test(notebooks): update file paths for sensor data loading and add markdown for clarity
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@@ -324,9 +324,9 @@
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"ready_data1 = []\n",
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"for file in os.listdir('D:/thesis/data/working/sensor1'):\n",
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" ready_data1.append(pd.read_csv(os.path.join('D:/thesis/data/working/sensor1', file)))\n",
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"# ready_data1[1]\n",
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"for file in os.listdir('D:/thesis/data/converted/raw/sensor1'):\n",
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" ready_data1.append(pd.read_csv(os.path.join('D:/thesis/data/converted/raw/sensor1', file)))\n",
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"ready_data1[0]\n",
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"# colormesh give title x is frequency and y is time and rotate/transpose the data\n",
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"# Plotting the STFT Data"
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]
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@@ -362,8 +362,8 @@
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"outputs": [],
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"source": [
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"ready_data2 = []\n",
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"for file in os.listdir('D:/thesis/data/working/sensor2'):\n",
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" ready_data2.append(pd.read_csv(os.path.join('D:/thesis/data/working/sensor2', file)))\n",
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"for file in os.listdir('D:/thesis/data/converted/raw/sensor2'):\n",
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" ready_data2.append(pd.read_csv(os.path.join('D:/thesis/data/converted/raw/sensor2', file)))\n",
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"ready_data2[5]"
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]
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},
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@@ -407,6 +407,13 @@
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"print(x2)"
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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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"### Appending"
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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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@@ -448,15 +455,10 @@
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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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"cell_type": "markdown",
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"metadata": {},
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"outputs": [],
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"source": [
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"y_1 = [1,1,1,1]\n",
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"y_2 = [0,1,1,1]\n",
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"y_3 = [1,0,1,1]\n",
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"y_4 = [1,1,0,0]"
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"### Labeling"
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]
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},
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{
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@@ -492,6 +494,16 @@
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" print(ready_data1[i].shape[0])"
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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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"for i in range(len(y_data)):\n",
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" print(ready_data2[i].shape[0])"
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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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@@ -509,7 +521,8 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"y_data"
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"# len(y_data[0])\n",
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"y_data[0]"
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]
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},
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{
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