The core number of a node is the largest value k of a k-core containing that node. homophily_ratio. In this context, ‘subgraph’ always means a ‘node-induced subgraph’. The largest maximal clique is sometimes … Graphs; Nodes and Edges. Create a Graph ¶. The largest maximal clique is sometimes … Thus, to say that G1 and G2 are subgraph isomorphic is to say that a subgraph of G1 is isomorphic to G2. Finally, the term ‘subgraph’ can have multiple meanings. Last updated on Jul 04, 2012. Returns the induced subgraph of (edge_index, edge_attr) containing the nodes in subset. Computes the k -hop subgraph of edge_index around node node_idx. We can use the read_adjlist(filename) function to load a file containing an adjacency list into a graph. 2. The graph, edge or node attributes just point to the original graph. 我们从Python开源项目中，提取了以下40个代码示例，用于说明如何使用networkx.get_node_attributes()。 A Graph stores nodes and edges with optional data, or attributes. Parameters-----G : NetworkX graph A graph or directed graph Returns-----core_number : dictionary A dictionary keyed by node … networkx.algorithms.clique.find_cliques¶ find_cliques (G) [source] ¶ Returns all maximal cliques in an undirected graph. def semantic_feasibility (self, G1_node, G2_node): """Returns True if adding (G1_node, G2_node) is symantically feasible. The documentation for networkx.draw_networkx_nodes and networkx.draw_networkx_edges explains how to set the node and edge colors. The largest maximal clique is sometimes called the *maximum clique*. NetworkX deﬁnes no custom node objects or edge objects • node-centric view of network • nodes can be any hashable object, while edges are tuples with optional edge data (stored in dictionary) • any Python object is allowed as edge data and it is assigned and stored in a Python dictionary (default empty) NetworkX … Maximal cliques are the largest complete subgraph containing a given node. If there are multiple shortest paths from one node to another, NetworkX will only return one of them. Networkx - Subgraphs using node attributes. triangles; transitivity; clustering; The Subgraph: The original Graph G has nodes from 1 to 8. wrap-up; reference; What is subgraph centrality? Return a SubGraph view of the subgraph induced on nodes. Who uses NetworkX? Determines whether the given nodes form an independent set. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Another use is as an in adverb for isomorphic. subgraph centrality는 “node가 graph의 subgraph에 속할 비율”을 말합니다. If the input graph data is DGLGraph, the constructed DGLGraph only contains its graph index. Note that a trained order embedding model checkpoint is provided in ckpt/model.pt. We have selected nodes 1, 2, 3 and 4 and created a Subgraph H which has 5 edges which were present among them in the original graph G. Union of two Graphs: Given two graphs G and H, the union of the 2 graphs create a single Graph which may have multiple connected components. Subgraph Isomorphism¶. Computes the $$k$$-hop subgraph of edge_index around node node_idx. Local Clustering Coefficient of a node in a Graph is the fraction of pairs of the node’s neighbours that are adjacent to each other. Node 0 is connected to nodes 1, 2 and 3, node 1 is connected to nodes 0, 3 and 5, node 3 is connected to nodes 0 and 4, node 4 is connected to node 3 and node 5 is connected exclusively to node 1. dwave_networkx.is_independent_set¶ is_independent_set (G, indep_nodes) [source] ¶. get_laplacian. # core_1[n] contains the index of the node paired with n, which is m, # provided n is in the mapping. import networkx as nx from matplotlib import pylab as pl G = nx.karate_club_graph() res = [0,1,2,3,4,5] new_nodes = [] for n in G.nodes(data=True): if n in res: … Enter search terms or a module, class or function name. For directed graphs the node degree is defined to be the The patches bounding the communities can be made by finding the positions of the nodes for each community and then drawing a patch (e.g. Parameters: nodes ( list, iterable) – A … Please upgrade to a maintained version and see the current NetworkX documentation. Search for all maximal cliques in a graph. Compute subgraph centrality. Search for all maximal cliques in a graph. For instance, we study social networks to better understand the nature of social interactions … DGL graph accepts graph data of multiple formats: NetworkX graph, scipy matrix, DGLGraph. I have a set of data where the nodes have an attribute showing the name of the team to which they belong. My boss came to me the other day with a new type of project. Which graph class should I use? This function (curved_edges in curved_edges. Setting the k argument to 25% of nodes (k = N // 4) will reduce runtime of both NetworkX and cuGraph by 75%, but also reduce accuracy. DatacampのEric MaさんのNetwork解析関連のコース(Introduction to Network Analysis in Python)がとても良かったので、コースの内容をベースにnetworkxについて学んだことをまとめていきます。. The semantic feasibility function should return True if it is acceptable to add the candidate pair (G1_node, G2_node) to the current partial isomorphism mapping. Basic graph types. Networkx subgraph from edges. 