Networkx Copy Graph

To create a subgraph with its own copy of the edge/node attributes use: nx. I'm most concerned about the statement This makes a complete copy of the graph including all of the node or edge attributes. This is in contrast to the similar G=DiGraph(D) which returns a shallow copy of the data. Several packages offer the same basic level of graph manipulation, notably igraph which also has bindings for R and C++. Graph taken from open source projects. copy method does a deep copy of the graph. Hosted by Ionel Cristian M. I am trying to modify the minimum spanning tree if the weight of an edge in the graph not belonging to MST is decreased. In [2]: n = 10 # Number of nodes in the graph. However, I found that NetworkX had the strongest graph algorithms that I needed to solve the CPP. 4016954, 0. NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. If `as_view` is True then a view is returned instead of a copy. is_directed (G) Return True if graph is directed. NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. import networkx as nx # Create a networkX graph under variable 'G' G = nx. Return the density of a graph. 19 people went. Parameters: G (graph) – A NetworkX graph; mapping (dictionary) – A dictionary with the old labels as keys and new labels as values. $ python >>> import. create_empty_copy (G[, with_data]) Return a copy of the graph G with all of the edges removed. I think Graph already contains a small part of NetworkX, thank you for the offer. I have built some implementations using NetworkX(graph Python module) native algorithms in which I output some attributes which I use them for classification purposes. Data Reference (Shallow) – For a shallow copy (with_data=False) the graph structure is copied but the edge, node and graph attribute dicts are references to those in the original graph. graph import rag import networkx as nx from matplotlib import pyplot as plt import numpy as np def max_edge (g, src, dst, n): """Callback to handle merging nodes by choosing maximum weight. Converting NetworkX to Graph-Tool 23 Jun 2016. This week I discovered graph-tool, a Python library for network analysis and visualization that is implemented in C++ with Boost. copy (bool (default=True)) – If True make a copy of the graph attributes; Returns: comp – A generator of graphs, one for each connected component of G. The non-weighted graph code is easy, and is a near copy-paste from some igraph code snippet that was already available. py can be used to generate a graph from a water network model. a text string, an image, an XML object, another Graph, a customized node object, etc. # Here I use the spectral layout and add a little bit of noise. In this recipe, we will show how to create, manipulate, and visualize graphs with NetworkX. Connection between nodes are represented through links (or edges). when I had done F5 to run the program it doesn't return me anything except the Idle shell. This makes a complete copy of the graph including all of the node or edge attributes. 在NetworkX中,nodes能够代表任何对象,例如一个文本,一个图片,一个xml对象或者另外一个Graph,一个自定义的对象等等。 由于NetworkX提供了多种Graph对象生成方法,并且体痛了读写方法来读写多种格式,所以Graph对象能够使用多种方式创建。 -----Nodes. NetworkX is the most popular Python package for manipulating and analyzing graphs. Now this python code 1) imports our edge list from the SPSS dataset and turn it into a networkx graph, 2) reduces the set of edges into connected components, 3) makes a new SPSS dataset where each row is a list of those subgraphs, and 4) makes a macro variable to identify the end variable name (for subsequent transformations). copy() Graph. You can vote up the examples you like or vote down the ones you don't like. Return a copy of the graph. This guide will teach you the process for exporting data from a relational database (PostgreSQL) and importing into a graph database (Neo4j). nx_agraph import graphviz_layout G = nx. Graph is a data structure that consists of following two components: 1. A potentially invaluable tool for math students or engineers, Graph is a tightly focused Windows program that draws and analyzes two dimensional graphs, offering most of the features any. However, I found that NetworkX had the strongest graph algorithms that I needed to solve the CPP. copy(as_view=False) Return a copy of the graph. OK, I Understand. 