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feat/90-fe
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5
.vscode/settings.json
vendored
5
.vscode/settings.json
vendored
@@ -1,4 +1,7 @@
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|||||||
{
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{
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"python.analysis.extraPaths": ["./code/src/features"],
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"python.analysis.extraPaths": [
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"./code/src/features",
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"${workspaceFolder}/code/src"
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],
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"jupyter.notebookFileRoot": "${workspaceFolder}/code"
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"jupyter.notebookFileRoot": "${workspaceFolder}/code"
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}
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}
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@@ -17,8 +17,8 @@
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"metadata": {},
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"metadata": {},
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||||||
"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"sensor1 = pd.read_csv('D:/thesis/data/converted/raw/DAMAGE_1/DAMAGE_1_TEST1_01.csv',sep=',')\n",
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"sensor1 = pd.read_csv('D:/thesis/data/converted/raw/DAMAGE_1/DAMAGE_0_TEST1_01.csv',sep=',')\n",
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"sensor2 = pd.read_csv('D:/thesis/data/converted/raw/DAMAGE_1/DAMAGE_1_TEST1_02.csv',sep=',')"
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"sensor2 = pd.read_csv('D:/thesis/data/converted/raw/DAMAGE_1/DAMAGE_0_TEST1_02.csv',sep=',')"
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]
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]
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},
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},
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{
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{
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@@ -101,13 +101,16 @@
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"source": [
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"source": [
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"# Combined Plot for sensor 1 and sensor 2 from data1 file in which motor is operated at 800 rpm\n",
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"# Combined Plot for sensor 1 and sensor 2 from data1 file in which motor is operated at 800 rpm\n",
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"\n",
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"\n",
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"plt.plot(df1['s2'], label='sensor 2')\n",
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"plt.plot(df1['s2'], label='Sensor 1', color='C1', alpha=0.6)\n",
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"plt.plot(df1['s1'], label='sensor 1', alpha=0.5)\n",
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"plt.plot(df1['s1'], label='Sensor 2', color='C0', alpha=0.6)\n",
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"plt.xlabel(\"Number of samples\")\n",
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"plt.xlabel(\"Number of samples\")\n",
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"plt.ylabel(\"Amplitude\")\n",
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"plt.ylabel(\"Amplitude\")\n",
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"plt.title(\"Raw vibration signal\")\n",
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"plt.title(\"Raw vibration signal\")\n",
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"plt.ylim(-7.5, 5)\n",
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"plt.ylim(-7.5, 5)\n",
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"plt.legend()\n",
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"plt.legend()\n",
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"plt.locator_params(axis='x', nbins=8)\n",
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"plt.ylim(-1, 1) # Adjust range as needed\n",
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"plt.grid(True, linestyle='--', alpha=0.5)\n",
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"plt.show()"
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"plt.show()"
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]
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]
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},
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},
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@@ -334,9 +337,44 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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||||||
"# len(ready_data1a)\n",
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"import numpy as np\n",
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"# plt.pcolormesh(ready_data1[0])\n",
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"import matplotlib.pyplot as plt\n",
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"ready_data1a[0].max().max()"
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"from mpl_toolkits.mplot3d import Axes3D\n",
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"\n",
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"# Assuming ready_data1a[0] is a DataFrame or 2D array\n",
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"spectrogram_data = ready_data1a[0].values # Convert to NumPy array if it's a DataFrame\n",
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"\n",
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"# Get the dimensions of the spectrogram\n",
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"num_frequencies, num_time_frames = spectrogram_data.shape\n",
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"\n",
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"# Create frequency and time arrays\n",
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"frequencies = np.arange(num_frequencies) # Replace with actual frequency values if available\n",
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"time_frames = np.arange(num_time_frames) # Replace with actual time values if available\n",
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"\n",
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"# Create a meshgrid for plotting\n",
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"T, F = np.meshgrid(time_frames, frequencies)\n",
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"\n",
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"# Create a 3D plot\n",
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"fig = plt.figure(figsize=(12, 8))\n",
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"ax = fig.add_subplot(111, projection='3d')\n",
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"\n",
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"# Plot the surface\n",
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"surf = ax.plot_surface(T, F, spectrogram_data, cmap='bwr', edgecolor='none')\n",
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"\n",
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"# Add labels and a color bar\n",
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"ax.set_xlabel('Time Frames')\n",
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"ax.set_ylabel('Frequency [Hz]')\n",
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"ax.set_zlabel('Magnitude')\n",
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"ax.set_title('3D Spectrogram')\n",
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"# Resize the z-axis (shrink it)\n",
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"z_min, z_max = 0, 0.1 # Replace with your desired range\n",
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"ax.set_zlim(z_min, z_max)\n",
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"ax.get_proj = lambda: np.dot(Axes3D.get_proj(ax), np.diag([1, 1, 0.5, 1])) # Shrink z-axis by 50%\n",
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"ax.set_facecolor('white')\n",
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"fig.colorbar(surf, ax=ax, shrink=0.5, aspect=10)\n",
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"\n",
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"# Show the plot\n",
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"plt.show()"
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]
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]
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},
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},
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{
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{
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@@ -345,12 +383,31 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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||||||
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"from cmcrameri import cm\n",
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"# Create a figure and subplots\n",
