shallow-training/nncw.ipynb

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   "execution_count": 41,
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     "status": "ok",
     "timestamp": 1615991459232,
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     "user_tz": 0
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    "id": "TGIxH9Tmt5zp"
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "import tensorflow.keras.optimizers as tf_optim\n",
    "tf.get_logger().setLevel('ERROR')\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "import random\n",
    "import pickle\n",
    "import json\n",
    "import math\n",
    "import datetime\n",
    "import os\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "fig_dpi = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fksHv5rXACEX"
   },
   "source": [
    "# Neural Network Training\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l4zqVWyRAM0Z"
   },
   "source": [
    "## Load Dataset\n",
    "\n",
    "Read CSVs dumped from MatLab and parse into Pandas DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 331
    },
    "executionInfo": {
     "elapsed": 2441,
     "status": "ok",
     "timestamp": 1615991459234,
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      "displayName": "Andy Pack",
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     },
     "user_tz": 0
    },
    "id": "Hj5l_tdZuYh7",
    "outputId": "fbfa9406-f662-4ebc-8ba2-67950714627c"
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   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Clump thickness</th>\n",
       "      <th>Uniformity of cell size</th>\n",
       "      <th>Uniformity of cell shape</th>\n",
       "      <th>Marginal adhesion</th>\n",
       "      <th>Single epithelial cell size</th>\n",
       "      <th>Bare nuclei</th>\n",
       "      <th>Bland chomatin</th>\n",
       "      <th>Normal nucleoli</th>\n",
       "      <th>Mitoses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "      <td>699.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.441774</td>\n",
       "      <td>0.313448</td>\n",
       "      <td>0.320744</td>\n",
       "      <td>0.280687</td>\n",
       "      <td>0.321602</td>\n",
       "      <td>0.354363</td>\n",
       "      <td>0.343777</td>\n",
       "      <td>0.286695</td>\n",
       "      <td>0.158941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.281574</td>\n",
       "      <td>0.305146</td>\n",
       "      <td>0.297191</td>\n",
       "      <td>0.285538</td>\n",
       "      <td>0.221430</td>\n",
       "      <td>0.360186</td>\n",
       "      <td>0.243836</td>\n",
       "      <td>0.305363</td>\n",
       "      <td>0.171508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Clump thickness  Uniformity of cell size  Uniformity of cell shape  \\\n",
       "count       699.000000               699.000000                699.000000   \n",
       "mean          0.441774                 0.313448                  0.320744   \n",
       "std           0.281574                 0.305146                  0.297191   \n",
       "min           0.100000                 0.100000                  0.100000   \n",
       "25%           0.200000                 0.100000                  0.100000   \n",
       "50%           0.400000                 0.100000                  0.100000   \n",
       "75%           0.600000                 0.500000                  0.500000   \n",
       "max           1.000000                 1.000000                  1.000000   \n",
       "\n",
       "       Marginal adhesion  Single epithelial cell size  Bare nuclei  \\\n",
       "count         699.000000                   699.000000   699.000000   \n",
       "mean            0.280687                     0.321602     0.354363   \n",
       "std             0.285538                     0.221430     0.360186   \n",
       "min             0.100000                     0.100000     0.100000   \n",
       "25%             0.100000                     0.200000     0.100000   \n",
       "50%             0.100000                     0.200000     0.100000   \n",
       "75%             0.400000                     0.400000     0.500000   \n",
       "max             1.000000                     1.000000     1.000000   \n",
       "\n",
       "       Bland chomatin  Normal nucleoli     Mitoses  \n",
       "count      699.000000       699.000000  699.000000  \n",
       "mean         0.343777         0.286695    0.158941  \n",
       "std          0.243836         0.305363    0.171508  \n",
       "min          0.100000         0.100000    0.100000  \n",
       "25%          0.200000         0.100000    0.100000  \n",
       "50%          0.300000         0.100000    0.100000  \n",
       "75%          0.500000         0.400000    0.100000  \n",
       "max          1.000000         1.000000    1.000000  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('features.csv', header=None).T\n",
    "data.columns = ['Clump thickness', 'Uniformity of cell size', 'Uniformity of cell shape', 'Marginal adhesion', 'Single epithelial cell size', 'Bare nuclei', 'Bland chomatin', 'Normal nucleoli', 'Mitoses']\n",
    "labels = pd.read_csv('targets.csv', header=None).T\n",
    "labels.columns = ['Benign', 'Malignant']\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "executionInfo": {
     "elapsed": 2436,
     "status": "ok",
     "timestamp": 1615991459236,
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      "displayName": "Andy Pack",
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     },
     "user_tz": 0
    },
    "id": "qc1Mku6h041u",
    "outputId": "94e38c34-0419-4a02-ac8c-17bbc83f777b"
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Benign</th>\n",
       "      <th>Malignant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "   Benign  Malignant\n",
       "0       1          0\n",
       "1       1          0\n",
       "2       1          0\n",
       "3       0          1\n",
       "4       1          0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h9QsJjWEMbLu"
   },
   "source": [
    "### Explore Dataset\n",
    "\n",
    "The classes are uneven in their occurences, stratify when splitting later on"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2430,
     "status": "ok",
     "timestamp": 1615991459237,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "rjjiSYAZMa4k",
    "outputId": "ae0c3772-00be-4f2b-80d2-9cd62a6b6e08"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Benign       458\n",
       "Malignant    241\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels.astype(bool).sum(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E9lVYI14AUMf"
   },
   "source": [
    "## Split Dataset\n",
    "\n",
    "Using a 50/50 split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "executionInfo": {
     "elapsed": 2604,
     "status": "ok",
     "timestamp": 1615991459418,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "L83Ae5l9wM35"
   },
   "outputs": [],
   "source": [
    "data_train, data_test, labels_train, labels_test = train_test_split(data, labels, test_size=0.5\n",
    "#                                                                     , stratify=labels\n",
    "                                                                   )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Qf2U199fNjmJ"
   },
   "source": [
    "## Generate & Retrieve Model\n",
    "\n",
    "Get a shallow model with a single hidden layer of varying nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "executionInfo": {
     "elapsed": 2598,
     "status": "ok",
     "timestamp": 1615991459419,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "SgoQ-NjWB0T5"
   },
   "outputs": [],
   "source": [
    "def get_model(hidden_nodes=9, activation=lambda: 'sigmoid', weight_init=lambda: 'glorot_uniform'):\n",
    "    layers = [tf.keras.layers.InputLayer(input_shape=(9,), name='Input'), \n",
    "              tf.keras.layers.Dense(hidden_nodes, activation=activation(), kernel_initializer=weight_init(), name='Hidden'), \n",
    "              tf.keras.layers.Dense(2, activation='softmax', kernel_initializer=weight_init(), name='Output')]\n",
    "\n",
    "    model = tf.keras.models.Sequential(layers)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get a Keras Tensorboard callback for dumping data for later analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tensorboard_callback(path='tensorboard-logs', prefix=''):\n",
    "    return tf.keras.callbacks.TensorBoard(\n",
    "        log_dir=os.path.normpath(os.path.join(path, prefix + datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\"))), histogram_freq=1\n",
    "    ) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QT5B9PTUN3pj"
   },
   "source": [
    "# Example Training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mQGAUtIPAd6e"
   },
   "source": [
    "## Define Model\n",
    "\n",
    "Variable number of hidden nodes. All using 9D outputs except the last layer which is 2D for binary classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 7889,
     "status": "ok",
     "timestamp": 1615991464716,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "fYA34P0Vu_pX",
    "outputId": "aded18b8-aa7f-4362-a614-837c8a0f526f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_2 (Dense)              (None, 9)                 90        \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 2)                 20        \n",
      "=================================================================\n",
      "Total params: 110\n",
      "Trainable params: 110\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = get_model(9)\n",
    "model.compile('sgd', loss='categorical_crossentropy', metrics=['accuracy'])\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KZSwFe-AAs1y"
   },
   "source": [
    "## Train Model\n",
    "\n",
    "Example 10 epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11304,
     "status": "ok",
     "timestamp": 1615991468137,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "s8U9Atu3zelS",
    "outputId": "8439e8d2-7a5d-495f-a192-a34f01e95bfa"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "11/11 [==============================] - 1s 2ms/step - loss: 0.6257 - accuracy: 0.6607\n",
      "Epoch 2/5\n",
      "11/11 [==============================] - 0s 3ms/step - loss: 0.6226 - accuracy: 0.6651\n",
      "Epoch 3/5\n",
      "11/11 [==============================] - 0s 2ms/step - loss: 0.6326 - accuracy: 0.6424\n",
      "Epoch 4/5\n",
      "11/11 [==============================] - 0s 3ms/step - loss: 0.6158 - accuracy: 0.6696\n",
      "Epoch 5/5\n",
      "11/11 [==============================] - 0s 2ms/step - loss: 0.6228 - accuracy: 0.6534\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x2cd249f3400>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(data_train.to_numpy(), labels_train.to_numpy(), epochs=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11294,