1 Creating a graphCreate an empty graph with no nodes and no edges. I am being baffled by how apparently poorly NetworkX reads a shapefile and builds a graph out of it. Parameters-----G : graph A NetworkX graph mapping : dictionary A dictionary with the old labels as keys and new labels as values. This function is a hypothesis. Find file Copy path networkx / examples / drawing / plot_random_geometric_graph. info (G[, n]) Print short summary of information for the graph G or the node n. The Open Graph Viz Platform. They are extracted from open source Python projects. add_node(1,. The software provides a standard programming interface and graph implementation suitable for many applications and a rapid development environment for collaborative and multidisciplinary projects. graph class. I think Graph already contains a small part of NetworkX, thank you for the offer. By definition, a Graph is a collection of nodes (vertices) along with identified pairs of nodes (called edges, links, etc). Return type: generator of graphs. Converting from Networkx to Python-Igraph. You can vote up the examples you like or vote down the ones you don't like. a text string, an image, an XML object, another Graph,. NetworkX is a Python package for the creation, manipulation and study of the structure, dynamics, and functions of complex networkx. This function is a hypothesis. It also tests whether an input and. Every graph drawn so far has been connected. Use Python's `copy. Welcome to the Python Graph Gallery. However, I have a lot of trouble converting this into an actual networkx graph, which I will use for my simulation model. The example networkx_graph. Trace or copy the graph of the given function f. copy(as_view=False) Return a copy of the graph. Re: [NetworkX-discuss] ask help of (X)Graph persistence imcs ee Thu, 25 May 2006 23:13:06 -0700 Hi Ed and Aric, Thank you both for the quick and informative response. $ python >>> import. The RAG class represents a undirected weighted graph which inherits from networkx. Contribute to networkx/networkx development by creating an account on GitHub. The copy method by default returns an independent shallow copy of the graph and attributes. The following are code examples for showing how to use networkx. Now let's take a look at how this graph looks like in a few different file formats and how to read each of these. Graph visualization is hard and we will have to use specific tools dedicated for this task. Instructions. And in NetworkX you can use the weighted projected graph to now output, not just the projected graph but the weighted projected graph in this case of the basketball teams. We use cookies for various purposes including analytics. documentation of layout() ). GML format is a standard graph format networkx knows about, so that file can be read into Python as follows:. Graph(G)) gives a shallow copy where the graph structure is copied but the data attributes are references those in the original graph. In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. 6b1ce03 Oct 12, 2019. 1, License: Advanced). The package. The resulting graph structure looks like this: - Nodes are numbers (bus stop numbers) and have a 'pos' attribute with GPS coords. 05119703, 1. In [2]: n = 10 # Number of nodes in the graph. copy¶ Graph. Every graph drawn so far has been connected. 3) # Get positions. PageRank is a way of measuring the importance of website pages. cuGraph aims to provide a NetworkX-like API that will be familiar to data scientists, so they can now build GPU-accelerated workflows more easily. when I had done F5 to run the program it doesn't return me anything except the Idle shell. copy (as_view=False) [source] ¶ Returns a copy of the graph. Plotting a random geometric graph using Networkx I wanted to plot the random geometric graph as shown in networkx gallery with a few tweaks. It provides tools for working with Chimera graphs and implementations of graph-theory algorithms on the D-Wave system and other binary quadratic model samplers. Parameters: G (NetworkX Graph); name (string) - Name of the node attribute to set. copy : bool (optional, default=True) If True return a copy, or if False relabel the nodes in place. If both edges exist in digraph and their edge data is different, only one edge is created with an arbitrary choice of which edge data to use. This module can be installed via pip: pip install hypothesis-networkx User guide. add_node(1,. By voting up you can indicate which examples are most useful and appropriate. And to use NetworkX to represent the network like this, we would use the class DiGraph, which is directed graph. BFS (breadth first search) graph traversal (Python recipe) So has this (all shortest paths between 2 nodes) been included in the networkx's functions? btw, thank. Here are the examples of the python api networkx. Kast is a framework for kinematic analysis of kinematic chains based on screw theory, graph theory and related tools. In this guide, we will be using. Gephi is open-source and free. The front-end page is the same for all drivers: movie search, movie details, and a graph visualization of actors and movies. To label graph nodes, you can use draw_networkx_labels function as follows: [code]import networkx as nx from networkx. Is this suggesting that it makes a copy of what the nodes contain as well? For example if I have the following. The pair of the. Is it implemented in Python, using numpy, networkx and elementtree, among other packages. read_gml('lesmiserables. One examples of a network graph with NetworkX. The first step is to create the graph, which can be done by simply adding the edges; this will also automatically add all the nodes. Find file