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  • Graph Isomorphism > What kind of Graph is this?

    - by oodavid
    Essentially, this is a variation of Comparing Two Tree Structures, however I do not have "trees", but rather another type of graph. I need to know what kind of Graph I have in order to figure out if there's a Graph Isomorphism Special Case... As you can see, they are: Not Directed Not A Tree Cyclic Max 4 connections But I still don't know the correct terminology, nor the which Isomorphism algorithm to pursue, guidance appreciated.

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  • Finding most Important Node(s) in a Directed Graph

    - by Srikar Appal
    I have a large (˜ 20 million nodes) directed Graph with in-edges & out-edges. I want to figure out which parts of of the graph deserve the most attention. Often most of the graph is boring, or at least it is already well understood. The way I am defining "attention" is by the concept of "connectedness" i.e. How can i find the most connected node(s) in the graph? In what follows, One can assume that nodes by themselves have no score, the edges have no weight & they are either connected or not. This website suggest some pretty complicated procedures like n-dimensional space, Eigen Vectors, graph centrality concepts, pageRank etc. Is this problem that complex? Can I not do a simple Breadth-First Traversal of the entire graph where at each node I figure out a way to find the number of in-edges. The node with most in-edges is the most important node in the graph. Am I missing something here?

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  • Hurricanes Since 1851 [Visualization]

    - by Jason Fitzpatrick
    Much like you can map out volcanic eruptions to create a neat pattern around the Pacific Ring of Fire, you can also map out hurricanes and tropical storms. Check out this high-resolution visualization to see the pattern formed by a century and a half of storms. Courtesy of UXBlog and data from the National Oceanic and Atmospheric Administration, the above projection shows the path of tropical storms around the equator (the perspective, if the map looks unfamiliar to you, is bottom up with Antarctica and the lower portion of South America in the center). For a full resolution copy of the image and more information about how it was rendered, hit up the link below. Hurricanes Since 1851 [via Cool Infographics] How To Get a Better Wireless Signal and Reduce Wireless Network Interference How To Troubleshoot Internet Connection Problems 7 Ways To Free Up Hard Disk Space On Windows

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  • Class instance clustering in object reference graph for multi-entries serialization

    - by Juh_
    My question is on the best way to cluster a graph of class instances (i.e. objects, the graph nodes) linked by object references (the -directed- edges of the graph) around specifically marked objects. To explain better my question, let me explain my motivation: I currently use a moderately complex system to serialize the data used in my projects: "marked" objects have a specific attributes which stores a "saving entry": the path to an associated file on disc (but it could be done for any storage type providing the suitable interface) Those object can then be serialized automatically (eg: obj.save()) The serialization of a marked object 'a' contains implicitly all objects 'b' for which 'a' has a reference to, directly s.t: a.b = b, or indirectly s.t.: a.c.b = b for some object 'c' This is very simple and basically define specific storage entries to specific objects. I have then "container" type objects that: can be serialized similarly (in fact their are or can-be "marked") they don't serialize in their storage entries the "marked" objects (with direct reference): if a and a.b are both marked, a.save() calls b.save() and stores a.b = storage_entry(b) So, if I serialize 'a', it will serialize automatically all objects that can be reached from 'a' through the object reference graph, possibly in multiples entries. That is what I want, and is usually provides the functionalities I need. However, it is very ad-hoc and there are some structural limitations to this approach: the multi-entry saving can only works through direct connections in "container" objects, and there are situations with undefined behavior such as if two "marked" objects 'a'and 'b' both have a reference to an unmarked object 'c'. In this case my system will stores 'c' in both 'a' and 'b' making an implicit copy which not only double the storage size, but also change the object reference graph after re-loading. I am thinking of generalizing the process. Apart for the practical questions on implementation (I am coding in python, and use Pickle to serialize my objects), there is a general question on the way to attach (cluster) unmarked objects to marked ones. So, my questions are: What are the important issues that should be considered? Basically why not just use any graph parsing algorithm with the "attach to last marked node" behavior. Is there any work done on this problem, practical or theoretical, that I should be aware of? Note: I added the tag graph-database because I think the answer might come from that fields, even if the question is not.

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  • Where Are You on the Visualization Maturity Curve?

