adj[src].push_back(dest); * Function performs the breadth first search algorithm over the graph
// adj[dest].push_back(src); *
* @param adj Adjacency list representation of graph
* @param start vertex from where traversing starts
*
*/
std::vector<int> beadth_first_search(const std::vector<std::vector<int>> &adj,
int start) {
size_t vertices = adj.size();
std::vector<int> result;
/// vector to keep track of visited vertices
std::vector<bool> visited(vertices, 0);
std::queue<int> tracker;
/// marking the start vertex as visited
visited[start] = true;
tracker.push(start);
while (!tracker.empty()) {
size_t vertex = tracker.front();
tracker.pop();
result.push_back(vertex + 1);
for (auto x : adj[vertex]) {
/// if the vertex is not visited then mark this as visited
/// and push it to the queue
if (!visited[x]) {
visited[x] = true;
tracker.push(x);
}
}
}
return result;
} }
void graph::printgraph() { } // namespace graph
for (int i = 0; i < this->v; i++) {
cout << "Adjacency list of vertex " << i + 1 << " is \n"; void tests() {
list<int>::iterator it; std::cout << "Initiating Tests" << std::endl;
for (it = adj[i].begin(); it != adj[i].end(); ++it) {
cout << *it + 1 << " "; /// Test 1 Begin
} std::vector<std::vector<int>> graphData(4, std::vector<int>());
cout << endl; graph::addEdge(&graphData, 1, 2);
} graph::addEdge(&graphData, 1, 3);
} graph::addEdge(&graphData, 2, 3);
void graph::bfs(int s) { graph::addEdge(&graphData, 3, 1);
bool *visited = new bool[this->v + 1]; graph::addEdge(&graphData, 3, 4);
memset(visited, false, sizeof(bool) * (this->v + 1)); graph::addEdge(&graphData, 4, 4);
visited[s] = true;
list<int> q; std::vector<int> returnedResult = graph::beadth_first_search(graphData, 2);
q.push_back(s); std::vector<int> correctResult = {3, 1, 4, 2};
list<int>::iterator it;
while (!q.empty()) { assert(std::equal(correctResult.begin(), correctResult.end(),
int u = q.front(); returnedResult.begin()));
cout << u << " "; std::cout << "Test 1 Passed..." << std::endl;
q.pop_front();
for (it = adj[u].begin(); it != adj[u].end(); ++it) { /// Test 2 Begin
if (visited[*it] == false) { /// clear data from previous test
visited[*it] = true; returnedResult.clear();
q.push_back(*it); correctResult.clear();
}
} returnedResult = graph::beadth_first_search(graphData, 0);
} correctResult = {1, 2, 3, 4};
assert(std::equal(correctResult.begin(), correctResult.end(),
returnedResult.begin()));
std::cout << "Test 2 Passed..." << std::endl;
/// Test 3 Begins
/// clear data from previous test
graphData.clear();
returnedResult.clear();
correctResult.clear();
graphData.resize(6);
graph::addEdge(&graphData, 1, 2);
graph::addEdge(&graphData, 1, 3);
graph::addEdge(&graphData, 2, 4);
graph::addEdge(&graphData, 3, 4);
graph::addEdge(&graphData, 2, 5);
graph::addEdge(&graphData, 4, 6);
returnedResult = graph::beadth_first_search(graphData, 0);
correctResult = {1, 2, 3, 4, 5, 6};
assert(std::equal(correctResult.begin(), correctResult.end(),
returnedResult.begin()));
std::cout << "Test 3 Passed..." << std::endl;
} }
/** Main function */
int main() { int main() {
graph g(4); /// running predefined test cases
g.addedge(1, 2); tests();
g.addedge(2, 3);
g.addedge(3, 4); size_t vertices, edges;
g.addedge(1, 4); std::cout << "Enter the number of vertices : ";
g.addedge(1, 3); std::cin >> vertices;
// g.printgraph(); std::cout << "Enter the number of edges : ";
g.bfs(2); std::cin >> edges;
/// creating a graph
std::vector<std::vector<int>> adj(vertices, std::vector<int>());
/// taking input for edges
std::cout << "Enter vertices in pair which have edges between them : "
<< std::endl;
while (edges--) {
int u, v;
std::cin >> u >> v;
graph::addEdge(&adj, u, v);
}
/// running Breadth First Search Algorithm on the graph
graph::beadth_first_search(adj, 0);
return 0; return 0;
} }

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@ -7,9 +7,11 @@
#include <algorithm> // for min & max #include <algorithm> // for min & max
#include <iostream> // for cout #include <iostream> // for cout
#include <vector> // for std::vector #include <vector> // for std::vector
using std::cout; using std::cout;
using std::min; using std::min;
using std::vector; using std::vector;
class Solution { class Solution {
vector<vector<int>> graph; vector<vector<int>> graph;
vector<int> in_time, out_time; vector<int> in_time, out_time;

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@ -15,9 +15,9 @@
* <pre> * <pre>
* Example - Here is graph with 3 connected components * Example - Here is graph with 3 connected components
* *
* 3 9 6 8 * 1 4 5 8
* / \ / / \ / \ * / \ / / \ / \
* 2---4 2 7 3 7 * 2---3 6 7 9 10
* *
* first second third * first second third
* component component component * component component component
@ -26,97 +26,123 @@
*/ */
#include <algorithm> #include <algorithm>
#include <cassert>
#include <iostream> #include <iostream>
#include <vector> #include <vector>
using std::vector;
/** /**
* Class for representing graph as a adjacency list. * @namespace graph
* @brief Graph Algorithms
*/ */
class graph {
private:
/** \brief adj stores adjacency list representation of graph */
vector<vector<int>> adj;
/** \brief keep track of connected components */
int connected_components;
void depth_first_search();
void explore(int, vector<bool> &);
public:
/**
* \brief Constructor that intiliazes the graph on creation and set
* the connected components to 0
*/
explicit graph(int n) : adj(n, vector<int>()) { connected_components = 0; }
void addEdge(int, int);
/**
* \brief Function the calculates the connected compoents in the graph
* by performing the depth first search on graph
*
* @return connected_components total connected components in graph
*/
int getConnectedComponents() {
depth_first_search();
return connected_components;
}
};
namespace graph {
/** /**
* \brief Function that add edge between two nodes or vertices of graph * @brief Function that add edge between two nodes or vertices of graph
* *
* @param u any node or vertex of graph * @param adj adjacency list of graph.
