Chapter6-5 Logistic_Regression_CWRU_Fault_Diagnosis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f43af3fc",
   "metadata": {},
   "source": [
    "# CWRU 轴承故障诊断数据集\n",
    "## 振动信号\n",
    "## 正常工况、内圈故障、外圈故障、滚动体故障\n",
    "- 训练集 测试集：400x4 8:2\n",
    "- 样本大小：1x1024x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5ae095e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn\n",
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "764ce8ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1600, 1024)\n"
     ]
    }
   ],
   "source": [
    "data = np.loadtxt(\"./fault_data/CSWU_4Class.txt\")\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "93986baf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1280, 1024) (320, 1024)\n",
      "(1280,) (320,)\n"
     ]
    }
   ],
   "source": [
    "# create training set and testing set\n",
    "train_data = np.vstack((data[0: 320, :], data[400: 720, :], data[800: 1120, :], data[1200: 1520, :]))\n",
    "test_data = np.vstack((data[320: 400, :], data[720: 800, :], data[1120: 1200, :], data[1520: 1600, :]))\n",
    "\n",
    "print(train_data.shape, test_data.shape)\n",
    "\n",
    "# make label\n",
    "train_label = np.vstack((np.zeros((320, 1), dtype = int), np.full((320, 1), 1), np.full((320, 1), 2), np.full((320, 1), 3)))\n",
    "test_label = np.vstack((np.zeros((80, 1), dtype = int), np.full((80, 1), 1), np.full((80, 1), 2), np.full((80, 1), 3)))\n",
    "\n",
    "train_label = train_label.reshape(-1)\n",
    "test_label = test_label.reshape(-1)\n",
    "\n",
    "print(train_label.shape, test_label.shape)\n",
    "\n",
    "# 打乱样本\n",
    "train_data, train_label = sklearn.utils.shuffle(train_data, train_label, random_state= 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "552d5550",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = LogisticRegression(max_iter= 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ea1276e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(max_iter=200)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(max_iter=200)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(max_iter=200)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(train_data, train_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "804f2146",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.675"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 测试集准确率\n",
    "clf.score(test_data, test_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7cff7889",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.16864086  0.15804494  0.30762431 ...  0.3678884   0.27762931\n",
      "   0.20751829]\n",
      " [-0.08218242 -0.35632894 -0.08907999 ... -0.17217509 -0.06680509\n",
      "   0.10221569]\n",
      " [ 0.20849448  0.27288855  0.22950967 ... -0.40071361 -0.39157583\n",
      "  -0.34915244]\n",
      " [-0.29495291 -0.07460454 -0.448054   ...  0.2050003   0.18075161\n",
      "   0.03941846]] [-1.82838103  2.12149095 -0.6794666   0.38635667]\n"
     ]
    }
   ],
   "source": [
    "print(clf.coef_, clf.intercept_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "22acbd3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(clf.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0656ce70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1024"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(clf.coef_[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ebdee9af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "320\n"
     ]
    }
   ],
   "source": [
    "y_pre = clf.predict(test_data)\n",
    "print(len(y_pre))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "24de2c53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pre[0: 10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0000a84a",
   "metadata": {},
   "source": [
    "# confusion matraix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9bc4414b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "# import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "425296ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_confusion_matrix(true_label, pred_label, class_name):\n",
    "    y_true = true_label\n",
    "    y_pred = pred_label\n",
    "    confusion_mat = confusion_matrix(y_true, y_pred)\n",
    "    print(confusion_mat)\n",
    "    \n",
    "    plt.rcParams['xtick.direction'] = 'in'\n",
    "    plt.rcParams['ytick.direction'] = 'in'\n",
    "    \n",
    "    plt.figure(figsize=(4, 3), dpi = 300)\n",
    "    plt.imshow(confusion_mat, cmap = plt.cm.get_cmap(\"Blues\"))\n",
    "    plt.colorbar()\n",
    "    \n",
    "    indices = range(len(confusion_mat))\n",
    "    \n",
    "    plt.xticks(indices, class_name, rotation = 0)\n",
    "    plt.yticks(indices, class_name)\n",
    "    \n",
    "    plt.title(\"confusion matrix\", fontdict={'fontsize': 12})\n",
    "    plt.xlabel(\"Predcited label\", fontdict={'fontsize': 12})\n",
    "    plt.ylabel(\"True label\", fontdict= {'fontsize': 12})\n",
    "    \n",
    "    for first_index in range(len(confusion_mat)):\n",
    "        for second_index in range(len(confusion_mat[first_index])):\n",
    "            if first_index == second_index:\n",
    "                plt.text(first_index, second_index, confusion_mat[first_index][second_index],\n",
    "                        color = 'white', fontsize = 12, va = 'center', ha = 'center')\n",
    "            else:\n",
    "                plt.text(first_index, second_index, confusion_mat[first_index][second_index],\n",
    "                        color = 'black', fontsize = 12, va = 'center', ha = 'center')\n",
    "                \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2d4580e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[80  0  0  0]\n",
      " [ 0 65  3 12]\n",
      " [ 8 29 30 13]\n",
      " [ 0 32  7 41]]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_true = test_label\n",
    "y_pre = y_pre\n",
    "\n",
    "class_name = [\"Health\", \"Inner\", \"Outer\", \"Ball\"]\n",
    "plot_confusion_matrix(y_true, y_pre, class_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b3736f2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}