    - by Celine Beck
    The old phrase “A picture is worth a thousand words” is as true now as ever. Providing the right users with access to the right product data, at the right time, can provide significant benefits to a business. This is especially evident with increasing technical and product complexities, elongated supply chains, and growing pressure to bring innovative products to market faster. With this in mind, it is easy to understand why visualization is an integral part of any successful product lifecycle management (PLM) strategy. At a bare minimum, knowledge workers use multiple individual documents of different formats and structure, and leverage visualization solutions to access information; but the real value of visualization can be fully reaped when it is connected to enterprise applications like PLM and tied to the appropriate business context. The picture below illustrates this visualization maturity curve, as we presented during the last Oracle Open World and the transformational effect that visualization can have on PLM processes and performance (check out the post about AutoVue Key Highlights from Oracle Open World 2012 for more information). Organizations are likely to see greater positive impact on business performance when visualization is connected to enterprise systems, allowing access to information coming from multiple sources, such as PLM, supply chain management (SCM) and enterprise resource planning (ERP). This allows organizations to reach higher levels of collaboration and optimize decision-making capacity as users can benefit from in-context access to visual information. For instance, within a PLM system, a design engineer can access a product assembly and review digital annotations added by other users specific to the engineering change request he is reviewing rather than all historical annotations. The last stage on the curve is what we call augmented business visualization (ABV).  ABV is an innovative framework which lets structured data (from Oracle’s Agile PLM for instance) interact with unstructured data (documents, design, 3D models, etc). With this new level of integration, information coming from multiple sources can be presented in a highly visual fashion; color displays can be used in order to identify parts with specific characteristics (for example pending quality issues) and you can take actions directly from within the context of documents and designs, maximizing user productivity. Those who had the chance to attend our PLM session during Oracle Open World already got a sneak peek of our latest augmented business visualization for Oracle’s Agile PLM. The solution generated a lot of wows. Stephen Porter, CEO at Zero Wait State, indicated in a post entitled “The PLM State: the Manhattan Project-Oracle’s Next Big Secret Weapon” that “this kind of synergy between visualization and PLM could qualify as a powerful weapon differentiating Agile PLM from other solutions.” If you are interested in learning more about ABV for Oracle’s Agile PLM and hear about real examples of usage of visualization at all stages of the visualization maturity curve, don’t miss our Visual Decision Making to Optimize New Product Development and Introduction session during the Oracle Value Chain Summit (Feb. 4-6, 2013, San Francisco). We look forward to seeing you there!

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  • Cutting Paper through Visualization and Collaboration

    - by [email protected]
    It's hard not to hear about "Going Green" these days. Many are working to be more environmentally conscious in their personal lives, and this has extended to the corporate world as well. I know I'm always looking for new ways. Environmental responsibility is important at Oracle too, and we have an entire section of our website dedicated to our solutions around the Eco-Enterprise. You can check it out here: http://www.oracle.com/green/index.html Perhaps the biggest and most obvious challenge in the world of business is the fact that we use so much paper. There are many good reasons why we print today too. For example: Printing off a document, spreadsheet, or CAD design that will be reviewed and marked up while on a plane Having a printout of a facility when a field engineer performs on-site maintenance During a multi-party design review where a number of people will review a drawing in a meeting room, scribbling onto a large scale drawing print to provide their collaborative comments These are just a few potential use cases, and they're valid ones. However, there's a way in which you can turn these paper processes into digital ones. AutoVue allows you to view, mark-up, and collaborate on all the data you would print. Indeed, this is the core of what AutoVue does. So if we take the examples above, we could address each as follows: Allow you to view the document, spreadsheet, or CAD drawing in AutoVue on your laptop. Even if you originally had this data vaulted in some time of system of record (like an ECM solution) and view your data from there, AutoVue allows you to "Work Offline" and take the documents you need to review on your laptop. From there, the many annotation tools in AutoVue will give you what you need to comment upon the documents that you are reviewing. The challenge with the mobile workforce is always access to information. People who perform maintenance and repair operations often are in locations with little to no Internet connectivity. However, technology is coming to these people in the form of laptops, tablet PCs, and other portable devices too. AutoVue can address situations with limited bandwidth through our streaming technology for viewing, meaning that the most up to date information can be pulled up from the central server - without the need for large data transfer. When there is no connectivity at all, the "Work Offline" option will handle this. For a design review session, the Real-Time Collaboration capabilities of AutoVue will let all the participants view the same document in a synchronized view, allowing each person to be able to mark-up the document at the same time. Since this is done in a web-based manner, not only is it not necessary to print the document, but you benefit by reducing the travel needed for these sessions. Not only are trees spared, but jet fuel as well. There are many steps involved with "Going Green", but each step is a necessary one. What we do today will directly influence our future generations, and we're looking to help.

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  • Is finding graph minors without single node pinch points possible?

    - by Alturis
    Is it possible to robustly find all the graph minors within an arbitrary node graph where the pinch points are generally not single nodes? I have read some other posts on here about how to break up your graph into a Hamiltonian cycle and then from that find the graph minors but it seems to be such an algorithm would require that each "room" had "doorways" consisting of single nodes. To explain a bit more a visual aid is necessary. Lets say the nodes below are an example of the typical node graph. What I am looking for is a way to automatically find the different colored regions of the graph (or graph minors)

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  • Best Planar graph program

    - by brian
    In graph theory, a planar graph is a graph that can be embedded in the plane, i.e., it can be drawn on the plane in such a way that its edges intersect only at their endpoints. What is the best open source program for drawing the planar graph with support of input nodes size and fixed drawing boundary region

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  • Visualization tools for physical simulations

    - by Nick
    I'm interested in starting some physics simulations and I'm getting hung up on the visualization side of things. I have lots of resources for reading how to implement the simulation itself but I'd rather not learn two things at once - the simulation part and a new complex visualization API. Are there any high-level visualization tools that are language independent? I understand that I'll have to learn some new code for visualization but I'd like to start at a high level, OpenGL is my long-term goal and not my prototype goal.