* @param v any node or vertex of graph * @param u any node or vertex of graph.
* @param v any node or vertex of graph.
*/ */
void graph::addEdge(int u, int v) { void addEdge(std::vector<std::vector<int>> *adj, int u, int v) {
adj[u - 1].push_back(v - 1); (*adj)[u - 1].push_back(v - 1);
adj[v - 1].push_back(u - 1); (*adj)[v - 1].push_back(u - 1);
} }
/** /**
* \brief Function that perfoms depth first search algorithm on graph * @brief Utility function for depth first seach algorithm
* this function explores the vertex which is passed into.
*
* @param adj adjacency list of graph.
* @param u vertex or node to be explored.
* @param visited already visited vertices.
*/ */
void graph::depth_first_search() { void explore(const std::vector<std::vector<int>> *adj, int u,
int n = adj.size(); std::vector<bool> *visited) {
vector<bool> visited(n, false); (*visited)[u] = true;
for (auto v : (*adj)[u]) {
if (!(*visited)[v]) {
explore(adj, v, visited);
}
}
}
/**
* @brief Function that perfoms depth first search algorithm on graph
* and calculated the number of connected components.
*
* @param adj adjacency list of graph.
*
* @return connected_components number of connected components in graph.
*/
int getConnectedComponents(const std::vector<std::vector<int>> *adj) {
int n = adj->size();
int connected_components = 0;
std::vector<bool> visited(n, false);
for (int i = 0; i < n; i++) { for (int i = 0; i < n; i++) {
if (!visited[i]) { if (!visited[i]) {
explore(i, visited); explore(adj, i, &visited);
connected_components++; connected_components++;
} }
} }
return connected_components;
} }
/** } // namespace graph
* \brief Utility function for depth first seach algorithm
* this function explores the vertex which is passed into. /** Function to test the algorithm */
* void tests() {
* @param u vertex or node to be explored std::cout << "Running predefined tests..." << std::endl;
* @param visited already visited vertex std::cout << "Initiating Test 1..." << std::endl;
*/ std::vector<std::vector<int>> adj1(9, std::vector<int>());
void graph::explore(int u, vector<bool> &visited) { graph::addEdge(&adj1, 1, 2);
visited[u] = true; graph::addEdge(&adj1, 1, 3);
for (auto v : adj[u]) { graph::addEdge(&adj1, 3, 4);
if (!visited[v]) { graph::addEdge(&adj1, 5, 7);
explore(v, visited); graph::addEdge(&adj1, 5, 6);
} graph::addEdge(&adj1, 8, 9);
}
assert(graph::getConnectedComponents(&adj1) == 3);
std::cout << "Test 1 Passed..." << std::endl;
std::cout << "Innitiating Test 2..." << std::endl;
std::vector<std::vector<int>> adj2(10, std::vector<int>());
graph::addEdge(&adj2, 1, 2);
graph::addEdge(&adj2, 1, 3);
graph::addEdge(&adj2, 1, 4);
graph::addEdge(&adj2, 2, 3);
graph::addEdge(&adj2, 3, 4);
graph::addEdge(&adj2, 4, 8);
graph::addEdge(&adj2, 4, 10);
graph::addEdge(&adj2, 8, 10);
graph::addEdge(&adj2, 8, 9);
graph::addEdge(&adj2, 5, 7);
graph::addEdge(&adj2, 5, 6);
graph::addEdge(&adj2, 6, 7);
assert(graph::getConnectedComponents(&adj2) == 2);
std::cout << "Test 2 Passed..." << std::endl;
} }
/** Main function */ /** Main function */
int main() { int main() {
/// creating a graph with 4 vertex /// running predefined tests
graph g(4); tests();
/// Adding edges between vertices int vertices = int(), edges = int();
g.addEdge(1, 2); std::cout << "Enter the number of vertices : ";
g.addEdge(3, 2); std::cin >> vertices;
std::cout << "Enter the number of edges : ";
std::cin >> edges;
/// printing the connected components std::vector<std::vector<int>> adj(vertices, std::vector<int>());
std::cout << g.getConnectedComponents();
int u = int(), v = int();
while (edges--) {
std::cin >> u >> v;
graph::addEdge(&adj, u, v);
}
int cc = graph::getConnectedComponents(&adj);
std::cout << cc << std::endl;
return 0; return 0;
} }

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@ -1,313 +1,57 @@
/** #include <iostream>
* @file cycle_check_directed graph.cpp #include <vector>
* #include <stdlib.h>
* @brief BFS and DFS algorithms to check for cycle in a directed graph. using std::vector;
* using std::pair;
* @author [Anmol3299](mailto:mittalanmol22@gmail.com)
*
*/
#include <iostream> // for std::cout void explore(int i, vector<vector<int>> &adj, int *state)
