Added iGraph

This commit is contained in:
Tim committed 2023-11-10 18:48:17 +01:00
1 parent 5cd03306d6
commit 5f4f732eb2
10 files changed
+212840 -164

No files matched your search

Binary file not shown.

Before

Width:  |  Height:  |  Size: 1.2 KiB

After

Width:  |  Height:  |  Size: 2.3 KiB

@@ -0,0 +1,180 @@
<html>
<head>
<meta charset="utf-8">
<script src="lib/bindings/utils.js"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/dist/vis-network.min.css" integrity="sha512-WgxfT5LWjfszlPHXRmBWHkV2eceiWTOBvrKCNbdgDYTHrT2AeLCGbF4sZlZw3UMN3WtL0tGUoIAKsu8mllg/XA==" crossorigin="anonymous" referrerpolicy="no-referrer" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/vis-network.min.js" integrity="sha512-LnvoEWDFrqGHlHmDD2101OrLcbsfkrzoSpvtSQtxK3RMnRV0eOkhhBN2dXHKRrUU8p2DGRTk35n4O8nWSVe1mQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
<center>
<h1></h1>
</center>
<!-- <link rel="stylesheet" href="../node_modules/vis/dist/vis.min.css" type="text/css" />
<script type="text/javascript" src="../node_modules/vis/dist/vis.js"> </script>-->
<link
href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/css/bootstrap.min.css"
rel="stylesheet"
integrity="sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6"
crossorigin="anonymous"
/>
<script
src="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/js/bootstrap.bundle.min.js"
integrity="sha384-JEW9xMcG8R+pH31jmWH6WWP0WintQrMb4s7ZOdauHnUtxwoG2vI5DkLtS3qm9Ekf"
crossorigin="anonymous"
></script>
<center>
<h1></h1>
</center>
<style type="text/css">
#mynetwork {
width: 100%;
height: 600px;
background-color: white;
border: 1px solid lightgray;
position: relative;
float: left;
}
#config {
float: left;
width: 400px;
height: 600px;
}
</style>
</head>
<body>
<div class="card" style="width: 100%">
<div id="mynetwork" class="card-body"></div>
</div>
<div id="config"></div>
<script type="text/javascript">
// initialize global variables.
var edges;
var nodes;
var allNodes;
var allEdges;
var nodeColors;
var originalNodes;
var network;
var container;
var options, data;
var filter = {
item : '',
property : '',
value : []
};
// This method is responsible for drawing the graph, returns the drawn network
function drawGraph() {
var container = document.getElementById('mynetwork');
// parsing and collecting nodes and edges from the python
nodes = new vis.DataSet([{"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 2, "label": "Volkswagen AG", "shape": "dot", "size": 10, "title": "Volkswagen AG\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 1, "label": "Porsche Automobil Holding", "shape": "dot", "size": 10, "title": "Porsche Automobil Holding\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 3, "label": "Volkswagen", "shape": "dot", "size": 10, "title": "Volkswagen\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 4, "label": "Audi", "shape": "dot", "size": 10, "title": "Audi\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 5, "label": "Seat", "shape": "dot", "size": 10, "title": "Seat\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 6, "label": "Skoda Auto", "shape": "dot", "size": 10, "title": "Skoda Auto\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 7, "label": "Porsche AG", "shape": "dot", "size": 10, "title": "Porsche AG\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 8, "label": "Lamborghini", "shape": "dot", "size": 10, "title": "Lamborghini\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilhersteller", "color": " #729b79ff", "font": {"color": "black"}, "id": 9, "label": "Bentley", "shape": "dot", "size": 10, "title": "Bentley\nAutomobilhersteller", "type": "Company"}, {"branche": "Automobilzulieferer", "color": "#475b63ff", "font": {"color": "black"}, "id": 10, "label": "Forvia", "shape": "dot", "size": 10, "title": "Forvia\nAutomobilzulieferer", "type": "Company"}, {"branche": "Automobilzulieferer", "color": "#475b63ff", "font": {"color": "black"}, "id": 11, "label": "Hella", "shape": "dot", "size": 10, "title": "Hella\nAutomobilzulieferer", "type": "Company"}]);
