Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis on ResMaskNet FER method using Padova Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lib Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.formula.api import ols\n",
    "from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Directory\n",
    "pred_dir = 'data/combined_results.csv'\n",
    "clips_dir  = 'data/PEDFE_set_clips/'  \n",
    "labels_dir = 'data/Supplemental_Material_T1.csv'\n",
    "\n",
    "# load data to panda dataframe\n",
    "labels = pd.read_csv(labels_dir)\n",
    "predicted_data = pd.read_csv(pred_dir)\n",
    "\n",
    "# emotion to lowercase for comparison\n",
    "labels['Emotion'] = labels['Emotion'].str.lower()\n",
    "\n",
    "# extract highest mean as predicted emotion\n",
    "predicted_data['predicted_emotion'] = predicted_data.iloc[:, 1:].idxmax(axis=1).str.split('_').str[1]\n",
    "\n",
    "# Merge actual and predicted data on 'PEDFE_code'\n",
    "merged_data = pd.merge(labels, predicted_data, on='PEDFE_code')\n",
    "\n",
    "# Create a column (pred) for binary prediction \n",
    "merged_data['pred'] = (merged_data['Emotion'] == merged_data['predicted_emotion']).astype(int)\n",
    "\n",
    "# Select the columns to consider for the highest value\n",
    "emotion_columns = ['mean_anger', 'mean_disgust', 'mean_fear', 'mean_happiness', 'mean_sadness', 'mean_surprise', 'mean_neutral']\n",
    "\n",
    "# Create column (pred (%)) for predication confident (%)\n",
    "merged_data['pred (%)'] = merged_data[emotion_columns].max(axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merged_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "merged_data\n",
      "      PEDFE_code Gender     Type  Mean_Intensity  Mean_Genuineness  \\\n",
      "0        1_dg_1      F  Genuine            2.94              2.12   \n",
      "1        1_dg_2      F  Genuine            3.52              3.00   \n",
      "2        1_dg_3      F  Genuine            5.92              4.96   \n",
      "3        1_dg_4      F  Genuine            3.88              1.88   \n",
      "4        1_dg_5      F  Genuine            3.94              1.30   \n",
      "...         ...    ...      ...             ...               ...   \n",
      "1451    57_tg_3      F  Genuine            2.67              2.62   \n",
      "1452    57_tg_4      F  Genuine            4.00              2.42   \n",
      "1453    57_ts_1      F    Posed            2.70             -0.26   \n",
      "1454    57_ts_2      F    Posed            2.76             -1.91   \n",
      "1455    57_ts_3      F    Posed            3.19             -1.58   \n",
      "\n",
      "      Hit rate Emotion (%)  Emotion predicted_emotion  pred (%)  pred  \n",
      "0                    78.79  disgust           disgust  0.521609     1  \n",
      "1                    54.55  disgust           sadness  0.583805     0  \n",
      "2                   100.00  disgust           sadness  0.712607     0  \n",
      "3                    87.88  disgust           disgust  0.710265     1  \n",
      "4                    63.64  disgust           disgust  0.549518     1  \n",
      "...                    ...      ...               ...       ...   ...  \n",
      "1451                 50.00  sadness           sadness  0.953975     1  \n",
      "1452                 66.67  sadness           sadness  0.888728     1  \n",
      "1453                 71.43  sadness           sadness  0.906891     1  \n",
      "1454                 57.58  sadness           sadness  0.946789     1  \n",
      "1455                 88.89  sadness           sadness  0.972013     1  \n",
      "\n",
      "[1456 rows x 10 columns]\n"
     ]
    }
   ],
   "source": [
    "# Select specified columns\n",
    "selected_columns = [\n",
    "    'PEDFE_code', 'Gender', 'Type', 'Mean_Intensity', 'Mean_Genuineness', \n",
    "    'Hit rate Emotion (%)', 'Emotion', 'predicted_emotion', 'pred (%)','pred'\n",
    "]\n",
    "print(\"merged_data\\n\", merged_data[selected_columns])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split Data to Genuine and Posed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "genuine_data = merged_data[merged_data['Type'] == 'Genuine']\n",
    "posed_data = merged_data[merged_data['Type'] == 'Posed']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation_matrix (Posed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation Matrix\n",
      "                       Mean_Intensity  Mean_Genuineness  Hit rate Emotion (%)  \\\n",
      "Mean_Intensity              1.000000          0.003613              0.316514   \n",