#include <map> // for std::map {
#include <queue> // for std::queue state[i] = 1;
#include <stdexcept> // for throwing errors for(auto it2 : adj[i])
#include <type_traits> // for std::remove_reference {
#include <utility> // for std::move if (state[it2] == 0)
#include <vector> // for std::vector {
explore(it2, adj,state);
/** }
* Implementation of non-weighted directed edge of a graph. if (state[it2] == 1)
* {
* The source vertex of the edge is labelled "src" and destination vertex is std::cout<<"1";
* labelled "dest". exit(0);
*/ }
struct Edge { }
unsigned int src; state[i] = 2;
unsigned int dest;
Edge() = delete;
~Edge() = default;
Edge(Edge&&) = default;
Edge& operator=(Edge&&) = default;
Edge(Edge const&) = default;
Edge& operator=(Edge const&) = default;
/** Set the source and destination of the vertex.
*
* @param source is the source vertex of the edge.
* @param destination is the destination vertex of the edge.
*/
Edge(unsigned int source, unsigned int destination)
: src(source), dest(destination) {}
}; };
int acyclic(vector<vector<int> > &adj,size_t n) {
//write your code here
using AdjList = std::map<unsigned int, std::vector<unsigned int>>; int state[n]; // permitted states are 0 1 and 2
/** // mark the states of all vertices initially to 0
* Implementation of graph class. for(int i=0;i<n;i++)
* state[i] = 0;
* The graph will be represented using Adjacency List representation.
* This class contains 2 data members "m_vertices" & "m_adjList" used to
* represent the number of vertices and adjacency list of the graph
* respectively. The vertices are labelled 0 - (m_vertices - 1).
*/
class Graph {
public:
Graph() : m_vertices(0), m_adjList({}) {}
~Graph() = default;
Graph(Graph&&) = default;
Graph& operator=(Graph&&) = default;
Graph(Graph const&) = default;
Graph& operator=(Graph const&) = default;
/** Create a graph from vertices and adjacency list. for(auto it1 = 0; it1 != adj.size(); it1++)
* {
* @param vertices specify the number of vertices the graph would contain. if (state[it1] == 0)
* @param adjList is the adjacency list representation of graph. explore(it1,adj,state);
*/ if (state[it1] == 1)
Graph(unsigned int vertices, AdjList const& adjList) {
: m_vertices(vertices), m_adjList(adjList) {} std::cout<<"1";
exit(0);
/** Create a graph from vertices and adjacency list.
*
* @param vertices specify the number of vertices the graph would contain.
* @param adjList is the adjacency list representation of graph.
*/
Graph(unsigned int vertices, AdjList&& adjList)
: m_vertices(vertices), m_adjList(std::move(adjList)) {}
/** Create a graph from vertices and a set of edges.
*
* Adjacency list of the graph would be created from the set of edges. If
* the source or destination of any edge has a value greater or equal to
* number of vertices, then it would throw a range_error.
*
* @param vertices specify the number of vertices the graph would contain.
* @param edges is a vector of edges.
*/
Graph(unsigned int vertices, std::vector<Edge> const& edges)
: m_vertices(vertices) {
for (auto const& edge : edges) {
if (edge.src >= vertices || edge.dest >= vertices) {
throw std::range_error(
"Either src or dest of edge out of range");
}
m_adjList[edge.src].emplace_back(edge.dest);
} }
} }
std::cout<<"0";
/** Return a const reference of the adjacency list.
*
* @return const reference to the adjacency list
*/
std::remove_reference<AdjList>::type const& getAdjList() const {
return m_adjList;
}
/**
* @return number of vertices in the graph.
*/
unsigned int getVertices() const { return m_vertices; }
/** Add vertices in the graph.
*
* @param num is the number of vertices to be added. It adds 1 vertex by
* default.
*
*/
void addVertices(unsigned int num = 1) { m_vertices += num; }
/** Add an edge in the graph.
*
* @param edge that needs to be added.
*/
void addEdge(Edge const& edge) {
if (edge.src >= m_vertices || edge.dest >= m_vertices) {
throw std::range_error("Either src or dest of edge out of range");
}
m_adjList[edge.src].emplace_back(edge.dest);
}
/** Add an Edge in the graph
*
* @param source is source vertex of the edge.
* @param destination is the destination vertex of the edge.