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"fig, axes = plt.subplots(2, 3, figsize=(15, 8), sharex=True, sharey=True)\n",
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"\n",
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"# Flatten the axes array for easier iteration\n",
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"axes = axes.flatten()\n",
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"\n",
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"# Loop through each subplot and plot the data\n",
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"for i in range(6):\n",
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"for i in range(6):\n",
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" plt.pcolormesh(ready_data1a[i], cmap=\"jet\", vmax=0.03, vmin=0.0)\n",
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" pcm = axes[i].pcolormesh(ready_data1a[i].transpose(), cmap='bwr', vmax=0.03, vmin=0.0)\n",
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||||||
" plt.colorbar() \n",
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" axes[i].set_title(f'Case {i} Sensor A', fontsize=12)\n",
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||||||
" plt.title(f'STFT Magnitude for case {i} sensor 1')\n",
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"\n",
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" plt.xlabel(f'Frequency [Hz]')\n",
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"# Add a single color bar for all subplots\n",
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" plt.ylabel(f'Time [sec]')\n",
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"# Use the first `pcolormesh` object (or any valid one) for the color bar\n",
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"cbar = fig.colorbar(pcm, ax=axes, orientation='vertical')\n",
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"# cbar.set_label('Magnitude')\n",
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"\n",
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"# Set shared labels\n",
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"fig.text(0.5, 0.04, 'Time Frames', ha='center', fontsize=12)\n",
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"fig.text(0.04, 0.5, 'Frequency [Hz]', va='center', rotation='vertical', fontsize=12)\n",
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"\n",
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"# Adjust layout\n",
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"# plt.tight_layout(rect=[0.05, 0.05, 1, 1]) # Leave space for shared labels\n",
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"plt.subplots_adjust(left=0.1, right=0.75, top=0.9, bottom=0.1, wspace=0.2, hspace=0.2)\n",
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"\n",
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"plt.show()"
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"plt.show()"
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]
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]
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},
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},
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@@ -576,6 +633,16 @@
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"X2a, y = create_ready_data('D:/thesis/data/converted/raw/sensor2')"
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"X2a, y = create_ready_data('D:/thesis/data/converted/raw/sensor2')"
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]
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]
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},
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},
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{
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"cell_type": "code",
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"execution_count": null,
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||||||
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"metadata": {},
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||||||
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"outputs": [],
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"source": [
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"X1a.iloc[-1,:]\n",
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"# y[2565]"
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]
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},
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{
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{
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||||||
"cell_type": "code",
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"cell_type": "code",
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||||||
"execution_count": null,
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"execution_count": null,
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||||||
@@ -621,23 +688,8 @@
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|||||||
"metadata": {},
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"metadata": {},
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||||||
"outputs": [],
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"outputs": [],
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||||||
"source": [
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"source": [
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||||||
"def train_and_evaluate_model(model, model_name, sensor_label, x_train, y_train, x_test, y_test):\n",
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"from src.ml.model_selection import train_and_evaluate_model\n",
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||||||
" model.fit(x_train, y_train)\n",
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"from sklearn.svm import SVC\n",
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||||||
" y_pred = model.predict(x_test)\n",
|
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||||||
" accuracy = accuracy_score(y_test, y_pred) * 100\n",
|
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||||||
" return {\n",
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" \"model\": model_name,\n",
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" \"sensor\": sensor_label,\n",
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" \"accuracy\": accuracy\n",
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||||||
" }"
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]
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||||||
},
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||||||
{
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||||||
"cell_type": "code",
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"execution_count": null,
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||||||
"metadata": {},
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||||||
"outputs": [],
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||||||
"source": [
|
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||||||
"# Define models for sensor1\n",
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"# Define models for sensor1\n",
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"models_sensor1 = {\n",
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"models_sensor1 = {\n",
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" # \"Random Forest\": RandomForestClassifier(),\n",
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" # \"Random Forest\": RandomForestClassifier(),\n",
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@@ -646,12 +698,12 @@
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" # \"KNN\": KNeighborsClassifier(),\n",
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" # \"KNN\": KNeighborsClassifier(),\n",
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" # \"LDA\": LinearDiscriminantAnalysis(),\n",
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" # \"LDA\": LinearDiscriminantAnalysis(),\n",
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" \"SVM\": SVC(),\n",
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" \"SVM\": SVC(),\n",
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" \"XGBoost\": XGBClassifier()\n",
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" # \"XGBoost\": XGBClassifier()\n",
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"}\n",
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"}\n",
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"\n",
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"\n",
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"results_sensor1 = []\n",
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"results_sensor1 = []\n",
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"for name, model in models_sensor1.items():\n",
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"for name, model in models_sensor1.items():\n",
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" res = train_and_evaluate_model(model, name, \"sensor1\", x_train1, y_train, x_test1, y_test)\n",
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" res = train_and_evaluate_model(model, name, \"sensor1\", x_train1, y_train, x_test1, y_test, export='D:/thesis/models/sensor1')\n",