      "Mean_Genuineness            0.003613          1.000000             -0.074059   \n",
      "Hit rate Emotion (%)        0.316514         -0.074059              1.000000   \n",
      "pred (%)                   -0.052041          0.023482              0.183449   \n",
      "\n",
      "                      pred (%)  \n",
      "Mean_Intensity       -0.052041  \n",
      "Mean_Genuineness      0.023482  \n",
      "Hit rate Emotion (%)  0.183449  \n",
      "pred (%)              1.000000  \n",
      "\n",
      "Report\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     disgust       0.70      0.41      0.52       149\n",
      "   happiness       0.74      0.98      0.84       156\n",
      "        fear       0.45      0.11      0.17        93\n",
      "       anger       0.44      0.09      0.15        90\n",
      "    surprise       0.68      0.46      0.55       131\n",
      "     sadness       0.39      0.76      0.52       132\n",
      "\n",
      "   micro avg       0.58      0.52      0.55       751\n",
      "   macro avg       0.57      0.47      0.46       751\n",
      "weighted avg       0.59      0.52      0.50       751\n",
      "\n"
     ]
    }
   ],
   "source": [
    "corr_1 = posed_data[['Mean_Intensity', 'Mean_Genuineness', 'Hit rate Emotion (%)', 'pred (%)']].corr()\n",
    "print(\"Correlation Matrix\\n\",corr_1)\n",
    "\n",
    "y_true = posed_data['Emotion']\n",
    "y_pred = posed_data['predicted_emotion']\n",
    "labels = posed_data['Emotion'].unique()\n",
    "\n",
    "report_1 = classification_report(y_true, y_pred, labels=labels)\n",
    "print(\"\\nReport\\n\",report_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation_matrix (Genuine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation Matrix\n",
      "                       Mean_Intensity  Mean_Genuineness  Hit rate Emotion (%)  \\\n",
      "Mean_Intensity              1.000000          0.356923              0.540691   \n",
      "Mean_Genuineness            0.356923          1.000000              0.214744   \n",
      "Hit rate Emotion (%)        0.540691          0.214744              1.000000   \n",
      "pred (%)                    0.155220          0.176916              0.261928   \n",
      "\n",
      "                      pred (%)  \n",
      "Mean_Intensity        0.155220  \n",
      "Mean_Genuineness      0.176916  \n",
      "Hit rate Emotion (%)  0.261928  \n",
      "pred (%)              1.000000  \n",
      "\n",
      "Report\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     disgust       0.66      0.24      0.35       154\n",
      "   happiness       0.72      0.93      0.81       214\n",
      "        fear       0.25      0.03      0.06        63\n",
      "       anger       0.69      0.14      0.24        76\n",
      "    surprise       0.48      0.19      0.27        79\n",
      "     sadness       0.34      0.66      0.45       119\n",
      "\n",
      "   micro avg       0.55      0.49      0.52       705\n",
      "   macro avg       0.52      0.37      0.36       705\n",
      "weighted avg       0.57      0.49      0.46       705\n",
      "\n"
     ]
    }
   ],
   "source": [
    "corr_2 = genuine_data[['Mean_Intensity', 'Mean_Genuineness', 'Hit rate Emotion (%)', 'pred (%)']].corr()\n",
    "print(\"Correlation Matrix\\n\",corr_2)\n",
    "\n",
    "y_true = genuine_data['Emotion']\n",
    "y_pred = genuine_data['predicted_emotion']\n",
    "labels = genuine_data['Emotion'].unique()\n",
    "\n",
    "report_2 = classification_report(y_true, y_pred, labels=labels)\n",
    "print(\"\\nReport\\n\",report_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlation Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "# Plot for posed correlations\n",
    "plt.subplot(1, 2, 1)  \n",
    "sns.heatmap(corr_1, annot=True, cmap='coolwarm')\n",
    "plt.title(\"Posed Expressions Correlation Matrix\")\n",
    "\n",
    "# Plot for genuine correlations\n",
    "plt.subplot(1, 2, 2)  \n",
    "sns.heatmap(corr_2, annot=True, cmap='coolwarm')\n",
    "plt.title(\"Genuine Expressions Correlation Matrix\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cnnfusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Posed Emotions [[0.43571429 0.11428571 0.         0.00714286 0.00714286 0.43571429]\n",
      " [0.         0.98709677 0.         0.         0.         0.01290323]\n",
      " [0.05063291 0.11392405 0.12658228 0.07594937 0.32911392 0.30379747]\n",
      " [0.18181818 0.03896104 0.         0.1038961  0.01298701 0.66233766]\n",
      " [0.02542373 0.20338983 0.08474576 0.02542373 0.50847458 0.15254237]\n",
      " [0.04587156 0.01834862 0.01834862 0.         0.         0.91743119]]\n",