*/
void addEdge(unsigned int source, unsigned int destination) {
if (source >= m_vertices || destination >= m_vertices) {
throw std::range_error(
"Either source or destination of edge out of range");
}
m_adjList[source].emplace_back(destination);
}
private:
unsigned int m_vertices;
AdjList m_adjList;
};
/**
* Check if a directed graph has a cycle or not.
*
* This class provides 2 methods to check for cycle in a directed graph:
* isCyclicDFS & isCyclicBFS.
*
* - isCyclicDFS uses DFS traversal method to check for cycle in a graph.
* - isCyclidBFS used BFS traversal method to check for cycle in a graph.
*/
class CycleCheck {
private:
enum nodeStates : uint8_t { not_visited = 0, in_stack, visited };
/** Helper function of "isCyclicDFS".
*
* @param adjList is the adjacency list representation of some graph.
* @param state is the state of the nodes of the graph.
* @param node is the node being evaluated.
*
* @return true if graph has a cycle, else false.
*/
static bool isCyclicDFSHelper(AdjList const& adjList,
std::vector<nodeStates>* state,
unsigned int node) {
// Add node "in_stack" state.
(*state)[node] = in_stack;
// If the node has children, then recursively visit all children of the
// node.
auto const it = adjList.find(node);
if (it != adjList.end()) {
for (auto child : it->second) {
// If state of child node is "not_visited", evaluate that child
// for presence of cycle.
auto state_of_child = (*state)[child];
if (state_of_child == not_visited) {
if (isCyclicDFSHelper(adjList, state, child)) {
return true;
}
} else if (state_of_child == in_stack) {
// If child node was "in_stack", then that means that there
// is a cycle in the graph. Return true for presence of the
// cycle.
return true;
}
}
}
// Current node has been evaluated for the presence of cycle and had no
// cycle. Mark current node as "visited".
(*state)[node] = visited;
// Return that current node didn't result in any cycles.
return false;
}
public:
/** Driver function to check if a graph has a cycle.
*
* This function uses DFS to check for cycle in the graph.
*
* @param graph which needs to be evaluated for the presence of cycle.
* @return true if a cycle is detected, else false.
*/
static bool isCyclicDFS(Graph const& graph) {
auto vertices = graph.getVertices();
/** State of the node.
*
* It is a vector of "nodeStates" which represents the state node is in.
* It can take only 3 values: "not_visited", "in_stack", and "visited".
*
* Initially, all nodes are in "not_visited" state.
*/
std::vector<nodeStates> state(vertices, not_visited);
// Start visiting each node.
for (unsigned int node = 0; node < vertices; node++) {
// If a node is not visited, only then check for presence of cycle.
// There is no need to check for presence of cycle for a visited
// node as it has already been checked for presence of cycle.
if (state[node] == not_visited) {
// Check for cycle.
if (isCyclicDFSHelper(graph.getAdjList(), &state, node)) {
return true;
}
}
}
// All nodes have been safely traversed, that means there is no cycle in
// the graph. Return false.
return false;
}
/** Check if a graph has cycle or not.
*
* This function uses BFS to check if a graph is cyclic or not.
*
* @param graph which needs to be evaluated for the presence of cycle.
* @return true if a cycle is detected, else false.
*/
static bool isCyclicBFS(Graph const& graph) {
auto graphAjdList = graph.getAdjList();
auto vertices = graph.getVertices();
std::vector<unsigned int> indegree(vertices, 0);
// Calculate the indegree i.e. the number of incident edges to the node.
for (auto const& list : graphAjdList) {
auto children = list.second;
for (auto const& child : children) {
indegree[child]++;
}
}
std::queue<unsigned int> can_be_solved;
for (unsigned int node = 0; node < vertices; node++) {
// If a node doesn't have any input edges, then that node will
// definately not result in a cycle and can be visited safely.
if (!indegree[node]) {
can_be_solved.emplace(node);
}
}
// Vertices that need to be traversed.
auto remain = vertices;
// While there are safe nodes that we can visit.
while (!can_be_solved.empty()) {
auto solved = can_be_solved.front();
// Visit the node.
can_be_solved.pop();
// Decrease number of nodes that need to be traversed.
remain--;
// Visit all the children of the visited node.
auto it = graphAjdList.find(solved);
if (it != graphAjdList.end()) {
for (auto child : it->second) {
// Check if we can visited the node safely.
if (--indegree[child] == 0) {
// if node can be visited safely, then add that node to
// the visit queue.
can_be_solved.emplace(child);
}
}
}
}
// If there are still nodes that we can't visit, then it means that
// there is a cycle and return true, else return false.
return !(remain == 0);
}
};
/**
* Main function.
*/
int main() {
// Instantiate the graph.
