GPT4DS_coding_explain.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"private_outputs":true,"provenance":[],"authorship_tag":"ABX9TyOGFJXBVbcbO1uJmSVb6+lv"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# ChatGPT code explaining"],"metadata":{"id":"ndZDzkX3wqiX"}},{"cell_type":"code","source":["import numpy as np\n","import matplotlib.pyplot as plt\n","from sklearn.cluster import DBSCAN\n","N=1000\n","t=np.linspace(0,2*np.pi,N)\n","d=np.array((np.cos(t),np.sin(t)))+np.random.randn(2,N)/15\n","dd=.3*np.array((np.cos(t),np.sin(t)))+np.random.randn(2,N)/15\n","d=np.hstack((d,dd)).T\n","q=DBSCAN(eps=.2,min_samples=6).fit(d)\n","k=q.labels_;j =max(k)+1;l= 'rkbgm'\n","for i in range(j): plt.plot(d[k==i,0],d[k==i,1],'o',color=l[i%len(l)],markerfacecolor='w')\n","plt.plot(d[k==-1,0],d[k==-1,1],'k+'),plt.axis('square')\n","plt.title('Result of dbscan clustering (k=' + str(j) + ')');"],"metadata":{"id":"8saTrJHIbRiI"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":[],"metadata":{"id":"eFQ_nRTvYgrg"},"execution_count":null,"outputs":[]}]}