     "status": "ok",
     "timestamp": 1615991468137,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "VnUEJdXovzi-",
    "outputId": "02075086-352c-4a23-fac5-ad54d11e0e35"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['loss', 'accuracy']"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.metrics_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11285,
     "status": "ok",
     "timestamp": 1615991468138,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "r0vxP3Ah42ib",
    "outputId": "061113ba-52db-4fbe-c7f9-b5d3d85438ed"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(), dtype=float32, numpy=0.6561605>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.metrics[1].result()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z7bn8pKTAynt",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "# Experiment 1\n",
    "\n",
    "The below function runs an iteration of layer/epoch investigations.\n",
    "Returns the amount of layers/epochs used as well as the results and the model.\n",
    "\n",
    "Using cancer dataset (as in E2) and 'trainscg' or an optimiser of your choice, vary nodes and epochs (that is using early stopping for epochs) over suitable range, to find optimal choice in terms of classification test error rate of node/epochs for 50/50% random train/test split (no validation set). It is suggested that you initially try epochs = [ 1 2 4 8 16 32 64], nodes = [2 8 32], so there would be 21 node/epoch combinations. \n",
    "\n",
    "(Hint1: from the 'advanced script' in E2, nodes can be changed to xx, with hiddenLayerSize = xx; and epochs changed to xx by addingnet. trainParam.epochs = xx; placed afternet = patternnet(hiddenLayerSize, trainFcn); --see 'trainscg' help documentation for changing epochs). \n",
    "\n",
    "Repeat each of the 21 node/epoch combinations at least thirty times, with different 50/50 split and take average and report classification error rate and standard deviation (std). Graph classification train and test error rate and std as node-epoch changes, that is plot error rate vs epochs for different number of nodes. Report the optimal value for test error rate and associated node/epoch values. \n",
    "\n",
    "(Hint2: as epochs increases you can expect the test error rate to reach a minimum and then start increasing, you may need to set the stopping criteria to achieve the desired number of epochs - Hint 3: to find classification error rates for train and test set, you need to check the code from E2, to determine how you may obtain the train and test set patterns)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "executionInfo": {
     "elapsed": 11274,
     "status": "ok",
     "timestamp": 1615991468138,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "mYWhCSW4A57V",
    "tags": [
     "exp1",
     "exp-func"
    ]
   },
   "outputs": [],
   "source": [
    "# hidden_nodes = [2, 8, 16, 24, 32]\n",
    "# epochs = [1, 2, 4, 8, 16, 32, 64, 100, 150, 200]\n",
    "hidden_nodes = [2, 8, 16]\n",
    "epochs = [1, 2, 4, 8]\n",
    "\n",
    "def evaluate_parameters(hidden_nodes=hidden_nodes, \n",
    "                        epochs=epochs, \n",
    "                        batch_size=128,\n",
    "                        optimizer=lambda: 'sgd',\n",
    "                        weight_init=lambda: 'glorot_uniform',\n",
    "                        loss=lambda: 'categorical_crossentropy',\n",
    "                        metrics=['accuracy'],\n",
    "                        callbacks=None,\n",
    "                        validation_split=None,\n",
    "\n",
    "                        verbose=0,\n",
    "                        print_params=True,\n",
    "                        return_model=True,\n",
    "                        run_eagerly=False,\n",
    "                        tboard=True,\n",
    "                        \n",
    "                        dtrain=data_train,\n",
    "                        dtest=data_test,\n",
    "                        ltrain=labels_train,\n",
    "                        ltest=labels_test):\n",
    "    for idx1, hn in enumerate(hidden_nodes):\n",
    "        for idx2, e in enumerate(epochs):\n",
    "            if print_params:\n",
    "                print(f\"Nodes: {hn}, Epochs: {e}\")\n",
    "\n",
    "            model = get_model(hn, weight_init=weight_init)\n",
    "            model.compile(\n",
    "                optimizer=optimizer(),\n",
    "                loss=loss(),\n",
    "                metrics=metrics,\n",
    "                run_eagerly=run_eagerly\n",
    "                )\n",
    "            \n",
    "            if tboard:\n",
    "                if callbacks is not None:\n",
    "                    cb = [i() for i in callbacks] + [tensorboard_callback(prefix=f'exp1-{hn}-{e}-')]\n",
    "                else:\n",
    "                    cb = [tensorboard_callback(prefix=f'exp1-{hn}-{e}-')]\n",
    "            \n",
    "            response = {\"nodes\": hn, \n",
    "                        \"epochs\": e,\n",
    "                        ##############\n",
    "                        ##   TRAIN\n",
    "                        ##############\n",
    "                        \"history\": model.fit(dtrain.to_numpy(), \n",
    "                                             ltrain.to_numpy(), \n",
    "                                             epochs=e, \n",
    "                                             verbose=verbose,\n",
    "                                             \n",
    "                                             callbacks=cb,\n",
    "                                             validation_split=validation_split).history,\n",
    "                        ##############\n",
    "                        ##   TEST\n",
    "                        ##############\n",
    "                        \"results\": model.evaluate(dtest.to_numpy(), \n",
    "                                                 ltest.to_numpy(),\n",
    "                                                 callbacks=cb,\n",
    "                                                 batch_size=batch_size, \n",
    "                                                 verbose=verbose),\n",
    "                        \"optimizer\": model.optimizer.get_config(),\n",
    "                        \"loss\": model.loss,\n",
    "                        \"model_config\": json.loads(model.to_json())\n",
    "                       }\n",
    "\n",
    "            if return_model:\n",
    "                response[\"model\"] = model\n",
    "\n",
    "            yield response"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "r-63V9qb-i4w",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "## Single Iteration\n",
    "Run a single iteration of epoch/layer investigations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 313592,
     "status": "ok",
     "timestamp": 1615991770468,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "ZmGFkE9y8E4H",
    "outputId": "243fb136-bc07-4438-afb7-f2d21758168d",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes: 2, Epochs: 1\n",
      "Nodes: 2, Epochs: 2\n",
      "Nodes: 2, Epochs: 4\n",
      "Nodes: 2, Epochs: 8\n",
      "Nodes: 8, Epochs: 1\n",
      "Nodes: 8, Epochs: 2\n",
      "Nodes: 8, Epochs: 4\n",
      "Nodes: 8, Epochs: 8\n",
      "Nodes: 16, Epochs: 1\n",
      "Nodes: 16, Epochs: 2\n",
      "Nodes: 16, Epochs: 4\n",
      "Nodes: 16, Epochs: 8\n"
     ]
    }
   ],
   "source": [
    "# es = tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', patience = 5)\n",
    "single_results = list(evaluate_parameters(return_model=False, validation_split=0.2\n",
    "                                          , optimizer = lambda: tf.keras.optimizers.SGD(learning_rate=0.5, momentum=0.5)\n",
    "#                                           , callbacks=[es]\n",
    "                                         ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mdWK3-M6SK8_",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Train/Test Curves\n",
    "\n",
    "For a single test from the set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 517
    },
    "executionInfo": {
     "elapsed": 314527,
     "status": "ok",
     "timestamp": 1615991771417,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "F9Xre1o6SesD",
    "outputId": "d6b817aa-58cd-4510-807f-e5e6bcf62f18",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes: 2, Epochs: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1050x490 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "single_result = random.choice([i for i in single_results if i[\"epochs\"] > 1])\n",
    "single_history = single_result[\"history\"]\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(15,7))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "################\n",
    "##    LOSS\n",
    "################\n",
    "ax = axes[0]\n",
    "ax.set_title(\"Training vs Validation Loss\")\n",
    "ax.plot(single_history['loss'], label=\"train\", lw=2)\n",
    "ax.plot(single_history['val_loss'], label=\"validation\", lw=2, c=(1,0,0))\n",
    "ax.set_xlabel(\"Epochs\")\n",
    "ax.grid()\n",
    "ax.legend()\n",
    "\n",
    "################\n",
    "##  ACCURACY\n",
    "################\n",
    "ax = axes[1]\n",
    "ax.set_title(\"Training vs Validation Accuracy\")\n",
    "ax.plot(single_history['accuracy'], label=\"train\", lw=2)\n",
    "ax.plot(single_history['val_accuracy'], label=\"validation\", lw=2, c=(1,0,0))\n",
    "ax.set_xlabel(\"Epochs\")\n",
    "# ax.set_ylim(0, 1)\n",
    "ax.grid()\n",
    "ax.legend()\n",
    "\n",
    "print(f\"Nodes: {single_result['nodes']}, Epochs: {single_result['epochs']}\")\n",
    "# plt.tight_layout()\n",
    "# plt.savefig('fig.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0IQ7HfJCSDud",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Accuracy Surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 705
    },
    "executionInfo": {
     "elapsed": 315450,
     "status": "ok",
     "timestamp": 1615991772345,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "X3MWHLxJElbc",
    "outputId": "134671d0-bfd3-4ee6-aa02-1a2a5b23f3ca",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x350 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, Y = np.meshgrid(epochs, hidden_nodes)\n",
    "\n",
    "shaped_result = np.reshape([r[\"results\"][1] for r in single_results], \n",
    "                           (len(hidden_nodes), len(epochs)))\n",
    "\n",
    "fig = plt.figure(figsize=(8, 5))\n",
    "fig.set_dpi(fig_dpi)\n",
    "ax = plt.axes(projection='3d')\n",
    "\n",
    "surf = ax.plot_surface(X, Y, shaped_result, cmap='viridis')\n",
    "ax.set_title('Model test accuracy over different training periods with different numbers of nodes')\n",