Graph g(7, std::vector<Edge>{{0, 1}, {1, 2}, {2, 0}, {2, 5}, {3, 5}});
// Check for cycle using BFS method.
std::cout << CycleCheck::isCyclicBFS(g) << '\n';
// Check for cycle using DFS method.
std::cout << CycleCheck::isCyclicDFS(g) << '\n';
return 0; return 0;
} }
int main() {
size_t n, m;
std::cin >> n >> m;
vector<vector<int> > adj(n, vector<int>());
for (size_t i = 0; i < m; i++) {
int x, y;
std::cin >> x >> y;
adj[x - 1].push_back(y - 1);
}
acyclic(adj,n);
}

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@ -1,26 +1,133 @@
/**
*
* \file
* \brief [Depth First Search Algorithm
* (Depth First Search)](https://en.wikipedia.org/wiki/Depth-first_search)
*
* \author [Ayaan Khan](http://github.com/ayaankhan98)
*
* \details
* Depth First Search also quoted as DFS is a Graph Traversal Algorithm.
* Time Complexity O(|V| + |E|) where V is number of vertices and E
* is number of edges in graph.
*
* Application of Depth First Search are
*
* 1. Finding connected components
* 2. Finding 2-(edge or vertex)-connected components.
* 3. Finding 3-(edge or vertex)-connected components.
* 4. Finding the bridges of a graph.
* 5. Generating words in order to plot the limit set of a group.
* 6. Finding strongly connected components.
*
* And there are many more...
*
* <h4>Working</h4>
* 1. Mark all vertices as unvisited first
* 2. start exploring from some starting vertex.
*
* While exploring vertex we mark the vertex as visited
* and start exploring the vertices connected to this
* vertex in recursive way.
*
*/
#include <algorithm>
#include <iostream> #include <iostream>
using namespace std; #include <vector>
int v = 4;
void DFSUtil_(int graph[4][4], bool visited[], int s) { /**
visited[s] = true; *
cout << s << " "; * \namespace graph
for (int i = 0; i < v; i++) { * \brief Graph Algorithms
if (graph[s][i] == 1 && visited[i] == false) { *
DFSUtil_(graph, visited, i); */
namespace graph {
/**
* \brief
* Adds and edge between two vertices of graph say u and v in this
* case.
*
* @param adj Adjacency list representation of graph
* @param u first vertex
* @param v second vertex
*
*/
void addEdge(std::vector<std::vector<size_t>> *adj, size_t u, size_t v) {
/**
*
* Here we are considering undirected graph that's the
* reason we are adding v to the adjacency list representation of u
* and also adding u to the adjacency list representation of v
*
*/
(*adj)[u - 1].push_back(v - 1);
(*adj)[v - 1].push_back(u - 1);
}
/**
*
* \brief
* Explores the given vertex, exploring a vertex means traversing
* over all the vertices which are connected to the vertex that is
* currently being explored.
*
* @param adj garph
* @param v vertex to be explored
* @param visited already visited vertices
*
*/
void explore(const std::vector<std::vector<size_t>> &adj, size_t v,
std::vector<bool> *visited) {
std::cout << v + 1 << " ";
(*visited)[v] = true;
for (auto x : adj[v]) {
if (!(*visited)[x]) {
explore(adj, x, visited);
} }
} }
} }
void DFS_(int graph[4][4], int s) { /**
bool visited[v]; * \brief
memset(visited, 0, sizeof(visited)); * initiates depth first search algorithm.
DFSUtil_(graph, visited, s); *
} * @param adj adjacency list of graph
* @param start vertex from where DFS starts traversing.
*
*/
void depth_first_search(const std::vector<std::vector<size_t>> &adj,
size_t start) {
size_t vertices = adj.size();
std::vector<bool> visited(vertices, false);
explore(adj, start, &visited);
}
} // namespace graph
/** Main function */
int main() { int main() {
int graph[4][4] = {{0, 1, 1, 0}, {0, 0, 1, 0}, {1, 0, 0, 1}, {0, 0, 0, 1}}; size_t vertices, edges;
cout << "DFS: "; std::cout << "Enter the Vertices : ";
DFS_(graph, 2); std::cin >> vertices;
cout << endl; std::cout << "Enter the Edges : ";
std::cin >> edges;
/// creating graph
std::vector<std::vector<size_t>> adj(vertices, std::vector<size_t>());
/// taking input for edges
std::cout << "Enter the vertices which have edges between them : "
<< std::endl;
while (edges--) {
size_t u, v;
std::cin >> u >> v;
graph::addEdge(&adj, u, v);
}
/// running depth first search over graph
graph::depth_first_search(adj, 2);
std::cout << std::endl;
return 0; return 0;
} }

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@ -1,52 +1,180 @@
#include <cstdio> /**
* @file
* @brief [Graph Dijkstras Shortest Path Algorithm
* (Dijkstra's Shortest Path)]
* (https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm)
*
* @author [Ayaan Khan](http://github.com/ayaankhan98)
*
* @details
* Dijkstra's Algorithm is used to find the shortest path from a source
* vertex to all other reachable vertex in the graph.
* The algorithm initially assumes all the nodes are unreachable from the
* given source vertex so we mark the distances of all vertices as INF
* (infinity) from source vertex (INF / infinity denotes unable to reach).
*
* in similar fashion with BFS we assume the distance of source vertex as 0
* and pushes the vertex in a priority queue with it's distance.
* we maintain the priority queue as a min heap so that we can get the
* minimum element at the top of heap
*
* Basically what we do in this algorithm is that we try to minimize the
* distances of all the reachable vertices from the current vertex, look
* at the code below to understand in better way.