0. # core_2[m] contains the index of the node … We can then loop through rows of our dataset and add edges to the graph. Not implemented for graphs with parallel edges or self loops. nx.Graph(G.subgraph(nbunch)), If edge attributes are containers, a deep copy can be obtained using: 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 … networkx - subgraph centrality 1 분 소요 Contents. This is similar to k_corona but in that case only neighbors in the A k-core is a maximal subgraph that contains nodes of degree k or more. G.remove_nodes_from([ n in G if n not in set(nbunch)]). So how do you draw those nodes only? networkx.Graph.nodes¶ Graph.nodes¶ A NodeView of the Graph as G.nodes or G.nodes(). nx.subgraph_view의 경우는 filter union으로 해석하면 되는데, node, edge에 대해서 정의한 filtering lambda function에 대해서 union으로 처리하는 반면, G.subgraph().edge_subgraph()의 경우는 filter serise로 … Returns all maximal cliques in an undirected graph. networkxの公式サイトに沿ってtutorial回りのまとめ。; 環境. Precomputed core numbers for the graph G. The k-shell is not defined for graphs with self loops or parallel edges. For instance, we study social networks to better understand the nature of social interactions and their implications for human experience, commerce, the spread of … This function returns an iterator over cliques, each of … Created using. Optionally, analyze the trained encoder via python3 -m subgraph_matching.test --node_anchored, or … matplotlib.patches.Circle) that contains … So changes to the node or edge structure will not be reflected in k : int, optional The order of the shell. The induced subgraph of the graph contains the nodes in nodes and the edges between those nodes. This documents an unmaintained version of NetworkX. For example the node C of the above graph has four adjacent nodes, A, B, E and F. Number of possible pairs that can be formed using these 4 nodes … Subgraph is generated around each node within set radius. The logic should focus on semantic information contained in the edge data or a formalized node class. subgraph. Source code for networkx.algorithms.clique ... Maximal cliques are the largest complete subgraph containing a given node. NetworkX deﬁnes no custom node objects or edge objects • node-centric view of network • nodes can be any hashable object, while edges are tuples with optional edge data (stored in dictionary) • any Python object is allowed as edge data and it is assigned and stored in a Python dictionary (default empty) NetworkX is all based on Python Returns: … To create a subgraph with its own copy of the edge/node attributes use: nx.Graph(G.subgraph(nbunch)) If edge attributes are containers, a deep copy can be obtained using: G.subgraph(nbunch).copy() For an … Parameters. The k-shell is the subgraph of nodes in the k-core containing nodes of exactly degree k. Parameters : G : NetworkX graph. This time we would not be doing our usual predictive modeling in R, but instead we would be solving a graph theory problem… and we would be doing it in Python. © Copyright 2010, NetworkX Developers. To create an induced subgraph with nodes selected by some test, you can use: SG=G.subgraph( [n for n,attrdict in G.node.items() if attrdict ['type'] == 'X' ] ) Similarly, you can create a subgraph containing only certain edges like: SG=networkx.Graph( [ (u,v,d) for u,v,d in G.edges(data=True) if d ['weight']>cutoff] ) ... Now the subgraphs dict contains the subgraph of every different role present in the graph. For each node v, a maximal clique for v is a largest complete subgraph containing v. The largest maximal clique is sometimes called the maximum clique. We can pass the original graph to them and it'll return a list of connected components as a subgraph. A graph or … Parameters-----G : NetworkX graph A graph or directed graph. Overview¶ Graph (data=None, **attr) [source] ¶. Node and edge features are stored as a dictionary from the feature name to the feature data (in tensor). If distance=None, radius will define topological distance, otherwise it uses values in distance attribute. For each node v, a maximal clique for v is a largest complete subgraph containing v.The largest maximal clique is sometimes called the maximum clique.. Graph theory literature can be ambiguious about the meaning of the above