    "ax.set_xlabel('Epochs')\n",
    "ax.set_ylabel('Hidden Nodes')\n",
    "ax.set_zlabel('Accuracy')\n",
    "ax.view_init(30, -110)\n",
    "# ax.set_zlim([0, 1])\n",
    "fig.colorbar(surf, shrink=0.3, aspect=6)\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('fig.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C793_RHvSGai",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Error Rate Curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 668
    },
    "executionInfo": {
     "elapsed": 316211,
     "status": "ok",
     "timestamp": 1615991773109,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "tpClZMptrq-q",
    "outputId": "f9fe93f9-7b67-4772-83e4-9e3567fd9318",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x350 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 5))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for layer in hidden_nodes:\n",
    "    plt.plot(epochs, \n",
    "             1 - np.array([i[\"results\"][1] \n",
    "                  for i in single_results \n",
    "                  if i[\"nodes\"] == layer]), \n",
    "             label=f'{layer} Nodes')\n",
    "\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.title(\"Test error rates for a single iteration of different epochs and hidden node training\")\n",
    "plt.xlabel(\"Epochs\")\n",
    "plt.ylabel(\"Error Rate\")\n",
    "plt.ylim(0)\n",
    "\n",
    "# plt.savefig('fig.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7mJaKjlCxEkt",
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "## Multiple Iterations\n",
    "\n",
    "Run multiple iterations of the epoch/layer investigations and average\n",
    "\n",
    "### CSV Results\n",
    "\n",
    "| test | learning rate | momentum | batch size | hidden nodes | epochs |\n",
    "| --- | --- | --- | --- | --- | --- |\n",
    "|1|0.01|0|128|2, 8, 12, 16, 24, 32, 64, 128, 256|1, 2, 4, 8, 16, 32, 64, 100, 150, 200|\n",
    "|2|0.5|0.1|128|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "|3|0.2|0.05|128|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "|4|0.08|0.04|128|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "|5|0.08|0|128|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "|6|0.06|0|128|1, 2, 3, 4, 5, 6, 7, 8|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "|7|0.06|0|35|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100|\n",
    "\n",
    "### Pickle Results\n",
    "\n",
    "| test | learning rate | momentum | batch size | hidden nodes | epochs | statified |\n",
    "| --- | --- | --- | --- | --- | --- | --- |\n",
    "|1|0.01|0|128|2, 8, 12, 16, 24, 32, 64, 128, 256|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| |\n",
    "|2|0.5|0.1|128|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100| |\n",
    "|3|1|0.3|20|2, 8, 12, 16, 24, 32, 64, 128|1, 2, 4, 8, 16, 32, 64, 100| |\n",
    "|4|0.6|0.1|20|2, 8, 16, 24, 32|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| |\n",
    "|5|0.05|0.01|20|2, 8, 16, 24, 32|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| |\n",
    "|6|1.5|0.5|20|2, 8, 16, 24, 32|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| |\n",
    "|2-1|0.01|0|35|2, 8, 16, 24, 32|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| n |\n",
    "|2-2|0.1|0|35|2, 16, 32|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-3|0.15|0|35|2, 16, 32|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-4|0.08|0.9|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-5|0.08|0.2|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-6|0.01|0.1|35|2, 8, 16, 24, 32|1, 2, 4, 8, 16, 32, 64, 100, 150, 200| n |\n",
    "|2-7|0.01|0.9|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-8|0.01|0.5|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-9|0.01|0.3|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-10|0.01|0.7|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-11|0.01|0.0|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| n |\n",
    "|2-12|0.1|0.0|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| y |\n",
    "|2-13|0.5|0.0|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| y |\n",
    "|2-14|0.05|0.0|35|1, 2, 8, 16, 32, 64|1, 2, 4, 8, 16, 32, 64, 100| y |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "id": "-lsKo4BCP3yw",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1/30\n",
      "Iteration 2/30\n",
      "Iteration 3/30\n",
      "Iteration 4/30\n",
      "Iteration 5/30\n",
      "Iteration 6/30\n",
      "Iteration 7/30\n",
      "Iteration 8/30\n",
      "Iteration 9/30\n",
      "Iteration 10/30\n",
      "Iteration 11/30\n",
      "Iteration 12/30\n",
      "Iteration 13/30\n",
      "Iteration 14/30\n",
      "Iteration 15/30\n",
      "Iteration 16/30\n",
      "Iteration 17/30\n",
      "Iteration 18/30\n",
      "Iteration 19/30\n",
      "Iteration 20/30\n",
      "Iteration 21/30\n",
      "Iteration 22/30\n",
      "Iteration 23/30\n",
      "Iteration 24/30\n",
      "Iteration 25/30\n",
      "Iteration 26/30\n",
      "Iteration 27/30\n",
      "Iteration 28/30\n",
      "Iteration 29/30\n",
      "Iteration 30/30\n"
     ]
    }
   ],
   "source": [
    "multi_param_results = list()\n",
    "multi_iterations = 30\n",
    "for i in range(multi_iterations):\n",
    "    print(f\"Iteration {i+1}/{multi_iterations}\")\n",
    "    data_train, data_test, labels_train, labels_test = train_test_split(data, labels, test_size=0.5\n",
    "#                                                                         , stratify=labels\n",
    "                                                                       )\n",
    "    multi_param_results.append(list(evaluate_parameters(dtrain=data_train, \n",
    "                                                  dtest=data_test, \n",
    "                                                  ltrain=labels_train, \n",
    "                                                  ltest=labels_test,\n",
    "                                                  hidden_nodes=[2, 16, 32],\n",
    "                                                  epochs=[1, 2, 4, 8, 16, 32, 64, 100],\n",
    "                                                  optimizer=lambda: tf.keras.optimizers.SGD(learning_rate=0.15, momentum=0.0),\n",
    "                                                  weight_init=lambda: 'random_uniform',\n",
    "                                                  return_model=False,\n",
    "                                                  print_params=False,\n",
    "                                                  batch_size=35)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Accuracy Tensor\n",
    "\n",
    "Create a tensor for holding the accuracy results\n",
    "\n",
    "(Iterations x [Test/Train] x Number of nodes x Number of epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 Tests\n",
      "Nodes: [1, 2, 8, 16, 32, 64]\n",
      "Epochs: [1, 2, 4, 8, 16, 32, 64, 100]\n",
      "\n",
      "Loss: categorical_crossentropy\n",
      "LR: 0.05\n",
      "Momentum: 0.0\n"
     ]
    }
   ],
   "source": [
    "multi_param_epochs = sorted(list({i[\"epochs\"] for i in multi_param_results[0]}))\n",
    "multi_param_nodes = sorted(list({i[\"nodes\"] for i in multi_param_results[0]}))\n",
    "multi_param_iter = len(multi_param_results)\n",
    "\n",
    "accuracy_tensor = np.zeros((multi_param_iter, 2, len(multi_param_nodes), len(multi_param_epochs)))\n",
    "for iter_idx, iteration in enumerate(multi_param_results):\n",
    "    for single_test in iteration:\n",
    "        accuracy_tensor[iter_idx, :,\n",
    "                        multi_param_nodes.index(single_test['nodes']), \n",
    "                        multi_param_epochs.index(single_test['epochs'])] = [single_test[\"results\"][1], \n",
    "                                                                            single_test[\"history\"][\"accuracy\"][-1]]\n",
    "        \n",
    "mean_param_accuracy = np.mean(accuracy_tensor, axis=0)\n",
    "std_param_accuracy = np.std(accuracy_tensor, axis=0)\n",
    "\n",
    "print(f'{multi_param_iter} Tests')\n",
    "print(f'Nodes: {multi_param_nodes}')\n",
    "print(f'Epochs: {multi_param_epochs}')\n",
    "print()\n",
    "print(f'Loss: {multi_param_results[0][0][\"loss\"]}')\n",
    "print(f'LR: {multi_param_results[0][0][\"optimizer\"][\"learning_rate\"]:.3}')\n",
    "print(f'Momentum: {multi_param_results[0][0][\"optimizer\"][\"momentum\"]:.3}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "#### Export/Import Test Sets\n",
    "\n",
    "Export mean and standard deviations for retrieval and visualisation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [],
   "source": [
    "pickle.dump(multi_param_results, open(\"results/exp1-test2-3.p\", \"wb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [],
   "source": [
    "exp1_testname = 'exp1-test2-14'\n",
    "multi_param_results = pickle.load(open(f\"results/{exp1_testname}.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "np.savetxt(\"exp1-mean.csv\", mean_param_accuracy, delimiter=',')\n",
    "np.savetxt(\"exp1-std.csv\", std_param_accuracy, delimiter=',')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mean_param_accuracy = np.loadtxt(\"results/test1-exp1-mean.csv\", delimiter=',')\n",
    "std_param_accuracy = np.loadtxt(\"results/test1-exp1-std.csv\", delimiter=',')\n",
    "# multi_iterations = 30"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Best Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes: 32, Epochs: 100, 96.1% Accurate\n"
     ]
    }
   ],
   "source": [
    "best_param_accuracy_idx = np.unravel_index(np.argmax(mean_param_accuracy[0, :, :]), mean_param_accuracy.shape)\n",
    "best_param_accuracy = mean_param_accuracy[best_param_accuracy_idx]\n",
    "best_param_accuracy_nodes = multi_param_nodes[best_param_accuracy_idx[1]]\n",
    "best_param_accuracy_epochs = multi_param_epochs[best_param_accuracy_idx[2]]\n",
    "\n",
    "print(f'Nodes: {best_param_accuracy_nodes}, Epochs: {best_param_accuracy_epochs}, {best_param_accuracy * 100:.3}% Accurate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Test Accuracy Surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "executionInfo": {
     "elapsed": 2653358,
     "status": "aborted",
     "timestamp": 1615994110345,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "ZGJVhz6iJU-7",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, Y = np.meshgrid(multi_param_epochs, multi_param_nodes)\n",
    "\n",
    "# fig = plt.figure(figsize=(10, 5))\n",
    "fig = plt.figure()\n",
    "fig.set_dpi(fig_dpi)\n",
    "ax = plt.axes(projection='3d')\n",
    "\n",
    "surf = ax.plot_surface(X, Y, mean_param_accuracy[0, :, :], cmap='coolwarm')\n",
    "ax.set_title(f'Average Accuracy')\n",
    "ax.set_xlabel('Epochs')\n",
    "ax.set_ylabel('Hidden Nodes')\n",