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  • evaluating a code of a graph [migrated]

    - by mazen.r.f
    This is relatively a long code,if you have the tolerance and the will to find out how to make this code work then take a look please, i will appreciate your feed back. i have spent two days trying to come up with a code to represent a graph , then calculate the shortest path using dijkastra algorithm , but i am not able to get the right result , even the code runs without errors , but the result is not correct , always i am getting 0. briefly,i have three classes , Vertex, Edge, Graph , the Vertex class represents the nodes in the graph and it has id and carried ( which carry the weight of the links connected to it while using dijkastra algorithm ) and a vector of the ids belong to other nodes the path will go through before arriving to the node itself , this vector is named previous_nodes. the Edge class represents the edges in the graph it has two vertices ( one in each side ) and a wight ( the distance between the two vertices ). the Graph class represents the graph , it has two vectors one is the vertices included in this graph , and the other is the edges included in the graph. inside the class Graph there is a method its name shortest takes the sources node id and the destination and calculates the shortest path using dijkastra algorithm, and i think that it is the most important part of the code. my theory about the code is that i will create two vectors one for the vertices in the graph i will name it vertices and another vector its name is ver_out it will include the vertices out of calculation in the graph, also i will have two vectors of type Edge , one its name edges for all the edges in the graph and the other its name is track to contain temporarily the edges linked to the temporarily source node in every round , after the calculation of every round the vector track will be cleared. in main() i created five vertices and 10 edges to simulate a graph , the result of the shortest path supposedly to be 4 , but i am always getting 0 , that means i am having something wrong in my code , so if you are interesting in helping me find my mistake and how to make the code work , please take a look. the way shortest work is as follow at the beginning all the edges will be included in the vector edges , we select the edges related to the source and put them in the vector track , then we iterate through track and add the wight of every edge to the vertex (node ) related to it ( not the source vertex ) , then after we clear track and remove the source vertex from the vector vertices and select a new source , and start over again select the edges related to the new source , put them in track , iterate over edges in tack , adding the weights to the corresponding vertices then remove this vertex from the vector vertices, and clear track , and select a new source , and so on . here is the code. #include<iostream> #include<vector> #include <stdlib.h> // for rand() using namespace std; class Vertex { private: unsigned int id; // the name of the vertex unsigned int carried; // the weight a vertex may carry when calculating shortest path vector<unsigned int> previous_nodes; public: unsigned int get_id(){return id;}; unsigned int get_carried(){return carried;}; void set_id(unsigned int value) {id = value;}; void set_carried(unsigned int value) {carried = value;}; void previous_nodes_update(unsigned int val){previous_nodes.push_back(val);}; void previous_nodes_erase(unsigned int val){previous_nodes.erase(previous_nodes.begin() + val);}; Vertex(unsigned int init_val = 0, unsigned int init_carried = 0) :id (init_val), carried(init_carried) // constructor { } ~Vertex() {}; // destructor }; class Edge { private: Vertex first_vertex; // a vertex on one side of the edge Vertex second_vertex; // a vertex on the other side of the edge unsigned int weight; // the value of the edge ( or its weight ) public: unsigned int get_weight() {return weight;}; void set_weight(unsigned int value) {weight = value;}; Vertex get_ver_1(){return first_vertex;}; Vertex get_ver_2(){return second_vertex;}; void set_first_vertex(Vertex v1) {first_vertex = v1;}; void set_second_vertex(Vertex v2) {second_vertex = v2;}; Edge(const Vertex& vertex_1 = 0, const Vertex& vertex_2 = 0, unsigned int init_weight = 0) : first_vertex(vertex_1), second_vertex(vertex_2), weight(init_weight) { } ~Edge() {} ; // destructor }; class Graph { private: std::vector<Vertex> vertices; std::vector<Edge> edges; public: Graph(vector<Vertex> ver_vector, vector<Edge> edg_vector) : vertices(ver_vector), edges(edg_vector) { } ~Graph() {}; vector<Vertex> get_vertices(){return vertices;}; vector<Edge> get_edges(){return edges;}; void set_vertices(vector<Vertex> vector_value) {vertices = vector_value;}; void set_edges(vector<Edge> vector_ed_value) {edges = vector_ed_value;}; unsigned int shortest(unsigned int src, unsigned int dis) { vector<Vertex> ver_out; vector<Edge> track; for(unsigned int i = 0; i < edges.size(); ++i) { if((edges[i].get_ver_1().get_id() == vertices[src].get_id()) || (edges[i].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[i]); edges.erase(edges.begin()+i); } }; for(unsigned int i = 0; i < track.size(); ++i) { if(track[i].get_ver_1().get_id() != vertices[src].get_id()) { track[i].get_ver_1().set_carried((track[i].get_weight()) + track[i].get_ver_2().get_carried()); track[i].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else { track[i].get_ver_2().set_carried((track[i].get_weight()) + track[i].get_ver_1().get_carried()); track[i].get_ver_2().previous_nodes_update(vertices[src].get_id()); } } for(unsigned int i = 0; i < vertices.size(); ++i) if(vertices[i].get_id() == src) vertices.erase(vertices.begin() + i); // removing the sources vertex from the vertices vector ver_out.push_back (vertices[src]); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int i = 0; i < vertices.size(); ++i) if((vertices[i].get_carried() < vertices[src].get_carried()) && (vertices[i].get_id() != dis)) src = vertices[i].get_id(); //while(!edges.empty()) for(unsigned int round = 0; round < vertices.size(); ++round) { for(unsigned int k = 0; k < edges.size(); ++k) { if((edges[k].get_ver_1().get_id() == vertices[src].get_id()) || (edges[k].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[k]); edges.erase(edges.begin()+k); } }; for(unsigned int n = 0; n < track.size(); ++n) if((track[n].get_ver_1().get_id() != vertices[src].get_id()) && (track[n].get_ver_1().get_carried() > (track[n].get_ver_2().get_carried() + track[n].get_weight()))) { track[n].get_ver_1().set_carried((track[n].get_weight()) + track[n].get_ver_2().get_carried()); track[n].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else if(track[n].get_ver_2().get_carried() > (track[n].get_ver_1().get_carried() + track[n].get_weight())) { track[n].get_ver_2().set_carried((track[n].get_weight()) + track[n].get_ver_1().get_carried()); track[n].get_ver_2().previous_nodes_update(vertices[src].get_id()); } for(unsigned int t = 0; t < vertices.size(); ++t) if(vertices[t].get_id() == src) vertices.erase(vertices.begin() + t); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int tt = 0; tt < edges.size(); ++tt) { if(vertices[tt].get_carried() < vertices[src].get_carried()) { src = vertices[tt].get_id(); } } } return vertices[dis].get_carried(); } }; int main() { cout<< "Hello, This is a graph"<< endl; vector<Vertex> vers(5); vers[0].set_id(0); vers[1].set_id(1); vers[2].set_id(2); vers[3].set_id(3); vers[4].set_id(4); vector<Edge> eds(10); eds[0].set_first_vertex(vers[0]); eds[0].set_second_vertex(vers[1]); eds[0].set_weight(5); eds[1].set_first_vertex(vers[0]); eds[1].set_second_vertex(vers[2]); eds[1].set_weight(9); eds[2].set_first_vertex(vers[0]); eds[2].set_second_vertex(vers[3]); eds[2].set_weight(4); eds[3].set_first_vertex(vers[0]); eds[3].set_second_vertex(vers[4]); eds[3].set_weight(6); eds[4].set_first_vertex(vers[1]); eds[4].set_second_vertex(vers[2]); eds[4].set_weight(2); eds[5].set_first_vertex(vers[1]); eds[5].set_second_vertex(vers[3]); eds[5].set_weight(5); eds[6].set_first_vertex(vers[1]); eds[6].set_second_vertex(vers[4]); eds[6].set_weight(7); eds[7].set_first_vertex(vers[2]); eds[7].set_second_vertex(vers[3]); eds[7].set_weight(1); eds[8].set_first_vertex(vers[2]); eds[8].set_second_vertex(vers[4]); eds[8].set_weight(8); eds[9].set_first_vertex(vers[3]); eds[9].set_second_vertex(vers[4]); eds[9].set_weight(3); unsigned int path; Graph graf(vers, eds); path = graf.shortest(2, 4); cout<< path << endl; return 0; }