*
*/
#include <cassert>
#include <iostream> #include <iostream>
#include <limits>
#include <queue> #include <queue>
#include <utility>
#include <vector> #include <vector>
using namespace std; #include <memory>
#define INF 10000010
vector<pair<int, int>> graph[5 * 100001];
int dis[5 * 100001];
int dij(vector<pair<int, int>> *v, int s, int *dis) {
priority_queue<pair<int, int>, vector<pair<int, int>>,
greater<pair<int, int>>>
pq;
// source distance to zero.
pq.push(make_pair(0, s));
dis[s] = 0;
int u;
while (!pq.empty()) {
u = (pq.top()).second;
pq.pop();
for (vector<pair<int, int>>::iterator it = v[u].begin();
it != v[u].end(); it++) {
if (dis[u] + it->first < dis[it->second]) {
dis[it->second] = dis[u] + it->first;
pq.push(make_pair(dis[it->second], it->second));
}
}
}
}
int main() {
int m, n, l, x, y, s;
// n--> number of nodes , m --> number of edges
cin >> n >> m;
for (int i = 0; i < m; i++) {
// input edges.
scanf("%d%d%d", &x, &y, &l);
graph[x].push_back(make_pair(l, y));
graph[y].push_back(
make_pair(l, x)); // comment this line for directed graph
}
// start node.
scanf("%d", &s);
// intialise all distances to infinity.
for (int i = 1; i <= n; i++) dis[i] = INF;
dij(graph, s, dis);
for (int i = 1; i <= n; i++) constexpr int64_t INF = std::numeric_limits<int64_t>::max();
if (dis[i] == INF)
cout << "-1 "; /**
else * @namespace graph
cout << dis[i] << " "; * @brief Graph Algorithms
*/
namespace graph {
/**
* @brief Function that add edge between two nodes or vertices of graph
*
* @param u any node or vertex of graph
* @param v any node or vertex of graph
*/
void addEdge(std::vector<std::vector<std::pair<int, int>>> *adj, int u, int v,
int w) {
(*adj)[u - 1].push_back(std::make_pair(v - 1, w));
// (*adj)[v - 1].push_back(std::make_pair(u - 1, w));
}
/**
* @brief Function runs the dijkstra algorithm for some source vertex and
* target vertex in the graph and returns the shortest distance of target
* from the source.
*
* @param adj input graph
* @param s source vertex
* @param t target vertex
*
* @return shortest distance if target is reachable from source else -1 in
* case if target is not reachable from source.
*/
int dijkstra(std::vector<std::vector<std::pair<int, int>>> *adj, int s, int t) {
/// n denotes the number of vertices in graph
int n = adj->size();
/// setting all the distances initially to INF
std::vector<int64_t> dist(n, INF);
/// creating a min heap using priority queue
/// first element of pair contains the distance
/// second element of pair contains the vertex
std::priority_queue<std::pair<int, int>, std::vector<std::pair<int, int>>,
std::greater<std::pair<int, int>>>
pq;
/// pushing the source vertex 's' with 0 distance in min heap
pq.push(std::make_pair(0, s));
/// marking the distance of source as 0
dist[s] = 0;
while (!pq.empty()) {
/// second element of pair denotes the node / vertex
int currentNode = pq.top().second;
/// first element of pair denotes the distance
int currentDist = pq.top().first;
pq.pop();
/// for all the reachable vertex from the currently exploring vertex
/// we will try to minimize the distance
for (std::pair<int, int> edge : (*adj)[currentNode]) {
/// minimizing distances
if (currentDist + edge.second < dist[edge.first]) {
dist[edge.first] = currentDist + edge.second;
pq.push(std::make_pair(dist[edge.first], edge.first));
}
}
}
if (dist[t] != INF) {
return dist[t];
}
return -1;
}
} // namespace graph
/** Function to test the Algorithm */
void tests() {
std::cout << "Initiatinig Predefined Tests..." << std::endl;
std::cout << "Initiating Test 1..." << std::endl;
std::vector<std::vector<std::pair<int, int>>> adj1(
4, std::vector<std::pair<int, int>>());
graph::addEdge(&adj1, 1, 2, 1);
graph::addEdge(&adj1, 4, 1, 2);
graph::addEdge(&adj1, 2, 3, 2);
graph::addEdge(&adj1, 1, 3, 5);
int s = 1, t = 3;
assert(graph::dijkstra(&adj1, s - 1, t - 1) == 3);
std::cout << "Test 1 Passed..." << std::endl;
s = 4, t = 3;
std::cout << "Initiating Test 2..." << std::endl;
assert(graph::dijkstra(&adj1, s - 1, t - 1) == 5);
std::cout << "Test 2 Passed..." << std::endl;
std::vector<std::vector<std::pair<int, int>>> adj2(
5, std::vector<std::pair<int, int>>());
graph::addEdge(&adj2, 1, 2, 4);
graph::addEdge(&adj2, 1, 3, 2);
graph::addEdge(&adj2, 2, 3, 2);
graph::addEdge(&adj2, 3, 2, 1);
graph::addEdge(&adj2, 2, 4, 2);
graph::addEdge(&adj2, 3, 5, 4);
graph::addEdge(&adj2, 5, 4, 1);
graph::addEdge(&adj2, 2, 5, 3);
graph::addEdge(&adj2, 3, 4, 4);
s = 1, t = 5;