    "ax.set_zlabel('Accuracy')\n",
    "ax.view_init(30, -110)\n",
    "# ax.set_zlim([0, 1])\n",
    "fig.colorbar(surf, shrink=0.3, aspect=6)\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig(f'graphs/{exp1_testname}-acc-surf.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Test Error Rate Curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "executionInfo": {
     "elapsed": 2653349,
     "status": "aborted",
     "timestamp": 1615994110347,
     "user": {
      "displayName": "Andy Pack",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GjA4K4ZhdArHXAFbAGr4n0aCv2HmyUpx4cy6zcUq34=s64",
      "userId": "16615063155528027547"
     },
     "user_tz": 0
    },
    "id": "Jrn3hKQAlGcc",
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(5, 4))\n",
    "# fig = plt.figure()\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for idx, (layer, std) in enumerate(zip(mean_param_accuracy[0, :, :], std_param_accuracy[0, :, :])):\n",
    "#     plt.errorbar(multi_param_epochs, 1 - layer, yerr=std, capsize=4, label=f'{multi_param_nodes[idx]} Nodes')\n",
    "    plt.plot(multi_param_epochs, 1 - layer, '-', label=f'{multi_param_nodes[idx]} Nodes', lw=2)\n",
    "\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.title(f\"Test error rates over hidden nodes\")\n",
    "plt.xlabel(\"Epochs\")\n",
    "plt.ylabel(\"Error Rate\")\n",
    "plt.ylim(0, 0.6)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'graphs/{exp1_testname}-error-rate-curves.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(5, 4))\n",
    "# fig = plt.figure()\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for idx, (layer, std) in enumerate(zip(mean_param_accuracy[0, :, :], std_param_accuracy[0, :, :])):\n",
    "#     plt.errorbar(multi_param_epochs, 1 - layer, yerr=std, capsize=4, label=f'{multi_param_nodes[idx]} Nodes')\n",
    "    plt.plot(multi_param_epochs, std, 'x-', label=f'{multi_param_nodes[idx]} Nodes', lw=2)\n",
    "\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.title(f\"Test error rate std. dev over hidden nodes\")\n",
    "plt.xlabel(\"Epochs\")\n",
    "plt.ylabel(\"Standard Deviation\")\n",
    "plt.ylim(0, 0.1)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'graphs/{exp1_testname}-error-rate-std.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "source": [
    "### Test/Train Error Over Nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(math.ceil(len(multi_param_nodes) / 2), 2, figsize=(6, 6*math.ceil(len(multi_param_nodes) / 2)/3))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for idx, (nodes, ax) in enumerate(zip(multi_param_nodes, axes.flatten())):\n",
    "    ax.set_title(f'Error Rates For {nodes} Nodes')\n",
    "#     ax.errorbar(multi_param_epochs, 1 - mean_param_accuracy[0, idx, :], fmt='x', ls='-', yerr=std_param_accuracy[0, idx, :], markersize=4, lw=1, label='Test', capsize=4, c=(0, 0, 1), ecolor=(0, 0, 1, 0.5))\n",
    "#     ax.errorbar(multi_param_epochs, 1 - mean_param_accuracy[1, idx, :], fmt='x', ls='-', yerr=std_param_accuracy[1, idx, :], markersize=4, lw=1, label='Train', capsize=4, c=(1, 0, 0), ecolor=(1, 0, 0, 0.5))\n",
    "    ax.plot(multi_param_epochs, 1 - mean_param_accuracy[0, idx, :], 'x', ls='-', lw=1, label='Test', c=(0, 0, 1))\n",
    "    ax.plot(multi_param_epochs, 1 - mean_param_accuracy[1, idx, :], 'x', ls='-', lw=1, label='Train', c=(1, 0, 0))\n",
    "    ax.set_ylim(0, np.round(np.max(1 - mean_param_accuracy + std_param_accuracy) + 0.05, 1))\n",
    "    ax.legend()\n",
    "    ax.grid()\n",
    "\n",
    "fig.tight_layout()\n",
    "fig.savefig(f'graphs/{exp1_testname}-test-train-error-rate.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "tags": [
     "exp1"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(math.ceil(len(multi_param_nodes) / 2), 2, figsize=(6, 6*math.ceil(len(multi_param_nodes) / 2)/3))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for idx, (nodes, ax) in enumerate(zip(multi_param_nodes, axes.flatten())):\n",
    "    ax.set_title(f'Error Rate Std Dev. For {nodes} Nodes')\n",
    "    ax.plot(multi_param_epochs, std_param_accuracy[0, idx, :], 'x', ls='-', lw=1, label='Test', c=(0, 0, 1))\n",
    "    ax.plot(multi_param_epochs, std_param_accuracy[1, idx, :], 'x', ls='-', lw=1, label='Train', c=(1, 0, 0))\n",
    "    ax.set_ylim(0, np.round(np.max(std_param_accuracy) + 0.05, 1))\n",
    "    ax.legend()\n",
    "    ax.grid()\n",
    "\n",
    "fig.tight_layout()\n",
    "fig.savefig(f'graphs/{exp1_testname}-test-train-error-rate-std.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eUPJuxUtVUc3",
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "# Experiment 2\n",
    "\n",
    "For cancer dataset, choose an appropriate value of node and epochs, based on Exp 1) and use ensemble of individual (base) classifiers with random starting weights and Majority Vote to see if performance improves - repeat the majority vote ensemble at least thirty times with different 50/50 split and average and graph (Each classifier in the ensemble sees the same training patterns). Repeat for a different odd number (prevents tied vote) of individual classifiers between 3 and 25, and comment on the result of individualclassifier accuracy vs ensemble accuracy as number of base classifiers varies. Consider changing the number of nodes/epochs (both less complex and more complex) to see if you obtain better performance, and comment on the result with respect to why the optimal node/epoch combination may be different for an ensemble compared with the base classifier, as in Exp 1). \n",
    "\n",
    "(Hint4: to implement majority vote you need to determine the predicted class labels -probably easier to implement yourself rather than use the ensemble matlab functions)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "tags": [
     "exp2",
     "exp-func"
    ]
   },
   "outputs": [],
   "source": [
    "num_models=[1, 3, 9, 15, 25]\n",
    "\n",
    "def evaluate_ensemble_vote(hidden_nodes=16, \n",
    "                           epochs=50, \n",
    "                           batch_size=128,\n",
    "                           learning_rates=None,\n",
    "                           optimizer=lambda: 'sgd',\n",
    "                           weight_init=lambda: 'glorot_uniform',\n",
    "                           loss=lambda: 'categorical_crossentropy',\n",
    "                           metrics=['accuracy'],\n",
    "                           callbacks=None,\n",
    "                           validation_split=None,\n",
    "                           round_predictions=True,\n",
    "\n",
    "                           nmodels=num_models,\n",
    "                           tboard=True,\n",
    "                           exp='2',\n",
    "\n",
    "                           verbose=0,\n",
    "                           print_params=True,\n",
    "                           return_model=True,\n",
    "\n",
    "                           dtrain=data_train,\n",
    "                           dtest=data_test,\n",
    "                           ltrain=labels_train,\n",
    "                           ltest=labels_test):\n",
    "    \n",
    "    for m in nmodels: # iterate over different ensemble sizes\n",
    "        if print_params:\n",
    "            print(f\"Models: {m}\")\n",
    "            \n",
    "        # response dict object for test stats\n",
    "        response = {\"epochs\": list(),\n",
    "                    \"num_models\": m}\n",
    "            \n",
    "        ###################\n",
    "        ##   GET MODELS\n",
    "        ###################\n",
    "        if isinstance(hidden_nodes, tuple): # for range of hidden nodes, calculate value per model\n",
    "            if m == 1:\n",
    "                # just average provided range\n",
    "                models = [get_model(int(np.mean(hidden_nodes)), weight_init=weight_init)]\n",
    "                response[\"nodes\"] = [int(np.mean(hidden_nodes))]\n",
    "                \n",
    "            else:\n",
    "                # use linspace to generate equally spaced nodes throughout range\n",
    "                models = [get_model(int(i), weight_init=weight_init) \n",
    "                          for i in np.linspace(*hidden_nodes, num=m)]\n",
    "                response[\"nodes\"] = [int(i) for i in np.linspace(*hidden_nodes, num=m)]\n",
    "        \n",
    "        elif hidden_nodes == 'm':\n",
    "            # incrementing mode, number of nodes ranges from 1 to m\n",
    "            # more nodes in larger ensembles\n",
    "            models = [get_model(i+1, weight_init=weight_init) for i in range(m)]\n",
    "            response[\"nodes\"] = [i+1 for i in range(m)]\n",
    "        else: \n",
    "            # not a range of epochs, just set to given value\n",
    "            models = [get_model(hidden_nodes, weight_init=weight_init) for _ in range(m)]\n",
    "            response[\"nodes\"] = hidden_nodes\n",
    "\n",
    "        ######################\n",
    "        ##   COMPILE MODELS\n",
    "        ######################\n",
    "        if learning_rates is None:\n",
    "            # default, use provided optimiser\n",
    "            for model in models:        \n",
    "                model.compile(\n",
    "                    optimizer=optimizer(),\n",
    "                    loss=loss(),\n",
    "                    metrics=metrics\n",
    "                    )     \n",
    "        else:\n",
    "            # ignore provided optimiser, use SGD with a range of learning rates\n",
    "            if isinstance(learning_rates, tuple):\n",
    "                lr_range = np.linspace(*learning_rates, num=m)\n",
    "            elif learning_rates == '+':\n",
    "                # incrementing mode, scale with size of ensemble\n",
    "                lr_range = [0.01 * (i + 1) for i in range(m)]\n",
    "                \n",
    "            for model, lr in zip(models, lr_range):        \n",
    "                model.compile(\n",
    "                    optimizer=tf.keras.optimizers.SGD(learning_rate=lr),\n",
    "                    loss=loss(),\n",
    "                    metrics=metrics\n",
    "                    )\n",
    "        \n",
    "        if tboard:\n",
    "            if callbacks is not None:\n",
    "                cb = [i() for i in callbacks] + [tensorboard_callback(prefix=f'exp{exp}-{m}-')]\n",
    "            else:\n",
    "                cb = [tensorboard_callback(prefix=f'exp{exp}-{m}-')]\n",
    "        \n",
    "        ###################\n",
    "        ##  TRAIN MODELS\n",
    "        ###################\n",
    "        histories = list()\n",
    "        for idx, model in enumerate(models):\n",
    "            if isinstance(epochs, tuple): # for range of epochs, calculate value per model\n",
    "                if m == 1:\n",