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" results_sensor1.append(res)\n",
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" results_sensor1.append(res)\n",
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" print(f\"{name} on sensor1: Accuracy = {res['accuracy']:.2f}%\")\n"
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" print(f\"{name} on sensor1: Accuracy = {res['accuracy']:.2f}%\")\n"
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]
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]
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@@ -669,12 +721,12 @@
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" # \"KNN\": KNeighborsClassifier(),\n",
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" # \"KNN\": KNeighborsClassifier(),\n",
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" # \"LDA\": LinearDiscriminantAnalysis(),\n",
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" # \"LDA\": LinearDiscriminantAnalysis(),\n",
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" \"SVM\": SVC(),\n",
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" \"SVM\": SVC(),\n",
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" \"XGBoost\": XGBClassifier()\n",
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" # \"XGBoost\": XGBClassifier()\n",
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"}\n",
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"}\n",
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"\n",
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"\n",
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"results_sensor2 = []\n",
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"results_sensor2 = []\n",
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"for name, model in models_sensor2.items():\n",
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"for name, model in models_sensor2.items():\n",
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" res = train_and_evaluate_model(model, name, \"sensor2\", x_train2, y_train, x_test2, y_test)\n",
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" res = train_and_evaluate_model(model, name, \"sensor2\", x_train2, y_train, x_test2, y_test, export='D:/thesis/models/sensor2')\n",
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" results_sensor2.append(res)\n",
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" results_sensor2.append(res)\n",
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" print(f\"{name} on sensor2: Accuracy = {res['accuracy']:.2f}%\")\n"
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" print(f\"{name} on sensor2: Accuracy = {res['accuracy']:.2f}%\")\n"
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]
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]
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@@ -787,6 +839,8 @@
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"source": [
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"source": [
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"from sklearn.metrics import accuracy_score, classification_report\n",
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"from sklearn.metrics import accuracy_score, classification_report\n",
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"# 4. Validate on Dataset B\n",
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"# 4. Validate on Dataset B\n",
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"from joblib import load\n",
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"svm_model = load('D:/thesis/models/sensor1/SVM.joblib')\n",
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"y_pred_svm = svm_model.predict(X1b)\n",
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"y_pred_svm = svm_model.predict(X1b)\n",
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"\n",
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"\n",
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"# 5. Evaluate\n",
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"# 5. Evaluate\n",
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@@ -794,6 +848,30 @@
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"print(classification_report(y, y_pred_svm))"
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"print(classification_report(y, y_pred_svm))"
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]
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]
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},
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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||||||
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"### Model sensor 1 to predict sensor 2 data"
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": null,
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||||||
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"metadata": {},
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"outputs": [],
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||||||
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"source": [
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||||||
|
"from sklearn.metrics import accuracy_score, classification_report\n",
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||||||
|
"# 4. Validate on Dataset B\n",
|
||||||
|
"from joblib import load\n",
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||||||
|
"svm_model = load('D:/thesis/models/sensor1/SVM.joblib')\n",
|
||||||
|
"y_pred_svm = svm_model.predict(X2b)\n",
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|
"\n",
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||||||
|
"# 5. Evaluate\n",
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||||||
|
"print(\"Accuracy on Dataset B:\", accuracy_score(y, y_pred_svm))\n",
|
||||||
|
"print(classification_report(y, y_pred_svm))"
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||||||
|
]
|
||||||
|
},
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||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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@@ -853,7 +931,7 @@
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"# Plot\n",
|
"# Plot\n",
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"disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=labels)\n",
|
"disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=labels)\n",
|
||||||
"disp.plot(cmap=plt.cm.Blues) # You can change colormap\n",
|
"disp.plot(cmap=plt.cm.Blues) # You can change colormap\n",
|
||||||
"plt.title(\"SVM Sensor1 CM Train w/ Dataset A Val w/ Dataset B\")\n",
|
"plt.title(\"SVM Sensor1 CM Train w/ Dataset A Val w/ Dataset B from Sensor2 readings\")\n",
|
||||||
"plt.show()"
|
"plt.show()"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
@@ -871,14 +949,14 @@
|
|||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
"# 1. Predict sensor 1 on Dataset A\n",
|
"# 1. Predict sensor 1 on Dataset A\n",
|
||||||
"y_train_pred = svm_model.predict(x_train1)\n",
|
"y_test_pred = svm_model.predict(x_test1)\n",
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"\n",
|
"\n",
|
||||||
"# 2. Import confusion matrix tools\n",
|
"# 2. Import confusion matrix tools\n",
|
||||||
"from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
|
"from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
|
||||||
"import matplotlib.pyplot as plt\n",
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"import matplotlib.pyplot as plt\n",
|
||||||
"\n",
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"\n",
|
||||||
"# 3. Create and plot confusion matrix\n",
|
"# 3. Create and plot confusion matrix\n",
|
||||||
"cm_train = confusion_matrix(y_train, y_train_pred)\n",
|
"cm_train = confusion_matrix(y_test, y_test_pred)\n",
|
||||||
"labels = svm_model.classes_\n",
|
"labels = svm_model.classes_\n",
|
||||||
"\n",
|
"\n",
|
||||||
"disp = ConfusionMatrixDisplay(confusion_matrix=cm_train, display_labels=labels)\n",
|
"disp = ConfusionMatrixDisplay(confusion_matrix=cm_train, display_labels=labels)\n",
|
||||||
|
|||||||
@@ -55,3 +55,101 @@ def create_ready_data(
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|||||||
y = np.array([])
|
y = np.array([])
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||||||
|
|
||||||
return X, y
|
return X, y
|
||||||
|
|
||||||
|
|
||||||
|
def train_and_evaluate_model(
|
||||||
|
model, model_name, sensor_label, x_train, y_train, x_test, y_test, export=None
|
||||||
|
):
|
||||||
|
"""
|
||||||
|
Train a machine learning model, evaluate its performance, and optionally export it.
|
||||||
|
|
||||||
|
This function trains the provided model on the training data, evaluates its
|
||||||
|
performance on test data using accuracy score, and can save the trained model
|
||||||
|
to disk if an export path is provided.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
model : estimator object
|
||||||
|
The machine learning model to train.
|
||||||
|
model_name : str
|
||||||
|
Name of the model, used for the export filename and in the returned results.
|
||||||
|
sensor_label : str
|
||||||
|
Label identifying which sensor's data the model is being trained on.
|
||||||
|
x_train : array-like or pandas.DataFrame
|
||||||
|
The training input samples.
|
||||||
|
y_train : array-like
|
||||||
|
The target values for training.
