105 lines
3.6 KiB
Python
105 lines
3.6 KiB
Python
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import pandas as pd
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import networkx as nx
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import matplotlib.pyplot as plt
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df = pd.read_csv('data\\temp.csv')
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df['succ_equipment_code'] = df['equipment_code'].str.rsplit('.', n=1)
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df['succ_equipment_code'] = df['succ_equipment_code'].apply(lambda lst: lst[0] if len(lst)>1 else None)
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assert len(df['equipment_code']) == len((df['equipment_code'].unique())),\
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"column equipment_code contains duplicate value"
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df.set_index('equipment_code', inplace=True)
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# graph bom
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g_bom = nx.DiGraph()
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g_bom.add_nodes_from(df.index)
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# edge
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for index, row in df.iterrows():
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if row['succ_equipment_code']:
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g_bom.add_edge(index, row['succ_equipment_code'])
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# attr
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df_attr = df.loc[:, ['equipment_name']]
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dct_attr = {}
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for code in df_attr.index:
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dct_attr[code] = df_attr.loc[code].to_dict()
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nx.set_node_attributes(g_bom, dct_attr)
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# show
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plt.rcParams['font.sans-serif'] = 'SimHei'
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plt.figure(figsize=(12, 12), dpi=300)
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pos = nx.nx_agraph.graphviz_layout(g_bom,
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prog='twopi',
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args='')
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node_label = nx.get_node_attributes(g_bom, 'equipment_name')
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nx.draw(g_bom,
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pos,
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labels=node_label,
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font_size=6)
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plt.savefig('g_bom_20230712.png')
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plt.close()
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# graph firm
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s_firm = pd.Series(df['firm_name'].unique())
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g_firm = nx.MultiDiGraph()
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g_firm.add_nodes_from(s_firm.index)
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# attr
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dct_attr = {}
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for firm_code in s_firm.index:
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firm_name = s_firm[firm_code]
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lst_prod_code = df.index[df['firm_name'] == firm_name].to_list()
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dct_attr[firm_code] = {'firm_name': firm_name,
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'lst_prod_code': lst_prod_code}
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nx.set_node_attributes(g_firm, dct_attr)
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print(g_firm.nodes)
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print(g_firm.nodes[0])
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# edge
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for prod_code, row in df.iterrows():
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firm_name = row['firm_name']
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firm_code = s_firm.index[s_firm == firm_name].to_list()[0]
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for succ_prod_code in g_bom.successors(prod_code):
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# 目前df中一个prod code只对应一个firm
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succ_firm_name = df.loc[df.index == succ_prod_code, 'firm_name'].to_list()[0]
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succ_firm_code = s_firm.index[s_firm == succ_firm_name].to_list()[0]
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g_firm.add_edges_from([(firm_code, succ_firm_code, {'product': prod_code})])
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print((firm_name, succ_firm_name, prod_code))
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# show
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plt.rcParams['font.sans-serif'] = 'SimHei'
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plt.figure(figsize=(12, 12), dpi=300)
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pos = nx.nx_agraph.graphviz_layout(g_firm,
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prog='twopi',
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args='')
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node_label = nx.get_node_attributes(g_firm, 'firm_name')
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nx.draw(g_firm,
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pos,
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labels=node_label,
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font_size=6)
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edge_label = nx.get_edge_attributes(g_firm, 'product')
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edge_label = {(n1, n2): label for (n1, n2, _), label in edge_label.items()}
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nx.draw_networkx_edge_labels(g_firm,
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pos,
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edge_label,
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font_size=4)
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plt.savefig('g_firm_20230712.png')
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plt.close()
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# pos = nx.random_layout(g_firm)
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# nx.draw_networkx_nodes(g_firm, pos, node_color = 'r', node_size = 100, alpha = 1)
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# ax = plt.gca()
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# for e in g_firm.edges:
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# ax.annotate("",
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# xy=pos[e[0]], xycoords='data',
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# xytext=pos[e[1]], textcoords='data',
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# arrowprops=dict(arrowstyle="->", color="0.5",
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# shrinkA=5, shrinkB=5,
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# patchA=None, patchB=None,
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# connectionstyle="arc3,rad=rrr".replace('rrr',str(0.3*e[2])
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# ),
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# ),
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# )
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# plt.axis('off')
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# plt.show()
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