83 lines
1.2 MiB
Plaintext
83 lines
1.2 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 3600x3600 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import pandas as pd\n",
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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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"plt.rcParams['font.sans-serif'] = 'SimHei'\n",
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"\n",
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"BomNodes = pd.read_csv('BomNodes.csv', index_col=0)\n",
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"BomNodes.set_index('Code', inplace=True)\n",
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"BomCateNet = pd.read_csv('BomCateNet.csv', index_col=0)\n",
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"BomCateNet.fillna(0, inplace=True)\n",
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"\n",
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"G = nx.from_pandas_adjacency(BomCateNet, create_using=nx.MultiDiGraph())\n",
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"\n",
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"labels_dict = {}\n",
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"for code in G.nodes:\n",
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" labels_dict[code] = BomNodes.loc[code].to_dict()\n",
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"nx.set_node_attributes(G, labels_dict)\n",
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"\n",
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"pos = nx.nx_agraph.graphviz_layout(G, prog=\"twopi\", args=\"\")\n",
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"node_labels = nx.get_node_attributes(G, 'Name')\n",
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"plt.figure(figsize=(12, 12), dpi=300)\n",
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"nx.draw_networkx_nodes(G, pos)\n",
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"nx.draw_networkx_edges(G, pos)\n",
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"nx.draw_networkx_labels(G, pos, labels = node_labels, font_size=6)\n",
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"plt.show()\n"
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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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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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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": "3.8.8"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "bcdafc093860683ffb58d6956591562b7f8ed5d58147d17d71a5d4d6605a08df"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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