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  • Evaluating code for a graph [migrated]

    - by mazen.r.f
    This is relatively long code. Please take a look at this code if you are still willing to do so. I will appreciate your feedback. I have spent two days trying to come up with code to represent a graph, calculating the shortest path using Dijkstra's algorithm. But I am not able to get the right result, even though the code runs without errors. The result is not correct and I am always getting 0. I have three classes: Vertex, Edge, and Graph. The Vertex class represents the nodes in the graph and it has id and carried (which carry the weight of the links connected to it while using Dijkstra's algorithm) and a vector of the ids belong to other nodes the path will go through before arriving to the node itself. This vector is named previous_nodes. The Edge class represents the edges in the graph and has two vertices (one in each side) and a width (the distance between the two vertices). The Graph class represents the graph. It has two vectors, where one is the vertices included in this graph, and the other is the edges included in the graph. Inside the class Graph, there is a method named shortest() that takes the sources node id and the destination and calculates the shortest path using Dijkstra's algorithm. I think that it is the most important part of the code. My theory about the code is that I will create two vectors, one for the vertices in the graph named vertices, and another vector named ver_out (it will include the vertices out of calculation in the graph). I will also have two vectors of type Edge, where one is named edges (for all the edges in the graph), and the other is named track (to temporarily contain the edges linked to the temporary source node in every round). After the calculation of every round, the vector track will be cleared. In main(), I've created five vertices and 10 edges to simulate a graph. The result of the shortest path supposedly is 4, but I am always getting 0. That means I have something wrong in my code. If you are interesting in helping me find my mistake and making the code work, please take a look. The way shortest work is as follow: at the beginning, all the edges will be included in the vector edges. We select the edges related to the source and put them in the vector track, then we iterate through track and add the width of every edge to the vertex (node) related to it (not the source vertex). After that, we clear track and remove the source vertex from the vector vertices and select a new source. Then we start over again and select the edges related to the new source, put them in track, iterate over edges in track, adding the weights to the corresponding vertices, then remove this vertex from the vector vertices. Then clear track, and select a new source, and so on. #include<iostream> #include<vector> #include <stdlib.h> // for rand() using namespace std; class Vertex { private: unsigned int id; // the name of the vertex unsigned int carried; // the weight a vertex may carry when calculating shortest path vector<unsigned int> previous_nodes; public: unsigned int get_id(){return id;}; unsigned int get_carried(){return carried;}; void set_id(unsigned int value) {id = value;}; void set_carried(unsigned int value) {carried = value;}; void previous_nodes_update(unsigned int val){previous_nodes.push_back(val);}; void previous_nodes_erase(unsigned int val){previous_nodes.erase(previous_nodes.begin() + val);}; Vertex(unsigned int init_val = 0, unsigned int init_carried = 0) :id (init_val), carried(init_carried) // constructor { } ~Vertex() {}; // destructor }; class Edge { private: Vertex first_vertex; // a vertex on one side of the edge Vertex second_vertex; // a vertex on the other side of the edge unsigned int weight; // the value of the edge ( or its weight ) public: unsigned int get_weight() {return weight;}; void set_weight(unsigned int value) {weight = value;}; Vertex get_ver_1(){return first_vertex;}; Vertex get_ver_2(){return second_vertex;}; void set_first_vertex(Vertex v1) {first_vertex = v1;}; void set_second_vertex(Vertex v2) {second_vertex = v2;}; Edge(const Vertex& vertex_1 = 0, const Vertex& vertex_2 = 0, unsigned int init_weight = 0) : first_vertex(vertex_1), second_vertex(vertex_2), weight(init_weight) { } ~Edge() {} ; // destructor }; class Graph { private: std::vector<Vertex> vertices; std::vector<Edge> edges; public: Graph(vector<Vertex> ver_vector, vector<Edge> edg_vector) : vertices(ver_vector), edges(edg_vector) { } ~Graph() {}; vector<Vertex> get_vertices(){return vertices;}; vector<Edge> get_edges(){return edges;}; void set_vertices(vector<Vertex> vector_value) {vertices = vector_value;}; void set_edges(vector<Edge> vector_ed_value) {edges = vector_ed_value;}; unsigned int shortest(unsigned int src, unsigned int dis) { vector<Vertex> ver_out; vector<Edge> track; for(unsigned int i = 0; i < edges.size(); ++i) { if((edges[i].get_ver_1().get_id() == vertices[src].get_id()) || (edges[i].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[i]); edges.erase(edges.begin()+i); } }; for(unsigned int i = 0; i < track.size(); ++i) { if(track[i].get_ver_1().get_id() != vertices[src].get_id()) { track[i].get_ver_1().set_carried((track[i].get_weight()) + track[i].get_ver_2().get_carried()); track[i].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else { track[i].get_ver_2().set_carried((track[i].get_weight()) + track[i].get_ver_1().get_carried()); track[i].get_ver_2().previous_nodes_update(vertices[src].get_id()); } } for(unsigned int i = 0; i < vertices.size(); ++i) if(vertices[i].get_id() == src) vertices.erase(vertices.begin() + i); // removing the sources vertex from the vertices vector ver_out.push_back (vertices[src]); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int i = 0; i < vertices.size(); ++i) if((vertices[i].get_carried() < vertices[src].get_carried()) && (vertices[i].get_id() != dis)) src = vertices[i].get_id(); //while(!edges.empty()) for(unsigned int round = 0; round < vertices.size(); ++round) { for(unsigned int k = 0; k < edges.size(); ++k) { if((edges[k].get_ver_1().get_id() == vertices[src].get_id()) || (edges[k].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[k]); edges.erase(edges.begin()+k); } }; for(unsigned int n = 0; n < track.size(); ++n) if((track[n].get_ver_1().get_id() != vertices[src].get_id()) && (track[n].get_ver_1().get_carried() > (track[n].get_ver_2().get_carried() + track[n].get_weight()))) { track[n].get_ver_1().set_carried((track[n].get_weight()) + track[n].get_ver_2().get_carried()); track[n].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else if(track[n].get_ver_2().get_carried() > (track[n].get_ver_1().get_carried() + track[n].get_weight())) { track[n].get_ver_2().set_carried((track[n].get_weight()) + track[n].get_ver_1().get_carried()); track[n].get_ver_2().previous_nodes_update(vertices[src].get_id()); } for(unsigned int t = 0; t < vertices.size(); ++t) if(vertices[t].get_id() == src) vertices.erase(vertices.begin() + t); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int tt = 0; tt < edges.size(); ++tt) { if(vertices[tt].get_carried() < vertices[src].get_carried()) { src = vertices[tt].get_id(); } } } return vertices[dis].get_carried(); } }; int main() { cout<< "Hello, This is a graph"<< endl; vector<Vertex> vers(5); vers[0].set_id(0); vers[1].set_id(1); vers[2].set_id(2); vers[3].set_id(3); vers[4].set_id(4); vector<Edge> eds(10); eds[0].set_first_vertex(vers[0]); eds[0].set_second_vertex(vers[1]); eds[0].set_weight(5); eds[1].set_first_vertex(vers[0]); eds[1].set_second_vertex(vers[2]); eds[1].set_weight(9); eds[2].set_first_vertex(vers[0]); eds[2].set_second_vertex(vers[3]); eds[2].set_weight(4); eds[3].set_first_vertex(vers[0]); eds[3].set_second_vertex(vers[4]); eds[3].set_weight(6); eds[4].set_first_vertex(vers[1]); eds[4].set_second_vertex(vers[2]); eds[4].set_weight(2); eds[5].set_first_vertex(vers[1]); eds[5].set_second_vertex(vers[3]); eds[5].set_weight(5); eds[6].set_first_vertex(vers[1]); eds[6].set_second_vertex(vers[4]); eds[6].set_weight(7); eds[7].set_first_vertex(vers[2]); eds[7].set_second_vertex(vers[3]); eds[7].set_weight(1); eds[8].set_first_vertex(vers[2]); eds[8].set_second_vertex(vers[4]); eds[8].set_weight(8); eds[9].set_first_vertex(vers[3]); eds[9].set_second_vertex(vers[4]); eds[9].set_weight(3); unsigned int path; Graph graf(vers, eds); path = graf.shortest(2, 4); cout<< path << endl; return 0; }

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  • C++: Error in Xcode; "Graph::Coordinate::Coordinate()", referenced from: ...

