Update clustering.md

lawrennd · Nov 6, 2023 · 1e4f15f · 1e4f15f
1 parent 69e5519
commit 1e4f15f
Showing 1 changed file with 3 additions and 5 deletions.
diff --git a/_ml/includes/clustering.md b/_ml/includes/clustering.md
@@ -98,10 +98,9 @@ for i in range(6):
           centres[j, :] = np.mean(Y[ind==j, :], 0)
     c[0].set_data(centres[:, 0], centres[:, 1])
     counter+=1
-    mlai.write_figure(f"kmeans_clustering_{counter:0>3}.svg", directory="ml")
+    mlai.write_figure(f"kmeans_clustering_{counter:0>3}.svg", directory="\writeDiagramsDir/ml")
     write_plot(counter, 'Allocate each data point to the nearest cluster centre.')}
 
-\setupdisplaycode{import notutils as nu}
 \setupdisplaycode{import notutils as nu}
 \displaycode{nu.display_plots('kmeans_clustering_{counter:0>3}.svg', directory='\writeDiagramsDir/ml', 
                             text_top='kmeans_clustering_{counter:0>3}.tex', counter=(0, 13))}
@@ -127,17 +126,16 @@ ax.plot(Y[:, 0], Y[:, 1], 'rx')
 ax.set_xlabel('$y_1$', fontsize=20)
 ax.set_ylabel('$y_2$', fontsize=20)
 
-mlai.write_figure(\writeDiagramsDir/ml/cluster_data00.svg')
+mlai.write_figure("cluster_data00.svg', directory="\writeDiagramsDir/ml/")
 pi_vals = np.linspace(-np.pi, np.pi, 200)[:, None]
 for i in range(num_centres):
     ax.plot(centres[i, 0], centres[i, 1], 'o', markersize=5, color=[0, 0, 0], linewidth=2)
     x = np.hstack([np.sin(pi_vals), np.cos(pi_vals)])
     L = np.linalg.cholesky(np.outer(w[i, :],w[i, :]) + sigma[i]**2*np.eye(2))
     el = np.dot(x, L.T)
     ax.plot(centres[i, 0] + el[:, 0], centres[i, 1] + el[:, 1], linewidth=2, color=[0,0,0])
-mlai.write_figure(\writeDiagramsDir/ml/cluster_data01.svg')}
+mlai.write_figure("cluster_data01.svg", directory="\writeDiagramsDir/ml/")}
 
-\setupdisplaycode{import notutils as nu}
 \setupdisplaycode{import notutils as nu}
 \displaycode{nu.display_plots('cluster_data{counter:0>2}.svg', directory='\writeDiagramsDir/ml', counter=(0, 1))}