|
||||||
|
x_test : array-like or pandas.DataFrame
|
||||||
|
The test input samples.
|
||||||
|
y_test : array-like
|
||||||
|
The target values for testing.
|
||||||
|
export : str, optional
|
||||||
|
Directory path where the trained model should be saved. If None, model won't be saved.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
dict
|
||||||
|
Dictionary containing:
|
||||||
|
- 'model': model_name (str)
|
||||||
|
- 'sensor': sensor_label (str)
|
||||||
|
- 'accuracy': accuracy percentage (float)
|
||||||
|
|
||||||
|
Example
|
||||||
|
-------
|
||||||
|
>>> from sklearn.svm import SVC
|
||||||
|
>>> from sklearn.model_selection import train_test_split
|
||||||
|
>>> X_train, X_test, y_train, y_test = train_test_split(features, labels, test_size=0.2)
|
||||||
|
>>> result = train_and_evaluate_model(
|
||||||
|
... SVC(),
|
||||||
|
... "SVM",
|
||||||
|
... "sensor1",
|
||||||
|
... X_train,
|
||||||
|
... y_train,
|
||||||
|
... X_test,
|
||||||
|
... y_test,
|
||||||
|
... export="models/sensor1"
|
||||||
|
... )
|
||||||
|
>>> print(f"Model accuracy: {result['accuracy']:.2f}%")
|
||||||
|
"""
|
||||||
|
from sklearn.metrics import accuracy_score
|
||||||
|
|
||||||
|
result = {"model": model_name, "sensor": sensor_label, "success": False}
|
||||||
|
|
||||||
|
try:
|
||||||
|
# Train the model
|
||||||
|
model.fit(x_train, y_train)
|
||||||
|
|
||||||
|
try:
|
||||||
|
y_pred = model.predict(x_test)
|
||||||
|
except Exception as e:
|
||||||
|
result["error"] = f"Prediction error: {str(e)}"
|
||||||
|
return result
|
||||||
|
|
||||||
|
# Calculate accuracy
|
||||||
|
try:
|
||||||
|
accuracy = accuracy_score(y_test, y_pred) * 100
|
||||||
|
result["accuracy"] = accuracy
|
||||||
|
except Exception as e:
|
||||||
|
result["error"] = f"Accuracy calculation error: {str(e)}"
|
||||||
|
return result
|
||||||
|
|
||||||
|
# Export model if requested
|
||||||
|
if export:
|
||||||
|
try:
|
||||||
|
import joblib
|
||||||
|
|
||||||
|
full_path = os.path.join(export, f"{model_name}.joblib")
|
||||||
|
os.makedirs(os.path.dirname(full_path), exist_ok=True)
|
||||||
|
joblib.dump(model, full_path)
|
||||||
|
print(f"Model saved to {full_path}")
|
||||||
|
except Exception as e:
|
||||||
|
print(f"Warning: Failed to export model to {export}: {str(e)}")
|
||||||
|
result["export_error"] = str(e)
|
||||||
|
# Continue despite export error
|
||||||
|
|
||||||
|
result["success"] = True
|
||||||
|
return result
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
result["error"] = f"Training error: {str(e)}"
|
||||||
|
return result
|
||||||
|
|||||||
@@ -3,7 +3,7 @@ Alur keseluruhan penelitian ini dilakukan melalui tahapan-tahapan sebagai beriku
|
|||||||
|
|
||||||
\begin{figure}[H]
|
\begin{figure}[H]
|
||||||
\centering
|
\centering
|
||||||
\includegraphics[width=0.3\linewidth]{chapters/id/flow.png}
|
\includegraphics[width=0.3\linewidth]{chapters/img/flow.png}
|
||||||
\caption{Diagram alir tahapan penelitian}
|
\caption{Diagram alir tahapan penelitian}
|
||||||
\label{fig:flowchart}
|
\label{fig:flowchart}
|
||||||
\end{figure}
|
\end{figure}
|
||||||
|
|||||||
@@ -1,14 +1,18 @@
|
|||||||
\documentclass[draftmark]{thesis}
|
\documentclass[draftmark]{thesis}
|
||||||
|
|
||||||
% Title Information
|
% Metadata
|
||||||
\setthesisinfo
|
\title{Prediksi Lokasi Kerusakan dengan Machine Learning}
|
||||||
{Prediksi Lokasi Kerusakan dengan Machine Learning}
|
\author{Rifqi Damar Panuluh}
|
||||||
{Rifqi Damar Panuluh}
|
\date{\today}
|
||||||
{20210110224}
|
\authorid{20210110224}
|
||||||
{PROGRAM STUDI TEKNIK SIPIL}
|
\firstadvisor{Ir. Muhammad Ibnu Syamsi, Ph.D.}
|
||||||
{FAKULTAS TEKNIK}
|
\secondadvisor{}
|
||||||
{UNIVERSITAS MUHAMMADIYAH YOGYAKARTA}
|
\headdepartement{Puji Harsanto, S.T., M.T., Ph.D.}
|
||||||
{2025}
|
\headdepartementid{19740607201404123064}
|
||||||
|
\faculty{Fakultas Teknik}
|
||||||
|
\program{Program Studi Teknik Sipil}
|
||||||
|