    "                    e = np.mean(epochs) # average, not lower bound if single model\n",
    "                else:\n",
    "                    e = np.linspace(*epochs, num=m)[idx]\n",
    "                e = int(e)\n",
    "            else: # not a range of epochs, just set to given value\n",
    "                e = epochs\n",
    "                \n",
    "#             print(m, e) # debug\n",
    "            \n",
    "            history = model.fit(dtrain.to_numpy(), \n",
    "                                ltrain.to_numpy(), \n",
    "                                epochs=e, \n",
    "                                verbose=verbose,\n",
    "\n",
    "                                callbacks=cb,\n",
    "                                validation_split=validation_split)\n",
    "            histories.append(history.history)\n",
    "            response[\"epochs\"].append(e)\n",
    "\n",
    "        ############################\n",
    "        ##  FEEDFORWARD TEST DATA\n",
    "        ############################\n",
    "        # TEST DATA PREDICTIONS\n",
    "        response[\"predictions\"] = [model(dtest.to_numpy()) for model in models]\n",
    "        # TEST LABEL TENSOR\n",
    "        ltest_tensor = tf.constant(ltest.to_numpy())\n",
    "\n",
    "        ########################\n",
    "        ##  ENSEMBLE ACCURACY\n",
    "        ########################\n",
    "        ensem_sum_rounded = sum(tf.math.round(pred) for pred in response[\"predictions\"])\n",
    "        ensem_sum = sum(response[\"predictions\"])\n",
    "        # round predictions to onehot vectors and sum over all ensemble models\n",
    "        # take argmax for ensemble predicted class\n",
    "        \n",
    "        correct = 0 # number of correct ensemble predictions\n",
    "        correct_num_models = 0 # when correctly predicted ensembley, number of models correctly classifying\n",
    "        individual_accuracy = 0 # proportion of models correctly classifying\n",
    "        \n",
    "         # pc = predicted class, pcr = rounded predicted class, gt = ground truth\n",
    "        for pc, pcr, gt in zip(ensem_sum, ensem_sum_rounded, ltest_tensor):\n",
    "            gt_argmax = tf.math.argmax(gt)\n",
    "            \n",
    "            if round_predictions:\n",
    "                pred_val = pcr\n",
    "            else:\n",
    "                pred_val = pc\n",
    "            \n",
    "            correct_models = pcr[gt_argmax] / m # use rounded value so will divide nicely\n",
    "            individual_accuracy += correct_models\n",
    "            \n",
    "            if tf.math.argmax(pred_val) == gt_argmax: # ENSEMBLE EVALUATE HERE\n",
    "                correct += 1\n",
    "                correct_num_models += correct_models\n",
    "                \n",
    "#                 print(pc.numpy(), pcr.numpy(), gt.numpy(), (pcr[gt_argmax] / m).numpy(), True) # debug\n",
    "#             else:\n",
    "#                 print(pc.numpy(), pcr.numpy(), gt.numpy(), (pcr[gt_argmax] / m).numpy(), False)\n",
    "                \n",
    "        ########################\n",
    "        ##      RESULTS\n",
    "        ########################\n",
    "        response.update({\n",
    "            \"history\": histories,\n",
    "            \"optimizer\": model.optimizer.get_config(),\n",
    "            \"model_config\": json.loads(model.to_json()),\n",
    "            \"loss\": model.loss,\n",
    "            \"round_predictions\": round_predictions,\n",
    "            \n",
    "            \"accuracy\": correct / len(ltest), # average number of correct ensemble predictions\n",
    "            \"agreement\": correct_num_models / correct, # when correctly predicted ensembley, average proportion of models correctly classifying\n",
    "            \"individual_accuracy\": individual_accuracy / len(ltest) # average proportion of individual models correctly classifying\n",
    "        })\n",
    "\n",
    "        if return_model:\n",
    "            response[\"models\"] = models\n",
    "\n",
    "        yield response"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "## Single Iteration\n",
    "Run a single iteration of ensemble model investigations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Models: 1\n",
      "20 [30]\n",
      "Models: 3\n",
      "20 [30, 30, 30]\n",
      "Models: 9\n",
      "20 [30, 30, 30, 30, 30, 30, 30, 30, 30]\n",
      "Models: 15\n",
      "20 [30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30]\n",
      "Models: 25\n",
      "20 [30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30]\n"
     ]
    }
   ],
   "source": [
    "single_ensem_results = list()\n",
    "# for test in evaluate_ensemble_vote(epochs=(5, 300), optimizer=lambda: tf.keras.optimizers.SGD(learning_rate=0.02)):\n",
    "for test in evaluate_ensemble_vote(hidden_nodes=20,\n",
    "                                   epochs=30,\n",
    "                                   learning_rates=(0.01, 0.5),\n",
    "                                   optimizer=lambda: tf.keras.optimizers.SGD(learning_rate=0.02)):\n",
    "    single_ensem_results.append(test)\n",
    "    print(test[\"nodes\"], test[\"epochs\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 5))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "ensem_x = [i[\"num_models\"] for i in single_ensem_results]\n",
    "\n",
    "plt.plot(ensem_x, 1 - np.array([i[\"accuracy\"] for i in single_ensem_results]), 'x-', label='Ensemble Test')\n",
    "plt.plot(ensem_x, 1 - np.array([i[\"individual_accuracy\"] for i in single_ensem_results]), 'x-', label='Individual Test')\n",
    "plt.plot(ensem_x, 1 - np.array([i[\"agreement\"] for i in single_ensem_results]), 'x-', label='Disagreement')\n",
    "\n",
    "plt.title(\"Test Error Rates for Horizontal Model Ensembles\")\n",
    "plt.ylim(0)\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.ylabel(\"Error Rate\")\n",
    "plt.xlabel(\"Number of Models\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "## Multiple Iterations\n",
    "Run multiple iterations of the ensemble model investigations and average\n",
    "\n",
    "### CSV Results\n",
    "\n",
    "| test | learning rate | momentum | batch size | hidden nodes | epochs | models |\n",
    "| --- | --- | --- | --- | --- | --- | --- |\n",
    "|1|0.06|0|128|16|50|1, 3, 9, 15, 25|\n",
    "|2|0.06|0|35|16|1 - 100|1, 3, 9, 15, 25|\n",
    "\n",
    "### Pickle Results\n",
    "\n",
    "| test | learning rate | momentum | batch size | hidden nodes | epochs | models | stratify |\n",
    "| --- | --- | --- | --- | --- | --- | --- | --- |\n",
    "|3|0.06|0.05|35|16|1 - 300|1, 3, 9, 15, 25| |\n",
    "|4|0.06|0.05|35|1 - 50|50|1, 3, 9, 15, 25| |\n",
    "|5|0.06|0.05|35|1 - 300|50|1, 3, 9, 15, 25| |\n",
    "|6|0.001|0.01|35|1 - 400|50|1, 3, 9, 15, 25| |\n",
    "|7|0.01|0.01|35|1 - 400|30 - 150|1, 3, 9, 15, 25| |\n",
    "|8|0.03|0.01|35|1 - 400|5 - 100|1, 3, 9, 15, 25| |\n",
    "|9|0.1|0.01|35|1 - 400|20|1, 3, 9, 15, 25| |\n",
    "|10|0.15|0.01|35|1 - 400|20|1, 3, 9, 15, 25, 35, 45| |\n",
    "|11|0.15|0.01|35|1 - 400|10|1, 3, 9, 15, 25, 35, 45| |\n",
    "|12|0.02|0.01|35|m|50|1, 3, 9, 15, 25, 35, 45| |\n",
    "|13|0.01 exp 0.98, 1|0.01|35|1 - 200|50|1, 3, 9, 15, 25, 35, 45| n |\n",
    "|14|0.01|0.01|35|1 - 200|50|1, 3, 9, 15, 25, 35, 45| n |\n",
    "|15|0.01|0.9|35|50 - 100|50|1, 3, 5, 7, 9, 15, 25, 35, 45| n |\n",
    "|16|0.01|0.1|35|50 - 100|50|1, 3, 5, 7, 9, 15, 25, 35, 45| n |\n",
    "|17|0.1|0.1|35|50 - 100|50 - 100|1, 3, 5, 7, 9, 15, 25, 35, 45| n |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "batch_size=35\n",
    "test_size=0.5\n",
    "epochs=50\n",
    "lr_schedule = tf.keras.optimizers.schedules.ExponentialDecay(0.01,\n",
    "                                                             decay_steps=1,\n",
    "                                                             decay_rate=0.98)\n",
    "\n",
    "plt.plot(range(epochs+1), [lr_schedule(i) for i in range(epochs+1)])\n",
    "plt.grid()\n",
    "plt.ylim(0)\n",
    "plt.xlabel('Epochs')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1/30\n",
      "Iteration 2/30\n",
      "Iteration 3/30\n",
      "Iteration 4/30\n",
      "Iteration 5/30\n",
      "Iteration 6/30\n",
      "Iteration 7/30\n",
      "Iteration 8/30\n",
      "Iteration 9/30\n",
      "Iteration 10/30\n",
      "Iteration 11/30\n",
      "Iteration 12/30\n",
      "Iteration 13/30\n",
      "Iteration 14/30\n",
      "Iteration 15/30\n",
      "Iteration 16/30\n",
      "Iteration 17/30\n",
      "Iteration 18/30\n",
      "Iteration 19/30\n",
      "Iteration 20/30\n",
      "Iteration 21/30\n",
      "Iteration 22/30\n",
      "Iteration 23/30\n",
      "Iteration 24/30\n",
      "Iteration 25/30\n",
      "Iteration 26/30\n",
      "Iteration 27/30\n",
      "Iteration 28/30\n",
      "Iteration 29/30\n",
      "Iteration 30/30\n"
     ]
    }
   ],
   "source": [
    "multi_ensem_results = list()\n",
    "multi_ensem_iterations = 30\n",
    "for i in range(multi_ensem_iterations):\n",
    "    print(f\"Iteration {i+1}/{multi_ensem_iterations}\")\n",
    "    data_train, data_test, labels_train, labels_test = train_test_split(data, labels, test_size=test_size, \n",
    "#                                                                         stratify=labels\n",
    "                                                                       )\n",
    "    multi_ensem_results.append(list(evaluate_ensemble_vote(epochs=(50, 100),\n",
    "                                                           hidden_nodes=(50, 100),\n",
    "                                                           nmodels=[1, 3, 5, 7, 9, 15, 25, 35, 45],\n",
    "                                                           optimizer=lambda: tf.keras.optimizers.SGD(learning_rate=0.1, momentum=0.1),\n",
    "                                                           weight_init=lambda: 'random_uniform',\n",
    "                                                           batch_size=batch_size,\n",
    "                                                           dtrain=data_train, \n",
    "                                                           dtest=data_test, \n",
    "                                                           ltrain=labels_train, \n",
    "                                                           ltest=labels_test,\n",
    "                                                           return_model=False,\n",
    "                                                           print_params=False)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "### Accuracy Tensor\n",
    "\n",
    "Create a tensor for holding the accuracy results\n",
    "\n",
    "(Iterations x Param x Number of models)\n",
    "\n",
    "#### Params\n",
    "0. Test Accuracy\n",