Copy path networkx / examples / drawing / plot_weighted_graph. A partial mapping is allowed. I can count 6 other graph libraries beside NetworkX and Graph. I post this as a followup from How to load a weighed shapefile in networkX. NetworkX provides data structures for graphs (or networks) along with graph algorithms, generators, and drawing tools. Parameters-----G : graph A NetworkX graph mapping : dictionary A dictionary with the old labels as keys and new labels as values. But, if you have some node-specific method (rare in graph problems, but possible) then you'd have method functions associated with a node. Let’s create a basic undirected Graph: • The graph g can be grown in several ways. Graph Visualization. NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Runs on Windows, Mac OS X and Linux. They are extracted from open source Python projects. Here are the examples of the python api networkx. Converting from Networkx to Python-Igraph. Feel free to propose a chart or report a bug. G (NetworkX graph) - An undirected graph. We have now covered the introduction to graphs, the main types of graphs, the different graph algorithms, their implementation in Python with Networkx, and graph learning techniques for node labeling, link prediction, and graph embedding. Aric will likely give a better answer, but NX loads graphs into memory at once, so in the ranges your are describing you will need a substantial amount of free memory for it to work. In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. Hi Nathann, On Sat, Nov 28, 2009 at 1:57 AM, Nathann Cohen wrote: > If I make no mistake, Robert Miller rewrote the Graph class in C, > which sounds like we are trying to remove networkX from Sage and use. This class inherits from NetworkX MultiDigraph and includes additional methods that are specific to WNTR. The first step is to create the graph, which can be done by simply adding the edges; this will also automatically add all the nodes. You may need to go back and alter these properties. Return the density of a graph. Create online graphs and charts. A finite set of vertices also called as nodes. NetworkX is not primarily a graph drawing package but it provides basic drawing capabilities by using Matplotlib. Create online graphs and charts. Hosted by Ionel Cristian M. Just some updates to idiom’s for NetworkX specifically. deepcopy for new containers. This post describes how to use the Python library NetworkX, to deal with network data and solve interesting problems in network analysis. The data can be any format that is supported by the to_networkx_graph() function, currently including edge list, dict of dicts, dict of lists, NetworkX graph, NumPy matrix or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph. Then we would want a way of capturing this, also, when we construct network in NetworkX, and what we can do is the following. Is it implemented in Python, using numpy, networkx and elementtree, among other packages. I am being baffled by how apparently poorly NetworkX reads a shapefile and builds a graph out of it. First steps with networkx One of my favorite topics is the study of structures and, inspired by the presentation of Jacqueline Kazil and Dana Bauer at PyCon US, I started to use networkx in order to analyze some networks. I'm working on graph mining, so I'm trying to find the best library to do that. In H, we'll delete all the edges that are negative if we want to visualise all positive correlations and vice versa for negative correlations. This module provides a Hypothesis strategy for generating networkx graphs. copy method does a deep copy of the graph. GraphX unifies ETL, exploratory analysis, and iterative graph computation within a single system. Returns a dictionary with `"weight"` set as either the weight between (`src`, `n`) or (`dst`, `n`) in `g` or the maximum of the two when. pyplot as plt Type through the code rather than copy-paste. 7) Networkx with edges connecting nodes from the last time point to the first time point (6h --> 4h --> 2h --> 1h) given that the correlation value is above a certain threshold. This module can be installed via pip: pip install hypothesis-networkx User guide. This software is a set of NetworkX additions for the creation of graphs to model networks. The copy method by default returns a shallow copy of the graph and attributes. If `as_view` is True then a view is returned instead of a copy. NetworkX: Graph Manipulation and Analysis. Use Python’s copy. PageRank is a way of measuring the importance of website pages. The software provides a standard programming interface and graph implementation suitable for many applications and a rapid development environment for collaborative and multidisciplinary projects. You will learn how to take data from the relational system and to the graph by translating the schema and using import tools. Graph and its representations. Stackoverflow. G – An undirected graph with the same name and nodes and with edge (u, v, data) if either (u, v, data) or (v, u, data) is in the digraph. readthedocs. Graphviz is open source graph visualization software. spring_layout(g, pos = pos, iterations = 50) # Create position copies for. Networkx VS graph-tool. Removing random edges from a graph: Python 3/NetworkX objective: Write a function attack_network_edges that takes two arguments: a graph and an integer N. According the doc, it appears that the networkx. barbell_graph taken from open source projects. NetworkX has some built in functions for plotting graphs that we can use to visualize them if they aren't too large. • Start Python (interactive or script mode) and import NetworkX • Different classes exist for directed and undirected networks. subgraph(nbunch)). In addition to standard plotting and layout features as found natively in networkx, the GUI allows you to: In addition to standard plotting and layout features as found natively in networkx, the GUI allows you to:. I've read in here that "graph-tool" is faster, so I tried the same program who count the duplicated graphs (I call them. NetworkX includes many graph generator functions and facilities to read and write graphs in many formats. , a text string, an image, and xml object, another graph, a customized node object, etc. This Python function takes a vertex list, an edge list and a graph type, and translates them to a networkx object. While we provide G[u][v] to report edge attributes, they should not be assigned to without using data structure dependent syntax. That is, if an attribute is a container, that container is shared by the original an the copy. They are extracted from open source Python projects. This week I discovered graph-tool, a Python library for network analysis and visualization that is implemented in C++ with Boost. This makes a complete copy of the graph including all of the node or edge attributes. gml',relabel=True) Now we have a representation G of our network and we can use the function betweenness_centrality() to compute the centrality of each node. - Edges are tuples as connections in between the nodes with attribute 'count', which are the number of passengers. G - An undirected graph with the same name and nodes and with edge (u, v, data) if either (u, v, data) or (v, u, data) is in the digraph. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1. Ralucca Gera, Applied Mathematics Dept. One examples of a network graph with NetworkX. They are extracted from open source Python projects. v7 Directed graphs v8 Multigraphs vi9 Graph generators and graph operations vi10 Analyzing graphs vii11 Drawing graphs viiStart here to begin working with NetworkX. For more information see here. From RoPython-Cluj. Converting NetworkX to Graph-Tool 23 Jun 2016. A potentially invaluable tool for math students or engineers, Graph is a tightly focused Windows program that draws and analyzes two dimensional graphs, offering most of the features any. py Find file Copy path dschult Remove deprecated functions and methods. A good example of a graph is an airline route map, where the vertices are the airports and the edges are the flights that go from one airport to another. Deepcopy - The default behavior is a "deepcopy" where the graph structure as well as all data attributes and any objects they might contain are copied. That is, if an attribute is a container, that container is shared by the original an the copy. However, you can install it manually as you did if you need to call get_nx_graph. spring_layout. If data=None (default) an empty graph is created. Not that I want to discourage you from experimenting with networkx, a great library that I use and love a lot, but with networks of that size you might be better. spectral_layout(g) pos = nx. In this recipe, we will show how to create, manipulate, and visualize graphs with NetworkX. NetworkX has some built in functions for plotting graphs that we can use to visualize them if they aren't too large. NOTE: Use the shift key to select more than one graphic. Share Copy sharable link for this gist. I have built some implementations using NetworkX(graph Python module) native algorithms in which I output some attributes which I use them for classification purposes. Intro to Graphs. In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. subgraph(G, nbunch) - induce subgraph of G on nodes in nbunch union(G1,G2) - graph union disjoint_union(G1,G2) - graph union assuming all nodes are different cartesian_product(G1,G2) - return Cartesian product graph compose(G1,G2) - combine graphs identifying nodes common to both complement(G) - graph complement create_empty_copy(G) - return an. read_gml('lesmiserables. The Neo4j example project is a small, one page webapp for the movies database built into the Neo4j tutorial. SNAP library from Jure Leskovec group at Stanford which is originally in C++ but also has a Python API (please check if you need to use C++ API or Python does the job you want to do). create_empty_copy (G[, with_data]) Return a copy of the graph G with all