\university{Universitas Muhammadiyah Yogyakarta}
|
||||||
|
\yearofsubmission{2025}
|
||||||
|
|
||||||
% Input preamble
|
% Input preamble
|
||||||
\input{preamble/packages}
|
\input{preamble/packages}
|
||||||
@@ -16,13 +20,13 @@
|
|||||||
\input{preamble/macros}
|
\input{preamble/macros}
|
||||||
|
|
||||||
\begin{document}
|
\begin{document}
|
||||||
\input{frontmatter/maketitle}
|
% \input{frontmatter/maketitle}
|
||||||
\input{frontmatter/maketitle_secondary}
|
% \input{frontmatter/maketitle_secondary}
|
||||||
\frontmatter
|
\frontmatter
|
||||||
% \input{frontmatter/approval}\clearpage
|
% \input{frontmatter/approval}\clearpage
|
||||||
% \input{frontmatter/originality}\clearpage
|
% \input{frontmatter/originality}\clearpage
|
||||||
% \input{frontmatter/acknowledgement}\clearpage
|
% \input{frontmatter/acknowledgement}\clearpage
|
||||||
\tableofcontents
|
% \tableofcontents
|
||||||
\clearpage
|
\clearpage
|
||||||
\mainmatter
|
\mainmatter
|
||||||
\pagestyle{fancyplain}
|
\pagestyle{fancyplain}
|
||||||
|
|||||||
@@ -1,11 +0,0 @@
|
|||||||
\newcommand{\studentname}{Rifqi Damar Panuluh}
|
|
||||||
\newcommand{\studentid}{20210110224}
|
|
||||||
\newcommand{\thesistitle}{Prediksi Lokasi Kerusakan dengan Machine Learning}
|
|
||||||
\newcommand{\firstadvisor}{Ir. Muhammad Ibnu Syamsi, Ph.D.}
|
|
||||||
\newcommand{\secondadvisor}{}
|
|
||||||
\newcommand{\headdepartement}{Puji Harsanto, S.T. M.T., Ph.D.}
|
|
||||||
\newcommand{\headdepartementid}{19740607201404123064}
|
|
||||||
\newcommand{\faculty}{Fakultas Teknik}
|
|
||||||
\newcommand{\program}{Teknik Sipil}
|
|
||||||
\newcommand{\university}{Universitas Muhammadiyah Yogyakarta}
|
|
||||||
\newcommand{\yearofsubmission}{2025}
|
|
||||||
212
latex/thesis.cls
212
latex/thesis.cls
@@ -1,7 +1,7 @@
|
|||||||
\NeedsTeXFormat{LaTeX2e}
|
\NeedsTeXFormat{LaTeX2e}
|
||||||
\ProvidesClass{thesis}[2025/05/10 Bachelor Thesis Class]
|
\ProvidesClass{thesis}[2025/05/10 Bachelor Thesis Class]
|
||||||
|
|
||||||
\newif\if@draftmark
|
\newif\if@draftmark \@draftmarkfalse
|
||||||
\@draftmarkfalse
|
\@draftmarkfalse
|
||||||
|
|
||||||
\DeclareOption{draftmark}{\@draftmarktrue}
|
\DeclareOption{draftmark}{\@draftmarktrue}
|
||||||
@@ -12,6 +12,7 @@
|
|||||||
\RequirePackage{polyglossia}
|
\RequirePackage{polyglossia}
|
||||||
\RequirePackage{fontspec}
|
\RequirePackage{fontspec}
|
||||||
\RequirePackage{titlesec}
|
\RequirePackage{titlesec}
|
||||||
|
\RequirePackage{titling}
|
||||||
\RequirePackage{fancyhdr}
|
\RequirePackage{fancyhdr}
|
||||||
\RequirePackage{geometry}
|
\RequirePackage{geometry}
|
||||||
\RequirePackage{setspace}
|
\RequirePackage{setspace}
|
||||||
@@ -24,7 +25,8 @@
|
|||||||
\RequirePackage{svg} % Allows including SVG images directly
|
\RequirePackage{svg} % Allows including SVG images directly
|
||||||
\RequirePackage{indentfirst} % Makes first paragraph after headings indented
|
\RequirePackage{indentfirst} % Makes first paragraph after headings indented
|
||||||
\RequirePackage{float} % Provides [H] option to force figure/table placement
|
\RequirePackage{float} % Provides [H] option to force figure/table placement
|
||||||
\RequirePackage[style=apa, backend=biber, language=indonesian]{biblatex}
|
\RequirePackage[style=apa, backend=biber]{biblatex}
|
||||||
|
\RequirePackage[acronym, nogroupskip, toc]{glossaries}
|
||||||
% Polyglossia set language
|
% Polyglossia set language
|
||||||
\setdefaultlanguage[variant=indonesian]{malay} % Proper Indonesian language setup
|
\setdefaultlanguage[variant=indonesian]{malay} % Proper Indonesian language setup
|
||||||
\setotherlanguage{english} % Enables English as secondary language
|
\setotherlanguage{english} % Enables English as secondary language
|
||||||
@@ -36,17 +38,18 @@
|
|||||||
% Conditionally load the watermark package and settings
|
% Conditionally load the watermark package and settings
|
||||||
\if@draftmark
|
\if@draftmark
|
||||||
\RequirePackage{draftwatermark}
|