edges = new vis.DataSet([{"from": 2, "label": "part_of", "to": 1, "width": 1}, {"from": 1, "label": "part_of", "to": 3, "width": 1}, {"from": 1, "label": "part_of", "to": 4, "width": 1}, {"from": 1, "label": "part_of", "to": 5, "width": 1}, {"from": 1, "label": "part_of", "to": 6, "width": 1}, {"from": 1, "label": "part_of", "to": 7, "width": 1}, {"from": 4, "label": "part_of", "to": 8, "width": 1}, {"from": 4, "label": "part_of", "to": 9, "width": 1}, {"from": 4, "label": "supplierer", "to": 10, "width": 1}, {"from": 11, "label": "part_of", "to": 10, "width": 1}]);
nodeColors = {};
allNodes = nodes.get({ returnType: "Object" });
for (nodeId in allNodes) {
nodeColors[nodeId] = allNodes[nodeId].color;
}
allEdges = edges.get({ returnType: "Object" });
// adding nodes and edges to the graph
data = {nodes: nodes, edges: edges};
var options = {
"configure": {
"enabled": true,
"filter": [
"physics"
]
},
"edges": {
"color": {
"inherit": false
},
"smooth": {
"enabled": true,
"type": "dynamic"
}
},
"interaction": {
"dragNodes": true,
"hideEdgesOnDrag": false,
"hideNodesOnDrag": false
},
"physics": {
"enabled": true,
"repulsion": {
"centralGravity": 0.2,
"damping": 0.09,
"nodeDistance": 150,
"springConstant": 0.05,
"springLength": 50
},
"solver": "repulsion",
"stabilization": {
"enabled": true,
"fit": true,
"iterations": 1000,
"onlyDynamicEdges": false,
"updateInterval": 50
}
}
};
// if this network requires displaying the configure window,
// put it in its div
options.configure["container"] = document.getElementById("config");
network = new vis.Network(container, data, options);
network.on("click", neighbourhoodHighlight);
return network;
}
drawGraph();
</script>
</body>
</html>
@@ -141,7 +141,7 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 1,
"metadata": {},
"outputs": [
{
@@ -203,7 +203,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 2,
"metadata": {},
"outputs": [
{
@@ -241,14 +241,14 @@
},
{
"cell_type": "code",
"execution_count": 60,
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 864x864 with 1 Axes>"
"<Figure size 1200x1200 with 1 Axes>"
]
},
"metadata": {},
@@ -257,7 +257,7 @@
{
"data": {
"text/plain": [
"<Figure size 432x288 with 0 Axes>"
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
@@ -592,29 +592,19 @@
},
{
"cell_type": "code",
"execution_count": 96,
"execution_count": 7,
"metadata": {},
"outputs": [
{
"ename": "AssertionError",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAssertionError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\Tim\\Documents\\Master\\Semester 4\\Projektgruppe\\aki_prj23_transparenzregister\\documentations\\seminararbeiten\\Verflechtungsanalyse\\mockup_verflechtungsanalyse_with_networkx.ipynb Cell 17\u001b[0m in \u001b[0;36m<cell line: 4>\u001b[1;34m()\u001b[0m\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/Tim/Documents/Master/Semester%204/Projektgruppe/aki_prj23_transparenzregister/documentations/seminararbeiten/Verflechtungsanalyse/mockup_verflechtungsanalyse_with_networkx.ipynb#X41sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m net \u001b[39m=\u001b[39m Network(directed\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m, neighborhood_highlight\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m, bgcolor \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mwhite\u001b[39m\u001b[39m\"\u001b[39m, font_color\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mblack\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/Tim/Documents/Master/Semester%204/Projektgruppe/aki_prj23_transparenzregister/documentations/seminararbeiten/Verflechtungsanalyse/mockup_verflechtungsanalyse_with_networkx.ipynb#X41sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39m# pass networkx graph to pyvis\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/Tim/Documents/Master/Semester%204/Projektgruppe/aki_prj23_transparenzregister/documentations/seminararbeiten/Verflechtungsanalyse/mockup_verflechtungsanalyse_with_networkx.ipynb#X41sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m net\u001b[39m.