editing example notebook

ezarogia · Sep 27, 2022 · 4744d36 · 4744d36
1 parent c0ba34f
commit 4744d36
Showing 1 changed file with 14 additions and 35 deletions.
diff --git a/examples/cofrnet/cofrnet_example.ipynb b/examples/cofrnet/cofrnet_example.ipynb
@@ -76,13 +76,12 @@
     "                order 13 interactions. \n",
     "'''\n",
     "network_depth = 13\n",
-    "input_size = 30\n",
-    "output_size = 2 \n",
+    "input_size = 40\n",
+    "output_size = 3\n",
     "cofrnet_version = \"diag_ladder_of_ladder_combined\"\n",
-    "#Create CoFrNet\n",
-    "model = CoFrNet_Model(generate_connections(network_depth, \n",
-    "                                            input_size, \n",
-    "                                            output_size, \n",
+    "model = CoFrNet_Model(generate_connections(network_depth,\n",
+    "                                            input_size,\n",
+    "                                            output_size,\n",
     "                                            cofrnet_version))\n"
    ]
   },
@@ -99,37 +98,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = load_breast_cancer()\n",
-    "X = torch.from_numpy(data['data'])\n",
-    "y = torch.from_numpy(data['target'])\n",
-    "from sklearn.preprocessing import LabelEncoder\n",
-    "le = LabelEncoder()\n",
-    "y = le.fit_transform(y)\n",
-    "from sklearn.preprocessing import StandardScaler\n",
-    "sc = MinMaxScaler(feature_range=(0,1))\n",
-    "X = sc.fit_transform(X)\n",
-    "X.argmax()\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "X_train, X_test, y_train, y_test = train_test_split(X,\n",
-    "                                                y,\n",
-    "                                                test_size = 0.3,\n",
-    "                                                random_state = 100,\n",
-    "                                                shuffle = True)\n",
-    "X_train, X_val, y_train, y_val = train_test_split(X_train,\n",
-    "                                                y_train,\n",
-    "                                                test_size=0.05,\n",
-    "                                                random_state=100,\n",
-    "                                                shuffle = True)\n",
-    "#CONVERTING TO TENSOR\n",
-    "tensor_x_train = torch.Tensor(X_train)\n",
-    "tensor_x_val = torch.Tensor(X_val)\n",
-    "tensor_x_test = torch.Tensor(X_test)\n",
-    "tensor_y_val = torch.Tensor(y_val).long()\n",
-    "tensor_y_train = torch.Tensor(y_train).long()\n",
-    "tensor_y_test = torch.Tensor(y_test).long()\n",
+    "first_column_csv = 0\n",
+    "last_column_csv = -1\n",
+    "\n",
+    "\n",
+    "web_link = 'http://www.dropbox.com/s/qtdv1teptf097zl/waveformnoise.csv?dl=1'\n",
+    "tensor_x_train, tensor_y_train, tensor_x_val, tensor_y_val, tensor_x_test, y_test = process_data(first_column_csv = first_column_csv, \n",
+    "                                                                                                    last_column_csv = last_column_csv, \n",
+    "                                                                                                    web_link=web_link)\n",
     "\n",
     "train_dataset = OnlyTabularDataset(tensor_x_train, \n",
-    "                                tensor_y_train)\n",
+    "                                    tensor_y_train)\n",
     "\n",
     "batch_size = 100\n",
     "dataloader = DataLoader(train_dataset, batch_size) "