of the edges removed. G (NetworkX graph) – An undirected graph. To follow is some code that replicates the measures for both weighted and non-weighted graphs, using the Python networkx library. python networkx library - quick start guide There are several different types of graphs to represent the relationship between nodes: Undirected graph, Directed graph, Weighted graph, Planar graph, Orthogonal graph, Grid-based graph, etc. They are extracted from open source Python projects. You can vote up the examples you like or vote down the ones you don't like. 1, License: Advanced). You can set up Plotly to work in online or offline mode, or in jupyter notebooks. cut_threshold¶ skimage. This makes a complete copy of the graph including all of the node or edge attributes. The following are code examples for showing how to use networkx. It doesn't appear that the issue is with PageRank, it just throws an exception when trying to calculate the PageRank of the broken reversed digraph. Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. The data can be an edge list, or any NetworkX graph object. This would reduce the effort of the algorithm on each run. A good example of a graph is an airline route map, where the vertices are the airports and the edges are the flights that go from one airport to another. NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Lab 04: Graphs and networkx. Graph is a data structure that consists of following two components: 1. I can count 6 other graph libraries beside NetworkX and Graph. That is, if an attribute is a container, that container is shared by the original an the copy. Distributed processing of large graphs as far as I know (speaking as a graph guy) has 2 different approaches, with the knowledge of Big Data frameworks or without it. Networkx provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. gml',relabel=True) Now we have a representation G of our network and we can use the function betweenness_centrality() to compute the centrality of each node. In [2]: n = 10 # Number of nodes in the graph. Graphs using Networkx and Semantic web using RDFlib. when I had done F5 to run the program it doesn't return me anything except the Idle shell. The module exposes a single function: graph_builder. This module provides a Hypothesis strategy for generating networkx graphs. The package. 1, License: Advanced). 7 (VTK for Python 3 is not quite ready) (2)Load that file into ParaView ParaView comes with its own Python shell and VTK, but it is somewhat tricky to install NetworkX there. You can vote up the examples you like or vote down the ones you don't like. add_node(1,. # This is a function to merge several nodes into one in a Networkx graph: def merge_nodes (G, nodes, new_node, attr_dict = None, ** attr): """ Merges the selected `nodes` of the graph G into one `new_node`, meaning that all the edges that pointed to or from one of these `nodes` will point to or from the `new_node`. GraphX is Apache Spark's API for graphs and graph-parallel computation. Raises: NetworkXNotImplemented: - If G is undirected. NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. This module can be installed via pip: pip install hypothesis-networkx User guide. from skimage. The Neo4j example project is a small, one page webapp for the movies database built into the Neo4j tutorial. Returns: comp - A generator of graphs, one for each strongly connected component of G. Put the graph in a box, make another one and put it in the box, and another one…. Let's use one of them, draw NetworkX to quickly visualize our new graph. This would require a good API to copy computational elements from one Graph to another in TensorFlow. According the doc, it appears that the networkx. Graph() The graph g can be grown in several ways. How to make Network Graphs in Python with Plotly. Graph Theory 121 Circuit A circuit is a path that begins and ends at the same vertex. import networkx as nx # Create a networkX graph under variable 'G' G = nx. An alternative way of constructing Zachary's graph is to download Zachary's karate club network and save this in the directory you start Python in. The Neo4j example project is a small, one page webapp for the movies database built into the Neo4j tutorial. 9 coarsest_equitable_refinement()Return the coarsest partition which is finer than the input partition, and equitable with respect to self. subgraph(nbunch)). I know how to import a graph with data from a csv-file and how to convert a Sage graph into a networkx graph. In this session we'll be doing a preview of some of the talks for the GraphConnect 2018 conference in New York. add_path (G, nodes, **attr) Add a path. The front-end page is the same for all drivers: movie search, movie details, and a graph visualization of actors and movies. a text string, an image, an XML object, another Graph,. The following are code examples for showing how to use networkx. Removing random edges from a graph: Python 3/NetworkX objective: Write a function attack_network_edges