\u001b[39;49mfrom_nx(s)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/Tim/Documents/Master/Semester%204/Projektgruppe/aki_prj23_transparenzregister/documentations/seminararbeiten/Verflechtungsanalyse/mockup_verflechtungsanalyse_with_networkx.ipynb#X41sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m \u001b[39m# set edge options \u001b[39;00m\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/Tim/Documents/Master/Semester%204/Projektgruppe/aki_prj23_transparenzregister/documentations/seminararbeiten/Verflechtungsanalyse/mockup_verflechtungsanalyse_with_networkx.ipynb#X41sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m net\u001b[39m.\u001b[39minherit_edge_colors(\u001b[39mFalse\u001b[39;00m)\n",
"File \u001b[1;32mc:\\Users\\Tim\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pyvis\\network.py:689\u001b[0m, in \u001b[0;36mNetwork.from_nx\u001b[1;34m(self, nx_graph, node_size_transf, edge_weight_transf, default_node_size, default_edge_weight, show_edge_weights, edge_scaling)\u001b[0m\n\u001b[0;32m 660\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mfrom_nx\u001b[39m(\u001b[39mself\u001b[39m, nx_graph, node_size_transf\u001b[39m=\u001b[39m(\u001b[39mlambda\u001b[39;00m x: x), edge_weight_transf\u001b[39m=\u001b[39m(\u001b[39mlambda\u001b[39;00m x: x),\n\u001b[0;32m 661\u001b[0m default_node_size \u001b[39m=\u001b[39m\u001b[39m10\u001b[39m, default_edge_weight\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m, show_edge_weights\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m, edge_scaling\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m):\n\u001b[0;32m 662\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m 663\u001b[0m \u001b[39m This method takes an exisitng Networkx graph and translates\u001b[39;00m\n\u001b[0;32m 664\u001b[0m \u001b[39m it to a PyVis graph format that can be accepted by the VisJs\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 687\u001b[0m \u001b[39m >>> nt.show(\"nx.html\")\u001b[39;00m\n\u001b[0;32m 688\u001b[0m \u001b[39m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 689\u001b[0m \u001b[39massert\u001b[39;00m(\u001b[39misinstance\u001b[39m(nx_graph, nx\u001b[39m.\u001b[39mGraph))\n\u001b[0;32m 690\u001b[0m edges\u001b[39m=\u001b[39mnx_graph\u001b[39m.\u001b[39medges(data \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m)\n\u001b[0;32m 691\u001b[0m nodes\u001b[39m=\u001b[39mnx_graph\u001b[39m.\u001b[39mnodes(data \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m)\n",
"\u001b[1;31mAssertionError\u001b[0m: "
]
}
],
"outputs": [],
"source": [
"# visualize using pyvis\n",
"from pyvis.network import Network\n",
"\n",
"net = Network(\n",
" directed=False, neighborhood_highlight=True, bgcolor=\"white\", font_color=\"black\"\n",
")\n",
"\n",
"# pass networkx graph to pyvis\n",
"net.from_nx(s)\n",
"net.from_nx(graph)\n",
"\n",
"# set edge options\n",
"net.inherit_edge_colors(False)\n",
@@ -641,7 +631,7 @@
"net.show_buttons(filter_=[\"physics\"])\n",
"\n",
"# save graph as HTML\n",
"net.save_graph(\"./metrics/connected_components_networkx.html\")"
"net.save_graph(\"./metrics/test.html\")"
]
}
],
@@ -664,7 +654,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.11.4"
},
"orig_nbformat": 4
},