    "1. Train Accuracy\n",
    "2. Individual Accuracy\n",
    "3. Agreement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_tensor_data(test):\n",
    "    return [test[\"accuracy\"], \n",
    "            np.mean([i[\"accuracy\"][-1] for i in test[\"history\"]]), # avg train acc\n",
    "            test[\"individual_accuracy\"], \n",
    "            test[\"agreement\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 Tests\n",
      "Models: [1, 3, 5, 7, 9, 15, 25, 35, 45]\n",
      "\n",
      "Loss: categorical_crossentropy\n",
      "LR: 0.1\n",
      "Momentum: 0.1\n"
     ]
    }
   ],
   "source": [
    "multi_ensem_models = sorted(list({i[\"num_models\"] for i in multi_ensem_results[0]}))\n",
    "multi_ensem_iter = len(multi_ensem_results)\n",
    "\n",
    "accuracy_ensem_tensor = np.zeros((multi_ensem_iter, 4, len(multi_ensem_models)))\n",
    "for iter_idx, iteration in enumerate(multi_ensem_results):\n",
    "    for single_test in iteration:\n",
    "        \n",
    "        ensem_models_idx = multi_ensem_models.index(single_test['num_models'])\n",
    "        accuracy_ensem_tensor[iter_idx, :, ensem_models_idx] = test_tensor_data(single_test)\n",
    "        \n",
    "mean_ensem_accuracy = np.mean(accuracy_ensem_tensor, axis=0)\n",
    "std_ensem_accuracy = np.std(accuracy_ensem_tensor, axis=0)\n",
    "\n",
    "print(f'{multi_ensem_iter} Tests')\n",
    "print(f'Models: {multi_ensem_models}')\n",
    "print()\n",
    "print(f'Loss: {multi_ensem_results[0][0][\"loss\"]}')\n",
    "print(f'LR: {multi_ensem_results[0][0][\"optimizer\"][\"learning_rate\"]:.3}')\n",
    "print(f'Momentum: {multi_ensem_results[0][0][\"optimizer\"][\"momentum\"]:.3}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "#### Export/Import Test Sets\n",
    "\n",
    "Export mean and standard deviations for retrieval and visualisation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [],
   "source": [
    "exp2_testname = 'exp2-test17'\n",
    "pickle.dump(multi_ensem_results, open(f\"results/{exp2_testname}.p\", \"wb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp2_testname = 'exp2-test16'\n",
    "multi_ensem_results = pickle.load(open(f\"results/{exp2_testname}.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "np.savetxt(\"exp2-mean.csv\", mean_ensem_accuracy, delimiter=',')\n",
    "np.savetxt(\"exp2-std.csv\", std_ensem_accuracy, delimiter=',')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mean_ensem_accuracy = np.loadtxt(\"results/test1-exp2-mean.csv\", delimiter=',')\n",
    "std_ensem_accuracy = np.loadtxt(\"results/test1-exp2-std.csv\", delimiter=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "### Best Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Models: 5, 96.4% Accurate\n"
     ]
    }
   ],
   "source": [
    "best_ensem_accuracy_idx = np.unravel_index(np.argmax(mean_ensem_accuracy[0, :]), mean_ensem_accuracy.shape)\n",
    "best_ensem_accuracy = mean_ensem_accuracy[best_ensem_accuracy_idx]\n",
    "best_ensem_accuracy_models = multi_ensem_models[best_ensem_accuracy_idx[1]]\n",
    "\n",
    "print(f'Models: {best_ensem_accuracy_models}, {best_ensem_accuracy * 100:.3}% Accurate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "source": [
    "### Test/Train Error Over Model Numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {
    "tags": [
     "exp2"
    ]
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(6, 4))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "# plt.plot(multi_ensem_models, 1 - mean_ensem_accuracy[0, :], 'x-', label='Ensemble Test')\n",
    "# plt.plot(multi_ensem_models, 1 - mean_ensem_accuracy[2, :], 'x-', label='Individual Test')\n",
    "# plt.plot(multi_ensem_models, 1 - mean_ensem_accuracy[1, :], 'x-', label='Individual Train')\n",
    "# plt.plot(multi_ensem_models, 1 - mean_ensem_accuracy[3, :], 'x-', label='Agreement')\n",
    "\n",
    "plt.errorbar(multi_ensem_models, 1 - mean_ensem_accuracy[0, :], yerr=std_ensem_accuracy[0, :], capsize=4, label='Ensemble Test')\n",
    "plt.errorbar(multi_ensem_models, 1 - mean_ensem_accuracy[2, :], yerr=std_ensem_accuracy[2, :], capsize=4, label='Individual Test')\n",
    "plt.errorbar(multi_ensem_models, 1 - mean_ensem_accuracy[1, :], yerr=std_ensem_accuracy[1, :], capsize=4, label='Individual Train')\n",
    "plt.errorbar(multi_ensem_models, 1 - mean_ensem_accuracy[3, :], yerr=std_ensem_accuracy[3, :], capsize=4, label='Disagreement')\n",
    "\n",
    "plt.title(f\"Error Rate for Horizontal Ensemble Models\")\n",
    "# plt.ylim(0, 0.2)\n",
    "# plt.ylim(0, np.max(1 - mean_ensem_accuracy + std_ensem_accuracy) + 0.05)\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.xlabel(\"Number of Models\")\n",
    "plt.ylabel(\"Error Rate\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'graphs/{exp2_testname}-error-rate-curves.png')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FSZq1mNiVZq_",
    "tags": [
     "ex3"
    ]
   },
   "source": [
    "# Experiment 3\n",
    "\n",
    "Repeat Exp 2) for cancer dataset with two different optimisers of your choice e.g. 'trainlm' and 'trainrp'. Comment and discuss the result and decide which is more appropriate training algorithm for the problem. In your discussion, include in your description a detailed account of how the training algorithms (optimisations) work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_optimisers(optimizers=[(lambda: 'sgd', 'sgd'), \n",
    "                                    (lambda: 'adam', 'adam'), \n",
    "                                    (lambda: 'rmsprop', 'rmsprop')],\n",
    "                        weight_init=lambda: 'glorot_uniform',\n",
    "                        print_params=True,\n",
    "                        **kwargs\n",
    "                       ):\n",
    "    for o in optimizers:\n",
    "        \n",
    "        if print_params:\n",
    "            print(f'Optimiser: {o[1]}')\n",
    "            \n",
    "        yield list(evaluate_ensemble_vote(optimizer=o[0],\n",
    "                                          weight_init=weight_init,\n",
    "                                          exp=f'3-{o[1]}',\n",
    "                                          print_params=print_params,\n",
    "                                          **kwargs\n",
    "                                         ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single Iteration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimiser: sgd\n",
      "Models: 1\n",
      "Models: 3\n",
      "Models: 5\n",
      "Optimiser: adam\n",
      "Models: 1\n",
      "Models: 3\n",
      "Models: 5\n",
      "Optimiser: rmsprop\n",
      "Models: 1\n",
      "Models: 3\n",
      "Models: 5\n"
     ]
    }
   ],
   "source": [
    "single_optim_results = list()\n",
    "for test in evaluate_optimisers(epochs=(5, 300), nmodels=[1, 3, 5]):\n",
    "    single_optim_results.append(test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multiple Iterations\n",
    "\n",
    "### Pickle Results\n",
    "\n",
    "| test | optim1 | optim2 | optim3 | lr | momentum | epsilon | batch size | hidden nodes | epochs | models | stratified |\n",
    "| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n",
    "| 1 | SGD | Adam | RMSprop | 0.1 | 0.0 | 1e7 | 35 | 16 | 1 - 100 | 1, 3, 9, 15, 25 | y |\n",
    "| 2 | SGD | Adam | RMSprop | 0.05 | 0.01 | 1e7 | 35 | 16 | 1 - 100 | 1, 3, 9, 15, 25 | y |\n",
    "| 3 | SGD | Adam | RMSprop | 0.1 | 0.01 | 1e7 | 35 | 1 - 400 | 20 | 1, 3, 9, 15, 25, 35, 45 | y |\n",
    "| 4 | SGD | Adam | RMSprop | 0.075 | 0.01 | 1e7 | 35 | 1 - 400 | 20 | 1, 3, 9, 15, 25, 35, 45 | y |\n",
    "| 5 | SGD | Adam | RMSprop | 0.05 | 0.01 | 1e7 | 35 | 1 - 400 | 20 | 1, 3, 9, 15, 25, 35, 45 | n |\n",
    "| 6 | SGD | Adam | RMSprop | 0.02 | 0.01 | 1e7 | 35 | m | 50 | 1, 3, 9, 15, 25, 35, 45 | n |\n",
    "| 7 | SGD | Adam | RMSprop | 0.1 | 0.9 | 1e-8 | 35 | 1 - 400 | 50 - 100 | 1, 3, 5, 7, 9, 15, 25 | n |\n",
    "| 8 | SGD | Adam | RMSprop | 0.05 | 0.9 | 1e-8 | 35 | 1 - 400 | 50 - 100 | 1, 3, 5, 7, 9, 15, 25 | n |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1/30\n",
      "Iteration 2/30\n",
      "Iteration 3/30\n",
      "Iteration 4/30\n",
      "Iteration 5/30\n",
      "Iteration 6/30\n",
      "Iteration 7/30\n",
      "Iteration 8/30\n",
      "Iteration 9/30\n",
      "Iteration 10/30\n",
      "Iteration 11/30\n",
      "Iteration 12/30\n",
      "Iteration 13/30\n",
      "Iteration 14/30\n",
      "Iteration 15/30\n",
      "Iteration 16/30\n",
      "Iteration 17/30\n",
      "Iteration 18/30\n",
      "Iteration 19/30\n",
      "Iteration 20/30\n",
      "Iteration 21/30\n",
      "Iteration 22/30\n",
      "Iteration 23/30\n",
      "Iteration 24/30\n",
      "Iteration 25/30\n",
      "Iteration 26/30\n",
      "Iteration 27/30\n",
      "Iteration 28/30\n",
      "Iteration 29/30\n",
      "Iteration 30/30\n"
     ]
    }
   ],
   "source": [
    "multi_optim_results = list()\n",
    "multi_optim_iterations = 30\n",
    "\n",
    "multi_optim_lr = 0.05\n",
    "multi_optim_mom = 0.01\n",
    "multi_optim_eps = 1e-07\n",
    "multi_optims = [(lambda: tf_optim.SGD(learning_rate=multi_optim_lr, \n",
    "                                      momentum=multi_optim_mom), 'sgd'), \n",
    "                (lambda: tf_optim.Adam(learning_rate=multi_optim_lr, \n",
    "                                       epsilon=multi_optim_eps), 'adam'), \n",
    "                (lambda: tf_optim.RMSprop(learning_rate=multi_optim_lr, \n",
    "                                          momentum=multi_optim_mom, \n",
    "                                          epsilon=multi_optim_eps), 'rmsprop')]\n",
    "\n",
    "for i in range(multi_optim_iterations):\n",
    "    print(f\"Iteration {i+1}/{multi_optim_iterations}\")\n",
    "    data_train, data_test, labels_train, labels_test = train_test_split(data, labels, test_size=0.5, \n",
    "#                                                                         stratify=labels\n",
    "                                                                       )\n",
    "    multi_optim_results.append(list(evaluate_optimisers(epochs=(50, 100),\n",
    "                                                        hidden_nodes=(1, 400),\n",
    "                                                        nmodels=[1, 3, 9, 15, 25],\n",
    "                                                        optimizers=multi_optims,\n",
    "                                                        weight_init=lambda: 'random_uniform',\n",
    "                                                        batch_size=35,\n",
    "                                                        dtrain=data_train, \n",
    "                                                        dtest=data_test, \n",
    "                                                        ltrain=labels_train, \n",