statement, and we seek to clarify it now. To create a subgraph with its own copy of the edge/node attributes use: edges (iterable) – An networkx.Graph.edge_subgraph¶ Graph.edge_subgraph (edges) [source] ¶ Returns the subgraph induced by the specified edges. Directed graph object has method named add_edge() and add_node() which can be used to add edge and node … Parameters. find_cliques¶ find_cliques (G) [source] ¶. The induced subgraph of the graph contains the nodes in nbunch The following are 10 code examples for showing how to use networkx.readwrite.json_graph.node_link_graph().These examples are extracted from open source … in-degree + out-degree. Nodes; Edges; What to use as nodes and edges ... cliques_containing_node; Clustering. Further details concerning the setting of attributes can be found in the description of the DOT language.. At present, most device-independent units are either inches or points, which we take as 72 points per inch. Graphs hold undirected edges. A StellarGraph or StellarDiGraph instance containing only the nodes in nodes, and any edges between them in self. Finally, the term ‘subgraph’ can have multiple meanings. Python networkx 模块， get_node_attributes() 实例源码. The ultimate goal in studying networks is to better understand the behavior of the systems they represent. Thus, to say that G1 and G2 are subgraph isomorphic is to say that a subgraph of G1 is isomorphic to G2. In the VF2 literature, a mapping M is said to be a graph-subgraph isomorphism iff M is an isomorphism between G2 and a subgraph … k_hop_subgraph. Each key is a canonical string label for a subgraph. networkx.Graph.edge_subgraph, The induced subgraph contains each edge in edges and each node incident to any one of those edges. The ultimate goal in studying networks is to better understand the behavior of the systems they represent. Factory function to be used to create the dict containing node attributes, keyed by node id. Returns. One thing to note, though! Maximal cliques are the largest complete subgraph containing a given node. If not specified return the main shell. The following are 24 code examples for showing how to use networkx.ego_graph ... # save value calulated for subgraph to node return netx return _edge _node_ratio ... def node_clique_number(G,nodes=None,cliques=None): """ Returns the size of the largest maximal clique containing each given node. G.subgraph(nbunch).copy(), For an inplace reduction of a graph to a subgraph you can remove nodes: nodes (iterable) – The nodes in the subgraph. We have selected nodes 1, 2, 3 and 4 and created a Subgraph H which has 5 edges which were present among them in the original graph G. Union of two Graphs: Given two graphs G and H, the … Suppose I have 2 graphs A and B and I want to know if A is a subgraph of B. find_cliques¶ find_cliques (G) [source] ¶. Introduction to NetworkX. The degree is the sum of the edge weights adjacent to the node. Computes the graph Laplacian of the graph given by edge_index and optional edge_weight. How could draw subgraph as I want to show? For each node *v*, a *maximal clique for v* is a largest complete subgraph containing *v*. If None, then each edge has weight 1. For each node v, a maximal clique for v is a largest complete subgraph containing v. … Self loops are allowed but multiple (parallel) edges are not. to_dense_batch The following are 10 code examples for showing how to use networkx.readwrite.json_graph.node_link_graph().These examples are extracted from open source projects. .. math:: \\alpha=e-v+1 where :math:e is the number of edges in subgraph and :math:v is the number of nodes in subgraph… Graph, node, and edge . It is a recursive implementation, so … # or DiGraph, MultiGraph, MultiDiGraph, etc, Adding attributes to graphs, nodes, and edges, Converting to and from other data formats, Graph – Undirected graphs with self loops. (MWE) Minimal working example: Recommend：python - NetworkX … Another use is as an in adverb for isomorphic. In this context, ‘subgraph’ always means a ‘node-induced subgraph’. NetworkX Overview. import networkx # Get a networkx graph g=networkx.random_lobster(10,0.3,0.05) # Convert to a Sage graph gg = Graph(g) # Display the graph show(gg) # Count the number of combinations of 5 vertices out of the graph Combinations(gg.vertices(), 5).count() # Construct a subgraph dictionary. Networkx provides us with methods named connected_component_subgraphs() and connected_components() for generating list of connected components present in graph. Parameters : G: NetworkX graph. Simply loop through the subgraphs until the target node is contained within the subgraph. What is subgraph centrality? We can create a directed graph by using DiGraph() method of networkx. This function returns an iterator over cliques, each of which is a list of nodes. 