      "Genuine Emotions [[0.25170068 0.21088435 0.00680272 0.01360544 0.         0.5170068 ]\n",
      " [0.01869159 0.92990654 0.         0.0046729  0.01401869 0.03271028]\n",
      " [0.04255319 0.31914894 0.04255319 0.04255319 0.12765957 0.42553191]\n",
      " [0.11864407 0.06779661 0.         0.18644068 0.10169492 0.52542373]\n",
      " [0.03278689 0.3442623  0.08196721 0.         0.24590164 0.29508197]\n",
      " [0.04395604 0.08791209 0.         0.         0.01098901 0.85714286]]\n",
      "['disgust' 'happiness' 'fear' 'anger' 'surprise' 'sadness']\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 10))\n",
    "\n",
    "# Plot confusion matrix for posed_data\n",
    "actual_emotions = posed_data['Emotion']\n",
    "predicted_emotions = posed_data['predicted_emotion']\n",
    "cm1 = confusion_matrix(actual_emotions, predicted_emotions, labels=actual_emotions.unique(), normalize='true')\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm1, display_labels=actual_emotions.unique())\n",
    "disp.plot(cmap=plt.cm.Blues, ax=ax1)\n",
    "ax1.set_title('Posed Emotions')\n",
    "\n",
    "# Plot confusion matrix for genuine_data\n",
    "actual_emotions = genuine_data['Emotion']\n",
    "predicted_emotions = genuine_data['predicted_emotion']\n",
    "cm2 = confusion_matrix(actual_emotions, predicted_emotions, labels=actual_emotions.unique(), normalize='true')\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm2, display_labels=actual_emotions.unique())\n",
    "disp.plot(cmap=plt.cm.Blues, ax=ax2)\n",
    "ax2.set_title('Genuine Emotions')\n",
    "\n",
    "# raw data\n",
    "print('Posed Emotions',cm1)\n",
    "print('Genuine Emotions',cm2)\n",
    "print(actual_emotions.unique())\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot difference between two CMs\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "cm_diff = cm2-cm1\n",
    "ConfusionMatrixDisplay(cm_diff, display_labels=labels).plot(cmap=plt.cm.RdBu, ax=ax, values_format='.3f')\n",
    "ax.set_title('Difference in Confusion Matrices (Genuine - Posed)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ANOVA (Type II)\n",
    "- Dependent variable: Emotion Classifcation confident mean(%)\n",
    "- Independent variables: 'Mean_Intensity', 'Mean_Genuineness', and 'Hit rate Emotion (%)'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              sum_sq      df          F        PR(>F)\n",
      "Mean_Intensity              0.139040     1.0   3.758497  5.273335e-02\n",
      "Mean_Genuineness            0.511769     1.0  13.833991  2.072959e-04\n",
      "Q(\"Hit rate Emotion (%)\")   2.784032     1.0  75.257086  1.087738e-17\n",
      "Residual                   53.714744  1452.0        NaN           NaN\n"
     ]
    }
   ],
   "source": [
    "# Dependent variable = 'pred (%)'\n",
    "# Independent variables: 'Mean_Intensity', 'Mean_Genuineness', and 'Hit rate Emotion' as \n",
    "model_formula_full = 'Q(\"pred (%)\") ~ Mean_Intensity + Mean_Genuineness + Q(\"Hit rate Emotion (%)\")'\n",
    "\n",
    "# Fit the ANOVA model\n",
    "model_full = ols(model_formula_full, data=merged_data).fit()\n",
    "\n",
    "# Type II ANOVA\n",
    "anova_results_full = sm.stats.anova_lm(model_full, typ=2)\n",
    "\n",
    "# print ANOVA table\n",
    "print(anova_results_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - **Sum of squares**: \n",
    "   - amount of variance in the dependent variable explained by each factor\n",
    " - **Degrees of Freedom**: \n",
    "   - the number of independent values in a data set that are free to vary. \n",
    "   - 1 df means they are continuous variables.\n",
    " - **F-statistic**: \n",
    "   - the result of a ratio of two variances: the variance explained by the factor (between-group variance) divided by the unexplained variance. It helps determine if the means across different groups are significantly different.\n",
    "   - A high F-value indicates that there is more variation between groups than within groups, suggesting that the factor has a significant effect on the dependent variable. \n",
    " - **P-value**: \n",
    "   - the probability of obtaining a result at least as extreme as the one observed, assuming that the null hypothesis (of no effect) is true. Assess the significance of the results.\n",
    "   - A low p-value (less than 0.05) suggests that the observed data are unlikely under the null hypothesis and thus provides evidence against the null hypothesis. "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pyfeat",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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