    "                                                        ltest=labels_test,\n",
    "                                                        return_model=False,\n",
    "                                                        print_params=False)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Accuracy Tensor\n",
    "\n",
    "Create a tensor for holding the accuracy results\n",
    "\n",
    "(Iterations x Param x Number of models)\n",
    "\n",
    "#### Params\n",
    "0. Test Accuracy\n",
    "1. Train Accuracy\n",
    "2. Individual Accuracy\n",
    "3. Agreement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 Tests\n",
      "Optimisers: ['SGD', 'Adam', 'RMSprop']\n",
      "Models: [1, 3, 5, 7, 9, 15, 25]\n",
      "\n",
      "Loss: categorical_crossentropy\n"
     ]
    }
   ],
   "source": [
    "multi_optim_results_dict = dict() # indexed by optimiser name\n",
    "multi_optim_iter = len(multi_optim_results) # number of iterations (30)\n",
    "\n",
    "#####################################\n",
    "## INDIVIDUAL RESULTS TO DICTIONARY\n",
    "#####################################\n",
    "for iter_idx, iteration in enumerate(multi_optim_results): # of 30 iterations\n",
    "    for model_idx, model_test in enumerate(iteration): # of 3 optimisers\n",
    "        for single_optim_test in model_test: # single tests for each optimisers\n",
    "            \n",
    "            single_optim_name = single_optim_test[\"optimizer\"][\"name\"]\n",
    "            if single_optim_name not in multi_optim_results_dict:\n",
    "                multi_optim_results_dict[single_optim_name] = list(list() for _ in range(multi_optim_iter))\n",
    "\n",
    "            multi_optim_results_dict[single_optim_name][iter_idx].append(single_optim_test)\n",
    "\n",
    "# list of numbers of models used in test\n",
    "multi_optim_models = sorted(list({i[\"num_models\"] for i in multi_optim_results[0][0]}))\n",
    "\n",
    "##################################\n",
    "## DICTIONARY TO RESULTS TENSORS\n",
    "##################################\n",
    "optim_tensors = dict()\n",
    "for optim, optim_results in multi_optim_results_dict.items():\n",
    "    \n",
    "    accuracy_optim_tensor = np.zeros((multi_optim_iter, 4, len(multi_optim_models)))\n",
    "    for iter_idx, iteration in enumerate(optim_results):\n",
    "        for single_test in iteration:\n",
    "\n",
    "            optim_models_idx = multi_optim_models.index(single_test['num_models'])\n",
    "            accuracy_optim_tensor[iter_idx, :, optim_models_idx] = test_tensor_data(single_test)\n",
    "            \n",
    "    optim_tensors[optim] = {\n",
    "        \"accuracy\": accuracy_optim_tensor,\n",
    "        \"mean\": np.mean(accuracy_optim_tensor, axis=0),\n",
    "        \"std\": np.std(accuracy_optim_tensor, axis=0)\n",
    "    }\n",
    "\n",
    "print(f'{multi_optim_iter} Tests')\n",
    "print(f'Optimisers: {list(multi_optim_results_dict.keys())}')\n",
    "print(f'Models: {multi_optim_models}')\n",
    "print()\n",
    "print(f'Loss: {multi_optim_results[0][0][0][\"loss\"]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Export/Import Test Sets\n",
    "\n",
    "Export mean and standard deviations for retrieval and visualisation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(multi_optim_results, open(\"results/exp3-test5.p\", \"wb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp3_testname = 'exp3-test8'\n",
    "multi_optim_results = pickle.load(open(f\"results/{exp3_testname}.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Best Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SGD: 9 Models, 96.5% Accurate\n",
      "Adam: 7 Models, 96.3% Accurate\n",
      "RMSprop: 9 Models, 96.3% Accurate\n"
     ]
    }
   ],
   "source": [
    "for optim, optim_results in optim_tensors.items():\n",
    "    best_optim_accuracy_idx = np.unravel_index(np.argmax(optim_results[\"mean\"][0, :]), optim_results[\"mean\"].shape)\n",
    "    best_optim_accuracy = optim_results[\"mean\"][best_optim_accuracy_idx]\n",
    "    best_optim_accuracy_models = multi_optim_models[best_optim_accuracy_idx[1]]\n",
    "\n",
    "    print(f'{optim}: {best_optim_accuracy_models} Models, {best_optim_accuracy * 100:.3}% Accurate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimiser Error Rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [
    {
     "data": {
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LfB3mHPPXRr8xH8euNn+dbpr5+PbPZrZDoeZZi3OOD586/Uh6Xr7rUSdpRIHy3DyUp5P0hyKWf1hoPsNymH5QQll3ybM8FeH8CrSMA8LLKF/5fSOh3LHPUUnKUSmpo/zrH5NNc3HC/HpKmpwibfgzSVKPDGWvDKWvkO/qdl6SvBbk+Nt0T8ine4Rpvgul/3eadBfKn2gz/Q5O0v8krRthG830qUyRx6aSxkSY/jtJ+xZwn8r0qUgy/e8kLcgw3RpJt0hqGnHdzpR/r/O9KfK7NcdlHZzpt8/z9xsg/07pTzL8HtdkyHMDSW9nsV4OSpNXE0l/k++6PV0eqyX9Q5Jlsay7yt9AS5XnPIWOsZIOl28gmSr9LEk9M/w21elD63Rthjz3zGYdZkhbZ/tmin3DyT9ZenyU7UnS1aF0xwXThvPqnmHeBdm/Q/ltK2lahvzukX/KbGYW5TxevnvwTOvlOUkd0+RTEUqb8hgRbHdRzxcPFWI74MOnPj7yryqMbcvLJXUIhvcJDV8lqUvE/JpJGpphn5kqaWvFn7MHp8hvU/kn56Psi3Ml/TJD+cLH25mSmgbHt3T53q/g3CmpjaSnM6S/oYDrZ1go32EFyrMylGeFItTlVbt+sLekb1Isf6eE+ZVtPVLSLxPmu1eatBMibserJF2eJp8oeVSvqxR5FOScGvE3jVrWmUmmbSvfODTTtLMlHZbFuh0sX1/5OEV+O+e4rDMz/fb5/H7B/+dIWpHmt5grqXeGPFPt88k+szLkVbB6c5JlvVzp62IvS2oZpG0q31t6ujI8qvTHmAGhtMMkbSTprQx5PiupbTbLlSFtne2bKfaNx4JhLwT/V0naPMV0JunLIN3P8sfkc0J5VWaYb8H271Ce5yp9TDxf/nWzFVmUs6X8uSZTXLBM0vkZ8hoWSp/0GKECXifg07g/iq/vDY6Q/h+h9KsypK3T44aKcJ8jyW9UIam/0tdZl0k6K4vfZrCyqG/I90oc5RzwsKQ2GcoRd+5RAa6rZfnbzsx0vMshz2TLlOzY/HSKcnSXfz1fsvPEBwnzaibp9hT5J55XTstQ7gGh9MMU4R5QqezvKlAsroR7axE+3ZPkUbBr3xF+n2zKOyzJ9GV9Hy7L369S/lj/7wy/xXuS1suQ72AV6DptUMYZEfIZL2mTLJa1jXzMkS7PwaHpuyh9vFGlLOuXkvZU/L3SxM8aZThOJC5XhrR1tm+m2TfOCbaz2L7xVar5yG/zVUG654Nh4Zgk029TsP07yK+g11BD+RYyTp8ZSp/0GBFsd7MizC/2aVaI7SDxU+uJLaAOhLvj/ZWZbeec+yTPPCsS/h+RZ37F9Likm0L/7yvp/XoqSxQt5S/k7SZ/Qnxbfh22lG8MkYxJekg+WIsd4D8Jhu8QDPMJzbaVf/1Ml9D0U+SfhnCSdpHUKxi+m6S3zWw/F60L6L3kTwTN5YPpcfIV8PWDfIsuaEEffhL4xzTJN5a/WCv5iwCfyvcms0JSJ/nfYftg/AGSXjOzXzjnVibk85qkJZK2kXRgMGyafCOuRNOTlHnbIO1GwSAnfyL/RL7ysol8l8HtgzK/amaHOefGpFm2dGLllaSjVfP0y9PyJ92wuP/N7DJJQ0KDVspvT9/Iv0d9f/nXGTWVdLGkzczsOBeciTO4RTWvQZ0i6UP5ytlWKt1ugDeW/z03kr9Q84akH+S3wQPkG0pK0lVm9olzrtax0syayl+s2i00+OPgs0C+Qc2GknZSzTaSVJDXCEnHhgZ/J3/T7ydJ7STtIWkL+Qren+WPBWdFWNaukm4I0s+VX+/zJHWTX+/N5beBV8x3Bbuz/DbVXL4C9pakRfLrc1/5Cvomkp40s12c74ElLTO7UL7BkeQDpXflb1T2ktQ7GL6JpJfNrK/zXW/nrB72zXSeld8eOkn6rZkNTrFfxZ7qmC9/cybyExiF3r/NrJvifz/JBw2xQGVX+XPUOfIXM6OW8xL583ps2RbJB8WzgrJtL789mPx5sdLM9nbORZ5HwvwuUs12J/nt/x3VXBxdR/74v61qzilAQ3Va6PszzrlFkuScm2hm0+S39ebyrwFPfE10Mg9KOjH0/wL5iwA/S9pMPqbYTv4VJc9GyK+tpNiTx/Pljylfy9drWsg/NPIL+XPnupJeDM4Hb0fIW5L+Ln98q5I0Uf5430z+vNU9SHO6pOlm9i9JoyQdJl9nf0v+3NRG/ngZe13dH8xssnMu3MtYqcqlLr+lpFvl6zyLg2lmy5834l550QjqkYlPlKeLQ2I9X62U345nSFoof+7aSL6+tp78uviXmck5d0OSfO4K/maq00s+1olT1+fUUHnbq6bOsli1e8X4OaGcbSS9Lmn30ODZ8nXvJfLb4T5BmTeS9KyZneicGxWhTOvKN+bZTD4OfFP+uNJO/nhSksz3eHZP8O9n8tcAlssfp/eWX2fryv8W2zrnFibJo7f8cSx2rXK5fB1npvy22UE+buglf2xLV56i1ZvN7GxJ/wr+/Uj+2sVa+f0k1qPeIfI3S8+Wb4x1lmqO5Z/Kxx77yp8nJOk38seJf2aav/x++FQwv7Xy290XwbL0lW80I/nGPc+Z2cFRYpt06mHfTOdB+QdtYr1oXpMkTfi3HeGcWxX1QfBi7N/BNnNXaNBq+Rs1X8ufZyqCv6MU3/t/unK2lfSKanojlvx28J58nWSdYNzG8q89ucPMOjjnrouSf5L5Few6AZCDcJ0mXX0mlWIeN4pxnyNRb/kbxS3k6ySV8vt5d/njfnP5/fw+M1vrnBsaIc/I9Q0z+7V8Q6vY9YW1QfoZQfp9VbOOTpK0uZkd4JxbkakQdX1drS6Y2R9Us0xfyF8DXSa/vlanmOx4+Wuckj/nvCVfF99Y/ngey7uJpCfkG+jFzJPfJubJ3+TeX35b6SRpmJl1cs5FiZVzuQdUDFH390LF4t+p5hx9Xmj4XUpuUfifIl/7TiZc3kz3ft5JKGtZ34fL0b/lrztVyR9/psnX038h38hE8tt/7DxSSyGv05rZ8fLH21ivXOF4qEr+esKe8tvSLySNN7M+zrko58ah8jFH4vWiA1QTP1xtZp/Jx/Cj5e+nrJBfn9/IH1cOlL9eYpJuN7P3nHPjI8y/m6Sbg2mXyNe3f5Tf5/cPytI0KEMT59xVEfJMqR72zZSCOsUI+XsO3eXj0LFJkp6qmngrqx5+i7R/F/oaap3f3zL/Bp1Xgvwkfx6eKL/9L5M/l3SXj2GK2yNnMVp58eGT7iN/cA23Npwr6Q9K05o3Qp73h/L7vsjlHxaa17Ac85gdyuORPMtTEf49C7SMA0J5rlZNK+ruSdK2TFKO2DQfSeqVZpoWqjkhOPkTcK0n6CQdLH+SjKV7T1LzFGWvTChHlaS/JKaPlSGH36Z7wvZb6zdJUvZw+n5p0v5O0vnp9gVJO8qfMGL5/SXieoy0rcqfgMK9K70oaYsk6Too/inf2SrAU7AJ668iQ9q9FP/kwYuSNkhcz/IBbXgdDIqwbmP5fqMkrbDz2H4Gh+ZRme/vFeQ5LJRn7In0fyrhiTT5yv//Qmm/UJLW+PJPs4TX6x5p5r19MK/dU4z/Wyiv7yUdk2Kexyv+Sb8TsljWayS1SEi3g+Kf3LshWJer5Cu+TRLS7ycfCMTSn5pmmcPb0kr5iuLJSdLtrfiW9x8p9XErvFwDSm3fVJIesoLh94WGJdtP9gmNvzcYFqmHLBV4/w7SvxZKt0DSEUnSHKaaJ1ZWRSjngap5knOlpCuU5GlQ+QB2aii/u1PkVxFKU+sYIR8ghs+Hf0yzXa0j31AjZU8mfPiU8kf+psLC0PbeL2H8n0PjJkfI75SE48UdklonpNlINefKlaG0g1Pk2U3+hvvuSji3hNJ0kHRjKK/P0qQNH29XyddjP1XtJ9SbKb7nrHmSrgq+v6GEJ/+D33JEKH3SOkAO62hYKM9hBVrvlaE8I9XlE8oRi0PulNQuYZrmsd9ejaAeKd+9fSz9nHTrXL7ucHjiPhEa31Q+tojVl1Ylbmdp1mNFxOUr6Dk1y982vP5mRkgfrmutkXSRatcve8o3SoqlW6jU9Ynwuo1tw48rofc/+ZsDSc/7Eco8MzSPAfn+ZkGe4X1jRbCdHZok3X6KP55flSK/p0JpRknqnCJdq2B7vTfF+ILXm5Ms6/fJtm1Jlyasy0uC759I2inJfhU+li9Wih6tFB/bx85P7ymhd98gz78klPdPUdZhie6b4X0j1tNNK9XEjjNSTPd/oel+EQyL1EOWCr9/91T8U/mVkrompGkZ2hZWRizn8FC6z1Jsj00lDVRN7LxGKXqZUYaYVAW8TsCHj7LoMUe+3hvu+fTxDOnr9LihItznSPIbxY4LQ5RQj5R/WHFcKO1SJTnnJfltItU35G9ULw5N966kLZOkH6T4Xq5uT7Ns4d+rINfVsvxtZ6Y73uWYZ3iZVgfb21FJ0rVMUY7VwW9xphLq7AnTXJ4wr+tV+5rohvI3n8N5Jz1mK4d7QHluywXb31XgWDxxPWaxfAW99p3lbxtef8MypC37+3AR86wI5RerH02QtE1COpOvA4bnv1+KbbYg12nl60/Lgnyq5I/5nZKk66H4nuxezGJZ31JCz0jy14tGhtJ+HuxbTv4NSOsnpO8s3/Anlv71NL/3sFC62LnsIQW93yfk+UQo7Vql6OFbEXvIUv3um+F945xg2J6hYUNTTDc9GD9fNfdfMvaQpeLs38W4hlqMOH1mKF2tY4Ti4+1xkjZOkU8z+UbuDynCW1hy2i6KkSkfPpk+8q0lXcKnSr4F8oPyr27bXRG7hlP8TdaUJ4AClX1YaF7DcsxjTCiP/+VZnoqE3/HOLD6/TZHngIQ8P0o82EYox/fK3JXn6aH0q5Tm9Y3yr6ZZHUqftMGE4k92TtKVBV7/3RPy754mbVvFnwhnqjCBY0fVNDaZneoEodwaZP01NM2TShOkJNkfrijAsoXXX0WGtOGK31tKCEAT0t4WSrtQUvsI63appK0KvP0MDuX/XZb7a6rgeVhCua9LM/8NFN/wqFaeig9Uf5/nvhK7IfmzUlwQCqUPX8T6RMkryInLem2a/E5OSOuU5kKLpCtD6ZIGMkG6xDx/nSbt9op/bcvvIqzDpGWsz30zyb4RCwj2Cg37T5Lpwl0+7xkMi9ogq9D7d/i1TVWS9k+T376q6R44ZTnlLzp+HkpzdIbfcUP5Huti57yuSdJUhPKrTDJ+h9D4N/NZr3z4lPpH/unq2PY+RwlxgfwF2PC+WushgFDaJoq/sPtAmrSt5XspCR8DBhdgee4J5Zf09UZJjrdzJG2YIm1T1X4F6ydK3aCmvfz5OJY275ukij/XfKrs6jVJXxGsHOryql0/qHVOSjJNQ69HVmZI21fxsdM/ClSGX4fy/FeadOH1WBEh34KfU7NcrvD6m5kh7RaKv+F4Xpq0nRX/eu37I6xbJ38TLW1dL4dlnBnK/7Vs9tc0eYbLvELSjmnSnhdK+2mKNHNDebXLY1kLXm9OWNblkrZPk9+rCel/VMKNjFDaxGN5qgdTBiTkOUvSumnKcG0o7RIl3PRItlwpxtf3vhneNx4LDQ/HGXsnTBNuePFZaHiUhhXF2L8fDqX5WGle5SXpPwnrOVU5w690nqHM197C289LEfaDAUnGF+Q6AR8+ztWqJwzOkDaxkWmmV4DX6XEjSFfQ+xxJfiMn6Z40advJ18VjaR+M8NtEqm8ovvHndKV54E81jZBdcCxN9XrIxN8q7+tqWW5/M0P5FaNOtFZJGm5kKIdTkkZpCek7KL5x3JA0aVsq/pXkSe+XKYd7QDn83uFtuaD7exZlyBiLJ67HiPl2V4GvfWe5XOH1NyxD2nK4Dzc8i/31ohR5ViTk+bnSxB3yjVZTHodVwOu0in+Q/pIMadsq/kGIZPd4Epd1mlI//JF4vcgF5UnV2LFbaNuvUurrVsMS8nwhTZ7NFH/ffFyEdViZZtupz30zvG+cExr+WTBsoWo3bgrfZ7kvNDxKg6yC7t8q0jVUFSdOnxlK0z3J+PBDNFumm1+xP/U2Yz6N+yMfKDyZsJMm+ywJDjgpb5wG+YXfi/pkhPn3VGEaPwzLcfmfDuWR8Yn+DHlVRPgdU32Sll+1K+MpK6ppyjEwwjTvhNLfFiF9uFXs+BRpKkNpvlOB3/eqDA2y5C+obizpt4oPhhcrIeDPsxzh3yLpDUhl2SBLvteAH4P0K5TionHCNBur5mboRwVYrvD6q0iTbtuE9ZCykhGkb6v41t9nR1i3KW8y5bF8g/PYXwekyHNYKM0cBY1l0pQh3EPGBUnGhy9SHZnHst4SyueiiNO8HJpm1wzL+qPSPGEjXxkMt8x/P8O8e4TSzk2TLrxOkgYGCelvCqVPddwKL1et9Vzf+2aSfaNVaFzsyY0FCcNbyT/N4SR9njA85TE