\RequirePackage{draftwatermark}
|
||||||
\SetWatermarkText{nuluh/thesis (wip) draft: \today}
|
\SetWatermarkText{nuluh/thesis (wip) [draft: \today]}
|
||||||
\SetWatermarkColor[gray]{0.8} % Opacity: 0.8 = 20% transparent
|
\SetWatermarkColor[gray]{0.8} % Opacity: 0.8 = 20% transparent
|
||||||
\SetWatermarkFontSize{1.5cm}
|
\SetWatermarkFontSize{1.5cm}
|
||||||
\SetWatermarkAngle{90}
|
\SetWatermarkAngle{90}
|
||||||
\SetWatermarkHorCenter{1.5cm}
|
\SetWatermarkHorCenter{1.5cm}
|
||||||
|
\RequirePackage[left]{lineno}
|
||||||
|
\linenumbers
|
||||||
\fi
|
\fi
|
||||||
|
|
||||||
% Page layout
|
% Page layout
|
||||||
\geometry{left=3cm, top=3cm, right=3cm, bottom=3cm}
|
\geometry{left=4cm, top=3cm, right=3cm, bottom=3cm}
|
||||||
\setlength{\parskip}{0.5em}
|
\setlength{\parskip}{0.5em}
|
||||||
\setlength{\parindent}{0pt}
|
|
||||||
\onehalfspacing
|
\onehalfspacing
|
||||||
|
|
||||||
% Fonts
|
% Fonts
|
||||||
@@ -55,17 +58,45 @@
|
|||||||
\setsansfont{Arial}
|
\setsansfont{Arial}
|
||||||
\setmonofont{Courier New}
|
\setmonofont{Courier New}
|
||||||
|
|
||||||
|
\makeatletter
|
||||||
\newcommand{\setthesisinfo}[7]{%
|
% Extracting the Year from \today
|
||||||
\renewcommand{\thesistitle}{#1}%
|
\newcommand{\theyear}{%
|
||||||
\renewcommand{\studentname}{#2}%
|
\expandafter\@car\expandafter\@gobble\the\year\@nil
|
||||||
\renewcommand{\studentid}{#3}%
|
|
||||||
\renewcommand{\program}{#4}%
|
|
||||||
\renewcommand{\faculty}{#5}%
|
|
||||||
\renewcommand{\university}{#6}%
|
|
||||||
\renewcommand{\yearofsubmission}{#7}%
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
% Declare internal macros as initially empty
|
||||||
|
\newcommand{\@authorid}{}
|
||||||
|
\newcommand{\@firstadvisor}{}
|
||||||
|
\newcommand{\@secondadvisor}{}
|
||||||
|
\newcommand{\@headdepartement}{}
|
||||||
|
\newcommand{\@headdepartementid}{}
|
||||||
|
\newcommand{\@faculty}{}
|
||||||
|
\newcommand{\@program}{}
|
||||||
|
\newcommand{\@university}{}
|
||||||
|
\newcommand{\@yearofsubmission}{}
|
||||||
|
|
||||||
|
% Define user commands to set these values.
|
||||||
|
\newcommand{\authorid}[1]{\gdef\@authorid{#1}}
|
||||||
|
\newcommand{\firstadvisor}[1]{\gdef\@firstadvisor{#1}}
|
||||||
|
\newcommand{\secondadvisor}[1]{\gdef\@secondadvisor{#1}}
|
||||||
|
\newcommand{\headdepartement}[1]{\gdef\@headdepartement{#1}}
|
||||||
|
\newcommand{\headdepartementid}[1]{\gdef\@headdepartementid{#1}}
|
||||||
|
\newcommand{\faculty}[1]{\gdef\@faculty{#1}}
|
||||||
|
\newcommand{\program}[1]{\gdef\@program{#1}}
|
||||||
|
\newcommand{\university}[1]{\gdef\@university{#1}}
|
||||||
|
\newcommand{\yearofsubmission}[1]{\gdef\@yearofsubmission{#1}}
|
||||||
|
|
||||||
|
% Now expose robust “the‑” getters to access the values
|
||||||
|
\newcommand{\theauthorid}{\@authorid}
|
||||||
|
\newcommand{\thefirstadvisor}{\@firstadvisor}
|
||||||
|
\newcommand{\thesecondadvisor}{\@secondadvisor}
|
||||||
|
\newcommand{\theheaddepartement}{\@headdepartement}
|
||||||
|
\newcommand{\theheaddepartementid}{\@headdepartementid}
|
||||||
|
\newcommand{\thefaculty}{\@faculty}
|
||||||
|
\newcommand{\theprogram}{\@program}
|
||||||
|
\newcommand{\theuniversity}{\@university}
|
||||||
|
\newcommand{\theyearofsubmission}{\@yearofsubmission}
|
||||||
|
\makeatother
|
||||||
% % Header and footer
|
% % Header and footer
|
||||||
\fancypagestyle{fancy}{%
|
\fancypagestyle{fancy}{%
|
||||||
\fancyhf{}
|
\fancyhf{}
|
||||||
@@ -107,8 +138,6 @@
|
|||||||
\renewcommand{\cftchappresnum}{BAB~}
|
\renewcommand{\cftchappresnum}{BAB~}
|
||||||
\renewcommand{\cftchapaftersnum}{\quad}
|
\renewcommand{\cftchapaftersnum}{\quad}
|
||||||
|
|
||||||
% \titlespacing*{\chapter}{0pt}{-10pt}{20pt}
|
|
||||||
|
|
||||||
% Chapter & Section format
|
% Chapter & Section format
|
||||||
\renewcommand{\cftchapfont}{\normalsize\MakeUppercase}
|
\renewcommand{\cftchapfont}{\normalsize\MakeUppercase}
|
||||||
% \renewcommand{\cftsecfont}{}
|
% \renewcommand{\cftsecfont}{}
|