    - by Alexandstein
    In a program I am writing, I wrote for two classes (Coordinate, and Graph), with one of them taking the other as constructor arguments. When I try to compile it I get the following error for Graph.cpp: Undefined symbols: "Graph::Coordinate::Coordinate(double)", referenced from: Graph::Graph() in Graph.o Graph::Graph() in Graph.o "Graph::Coordinate::Coordinate()", referenced from: Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate, Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph(Graph::Coordinate)in Graph.o Graph::Graph() in Graph.o Graph::Graph() in Graph.o Graph::Graph() in Graph.o Graph::Graph() in Graph.o Graph::Graph() in Graph.o Graph::Graph() in Graph.o ld: symbol(s) not found collect2: ld returned 1 exit status I checked the code and couldn't find anything out of the ordinary. Here are the four class files: (Sorry if it's a lot of code to sift through.) Coordinate.h class Graph{ #include "Coordinate.h" public: Graph(); Graph(Coordinate); Graph(Coordinate, Coordinate); Graph(Coordinate, Coordinate, Coordinate); void setXSize(int); void setYSize(int); void setX(int); //int corresponds to coordinates 1, 2, or 3 void setY(int); void setZ(int); int getXSize(); int getYSize(); double getX(int); //int corresponds to coordinates 1, 2, or 3 double getY(int); double getZ(int); void outputGraph(); void animateGraph(); private: int xSize; int ySize; Coordinate coord1; Coordinate coord2; Coordinate coord3; }; Coordinate.cpp #include <iostream> #include "Coordinate.h" Coordinate::Coordinate() { xCoord = 1; yCoord = 1; zCoord = 1; xVel = 1; yVel = 1; zVel = 1; } Coordinate::Coordinate(double xCoo) { xCoord = xCoo; yCoord = 1; zCoord = 1; xVel = 1; yVel = 1; zVel = 1; } Coordinate::Coordinate(double xCoo,double yCoo) { xCoord = xCoo; yCoord = yCoo; zCoord = 1; xVel = 1; yVel = 1; zVel = 1; } Coordinate::Coordinate(double xCoo,double yCoo,double zCoo) { xCoord = xCoo; yCoord = yCoo; zCoord = zCoo; xVel = 1; yVel = 1; zVel = 1; } void Coordinate::setXCoord(double xCoo) { xCoord = xCoo; } void Coordinate::setYCoord(double yCoo) { yCoord = yCoo; } void Coordinate::setZCoord(double zCoo) { zCoord = zCoo; } void Coordinate::setXVel(double xVelo) { xVel = xVelo; } void Coordinate::setYVel(double yVelo) { yVel = yVelo; } void Coordinate::setZVel(double zVelo) { zVel = zVelo; } double Coordinate::getXCoord() { return xCoord; } double Coordinate::getYCoord() { return yCoord; } double Coordinate::getZCoord() { return zCoord; } double Coordinate::getXVel() { return xVel; } double Coordinate::GetYVel() { return yVel; } double Coordinate::GetZVel() { return zVel; } Graph.h class Graph{ #include "Coordinate.h" public: Graph(); Graph(Coordinate); Graph(Coordinate, Coordinate); Graph(Coordinate, Coordinate, Coordinate); void setXSize(int); void setYSize(int); void setX(int); //int corresponds to coordinates 1, 2, or 3 void setY(int); void setZ(int); int getXSize(); int getYSize(); double getX(int); //int corresponds to coordinates 1, 2, or 3 double getY(int); double getZ(int); void outputGraph(); void animateGraph(); private: int xSize; int ySize; Coordinate coord1; Coordinate coord2; Coordinate coord3; }; Graph.cpp #include "Graph.h" #include "Coordinate.h" #include <iostream> #include <ctime> using namespace std; Graph::Graph() { Coordinate coord1(0); } Graph::Graph(Coordinate cOne) { coord1 = cOne; xSize = 20; ySize = 20; } Graph::Graph(Coordinate cOne, Coordinate cTwo) { coord1 = cOne; coord2 = cTwo; xSize = 20; ySize = 20; } Graph::Graph(Coordinate cOne, Coordinate cTwo, Coordinate cThree) { coord1 = cOne; coord2 = cTwo; coord3 = cThree; xSize = 20; ySize = 20; } void Graph::setXSize(int size) { xSize = size; } void Graph::setYSize(int size) { ySize = size; } int Graph::getXSize() { return xSize; } int Graph::getYSize() { return ySize; } void Graph::outputGraph() { } void Graph::animateGraph() { } Thanks very much for any help!