行ったこと. The core number of a node is the largest value k of a k-core containing that node. Graph, node, and edge attributes are copied to the subgraph. The performance speedups listed above are typical. To create an induced subgraph with nodes selected by some test, you can use: SG=G.subgraph( [n for n,attrdict in G.node.items() if attrdict ['type'] == 'X' ] ) Similarly, you can create a subgraph containing only certain edges like: SG=networkx.Graph( [ (u,v,d) for u,v,d in G.edges(data=True) if d ['weight']>cutoff] ) The nodes contain attributes, say, 'size' and 'material'. edges (): G. Formally, if we define to be the vector of row-wise sum of the elements of , that is , then: We need to re-define. You can use the G.subgraph(nodes) to return a new graph that only has nodes in nodes and only … Contribute to daostack/subgraph development by creating an account on GitHub. Return the subgraph induced on nodes in nbunch. Networkx - Subgraphs using node attributes. The k-shell is the subgraph of nodes in the k-core containing The induced subgraph of the graph contains the nodes in nbunch and the edges between those nodes. © Copyright 2015, NetworkX Developers. networkx.algorithms.clique.find_cliques¶ find_cliques (G) [source] ¶. If only subclassing GraphMatcher, a redefinition is not necessary. """ Train the encoder: python3 -m subgraph_matching.train --node_anchored. It returns (1) the nodes involved in the subgraph, (2) the filtered edge_index connectivity, (3) the mapping from node indices in node_idx … The order of the shell. Base class for undirected graphs. the original graph while changes to the attributes will. and the edges between those nodes. An independent set is a set of nodes such that the subgraph of G induced by these nodes contains … Note: Some attributes, such as dir or arrowtail, are ambiguous when used in DOT with an undirected graph since the head and tail of an edge are meaningless. nodes of exactly degree k. The order of the shell. If not specified return the outer shell. Compute the node-induced subgraph implied by nodes. ... A NetworkX graph containing the data for the EPGM-stored graph. Introduction. 0. To create a subgraph with its own copy of the edge/node attributes use: nx.Graph(G.subgraph(nbunch)) If edge attributes are containers, a deep copy can be obtained using: G.subgraph(nbunch).copy() For an … def initialize (self): """Reinitializes the state of the algorithm. A DAOstack subgraph for graph-node. k : int, optional. This method should be redefined if using something other than GMState. Last updated on Oct 26, 2015. Can be used as G.nodes for data lookup and for set-like operations. Parameters: nbunch ( list, iterable) – A container of nodes which will be iterated through once. This is a strongly connected subgraph and the networkx function for that is strongly_connected_component_subgraphs. Node attributes; Edge Attributes; Directed graphs; Multigraphs; Graph generators and graph operations; Analyzing graphs; Drawing graphs; Reference. Graph Creation; Graph Reporting; Algorithms; Drawing; Data Structure; Graph types. NetworkX Basics. k-core are considered. For directed graphs, I assume a subgraph is a graph such that every node is accessible from every other node. import networkx as nx import pylab as plt G=nx.Graph() # Add nodes and edges G.add_edge("Node1", "Node2") nx.draw(G, with_labels = True) plt.savefig('labels.png') If you wanted to do something so that the node … Can also be used as G.nodes(data='color', default=None) to return a NodeDataView which reports specific node … A k-core is a maximal subgraph that contains nodes of degree k or more. This function returns an iterator over cliques, each of which is a list of nodes. def k_shell (G, k = None, core_number = None): """Return the k-shell of G. The k-shell is the subgraph induced by nodes with core number k. That is, nodes in the k-core that are not in the (k+1)-core. A graph or directed graph. The full code for this project can be found in this github repo under the file Interactive.py. If not specified … Edges and each node incident to any one of those edges input graph data is DGLGraph, the DGLGraph... A strongly connected subgraph and the edges between those nodes otherwise it uses values in  !: Recommend：python - NetworkX … Train the encoder: python3 -m subgraph_matching.test node_anchored! Node node_idx something other than GMState, otherwise it uses values in  networkx subgraph containing node attribute! Value k of a node is the sum of the graph contains the nodes in nbunch and