||||||
@@ -130,11 +159,15 @@
|
|||||||
\setlength{\cftsubsecnumwidth}{2.5em}
|
\setlength{\cftsubsecnumwidth}{2.5em}
|
||||||
\setlength{\cftfignumwidth}{5em}
|
\setlength{\cftfignumwidth}{5em}
|
||||||
\setlength{\cfttabnumwidth}{4em}
|
\setlength{\cfttabnumwidth}{4em}
|
||||||
\renewcommand \cftchapdotsep{1} % Denser dots (closer together) https://tex.stackexchange.com/a/273764
|
\renewcommand \cftchapdotsep{1} % https://tex.stackexchange.com/a/273764
|
||||||
\renewcommand \cftsecdotsep{1} % Apply to sections too
|
\renewcommand \cftsecdotsep{1} % https://tex.stackexchange.com/a/273764
|
||||||
\renewcommand \cftsubsecdotsep{1} % Apply to subsections too
|
\renewcommand \cftsubsecdotsep{1} % https://tex.stackexchange.com/a/273764
|
||||||
|
\renewcommand \cftfigdotsep{1.5} % https://tex.stackexchange.com/a/273764
|
||||||
|
\renewcommand \cfttabdotsep{1.5} % https://tex.stackexchange.com/a/273764
|
||||||
\renewcommand{\cftchapleader}{\normalfont\cftdotfill{\cftsecdotsep}}
|
\renewcommand{\cftchapleader}{\normalfont\cftdotfill{\cftsecdotsep}}
|
||||||
\renewcommand{\cftchappagefont}{\normalfont}
|
\renewcommand{\cftchappagefont}{\normalfont}
|
||||||
|
|
||||||
|
% Add Prefix in the Lof and LoT entries
|
||||||
\renewcommand{\cftfigpresnum}{\figurename~}
|
\renewcommand{\cftfigpresnum}{\figurename~}
|
||||||
\renewcommand{\cfttabpresnum}{\tablename~}
|
\renewcommand{\cfttabpresnum}{\tablename~}
|
||||||
|
|
||||||
@@ -159,6 +192,147 @@
|
|||||||
% \renewcommand{\cfttoctitlefont}{\bfseries\MakeUppercase}
|
% \renewcommand{\cfttoctitlefont}{\bfseries\MakeUppercase}
|
||||||
% \renewcommand{\cftaftertoctitle}{\vskip 2em}
|
% \renewcommand{\cftaftertoctitle}{\vskip 2em}
|
||||||
|
|
||||||
|
% Defines a new glossary called “notation”
|
||||||
|
\newglossary[nlg]{notation}{not}{ntn}{Notation}
|
||||||
|
|
||||||
|
% Define the header for the location column
|
||||||
|
\providecommand*{\locationname}{Location}
|
||||||
|
|
||||||
|
% Define the new glossary style called 'mylistalt' for main glossaries
|
||||||
|
\makeatletter
|
||||||
|
\newglossarystyle{mylistalt}{%
|
||||||
|
% start the list, initializing glossaries internals
|
||||||
|
\renewenvironment{theglossary}%
|
||||||
|
{\glslistinit\begin{enumerate}}%
|
||||||
|
{\end{enumerate}}%
|
||||||
|
% suppress all headers/groupskips
|
||||||
|
\renewcommand*{\glossaryheader}{}%
|
||||||
|
\renewcommand*{\glsgroupheading}[1]{}%
|
||||||
|
\renewcommand*{\glsgroupskip}{}%
|
||||||
|
% main entries: let \item produce "1." etc., then break
|
||||||
|
\renewcommand*{\glossentry}[2]{%
|
||||||
|
\item \glstarget{##1}{\glossentryname{##1}}%
|
||||||
|
\mbox{}\\
|
||||||
|
\glossentrydesc{##1}\space
|
||||||
|
[##2] % appears on page x
|
||||||
|
}%
|
||||||
|
% sub-entries as separate paragraphs, still aligned
|
||||||
|
\renewcommand*{\subglossentry}[3]{%
|
||||||
|
\par
|
||||||
|
\glssubentryitem{##2}%
|
||||||
|
\glstarget{##2}{\strut}\space
|
||||||
|
\glossentrydesc{##2}\space ##3%
|
||||||
|
}%
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
% Define the new glossary style 'altlong3customheader' for notation
|
||||||
|
\newglossarystyle{altlong3customheader}{%
|
||||||
|
% The glossary will be a longtable environment with three columns:
|
||||||
|
% 1. Symbol (left-aligned)
|
||||||
|
% 2. Description (paragraph, width \glsdescwidth)
|
||||||
|
% 3. Location (paragraph, width \glspagelistwidth)
|
||||||
|
\renewenvironment{theglossary}%
|
||||||
|
{\begin{longtable}{lp{\glsdescwidth}p{\glspagelistwidth}}}%
|
||||||
|
{\end{longtable}}%
|
||||||
|
% Define the table header row
|
||||||
|
\renewcommand*{\symbolname}{Simbol}
|
||||||
|
\renewcommand*{\descriptionname}{Keterangan}
|
||||||
|
\renewcommand*{\locationname}{Halaman}
|
||||||
|
\renewcommand*{\glossaryheader}{%
|
||||||
|
\bfseries\symbolname & \bfseries\descriptionname & \bfseries\locationname \tabularnewline\endhead}%
|
||||||
|
% Suppress group headings (e.g., A, B, C...)