std::cout << "Initiating Test 3..." << std::endl;
assert(graph::dijkstra(&adj2, s - 1, t - 1) == 6);
std::cout << "Test 3 Passed..." << std::endl;
std::cout << "All Test Passed..." << std::endl << std::endl;
}
/** Main function */
int main() {
// running predefined tests
tests();
int vertices = int(), edges = int();
std::cout << "Enter the number of vertices : ";
std::cin >> vertices;
std::cout << "Enter the number of edges : ";
std::cin >> edges;
std::vector<std::vector<std::pair<int, int>>> adj(
vertices, std::vector<std::pair<int, int>>());
int u = int(), v = int(), w = int();
while (edges--) {
std::cin >> u >> v >> w;
graph::addEdge(&adj, u, v, w);
}
int s = int(), t = int();
std::cin >> s >> t;
int dist = graph::dijkstra(&adj, s - 1, t - 1);
if (dist == -1) {
std::cout << "Target not reachable from source" << std::endl;
} else {
std::cout << "Shortest Path Distance : " << dist << std::endl;
}
return 0; return 0;
} }

View File

@ -4,8 +4,8 @@
#include <iostream> #include <iostream>
#include <vector> #include <vector>
#include <stack>
using namespace std;
/** /**
* Iterative function/method to print graph: * Iterative function/method to print graph:
@ -13,13 +13,13 @@ using namespace std;
* @param V : vertices * @param V : vertices
* @return void * @return void
**/ **/
void print(vector<int> a[], int V) { void print(std::vector<int> a[], int V) {
for (int i = 0; i < V; i++) { for (int i = 0; i < V; i++) {
if (!a[i].empty()) if (!a[i].empty())
cout << "i=" << i << "-->"; std::cout << "i=" << i << "-->";
for (int j = 0; j < a[i].size(); j++) cout << a[i][j] << " "; for (int j = 0; j < a[i].size(); j++) std::cout << a[i][j] << " ";
if (!a[i].empty()) if (!a[i].empty())
cout << endl; std::cout << std::endl;
} }
} }
@ -31,7 +31,7 @@ void print(vector<int> a[], int V) {
* @param adj[] : array of vectors to represent graph * @param adj[] : array of vectors to represent graph
* @return void * @return void
**/ **/
void push_vertex(int v, stack<int> &st, bool vis[], vector<int> adj[]) { void push_vertex(int v, std::stack<int> &st, bool vis[], std::vector<int> adj[]) {
vis[v] = true; vis[v] = true;
for (auto i = adj[v].begin(); i != adj[v].end(); i++) { for (auto i = adj[v].begin(); i != adj[v].end(); i++) {
if (vis[*i] == false) if (vis[*i] == false)
@ -47,7 +47,7 @@ void push_vertex(int v, stack<int> &st, bool vis[], vector<int> adj[]) {
* @param grev[] : graph with reversed edges * @param grev[] : graph with reversed edges
* @return void * @return void
**/ **/
void dfs(int v, bool vis[], vector<int> grev[]) { void dfs(int v, bool vis[], std::vector<int> grev[]) {
vis[v] = true; vis[v] = true;
// cout<<v<<" "; // cout<<v<<" ";
for (auto i = grev[v].begin(); i != grev[v].end(); i++) { for (auto i = grev[v].begin(); i != grev[v].end(); i++) {
@ -66,15 +66,15 @@ no SCCs i.e. none(0) or there will be x no. of SCCs (x>0)) i.e. it returns the
count of (number of) strongly connected components (SCCs) in the graph. count of (number of) strongly connected components (SCCs) in the graph.
(variable 'count_scc' within function) (variable 'count_scc' within function)
**/ **/
int kosaraju(int V, vector<int> adj[]) { int kosaraju(int V, std::vector<int> adj[]) {
bool vis[V] = {}; bool vis[V] = {};
stack<int> st; std::stack<int> st;
for (int v = 0; v < V; v++) { for (int v = 0; v < V; v++) {
if (vis[v] == false) if (vis[v] == false)
push_vertex(v, st, vis, adj); push_vertex(v, st, vis, adj);
} }
// making new graph (grev) with reverse edges as in adj[]: // making new graph (grev) with reverse edges as in adj[]:
vector<int> grev[V]; std::vector<int> grev[V];
for (int i = 0; i < V + 1; i++) { for (int i = 0; i < V + 1; i++) {
for (auto j = adj[i].begin(); j != adj[i].end(); j++) { for (auto j = adj[i].begin(); j != adj[i].end(); j++) {
grev[*j].push_back(i); grev[*j].push_back(i);
@ -102,20 +102,20 @@ int kosaraju(int V, vector<int> adj[]) {
// Input your required values: (not hardcoded) // Input your required values: (not hardcoded)
int main() { int main() {
int t; int t;
cin >> t; std::cin >> t;
while (t--) { while (t--) {
int a, b; // a->number of nodes, b->directed edges. int a, b; // a->number of nodes, b->directed edges.
cin >> a >> b; std::cin >> a >> b;
int m, n; int m, n;
vector<int> adj[a + 1]; std::vector<int> adj[a + 1];
for (int i = 0; i < b; i++) // take total b inputs of 2 vertices each for (int i = 0; i < b; i++) // take total b inputs of 2 vertices each
// required to form an edge. // required to form an edge.
