Rename the figure paths from *_diagram.png to *_plot.png

09_unsupervised_learning.ipynb

@@ -126,7 +126,7 @@
     "plt.xlabel(\"Petal length\", fontsize=14)\n",
     "plt.tick_params(labelleft=False)\n",
     "\n",
-    "save_fig(\"classification_vs_clustering_diagram\")\n",
+    "save_fig(\"classification_vs_clustering_plot\")\n",
     "plt.show()"
    ]
   },
@@ -265,7 +265,7 @@
    "source": [
     "plt.figure(figsize=(8, 4))\n",
     "plot_clusters(X)\n",
-    "save_fig(\"blobs_diagram\")\n",
+    "save_fig(\"blobs_plot\")\n",
     "plt.show()"
    ]
   },
@@ -445,7 +445,7 @@
    "source": [
     "plt.figure(figsize=(8, 4))\n",
     "plot_decision_boundaries(kmeans, X)\n",
-    "save_fig(\"voronoi_diagram\")\n",
+    "save_fig(\"voronoi_plot\")\n",
     "plt.show()"
    ]
   },
@@ -584,7 +584,7 @@
     "plt.subplot(326)\n",
     "plot_decision_boundaries(kmeans_iter3, X, show_ylabels=False)\n",
     "\n",
-    "save_fig(\"kmeans_algorithm_diagram\")\n",
+    "save_fig(\"kmeans_algorithm_plot\")\n",
     "plt.show()"
    ]
   },
@@ -641,7 +641,7 @@
     "plot_clusterer_comparison(kmeans_rnd_init1, kmeans_rnd_init2, X,\n",
     "                          \"Solution 1\", \"Solution 2 (with a different random init)\")\n",
     "\n",
-    "save_fig(\"kmeans_variability_diagram\")\n",
+    "save_fig(\"kmeans_variability_plot\")\n",
     "plt.show()"
    ]
   },
@@ -1163,7 +1163,7 @@
     "kmeans_k8 = KMeans(n_clusters=8, random_state=42)\n",
     "\n",
     "plot_clusterer_comparison(kmeans_k3, kmeans_k8, X, \"$k=3$\", \"$k=8$\")\n",
-    "save_fig(\"bad_n_clusters_diagram\")\n",
+    "save_fig(\"bad_n_clusters_plot\")\n",
     "plt.show()"
    ]
   },
@@ -1228,7 +1228,7 @@
     "             arrowprops=dict(facecolor='black', shrink=0.1)\n",
     "            )\n",
     "plt.axis([1, 8.5, 0, 1300])\n",
-    "save_fig(\"inertia_vs_k_diagram\")\n",
+    "save_fig(\"inertia_vs_k_plot\")\n",
     "plt.show()"
    ]
   },
@@ -1302,7 +1302,7 @@
     "plt.xlabel(\"$k$\", fontsize=14)\n",
     "plt.ylabel(\"Silhouette score\", fontsize=14)\n",
     "plt.axis([1.8, 8.5, 0.55, 0.7])\n",
-    "save_fig(\"silhouette_score_vs_k_diagram\")\n",
+    "save_fig(\"silhouette_score_vs_k_plot\")\n",
     "plt.show()"
    ]
   },
@@ -1364,7 +1364,7 @@
     "    plt.axvline(x=silhouette_scores[k - 2], color=\"red\", linestyle=\"--\")\n",
     "    plt.title(\"$k={}$\".format(k), fontsize=16)\n",
     "\n",
-    "save_fig(\"silhouette_analysis_diagram\")\n",
+    "save_fig(\"silhouette_analysis_plot\")\n",
     "plt.show()"
    ]
   },
@@ -1428,7 +1428,7 @@
     "plot_decision_boundaries(kmeans_bad, X, show_ylabels=False)\n",
     "plt.title(\"Inertia = {:.1f}\".format(kmeans_bad.inertia_), fontsize=14)\n",
     "\n",
-    "save_fig(\"bad_kmeans_diagram\")\n",
+    "save_fig(\"bad_kmeans_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2091,7 +2091,7 @@
     "plt.subplot(122)\n",
     "plot_dbscan(dbscan2, X, size=600, show_ylabels=False)\n",
     "\n",
-    "save_fig(\"dbscan_diagram\")\n",
+    "save_fig(\"dbscan_plot\")\n",
     "plt.show()\n"
    ]
   },
@@ -2151,7 +2151,7 @@
     "plt.figure(figsize=(6, 3))\n",
     "plot_decision_boundaries(knn, X, show_centroids=False)\n",
     "plt.scatter(X_new[:, 0], X_new[:, 1], c=\"b\", marker=\"+\", s=200, zorder=10)\n",
-    "save_fig(\"cluster_classification_diagram\")\n",
+    "save_fig(\"cluster_classification_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2581,7 +2581,7 @@
     "\n",
     "plot_gaussian_mixture(gm, X)\n",
     "\n",
-    "save_fig(\"gaussian_mixtures_diagram\")\n",
+    "save_fig(\"gaussian_mixtures_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2638,7 +2638,7 @@
    "source": [
     "compare_gaussian_mixtures(gm_tied, gm_spherical, X)\n",
     "\n",
-    "save_fig(\"covariance_type_diagram\")\n",
+    "save_fig(\"covariance_type_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2690,7 +2690,7 @@
     "plt.scatter(anomalies[:, 0], anomalies[:, 1], color='r', marker='*')\n",
     "plt.ylim(top=5.1)\n",
     "\n",
-    "save_fig(\"mixture_anomaly_detection_diagram\")\n",
+    "save_fig(\"mixture_anomaly_detection_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2832,7 +2832,7 @@
     "             arrowprops=dict(facecolor='black', shrink=0.1)\n",
     "            )\n",
     "plt.legend()\n",
-    "save_fig(\"aic_bic_vs_k_diagram\")\n",
+    "save_fig(\"aic_bic_vs_k_plot\")\n",
     "plt.show()"
    ]
   },
@@ -2989,7 +2989,7 @@
     "plot_gaussian_mixture(bgm_high, X[:nn], show_ylabels=False)\n",
     "plt.title(\"weight_concentration_prior = 10000\", fontsize=14)\n",
     "\n",
-    "save_fig(\"mixture_concentration_prior_diagram\")\n",
+    "save_fig(\"mixture_concentration_prior_plot\")\n",
     "plt.show()"
    ]
   },
@@ -3037,7 +3037,7 @@
     "plt.subplot(122)\n",
     "plot_gaussian_mixture(bgm, X_moons, show_ylabels=False)\n",
     "\n",
-    "save_fig(\"moons_vs_bgm_diagram\")\n",
+    "save_fig(\"moons_vs_bgm_plot\")\n",
     "plt.show()"
    ]
   },
@@ -3139,7 +3139,7 @@
     "plt.grid(True)\n",
     "plt.title(r\"$\\log \\, \\mathcal{L}(\\theta|x=2.5)$\", fontsize=14)\n",
     "\n",
-    "save_fig(\"likelihood_function_diagram\")\n",
+    "save_fig(\"likelihood_function_plot\")\n",
     "plt.show()"
    ]
   },