|
||||||
|
\renewcommand*{\glsgroupheading}[1]{}%
|
||||||
|
% Define how a main glossary entry is displayed
|
||||||
|
% ##1 is the entry label
|
||||||
|
% ##2 is the location list (page numbers)
|
||||||
|
\renewcommand{\glossentry}[2]{%
|
||||||
|
\glsentryitem{##1}% Inserts entry number if entrycounter option is used
|
||||||
|
\glstarget{##1}{\glossentryname{##1}} & % Column 1: Symbol (with hyperlink target)
|
||||||
|
\glossentrydesc{##1}\glspostdescription & % Column 2: Description (with post-description punctuation)
|
||||||
|
##2\tabularnewline % Column 3: Location list
|
||||||
|
}%
|
||||||
|
% Define how a sub-entry is displayed
|
||||||
|
% ##1 is the sub-entry level (e.g., 1 for first sub-level)
|
||||||
|
% ##2 is the entry label
|
||||||
|
% ##3 is the location list
|
||||||
|
\renewcommand{\subglossentry}[3]{%
|
||||||
|
& % Column 1 (Symbol) is left blank for sub-entries to create an indented look
|
||||||
|
\glssubentryitem{##2}% Inserts sub-entry number if subentrycounter is used
|
||||||
|
\glstarget{##2}{\strut}\glossentrydesc{##2}\glspostdescription & % Column 2: Description (target on strut for hyperlink)
|
||||||
|
##3\tabularnewline % Column 3: Location list
|
||||||
|
}%
|
||||||
|
% Define the skip between letter groups (if group headings were enabled)
|
||||||
|
% For 3 columns, we need 2 ampersands for a full blank row if not using \multicolumn
|
||||||
|
\ifglsnogroupskip
|
||||||
|
\renewcommand*{\glsgroupskip}{}%
|
||||||
|
\else
|
||||||
|
\renewcommand*{\glsgroupskip}{& & \tabularnewline}%
|
||||||
|
\fi
|
||||||
|
}
|
||||||
|
|
||||||
|
% Define a new style 'supercol' based on 'super' for acronyms glossaries
|
||||||
|
\newglossarystyle{supercol}{%
|
||||||
|
\setglossarystyle{super}% inherit everything from the original
|
||||||
|
% override just the main-entry format:
|
||||||
|
\renewcommand*{\glossentry}[2]{%
|
||||||
|
\glsentryitem{##1}%
|
||||||
|
\glstarget{##1}{\glossentryname{##1}}\space % <-- added colon here
|
||||||
|
&: \glossentrydesc{##1}\glspostdescription\space ##2\tabularnewline
|
||||||
|
}%
|
||||||
|
% likewise for sub‐entries, if you want a colon there too:
|
||||||
|
\renewcommand*{\subglossentry}[3]{%
|
||||||
|
&:
|
||||||
|
\glssubentryitem{##2}%
|
||||||
|
\glstarget{##2}{\strut}\glossentryname{##2}\space % <-- and here
|
||||||
|
\glossentrydesc{##2}\glspostdescription\space ##3\tabularnewline
|
||||||
|
}%
|
||||||
|
}
|
||||||
|
\makeatother
|
||||||
|
|
||||||
|
% A new command that enables us to enter bi-lingual (Bahasa Indonesia and English) terms
|
||||||
|
% syntax: \addterm[options]{label}{Bahasa Indonesia}{Bahasa Indonesia first use}{English}{Bahasa Indonesia
|
||||||
|
% description}
|
||||||
|
\newcommand{\addterm}[6][]{
|
||||||
|
\newglossaryentry{#2}{
|
||||||
|
name={#3 (angl.\ #5)},
|
||||||
|
first={#4 (\emph{#5})},
|
||||||
|
text={#3},
|
||||||
|
sort={#3},
|
||||||
|
description={#6},
|
||||||
|
#1 % pass additional options to \newglossaryentry
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
% A new command that enables us to enter (English) acronyms with bi-lingual
|
||||||
|
% (Bahasa Indonesia and English) long versions
|
||||||
|
% syntax: \addacronym[options]{label}{abbreviation}{Bahasa Indonesia long}{Bahasa Indonesia first
|
||||||
|
% use long}{English long}{Bahasa Indonesia description}
|
||||||
|
\newcommand{\addacronym}[7][]{
|
||||||
|
% Create the main glossary entry with \newacronym
|
||||||
|
% \newacronym[key-val list]{label}{abbrv}{long}
|
||||||
|
\newacronym[
|
||||||
|
name={#4 (angl.\ #6,\ #3)},
|
||||||
|
first={\emph{#5} (angl.\ \emph{#6},\ \emph{#3})},
|
||||||
|
sort={#4},
|
||||||
|
description={#7},
|
||||||
|
#1 % pass additional options to \newglossaryentry
|
||||||
|
]
|
||||||
|
{#2}{#3}{#4}
|
||||||
|
% Create a cross-reference from the abbreviation to the main glossary entry by
|
||||||
|
% creating an auxiliary glossary entry (note: we set the label of this entry
|
||||||
|
% to '<original label>_auxiliary' to avoid clashes)
|
||||||
|
\newglossaryentry{#2_auxiliary}{
|
||||||
|
name={#3},
|
||||||
|
sort={#3},
|
||||||
|
description={\makefirstuc{#6}},
|
||||||
|
see=[See:]{#2}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
% Change the text of the cross-reference links to the Bahasa Indonesia long version.
|
||||||
|
\renewcommand*{\glsseeitemformat}[1]{\emph{\acrlong{#1}}.}
|
||||||
|
|
||||||
% % Apply a custom fancyhdr layout only on the first page of each \chapter, and use no header/footer elsewhere
|
% % Apply a custom fancyhdr layout only on the first page of each \chapter, and use no header/footer elsewhere
|
||||||
% % \let\oldchapter\chapter
|
% % \let\oldchapter\chapter
|
||||||
% % \renewcommand{\chapter}{%
|
% % \renewcommand{\chapter}{%
|
||||||
|
|||||||
Reference in New Issue
Block a user