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  • How to use Boost 1.41.0 graph layout algorithmes

    - by daniil-k
    Hi I have problem using boost graph layout algorithmes. boost verision 1_41_0 mingw g++ 4.4.0. So there are issues I have encountered Can you suggest me with them? The function fruchterman_reingold_force_directed_layout isn't compiled. The kamada_kawai_spring_layout compiled but program crashed. Boost documentation to layout algorithms is wrong, sample to fruchterman_reingold_force_directed_layout isn't compiled. This is my example. To use function just uncomment one. String 60, 61, 63. #include <boost/config.hpp> #include <boost/graph/adjacency_list.hpp> #include <boost/graph/graph_utility.hpp> #include <boost/graph/simple_point.hpp> #include <boost/property_map/property_map.hpp> #include <boost/graph/circle_layout.hpp> #include <boost/graph/fruchterman_reingold.hpp> #include <boost/graph/kamada_kawai_spring_layout.hpp> #include <iostream> //typedef boost::square_topology<>::point_difference_type Point; typedef boost::square_topology<>::point_type Point; struct VertexProperties { std::size_t index; Point point; }; struct EdgeProperty { EdgeProperty(const std::size_t &w):weight(w) {} double weight; }; typedef boost::adjacency_list<boost::listS, boost::listS, boost::undirectedS, VertexProperties, EdgeProperty > Graph; typedef boost::property_map<Graph, std::size_t VertexProperties::*>::type VertexIndexPropertyMap; typedef boost::property_map<Graph, Point VertexProperties::*>::type PositionMap; typedef boost::property_map<Graph, double EdgeProperty::*>::type WeightPropertyMap; typedef boost::graph_traits<Graph>::vertex_descriptor VirtexDescriptor; int main() { Graph graph; VertexIndexPropertyMap vertexIdPropertyMap = boost::get(&VertexProperties::index, graph); for (int i = 0; i < 3; ++i) { VirtexDescriptor vd = boost::add_vertex(graph); vertexIdPropertyMap[vd] = i + 2; } boost::add_edge(boost::vertex(1, graph), boost::vertex(0, graph), EdgeProperty(5), graph); boost::add_edge(boost::vertex(2, graph), boost::vertex(0, graph), EdgeProperty(5), graph); std::cout << "Vertices\n"; boost::print_vertices(graph, vertexIdPropertyMap); std::cout << "Edges\n"; boost::print_edges(graph, vertexIdPropertyMap); PositionMap positionMap = boost::get(&VertexProperties::point, graph); WeightPropertyMap weightPropertyMap = boost::get(&EdgeProperty::weight, graph); boost::circle_graph_layout(graph, positionMap, 100); // boost::fruchterman_reingold_force_directed_layout(graph, positionMap, boost::square_topology<>()); boost::kamada_kawai_spring_layout(graph, positionMap, weightPropertyMap, boost::square_topology<>(), boost::side_length<double>(10), boost::layout_tolerance<>(), 1, vertexIdPropertyMap); std::cout << "Coordinates\n"; boost::graph_traits<Graph>::vertex_iterator i, end; for (boost::tie(i, end) = boost::vertices(graph); i != end; ++i) { std::cout << "ID: (" << vertexIdPropertyMap[*i] << ") x: " << positionMap[*i][0] << " y: " << positionMap[*i][1] << "\n"; } return 0; }

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  • Google Visualization API chart in Blogger / Blogspot

    - by gotgenes
    Is it possible to embed (chart) visualizations created by the Google Visualization API in a Blogger post? I tried stripping out the <head> and <body> tags (and closing tags) from the pie chart example, however, the pie chart visualization fails to render, even on a published post. NOTE: I'm asking about the Visualization API, rather than the Google Image Charts (Charts API).

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  • Randomly generate directed graph on a grid

    - by Talon876
    I am trying to randomly generate a directed graph for the purpose of making a puzzle game similar to the ice sliding puzzles from Pokemon. This is essentially what I want to be able to randomly generate: http://bulbanews.bulbagarden.net/wiki/Crunching_the_numbers:_Graph_theory. I need to be able to limit the size of the graph in an x and y dimension. In the example given in the link, it would be restricted to an 8x4 grid. The problem I am running into is not randomly generating the graph, but randomly generating a graph, which I can properly map out in a 2d space, since I need something (like a rock) on the opposite side of a node, to make it visually make sense when you stop sliding. The problem with this is that sometimes the rock ends up in the path between two other nodes or possibly on another node itself, which causes the entire graph to become broken. After discussing the problem with a few people I know, we came to a couple of conclusions that may lead to a solution. Including the obstacles in the grid as part of the graph when constructing it. Start out with a fully filled grid and just draw a random path and delete out blocks that will make that path work. The problem then becomes figuring out which ones to delete to avoid introducing an additional, shorter path. We were also thinking a dynamic programming algorithm may be beneficial, though none of us are too skilled with creating dynamic programming algorithms from nothing. Any ideas or references about what this problem is officially called (if it's an official graph problem) would be most helpful. Here are some examples of what I have accomplished so far by just randomly placing blocks and generating the navigation graph from the chosen start/finish. The idea (as described in the previous link) is you start at the green S and want to get to the green F. You do this by moving up/down/left/right and you continue moving in the direction chosen until you hit a wall. In these pictures, grey is a wall, white is the floor, and the purple line is the minimum length from start to finish, and the black lines and grey dots represented possible paths. Here are some bad examples of randomly generated graphs: http://i.stack.imgur.com/9uaM6.png Here are some good examples of randomly generated (or hand tweaked) graphs: i.stack.imgur.com/uUGeL.png (can't post another link, sorry) I've also seemed to notice the more challenging ones when actually playing this as a puzzle are ones which have lots of high degree nodes along the minimum path.

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  • Cluster Graph Visualization using python

    - by AlgoMan
    I am assembling different visualization tools that are available in python language. I found the Treemap. (http://pypi.python.org/pypi/treemap/1.05) Can you suggest some other tools that are available. I am exploring different ways of visualization of web data.