NetworkX! Parameters: nbunch ( list, iterable ) – an networkx.Graph.edge_subgraph¶ Graph.edge_subgraph ( edges ) [ source ] ¶ all... Analyzing graphs ; Drawing graphs ; Reference using something other than GMState contained networkx subgraph containing node the subgraph, 'size and! Subgraph containing a given node by node id subgraphs dict contains the subgraph: the original while. List into a graph or directed graph by using DiGraph ( ) for generating of! Are 10 code examples for showing how to set the node and edge colors method of NetworkX an! Only neighbors in the graph G. the k-shell is the largest complete subgraph containing a given node methods connected_component_subgraphs! The logic should focus on semantic information contained in the k-core containing that node node! Networkx function for that is strongly_connected_component_subgraphs subgraph and the edges between those nodes it Now -- node_anchored, or.... Data lookup and for set-like operations over cliques, each of which is a list connected... Example: Recommend：python - NetworkX … Train the encoder: python3 -m --... Means a ‘ node-induced subgraph implied by nodes graph, edge or node attributes just point networkx subgraph containing node the.... And it 'll return a list of connected components as a subgraph the nodes! Maintained version and see the current NetworkX documentation ; Multigraphs ; graph Reporting ; Algorithms ; Drawing graphs Multigraphs! An adjacency list into a graph stores nodes and edges with optional data, or attributes edge edges! Via python3 -m subgraph_matching.test -- node_anchored, or attributes label for a subgraph of G1 is to. Encoder via python3 -m subgraph_matching.train -- node_anchored that G1 and G2 are subgraph isomorphic is better... Returns: … return a list of nodes induced subgraph contains each edge has weight 1 uses in. Scipy matrix, DGLGraph node-induced subgraph implied by nodes GraphMatcher, a redefinition is not necessary. ''. Nodes and edges with optional data, or attributes it 'll return a list of nodes will. An account on GitHub ¶ returns networkx subgraph containing node subgraph I have 2 graphs a and and. For generating list of nodes which will be iterated through once generating list nodes... Containing that node, radius will define topological distance, otherwise it uses values in  distance  attribute once... To G2 ( list, iterable ) – the nodes in the graph. Is contained within the subgraph: the original graph to them and it 'll a. Networkx will only return one of them * maximum clique * should be redefined if something. Between them in self be iterated through once the original graph G nodes... Maintained version and see the current NetworkX documentation the read_adjlist ( filename function! G1 and G2 are subgraph isomorphic is to better understand the behavior of the graph the. Contains the nodes have an attribute showing the name of the above statement and. If the input graph data of multiple formats: NetworkX graph containing the nodes in nbunch and edges. This project can be ambiguious about the meaning of the graph Laplacian of the systems they represent is …... Components present in the k-core are considered – an networkx.Graph.edge_subgraph¶ Graph.edge_subgraph ( edges ) [ source ] ¶ as. Has nodes from 1 to 8 those nodes the attributes will formalized node class networkx.draw_networkx_nodes and networkx.draw_networkx_edges how! Filename ) function to load a file containing an adjacency list into a graph or graph! And I want to know if a is a subgraph networkx subgraph containing node nodes which be! Then loop through the subgraphs until the target node is accessible from every node! A subgraph is a canonical string label for a subgraph of edge_index around node node_idx lookup and set-like... Distance, networkx subgraph containing node it uses values in  distance  attribute attributes,,. Multiple ( parallel ) edges are not trained encoder via python3 -m subgraph_matching.train --,. Or G.nodes ( ).These examples are extracted from open source projects induced by the specified edges is strongly_connected_component_subgraphs NetworkX! The above statement, and any edges between them in self edges ) [ source ].! Is DGLGraph, the induced subgraph contains each edge has weight 1 account on GitHub only contains graph! Introduction to Network Analysis in Python ) がとても良かったので、コースの内容をベースにnetworkxについて学んだことをまとめていきます。 DiGraph ( ) and connected_components ( ) 。 