v20240317.4

gfmei · Mar 17, 2024 · 11f665e · 11f665e
1 parent 6bbcd53
commit 11f665e
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Showing 4 changed files with 77 additions and 62 deletions.
diff --git a/codes/02_Graph_Science/code01.ipynb b/codes/02_Graph_Science/code01.ipynb
diff --git a/codes/02_Graph_Science/code02.ipynb b/codes/02_Graph_Science/code02.ipynb
@@ -27,7 +27,8 @@
     "    print(path_to_file)\n",
     "    # change current path to the folder containing \"path_to_file\"\n",
     "    os.chdir(path_to_file)\n",
-    "    !pwd"
+    "    !pwd\n",
+    "    "
    ]
   },
   {
@@ -81,7 +82,7 @@
     "\n",
     "# Remove warnings\n",
     "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")"
+    "warnings.filterwarnings(\"ignore\")\n"
    ]
   },
   {
@@ -102,7 +103,7 @@
     "mat = scipy.io.loadmat('datasets/discoboy_network.mat')\n",
     "X = mat['X']\n",
     "W = mat['W']\n",
-    "print(X.shape,W.shape)"
+    "print(X.shape,W.shape)\n"
    ]
   },
   {
@@ -126,7 +127,7 @@
     "plt.figure(10)\n",
     "size_vertex_plot = 20.\n",
     "plt.scatter(X[:,0], X[:,1], s=size_vertex_plot*np.ones(X.shape[0]), color=pyplot.jet())\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -139,7 +140,7 @@
     "L = graph_laplacian(W)\n",
     "\n",
     "# Compute modes of variations of graph system = Fourier functions\n",
-    "lamb, U = scipy.sparse.linalg.eigsh(L, k=9, which='SM')"
+    "lamb, U = scipy.sparse.linalg.eigsh(L, k=9, which='SM')\n"
    ]
   },
   {
@@ -243,7 +244,8 @@
     "for i in range(1,10):\n",
     "    plt.figure(str(10+i))\n",
     "    plt.scatter(X[:,0], X[:,1], c=U[:,i-1], s=size_vertex_plot*np.ones(X.shape[0]), color=pyplot.jet())\n",
-    "    plt.show()"
+    "    plt.show()\n",
+    "    "
    ]
   },
   {
@@ -280,7 +282,7 @@
     "plt.figure(20)\n",
     "size_vertex_plot = 20.\n",
     "plt.scatter(X[:,0], X[:,1], s=size_vertex_plot*np.ones(X.shape[0]), color=pyplot.jet())\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -390,7 +392,8 @@
     "for i in range(1,10):\n",
     "    plt.figure(str(20+i))\n",
     "    plt.scatter(X[:,0], X[:,1], c=U[:,i-1], s=size_vertex_plot*np.ones(X.shape[0]), color=pyplot.jet())\n",
-    "    plt.show()"
+    "    plt.show()\n",
+    "    "
    ]
   },
   {

diff --git a/codes/02_Graph_Science/code03.ipynb b/codes/02_Graph_Science/code03.ipynb
@@ -27,7 +27,8 @@
     "    print(path_to_file)\n",
     "    # change current path to the folder containing \"path_to_file\"\n",
     "    os.chdir(path_to_file)\n",
-    "    !pwd"
+    "    !pwd\n",
+    "    "
    ]
   },
   {
@@ -81,7 +82,7 @@
     "\n",
     "# Remove warnings\n",
     "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")"
+    "warnings.filterwarnings(\"ignore\")\n"
    ]
   },
   {
@@ -120,7 +121,7 @@
     "size_vertex_plot = 20.\n",
     "plt.scatter(X[:,0], X[:,1], s=size_vertex_plot*np.ones(n), c=C, color=pyplot.jet())\n",
     "plt.title('Visualization of two-moon datase (with ground truth), DIMENTIONALITY= ' + str(dim))\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -154,7 +155,7 @@
     "plt.figure(31)\n",
     "plt.scatter(Xzc[:,0], Xzc[:,1], s=size_vertex_plot*np.ones(n), c=C, color=pyplot.jet())\n",
     "plt.title('Center the data')\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -188,7 +189,7 @@
     "plt.figure(32)\n",
     "plt.scatter(Xnvar[:,0], Xnvar[:,1], s=size_vertex_plot*np.ones(n), c=C, color=pyplot.jet())\n",
     "plt.title('Normalize the variance')\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -222,7 +223,7 @@
     "plt.figure(33)\n",
     "plt.scatter(Xl2proj[:,0], Xl2proj[:,1], s=size_vertex_plot*np.ones(n), c=C, color=pyplot.jet())\n",
     "plt.title('Projection on the L2-ball')\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -282,7 +283,7 @@
     "#W.setdiag(0)\n",
     "\n",
     "print(W.shape)\n",
-    "print(W.nnz)"
+    "print(W.nnz)\n"
    ]
   },
   {
@@ -320,7 +321,7 @@
     "\n",
     "fig.tight_layout()\n",
     "\n",
-    "fig.show()"
+    "fig.show()\n"
    ]
   },
   {
@@ -342,7 +343,7 @@
    "source": [
     "plt.figure(50)\n",
     "plt.spy(W,precision=0.01, markersize=1, color=pyplot.jet())\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -360,7 +361,7 @@
    ],
    "source": [
     "Cncut,acc = compute_ncut(W, C, 2)\n",
-    "print(acc)"
+    "print(acc)\n"
    ]
   },
   {
@@ -383,7 +384,7 @@
     "plt.figure(75)\n",
     "plt.scatter(X[:,0], X[:,1], s=size_vertex_plot*np.ones(n), c=Cncut, color=pyplot.jet())\n",
     "plt.title('Clustering result with EUCLIDEAN distance, ACCURACY= '+ str(acc))\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -448,7 +449,7 @@
     "#W.setdiag(0)\n",
     "\n",
     "print(W.shape)\n",
-    "print(W.nnz)"
+    "print(W.nnz)\n"
    ]
   },
   {
@@ -486,7 +487,7 @@
     "\n",
     "fig.tight_layout()\n",
     "\n",
-    "fig.show()"
+    "fig.show()\n"
    ]
   },
   {
@@ -508,7 +509,7 @@
    "source": [
     "plt.figure(70)\n",
     "plt.spy(W,precision=0.01, markersize=1, color=pyplot.jet())\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {
@@ -526,7 +527,7 @@
    ],
    "source": [
     "Cncut,acc = compute_ncut(W, C, 2)\n",
-    "print(acc)"
+    "print(acc)\n"
    ]
   },
   {
@@ -549,7 +550,7 @@
     "plt.figure(77)\n",
     "plt.scatter(X[:,0], X[:,1], s=size_vertex_plot*np.ones(n), c=Cncut, color=pyplot.jet())\n",
     "plt.title('Clustering result with EUCLIDEAN distance, ACCURACY= '+ str(acc))\n",
-    "plt.show()"
+    "plt.show()\n"
    ]
   },
   {