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  • [C++] Write connected components of a graph using Boost Graph

    - by conradlee
    I have an file that is a long list of weighted edges, in the following form node1_id node2_id weight node1_id node3_id weight and so on. So one weighted edge per line. I want to load this file into boost graph and find the connected components in the graph. Each of these connected components is a subgraph. For each of these component subgraphs, I want to write the edges in the above-described format. I want to do all this using boost graph. This problem is in principle simple, it's just I'm not sure how to implement it neatly because I don't know my way around Boost Graph. I have already spent some hours and have code that will find the connected components, but my version is surely much longer and more complicated that necessary---I'm hoping there's a boost-graph ninja out there that can show me the right, easy way.

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  • Scene Graph for Deferred Rendering Engine

    - by Roy T.
    As a learning exercise I've written a deferred rendering engine. Now I'd like to add a scene graph to this engine but I'm a bit puzzled how to do this. On a normal (forward rendering engine) I would just add all items (All implementing IDrawable and IUpdateAble) to my scene graph, than travel the scene-graph breadth first and call Draw() everywhere. However in a deferred rendering engine I have to separate draw calls. First I have to draw the geometry, then the shadow casters and then the lights (all to different render targets), before I combine them all. So in this case I can't just travel over the scene graph and just call draw. The way I see it I either have to travel over the entire scene graph 3 times, checking what kind of object it is that has to be drawn, or I have to create 3 separate scene graphs that are somehow connected to each other. Both of these seem poor solutions, I'd like to handle scene objects more transparent. One other solution I've thought of was traveling trough the scene graph as normal and adding items to 3 separate lists, separating geometry, shadow casters and lights, and then iterating these lists to draw the correct stuff, is this better, and is it wise to repopulate 3 lists every frame?

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  • Display Graph using Boost Graph Library

    - by TheTSPSolver
    Can anyone please tell me that once I've created a graph using Boost Graph library, how can I display that graph? My biggest concern is that the edge weights are coming from an exernal data source over the network. And I need to be able to display the edgeweights live as they get updated.

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  • Architecture for Social Graph data that has a Time Frame Associated?

    - by Jay Stevens
    I am adding some "social" type features to an existing application. There are a limited # of node & edge types. Overall the data itself is relatively small (50,000 - 70,000 for each type of node) there will be a number of edges (relationships) between them (almost all directional). This, I know, is relatively easy to represent with an SDF store (such as BrightstarDB) or something like Microsoft's Trinity (or really many of the noSQL options). The thing that, I think, makes this a unique use case is that each relationship will have a timeframe associated with it (start and end dates). Right now, I'm thinking of just storing this in a relational structure and dealing with the headaches of "traversing the graph", but I'm looking for suggestions on a better approach (both in terms of data structure and server): Column ================ From_Node_ID Relationship To_Node_ID StartDate EndDate Any suggestions or thoughts are welcomed.

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  • How to fit a custom graph to the boost graph library template?

    - by Michael
    I'm rusty on C++ templates and I'm using the boost graph library (a fatal combination). I've searched the web and can't find any direct instructions on how to take a custom graph structure and fit enough of it to BGL (boost graph library) that I can use boosts graph traversing algorithms. Anyone familiar enough with the library to help me out?

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  • C# graph library to be used from Unity3D

    - by Heisenbug
    I'm looking for a C# graph library to be used inside Unity3D script. I'm not looking for pathfinding libraries (I know there are good one available). I could consider using a path finding library only if it gives me direct access to underlying graph classes (I need nodes and edges, and classic graph algorithms) The only product I've seen that seems intersting is QuickGraph. I have the following question: Is it possible to use QuickGraph inside Unity3d? If yes. Is this a good idea? Does it have any drawbacks? Is it a quite fast and well written/supported library? Does anyone has ever used it? Are available other C# graph library that can be easily integrated in Unity3d?

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  • Scene Graph as Object Container?

    - by Bunkai.Satori
    Scene graph contains game nodes representing game objects. At a first glance, it might seem practical to use Scene Graph as physical container for in game objects, instead of std::vector< for example. My question is, is it practical to use Scene Graph to contain the game objects, or should it be used only to define scene objects/nodes linkages, while keepig the objects stored in separate container, such as std::vector<?

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  • Splitting Graph into distinct polygons in O(E) complexity

    - by Arthur Wulf White
    If you have seen my last question: trapped inside a Graph : Find paths along edges that do not cross any edges How do you split an entire graph into distinct shapes 'trapped' inside the graph(like the ones described in my last question) with good complexity? What I am doing now is iterating over all edges and then starting to traverse while always taking the rightmost turn. This does split the graph into distinct shapes. Then I eliminate all the excess shapes (that are repeats of previous shapes) and return the result. The complexity of this algorithm is O(E^2). I am wondering if I could do it in O(E) by removing edges I already traversed previously. My current implementation of that returns unexpected results.

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  • Online graphing and data visualization frameworks

    - by Marques
    I have been looking around at web applications and websites with rich graphs, charts, and data visualization and for the most part have been able to determine which frameworks or tools websites are using. However I was looking over 'resumup.com' and couldn't determine what they are using. Does anyone know off hand or can you tell? It doesn't seem like any javascript framework i've seen unless its custom...is it some sort of flash or flex framework? Any help would be greatly appreciated. Thanks, Marques

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