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finish-timeseriesclustering_gas_vensim_NO_policy.py

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+import matplotlib.pyplot as plt
+import seaborn as sns
+
+from ema_workbench import load_results
+from ema_workbench.analysis import clusterer, plotting, Density
+
+# load data
+fn = r'./data/500 gas cases no policy.tar.gz'
+experiments, outcomes = load_results(fn)
+data = outcomes['Cumulative profit']
+
+# calcuate distances
+distances = clusterer.calculate_cid(data)
+
+# plot dedrog
+# clusterer.plot_dendrogram(distances)
+
+# do agglomerative clustering on the distances
+clusters = clusterer.apply_agglomerative_clustering(distances,
+                                                    n_clusters=5)
+
+# show the clusters in the output space
+x = experiments.copy()
+x['clusters'] = clusters.astype('object')
+plotting.lines(x, outcomes,  group_by='clusters',
+               density=Density.VIOLIN)
+
+# show the input space
+# sns.pairplot(x, hue='clusters',
+#              vars=['Initial well productivity per year','Carbon price multiplier',
+#                    'Initial costs for well development','Operating costs per m3 NG', 'Societal urge to become carbon neutral',
+#                    'Subsidy provision factor', 'Factor onshore to offshore BoP costs',
+#                    'Competition constant offshore hydrogen production', 'Platform modification costs', 'Transitioning factor',
+#                    'Price volatility'],
+#              plot_kws=dict(s=13))
+plt.show()