{ {
cin >> m >> n; // take input m,n denoting edge from m->n. std::cin >> m >> n; // take input m,n denoting edge from m->n.
adj[m].push_back(n); adj[m].push_back(n);
} }
// pass number of nodes and adjacency array as parameters to function: // pass number of nodes and adjacency array as parameters to function:
cout << kosaraju(a, adj) << endl; std::cout << kosaraju(a, adj) << std::endl;
} }
return 0; return 0;
} }

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@ -1,4 +1,6 @@
#include <iostream> #include <iostream>
#include <vector>
#include <algorithm>
//#include <boost/multiprecision/cpp_int.hpp> //#include <boost/multiprecision/cpp_int.hpp>
// using namespace boost::multiprecision; // using namespace boost::multiprecision;
const int mx = 1e6 + 5; const int mx = 1e6 + 5;

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@ -1,7 +1,9 @@
//#include<bits/stdc++.h> //#include<bits/stdc++.h>
#include <iostream> #include <iostream>
#include <vector>
using namespace std; #include <cmath>
#include <cassert>
#include <cstring>
// Find the lowest common ancestor using binary lifting in O(nlogn) // Find the lowest common ancestor using binary lifting in O(nlogn)
// Zero based indexing // Zero based indexing
// Resource : https://cp-algorithms.com/graph/lca_binary_lifting.html // Resource : https://cp-algorithms.com/graph/lca_binary_lifting.html
@ -9,7 +11,7 @@ const int N = 1005;
const int LG = log2(N) + 1; const int LG = log2(N) + 1;
struct lca { struct lca {
int n; int n;
vector<int> adj[N]; // Graph std::vector<int> adj[N]; // Graph
int up[LG][N]; // build this table int up[LG][N]; // build this table
int level[N]; // get the levels of all of them int level[N]; // get the levels of all of them
@ -18,7 +20,7 @@ struct lca {
memset(level, 0, sizeof(level)); memset(level, 0, sizeof(level));
for (int i = 0; i < n - 1; ++i) { for (int i = 0; i < n - 1; ++i) {
int a, b; int a, b;
cin >> a >> b; std::cin >> a >> b;
a--; a--;
b--; b--;
adj[a].push_back(b); adj[a].push_back(b);
@ -30,15 +32,15 @@ struct lca {
} }
void verify() { void verify() {
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {
cout << i << " : level: " << level[i] << endl; std::cout << i << " : level: " << level[i] << std::endl;
} }
cout << endl; std::cout << std::endl;
for (int i = 0; i < LG; ++i) { for (int i = 0; i < LG; ++i) {
cout << "Power:" << i << ": "; std::cout << "Power:" << i << ": ";
for (int j = 0; j < n; ++j) { for (int j = 0; j < n; ++j) {
cout << up[i][j] << " "; std::cout << up[i][j] << " ";
} }
cout << endl; std::cout << std::endl;
} }
} }
@ -65,7 +67,7 @@ struct lca {
u--; u--;
v--; v--;
if (level[v] > level[u]) { if (level[v] > level[u]) {
swap(u, v); std::swap(u, v);
} }
// u is at the bottom. // u is at the bottom.
int dist = level[u] - level[v]; int dist = level[u] - level[v];

View File

@ -1,12 +1,11 @@
#include <algorithm> #include <algorithm>
#include <iostream> #include <iostream>
#include <vector> #include <vector>
using namespace std;
int n, m; // For number of Vertices (V) and number of edges (E) int n, m; // For number of Vertices (V) and number of edges (E)
vector<vector<int>> G; std::vector<std::vector<int>> G;
vector<bool> visited; std::vector<bool> visited;
vector<int> ans; std::vector<int> ans;
void dfs(int v) { void dfs(int v) {
visited[v] = true; visited[v] = true;
@ -27,21 +26,21 @@ void topological_sort() {
reverse(ans.begin(), ans.end()); reverse(ans.begin(), ans.end());
} }
int main() { int main() {
cout << "Enter the number of vertices and the number of directed edges\n"; std::cout << "Enter the number of vertices and the number of directed edges\n";
cin >> n >> m; std::cin >> n >> m;
int x, y; int x, y;
G.resize(n, vector<int>()); G.resize(n, std::vector<int>());
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {
cin >> x >> y; std::cin >> x >> y;
x--, y--; // to convert 1-indexed to 0-indexed x--, y--; // to convert 1-indexed to 0-indexed
G[x].push_back(y); G[x].push_back(y);
} }
topological_sort(); topological_sort();
cout << "Topological Order : \n"; std::cout << "Topological Order : \n";
for (int v : ans) { for (int v : ans) {
cout << v + 1 std::cout << v + 1
<< ' '; // converting zero based indexing back to one based. << ' '; // converting zero based indexing back to one based.
} }
cout << '\n'; std::cout << '\n';
return 0; return 0;
} }