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Claudio StamileClaudio Stamile
Claudio Stamile
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Claudio Stamile
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Chapter 1
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‎01_started_with_graphs/01_Introduction_Networkx.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Undirected Graph"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import networkx as nx\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"G = nx.Graph()\n",
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"V = {'Dublin', 'Paris', 'Milan', 'Rome'}\n",
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"E = [('Milan','Dublin'), ('Milan','Paris'), ('Paris','Dublin'), ('Milan','Rome')]\n",
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"G.add_nodes_from(V)\n",
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"G.add_edges_from(E)\n",
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"draw_graph(G, pos_nodes=nx.shell_layout(G), node_size=500)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"V = {G.nodes}\")\n",
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"print(f\"E = {G.edges}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"{G.degree(v): v for v in G.nodes}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"print(f\"Graph Order: {G.number_of_nodes()}\")\n",
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"print(f\"Graph Size: {G.number_of_edges()}\")\n",
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"print(f\"Degree for nodes: { {v: G.degree(v) for v in G.nodes} }\")\n",
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"print(f\"Neighbors for nodes: { {v: list(G.neighbors(v)) for v in G.nodes} }\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"ego_graph_milan = nx.ego_graph(G, \"Milan\")\n",
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"print(f\"Nodes: {ego_graph_milan.nodes}\")\n",
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"print(f\"Edges: {ego_graph_milan.edges}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"new_nodes = {'London', 'Madrid'}\n",
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"new_edges = [('London','Rome'), ('Madrid','Paris')]\n",
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"G.add_nodes_from(new_nodes)\n",
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"G.add_edges_from(new_edges)\n",
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"print(f\"V = {G.nodes}\")\n",
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"print(f\"E = {G.edges}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"node_remove = {'London', 'Madrid'}\n",
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"G.remove_nodes_from(node_remove)\n",
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"print(f\"V = {G.nodes}\")\n",
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"print(f\"E = {G.edges}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"node_edges = [('Milan','Dublin'), ('Milan','Paris')]\n",
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"G.remove_edges_from(node_edges)\n",
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"print(f\"V = {G.nodes}\")\n",
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"print(f\"E = {G.edges}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(nx.to_edgelist(G))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(nx.to_pandas_adjacency(G))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Directed Graph"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import networkx as nx\n",
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"G = nx.DiGraph()\n",
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"V = {'Dublin', 'Paris', 'Milan', 'Rome'}\n",
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"E = [('Milan','Dublin'), ('Paris','Milan'), ('Paris','Dublin'), ('Milan','Rome')]\n",
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"G.add_nodes_from(V)\n",
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"G.add_edges_from(E)\n",
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"print(nx.to_pandas_edgelist(G))\n",
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"print(nx.to_pandas_adjacency(G))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"Indegree for nodes: { {v: G.in_degree(v) for v in G.nodes} }\")\n",
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"print(f\"Outegree for nodes: { {v: G.out_degree(v) for v in G.nodes} }\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"draw_graph(G, pos_nodes=nx.shell_layout(G), node_size=500)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Weighted Directed Graph"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import networkx as nx\n",
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"G = nx.MultiDiGraph()\n",
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"V = {'Paris', 'Dublin','Milan', 'Rome'}\n",
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"E = [ ('Paris','Dublin', 11), ('Paris','Milan', 8),\n",
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" ('Milan','Rome', 5),('Milan','Dublin', 19)]\n",
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"G.add_nodes_from(V)\n",
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"G.add_weighted_edges_from(E)\n",
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"draw_graph(G, pos_nodes=nx.shell_layout(G), node_size=500, plot_weight=True)\n",
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"print(nx.to_pandas_edgelist(G))\n",
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"print(nx.to_pandas_adjacency(G))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Multi Graph"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import networkx as nx\n",
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"directed_multi_graph = nx.MultiDiGraph()\n",
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"V = {'Dublin', 'Paris', 'Milan', 'Rome'}\n",
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"E = [('Milan','Dublin'), ('Milan','Dublin'), ('Paris','Milan'), ('Paris','Dublin'), ('Milan','Rome'), ('Milan','Rome')]\n",
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"directed_multi_graph.add_nodes_from(V)\n",
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"directed_multi_graph.add_edges_from(E)\n",
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"\n",
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"draw_graph(G, pos_nodes=nx.shell_layout(G), node_size=500)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot Graphs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def draw_graph(G, pos_nodes, node_names={}, node_size=50, plot_weight=False):\n",
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" nx.draw(G, pos_nodes, with_labels=False, node_size=node_size, edge_color='gray', arrowsize=30)\n",
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" \n",
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" pos_attrs = {}\n",
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" for node, coords in pos_nodes.items():\n",
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" pos_attrs[node] = (coords[0], coords[1] + 0.08)\n",
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" \n",
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" nx.draw_networkx_labels(G, pos_attrs, font_family='serif', font_size=20)\n",
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" \n",
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" \n",
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" if plot_weight:\n",
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" pos_attrs = {}\n",
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" for node, coords in pos_nodes.items():\n",
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" pos_attrs[node] = (coords[0], coords[1] + 0.08)\n",
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" \n",
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" nx.draw_networkx_labels(G, pos_attrs, font_family='serif', font_size=20)\n",
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" edge_labels=dict([((a,b,),d[\"weight\"]) for a,b,d in G.edges(data=True)])\n",
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" nx.draw_networkx_edge_labels(G, pos_nodes, edge_labels=edge_labels)\n",
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" \n",
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" plt.axis('off')\n",
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" axis = plt.gca()\n",
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" axis.set_xlim([1.2*x for x in axis.get_xlim()])\n",
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" axis.set_ylim([1.2*y for y in axis.get_ylim()])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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