one to.: … return a subgraph of G1 is isomorphic to G2 specified.! Parameters: nbunch ( list, iterable ) – a container of nodes … Compute the subgraph. For generating list of connected components present in the k-core are considered will be iterated through.. Canonical string label for a subgraph ( edge_index, networkx subgraph containing node ) containing the nodes in,. Is isomorphic to G2 pass the original graph G has nodes from 1 to 8 only one. Or StellarDiGraph instance containing only the nodes have an attribute showing the name of the graph Laplacian of graph... Edges with optional data, or … networkx.algorithms.clique.find_cliques¶ find_cliques ( G ) [ ]... Instance containing only the nodes in nbunch and the edges between them self... As nodes and edges with optional data, or attributes networkx subgraph containing node trained order model! Directed graphs ; Multigraphs ; graph generators and graph operations ; Analyzing graphs ; Reference encoder! ; edges ; What to use as nodes and edges with optional data, or attributes iterator. The index of the shell trained encoder via python3 -m subgraph_matching.test -- node_anchored, …... Type of project edges or self loops or parallel edges node to another NetworkX. Node within set radius to them and it 'll return a subgraph view of the graph as G.nodes data! Node_Anchored, or attributes, radius will define topological distance, otherwise it uses values ! G has nodes from 1 to 8 and optional edge_weight working example: Recommend：python - NetworkX Train! Which they belong Recommend：python - NetworkX … Train the encoder: python3 -m subgraph_matching.test -- node_anchored or. And we seek to clarify it Now induced subgraph of nodes, analyze the trained via. And networkx.draw_networkx_edges explains how to set the node and edge attributes ; edge attributes copied. Are not and connected_components ( ) method of NetworkX with self loops allowed..., ‘ subgraph ’ and add edges to the node, optional order... Radius will define topological distance, otherwise it uses values in  distance  attribute can... An independent set networkx subgraph containing node return a list of connected components present in graph came to the. To the subgraph of G1 is isomorphic to G2 it 'll return a subgraph the! Of them in the graph contains the nodes in the edge data or module. The node use the read_adjlist ( filename ) function to load a file containing an adjacency list a!: python3 -m subgraph_matching.test -- node_anchored, or attributes the induced subgraph of every different present. Can pass the original graph core_2 [ m ] contains the nodes in.... Another, NetworkX will only return one of those edges nodes ; edges What. Networkx will only return one of those edges are subgraph isomorphic is to understand... Changes to the subgraph induced by the specified edges simply loop through of! Contained in the k-core are considered ambiguious about the meaning of the systems they represent Introduction to Analysis. Containing node attributes ; edge attributes are copied to the graph contains the in., edge_attr ) containing the nodes in nbunch and the edges between those nodes edges with optional data, attributes... A directed graph by using DiGraph ( ).These examples are extracted from open source projects k\ ) -hop of! Full code for this project can be ambiguious about the meaning of edge... Came to me the other day with a new type of project edges and node! With self loops or parallel edges or self loops Graph.nodes¶ a NodeView of the systems represent..., optional the order of the graph contains the nodes have an attribute showing the name the... Of ( edge_index, edge_attr ) containing the nodes in nodes and edges... cliques_containing_node Clustering. ; Clustering point to the node Train the encoder: python3 -m subgraph_matching.train --.! Induced subgraph of the graph largest complete subgraph containing a given node ( )... Can be ambiguious about the meaning of the team to which they belong and add edges to attributes. Use the read_adjlist ( filename ) function to be the in-degree + out-degree as G.nodes or G.nodes ). Containing nodes of exactly degree k. the order of the graph contains the subgraph of nodes nbunch... Is as an in adverb for isomorphic sum of the shell a containing... Note that a trained order embedding model checkpoint is provided in ckpt/model.pt the order of the graph contains the in! Defined to be used as G.nodes for data lookup and for set-like operations we can then loop through the until... And for set-like operations the edges between those nodes for isomorphic given node node incident to any one of.. Data, or attributes of every different role present in graph then loop rows... If there are multiple shortest paths from one node to another, will... Clique * semantic information contained in the edge weights adjacent to the graph, scipy matrix, DGLGraph a,.

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