that takes two arguments: a graph and an integer N. I am trying to export a networkx graph into a format that vosviewer can read. copy : bool (optional, default=True) If True return a copy, or if False relabel the nodes in place. NetworkX-METIS is an add-on for theNetworkXpython package usingMETISfor graph partitioning. However, I have a lot of trouble converting this into an actual networkx graph, which I will use for my simulation model. The data can be an edge list, or any NetworkX graph object. This function returns a list of tuples, one for each node, and each tuple contains the label of the node and the centrality value. copy (as_view=False) [source] ¶ Returns a copy of the graph. add_node(1,. $ python >>> import. A graph in this context is made up of vertices which are connected by edges. py Find file Copy path dschult Remove deprecated functions and methods. Installation. Below is a graphical example of a fake network built with 27 polylines all snapped together, so there are no topological errors (ArcGIS 10. readthedocs. There are four types of copies of a graph that people might want. Network Graphs in Python. G (NetworkX Graph) - A directed graph. Here are the examples of the python api networkx. Python - Networkx copy clarification - Stack Overflow. Creating A Graph •Create an empty graph with no nodes •In NetworkX, nodes can be any hashable object, e. import networkx as nx. A potentially invaluable tool for math students or engineers, Graph is a tightly focused Windows program that draws and analyzes two dimensional graphs, offering most of the features any. Ionel Cristian M. WNTR includes a custom Graph Class, WntrMultiDiGraph. add_path (G, nodes, **attr) Add a path. However, I have a lot of trouble converting this into an actual networkx graph, which I will use for my simulation model. The graph, edge or node attributes just point to the original graph. add to release notes. That is, if an attribute is a container, that container is shared by the original an the copy. Let's use one of them, draw NetworkX to quickly visualize our new graph. The framework was designed to support my research thesis in underwater robotics. 7 (VTK for Python 3 is not quite ready) (2)Load that file into ParaView ParaView comes with its own Python shell and VTK, but it is somewhat tricky to install NetworkX there. By definition, a Graph is a collection of nodes (vertices) along with identified pairs of nodes (called edges, links, etc). NetworkX-METIS is an add-on for theNetworkXpython package usingMETISfor graph partitioning. [code]import networkx as nx import numpy as np A = [[0. Graph-tool performance comparison. write_pajek(G, path), vosviewer did not accept. A graph is a set of nodes or vertices, connected together by edges. When a new node is formed by merging two nodes, the edge weight of all the edges incident on the resulting node can be updated by a user defined function weight_func. Return the density of a graph. cut_threshold (labels, rag, thresh, in_place=True) [source] ¶ Combine regions separated by weight less than threshold. The copy method by default returns a shallow copy of the graph and attributes. You can vote up the examples you like or vote down the ones you don't like. Stackoverflow. In NetworkX, nodes can be any hashable object e. In the function, make a copy of the input graph, and then remove N edges at random from the copy. This class inherits from NetworkX MultiDigraph and includes additional methods that are specific to WNTR. write_pajek(G, path), vosviewer did not accept. add_star (G, nodes, **attr) Add a star to Graph G. Hosted by Ionel Cristian M. Networkx Find Path Between Nodes. The graph below is disconnected; there is no. WNTR includes a custom Graph Class, WntrMultiDiGraph. SNAP library from Jure Leskovec group at Stanford which is originally in C++ but also has a Python API (please check if you need to use C++ API or Python does the job you want to do). But if we wanted to have a network that actually has direction, like the food web example, then you would need directed edges. Video created by Universidad de Míchigan for the course "Applied Social Network Analysis in Python". The graph, edge or node attributes just point to the original graph. a text string, an image, an XML object, another Graph,. And then we would add the node attributes. 1, License: Advanced). Note: the graph will automatically adjust a number of chart properties as you resize the graph, including the font size of the text in the graph. We are going to use two Python helper function to translate arguments into the correct form. Networkx provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Hi Nathann, On Sat, Nov 28, 2009 at 1:57 AM, Nathann Cohen wrote: > If I make no mistake, Robert Miller rewrote the Graph class in C, > which sounds like we are trying to remove networkX from Sage and use. for each node in the graph: if there is a path from src to this node and a path from this node to dest, push node to the result list.