0SFOM/Tu83Y+MsMwPRyjnkaHxT0X8Lf8YmqZWLyvK3CBrr2znyYdPQ/0o/qnepPVExdcbbkyT12GhdMuU5iZ2kD7ciNOpMA2ydg/ld1OKNInH24sz5Pm3hPRHZkj/YCjt+QVYpmEJ88/mUxFhnUaqyyeUY7lS9KoTSl8O9cjKJONby3dBf63ib1y9oRQXXnMoQ1PV3Ah6L0268HpMuq4T0hf8nJrlcoXX38wMaf8ZSvu+MlyslXRCKP0KJbmRqdoxwrZF2H5m5rq/pskznC5lTxhB2vaqufBbpSQNhFTTO+m8PJazKPXmhGW9NUN+v0tIf1GG9OFjedJzmWpfo0l7Q1r+Rmy4Z/Zax63E5Uoxvr73zfC+EW5YEe6J976EaX4TGndlaHiUBlkF3b/lX+sSPh4fniG/2CtcMpXzqVCaIyP+lrHrU1VKUg9S5pi0INcJ+PBxrlY9YXCS8R3kGx6Ge/t0km6OkHedHjeCdAW9z5HkN1qUeHxJkv5XofTLk6VXlvWNJMewTI1ym8g3PI2lvz5FunAZCnJdLcvtb2aEdZX0kybPcLoROZTj3Qjpw9vjD8r88PzuCeXaOkmaAQlpMt4DyuH3Dm/LBd3fsyhDxlg8cT1GzPeW0DQXRZwm7bXvLJcrvP6GZUhbDvfhsvlUpsizIiHdMRnKEL6WVCv+VYGu08q/Li2Wz2RFaBCk+HNXrVgsybIelSG/BxPS75Qhfbh3xlpvoQjSDAulqVLmhlG9EsqQ7LgVXq5U67m+983wvhFukBVudHpiwjT3hsbtHRoepUFWQfdvFeEaqooXp88Mzbd7kvHhh4s65rNe8/00EVAPnHNLnHPHSOon//RgVYqkbeWfwn3dzJ4xs84p0rUPfV8aoQibyD+hme6zbYR8crUk9L19ylSlYb78+4KzNSLdSDNrr5p3wUv+tZOZ/F/oex8za5sh/Sjn3JoI+ebjKzNzsY98y+vvJP1X/t3Qkm+F+0vn3FtRMzWz9c2sv5ldYWb/NLM7zOzO2Efxv93OBVqW3vLv9ZZ8z21zMk3gnJst37peknYws44FKksm+4e+f+Ccez9dYufcUkmPppg+lcdyKVg9e845tyJDmvBv1T3J+G9D388M3redi/B71R+JOM3roe/7ZEj7nHNuZaqRzrnl8k8Lx4xKl5lz7kv5CqYkrRscozKJ8i7v4aHvUY5byZTyvvnf4G9H+Rs2MUfKX7wLp4mqGPt3eFi26y2VYm/jyYT3z/3NbKsc8gBKnpltIumg0KBUx5Hw/nxymnNW+BjwonPu5wxFeE2+PheZmTU3s33M7Dwzu9bMbk2ou50XSr5zxGzTnrskTQl9Xy7f3Xc6H4e+bx6xDPUpl7r8aOfc/AxpyqEe2TccgwRxyDL5p9r/It8YY5V8jHVYsAyRmNmOZnaamV1tZjclbMex3sIkqZeZFeqaUn2cU3N1QOj7MBdc5UvjKfnXikp+veyZIf1HzrlPcy1cPXo83Ujn3GL516VK/hUg3ZIki9VzOpvZr3MsR13Um7M5NkdJn+2xeaX8a0VSCuKk8HEoynErmZLcN51zb0r6Mvj3BDNrGRp9WiyZso9DCr1/7xUMl/zDUy+nyyw4fz2bLo2ZNZO/6SH5RhrPZyhjzJhYFvKvActWoa4TAImuTlKnWSh/o/fEIM3Pkv7onBuU60yKeNwoxn2ORM865xZmSPOi/AMEkn8QrhD1jfAxbK6k59Ilds5VKf76fpRzT11dV6tLucQBUaYJn6MeDa57puScm6D4Okmm9ZHrPaBsFGV/L1IsHkVJ1pMSldF9uEJboQzHNWV3HyWf67ThbenRCHVQKbttabl871TphI8XM5xzH2ZIn20M87Zz7ot0CZxzUxT/m5dVDCNfx4it21NjA4M6SSz+/SLL+8jF2L+LcQ21vu5vhffRc3KYvmCa1efMAefci5JeNLMu8i1b95K0m6Rd5J8uCesv6Q0z2zO4mBcW/r/UK+VSfCOsRYXM2DlnhcxP/ibF2iyn+co5Ny9Dmh3ln7CWfAO1j6KURb7BXdtg2p0kvZ0m/XsR8iy2z+W7HP48SmIz207Sv+RbIUe9wLVejmVLFA7WuwYBSxSdgr8mqat8IFVsu4S+p9sGwt6SdEHwfdcMaVer9oX0QhvrnKsocJ5RyhyuQHVIMn6U/FNzTeQvJn1sZvdLeknS1CgBgZmtKykWgKySD7gjFE3bhb5vmiHtxxnGS/5iQszUiOnbBN9jXYGnMz5CnlPkj3Ht5PfpHSNOF1bK++Z/5bcXkw8kYo1xY0FFLhc0C7p/Bw07uoQGvRMhv9iTJek23PB6OdbM+kbINxw4ZNrGa3HOfWtm70j6RZDXe2b2X/mbQW8555alzQBoOH4rVT88NM05NylFulGS7pK/6bChpEOUvFFS+LiS8RjsnHNm9q6kYzKlNbPWkv4sH9hHrZNFSbfQOTcrQ5rwee5z59zqDOnD9fNkdYB8DHfODShwnrnU5aNMUw71yCjul3/VQabG+pIkMztNfluOehG5ufy5KFMDuCjq/JyaC/MV2p1DgzJuP8651WY2QdKhwaBdlb5RRl3EsKc754YVOM9CxCEj5XtXkqRHg0ZZIySNiXLBNlAX9eZMcUh4n1jonMt0cTrbY/MU59ySzMk0Xv71UVL8cS8bpbxv/lfS1fLrrr+kx81sQ9U0VhrrnPsmamZF2r/Dv/uEoLFCJuNVc1M6mR1Vc91ztaTbIsbafULfc1kveV8nAHK0Vv41NUMLkFdBjxuJCnifI1GU+GWtmU1UzU3oXZR/fSPxGBalsUX4JvIuZmYZjg91dV0tlWLUiUothukVfM8Uw+RyD6jQstrfixiLR5l3XVz7LpRyuQ+3uXNuZgHz+yzCNZS08UsBr9OG69z7m1myh1cShTe4TNtSlOtF2d5HyTaGiXrcHq+a413WMUwp75vOua/NbJykvpJ+aWYbOud+kK8TdAqSZXsfpRj7dzGuodbX/a2RqmnQ/E8z+6X8m1FejXDNtaBokIWS4Jz7Sf6Jysel6ie+fiH/7tNTVbOtbi/pH/LvXg8LH/w7RZhfpZLcZDWzmUr+pGahhS9QZWq4VN9+ypwkp2nCN8e/jXLxxjlXZWbfqqbnqUwV6FzKnq0HVdNow+Rb+W4j//5oyZ/8J5jZL51zE9NlZGaHSHpGNU8fRVWoXtY2Dn3fMfhkK+rTXfkKbz9fR5xmZuh7pm1nfgN8qkOKViEJV76bJ450zn1qZpdLGiK/TW8j6YbgM9/M3pY0VtIzaRoabhT63kLxTyJFlWlbirKs4XWYbfpav00SGS/UBRXSWao5bnVJlz6Fkt03nXNfmdmb8t2LH2xmGwSjDg7+vpFDsFzo/Tuc3zLn3NxMmTnnFpnZQqWvU4TXSy69OOS6Ts6Qf2pnA/kLkgODzxoz+0D+ycJX5J82qe+LaUCuTgt9T3kxIthXn1HNPniakjfICh8Hot5kyZgueKr9dWX/lG2UulspnOfqW13EIQ21Hjlb/iJvTAv5i1N9VFO+cyT1NLNfpXuCPmiEMFQ+9s5WexWmQVZ9nVOz1VHx+04xtp+6iGGLIe84RNLf5W9g/0I+Djk6+MjMpsu/fvN/8j3lprp5XRf15kzLWu8xSJJ0ucQgUmnvmw/KN6yQ/HXDxyWdrJobElF6XQkrxv5djPpHeJ2sq+LE2rUU6DoBkMxESRNC/7eTtJlqemdqKun/zKyHc+7KPOdV6ONGUgW4z5GoGMf9uqgzt5CvK6Z7GL2urqvVpYYaw9RFHbRg+3uRY/Eo6uLad6GUy324QstYTw8a38f+TdWeohDXacP1u8Mylry2sriPkiRdLsf7Ut83H5RvkNVUvg5yk/J7sL0Y+3exY5i6vL/1f/IPzxwV/H9g8JGZfSN/jWGMfAyT8Z5RPnhlIUqSc26Nc+5N59wZ8gen8NN/Zwat38PCldBivmqwULYJff+h3koRTdrub/OYJvxkUORXaCSkzVSBzqXs2braOXd+8DnPOXe8c66XpP1Us112lPSUma2TKpPg6akRqmmM9bWkP8l3j7mxfK89TZxzFvSCdk1o8kIdywvxSrO6auiby/ZTattOMRTkqVTn3E3yXZP+LyHPzvJPw94g6TMze83MeiXJoi62pWyXtRhP7EZ9yiWbbS+ZUt83Y93HN5N0UvBpljAuG4Xev8P5ZdODVKZ557teclonzrlP5J9cuUPxAXIz+e5/B8kH+l+b2e/zLCNQ58ysj2rq807+yaV0whcr+ptZpyRpcjkORDn+3KWaC8Cr5AP9I+Ub5LeX1CxUdwt34R6l7lYK57n6VkpxSKnVI6eHYpDznXNnOecOl7+h8UfVvCrnQEk3Z8jrTMU3xnpZvnFjL/m6X8vYdhxsy+HYu1TikPqIQaSGu/0UXCF6x3H+1Zp9Jf1B8TcQJamnpN/JnxN+MLMbklwXkuqg3pzlsjbkGEQq4X3T+VfOvxn8e2hwTSV2M2OZMr8qMlEx9u9i1D/qLTYswHUCIJkXE+o0A5xzB8i/Gir8yug/m9kJ+cyoCMeNqPPN9j5HomIc9+uizhylHHV5TqsT6R6ESKOxxDCF3N+LGYtHUerXasPK5T5coRXqPkohrtPmuz1letNOKVxf4j6K97hqfotTzWx91fS2+2ZQV8lGMfbvsolhgkaQx0j6vaRPEkZvJt8o7v8kzTaz/0t3Dz9fNMhCyXPOvS3putCgVorvalvyrRhjNjSzzYpesBwF3U1uEBoU5dVJ5SgcfGbzmslw2kxdOtcb59wb8q/NiS3nJvKtnVM5UzUnpQ8l7eic+6dz7i3n3PfOueUJF36LEXyGT5q3h2+8ZPGpLEK5ksll+2kQ206pcM6Ndc4dJP9Uwa8l3S5psmpu8En+Jt+7ZrZ3wuThbWlRjtvSgGIuX4G0yZxEUv7bXqnvm4+rJvA+VTU92ywPxmWr0Pt3OL+o6yzKvMPrZdcc1kn3LMoSxzn3o3PuQvn6RIWkv8q/LiT85Okmkv5jZrfnOh+gnoR7xzJJM83MpfpIej6UvpWS9+CRy3Eg7TEgeB3qb4J/qyQd6pw70zn3rHNuunNuScLTjyV946CRKdt6ZBAz/EvSVaHB55hZRZrJLgt9v9o5d5hz7kHn3MfOuQXOuVUJ6Ysdh9TpOTVLia+JK6vtpxQ451Y5526U1EP+JtuFkh6TFH7tXxv5RltjktzELvV6cyHUVQwilf6+GevNppl8Y6DYk9ZPucyvAEtUjP274PUPxa+Tj3LcxgdHLEsteV4nACJz/hU+v5W/iR1zT9ArTj4KedzImot2nyNRXR73w/KtM0cpR30tW0NUzjFMVvt7icTiDenad1nfhysFBbhOG96ejslleyrWshVQfdxHKbl9M6hrPB38u6Okf6mmoVEuPXUWY/8udgxTp3G684Y657aXtLWks+Q7EQg3fmsu39vdhKDBfsHRIAsNReI7zzdK+L8y4f/fqHQdn/D/uHopRf0Ld2Pa1SK8yNfMmij+/b1F7UIwX865zxR/M+TUNE8JHhj6/nfnXLrunKXivFrzx9D3DYuQfyGFt5+oDTC7h76X9LZTSoKAYqRz7iLn3G7y28bFqnmHemtJ9yVMFt6WOphZNo1gGpKM215wbNskNCiXba+k983gePVM8O/O8k8FSdLTOV7QLPT+Hc6vTfAu+bTMrL0yP7lR7+vFObcyuCnyd+d7RllPvmvrN0PJLgh6HAJKnpm1kHRintmclmRYLseVTTOMP0A1r0B/yTk3JkP6ungtOqJpDPXIf8rfII/5V7JEZrapfM9DkrRA0vXpMjWzDipO9/31fk6NaKHiX7tXrttPvQsumn7onLvDOXeic66rpF0lPRBKtodqv4KioWxL+cjlPJbrdlfqv+dISSuC7wNCw3O5mVGM/bsY9Y+SWCc5XicAsuKcq5Lv0SB2E28dSX/OM9tCHjdylek+R6K6PO6H5VtnXqXMN9Pr6rpaOSjrGCbL/b0UYvGGdO277O/DlYo8rtOWRP2uyOrqXNYQ9s1wnWNA8HeFcnuwvRj7dznHMJ875/7jfA+NW8g30LpZUqwR7xaqeb11QdEgCw3FioT/V4b/cc7NVHwL+nPMrFWxC5UtM2up+AuGHwefxugj1Rzk2su/EiOTnVTT0natfE9Spe4uSV8F35tIujZFuvA7dKeky9DMmkqK8qRhtl2Lvhv6vleUk3c9ej/0fa+I04TTTU6ZCmk5535yzt0m3w10zPZm1iOU5ntJ34bGR11HDc0vIqTZQTVPYuV63GoI+2ayi5e5XtAs6P7tnPtO8YFElPX2C9Vc3EklvF5K4ulv59xq59zLkg5SfP3iV/VUJCBbR8hfeJWkNfL7WZTPxFAee5rZVgn5ho8rGY8BwXF2jwzJItfdAvtFSIO6Ufb1yOCJ8CtCg3Y3s6OSJA1vx9Occ6uTpAnbR5nPj1J+cUhJnFOTcc45SR+EBmXcfsysmeJ7vij57adUOefed879Tv6VAjH9E5I1hHpzvnYwsyhPP+8Z+p7rdlfS+6ZzbqGkZxMGz5b0Wg55FWP/Dp9v+gQ3PzLZM8P4D1RzTXR9M9syQp5FF+U6AZAL59wsSbeGBp1vZjnfyCvkcSMPae9zJBElfmmqwtc3wsew3YN5ZBI+dr4fHFvTqavrauWgMcQwUff3eo/FG9i178ZyH67kZHGdtqTr3AUS5Xgv5RnDNJB98zVJ3ycMeyaoo2SrGPt3Ma6hlmScHjTQulTxjbASrzEUBA2y0FDslPD/N0nShJ/m3Vz+qeBSc7Pin0y4LkJgUpaCXlMmhQYNiDDZGaHvE5xz2bwTt144/4qPcFfU/c0scXuW4rt3z9Rq+yhFa0UcDvCbR0j/lvyT8ZLUVaV9A//10PddzGzHlCklBS3hwz3nvZ4qLaJxzr0laV5o0AYJScKvkDq3+CWqF7+NkObU0PeJOR63GsK+OVrSD6H/v5f0ao55FWP/Dj8td0qEMpyaOUncNv67UmoI7pxbKb9OYhL3T6BUhXu3esk594uIn90Vf3ErcR8OHwMON7N1lN4B8sfbdCLX3YLjVJTjCupGo6hHOudek69DxPw1SbJsYhBJGhhx9tnGISV7Tk0ivP5Pi3Ah8ShJsd45V0gaX4xCNTLhG+mJdZyGUG/OVyvV7nk9TtDjZPgVvpl6jkilIeybiQ+BPBz0spGLQu/fb6umocUGkg5Ol5mZdVSGGwDOueUJ5SypWDvCdQIgFzeppqelVpIuzzO/Qh43chHlPkdY/6CX0nQOlbR+8L1Q9Y3wMayLpH7pEgeNTk8PDYpSZ66r62rlIPx7/ibTOdnMeqvmlZxS7nWBuhZlfy9WLF4dw5hZtjFMSZ2PwxrLfbhSFuE6bXhbOsbMyrH+tLeZbZ4ugZltL98rckxljvMq6X0zeIDu4YTBOT3YXqT9uxjXUEs9Tk93jaEgaJCFOmdmg8zsoCzSt1F896Q/Kv6pNUmSc26spHtDgy4ys1S9EdUpM2tuZrcq/uBfKd9NcmMW7r78vHQ3Q8xsN0lnhwbdmyptCRou6evgu0n6S5I04ffVprwAF7y/9paI8/059H2TlKkCQcXw1tCgu4N3skdSlxVF59w0xb/u884MgdLfVXNhYpGkR4pVtobOzNaLmK6TpHahQXMSktykmtb5R5vZgCzK0FC65q0ws+NSjTSzbSWdHxr0f6nSptMQ9s0gkNhX/onMPpL2C4blklcx9u/wb3+CmaV8Os7M9pZ0UoSiPiFpRvB9I/n1EunpDjNrF7Fng8TpOkd8sl6K7yo4cf8ESk5QxzksNOihLLMIpz8lYX8crZon5NpIuiFNOVrJn8MyCdfdDs/wxPhN4oZkyWhk9chrQt93NbPEG2lfqaY3qx3S9WRiZr+W78UuiqziENXDOTUP/1HNTaBdJZ2VKmFQXw4fbx7N8anXsmdmLc2sXeaUktLUcRpCvblA/mZm6V4f+mfV7HtLJT2a43wawr75smpikD6KfyAuWwXdv51zC+R/w5gbzKx1mvn/S/Exdrp0MRdkeY01p1i7gNcJgKw55+ZLuiM06OwgdshVwY4bxbrPkaCD0pQxONaGj0ejClHfCI5hI0KDhphZ+xTJJX/9K9YzR5Wkf0eYTZ1cVysTj0haEnzfSGleqRQ0zA7vM2Occ58VsWwFE3F/L1Ysnm0M05CufTeW+3B1qlDXaZ1zE1TT+Ki1pP8G+3GUMrTIEBeUCpN0W6pYItiPbw8NejO4dpOLhrBv/kPxdZFX0idPq9D7d8GvodZXnB41hlEd3EehQRbqw+6SXjWziWZ2brodycz2kDRW8d3s/SvNUysXKf4p4L+Y2Ttm1i/dCczMtjWze5W5FWdWzGwdMztLvtvAi0Kjpks6Nteb1WXkYdV0h9hC0itmtn9ioiCwfUlSs2DQZOV+QbHOBa/+CPfgdqyZbZeQ7LnQ9z+ZWa0nhMxsV/n9YVPVvE89nXBPEXuYWZT3/d4kaWrwfRNJk8zs+FQVSzNbz8zOMrPJkv4QIf9C+pNqKlb7SnrCzNYPJwgqpNdLuiQ0+Brn3BIhlZFm9ryZHWcp3rEdVJYekd9vJelz59wX4TTB/38PDbrfzG5MVQkys2Z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      "text/plain": [
       "<Figure size 2400x600 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 3, figsize=(12, 3))\n",
    "fig.set_dpi(fig_dpi)\n",
    "\n",
    "for idx, ((optimiser_name, tensors_dict), ax) in enumerate(zip(optim_tensors.items(), axes.flatten())):\n",
    "    ax.plot(multi_optim_models, 1 - tensors_dict[\"mean\"][0, :], 'x-', label='Ensemble Test')\n",
    "    ax.plot(multi_optim_models, 1 - tensors_dict[\"mean\"][2, :], 'x-', label='Individual Test')\n",
    "    ax.plot(multi_optim_models, 1 - tensors_dict[\"mean\"][1, :], 'x-', label='Individual Train')\n",
    "    ax.plot(multi_optim_models, 1 - tensors_dict[\"mean\"][3, :], 'x-', label='Disagreement')\n",
    "\n",
    "#     ax.errorbar(multi_optim_models, 1 - tensors_dict[\"mean\"][0, :], yerr=tensors_dict[\"std\"][0, :], capsize=4, label='Ensemble Test')\n",
    "#     ax.errorbar(multi_optim_models, 1 - tensors_dict[\"mean\"][2, :], yerr=tensors_dict[\"std\"][2, :], capsize=4, label='Individual Test')\n",
    "#     ax.errorbar(multi_optim_models, 1 - tensors_dict[\"mean\"][1, :], yerr=tensors_dict[\"std\"][1, :], capsize=4, label='Individual Train')\n",
    "#     ax.errorbar(multi_optim_models, 1 - tensors_dict[\"mean\"][3, :], yerr=tensors_dict[\"std\"][3, :], capsize=4, label='Disagreement')\n",
    "\n",
    "    ax.set_title(f\"{optimiser_name} Error Rate for Ensemble Models\")\n",
    "    ax.set_ylim(0, 0.1)\n",
    "#     ax.set_ylim(0, np.max([np.max(1 - i[\"mean\"] + i[\"std\"]) for i in optim_tensors.values()]) + 0.03)\n",
    "    ax.grid()\n",
    "#     if idx > 0:\n",
    "    ax.legend()\n",
    "    ax.set_xlabel(\"Number of Models\")\n",
    "    ax.set_ylabel(\"Error Rate\")\n",
    "\n",
    "# axes[0].set_ylim(0, 0.4)\n",
    "axes[1].legend()\n",
    "axes[2].legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'graphs/{exp3_testname}-error-rate-curves.png')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "authorship_tag": "ABX9TyNAMGLKzaoWaq1wvQ+w0w8h",
   "collapsed_sections": [],
   "name": "nncw.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.9"
  },
  "toc-autonumbering": false,
  "toc-showcode": false,
  "toc-showmarkdowntxt": false,
  "toc-showtags": false
 },
 "nbformat": 4,
 "nbformat_minor": 4
}