{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.9","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":22559,"databundleVersionId":1923081,"sourceType":"competition"}],"dockerImageVersionId":30055,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"![header.png](attachment:header.png)\n\n# **Indoor Location Navigation EDA**\n\nIn this competition (hosted by [Microsoft Research](https://www.microsoft.com/en-us/research/)), we aim to predict the position of a smartphone in an indoor location based on smartphone-provided data like accelerometer, gyroscope, magnometer readings, as well as WiFi and Bluetooth scans. The data is taken from hundreds of buildings in China. More details on the data collection is provided [here](https://github.com/location-competition/indoor-location-competition-20) and [here](https://www.youtube.com/watch?v=xt3OzMC-XMU).\n\n\nIn this notebook, I will provide an in-depth exploration of the data available for this competition. Please upvote if you find this notebook useful!\n\n# Table of Contents\n\n* [Dataset organization](#1) - Here, I briefly go over how the training and test dataset is organized.\n* [Metadata organization](#2) - Here, I briefly go over what extra information is provided in the metadata.\n* [Path text files](#3) - Here, I briefly analyze the path text files, how to open them, what features are available, etc.\n* [Submission CSV and evaluation](#4) - Here, I show what needs to be predicted and how the results are evaluated.","metadata":{},"attachments":{"header.png":{"image/png":"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"}}},{"cell_type":"code","source":"import os\nimport glob\nfrom PIL import Image\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport json\nfrom tqdm.notebook import tqdm\nfrom pathlib import Path\nfrom dataclasses import dataclass","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:48:45.972978Z","iopub.execute_input":"2025-12-23T13:48:45.973320Z","iopub.status.idle":"2025-12-23T13:48:45.977826Z","shell.execute_reply.started":"2025-12-23T13:48:45.973288Z","shell.execute_reply":"2025-12-23T13:48:45.976934Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n## Dataset organization\n\nLet's see what folders we have:","metadata":{}},{"cell_type":"code","source":"dataset_path = Path('../input/indoor-location-navigation')\nos.listdir(dataset_path)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:21.524485Z","iopub.execute_input":"2025-12-23T13:49:21.524859Z","iopub.status.idle":"2025-12-23T13:49:21.534799Z","shell.execute_reply.started":"2025-12-23T13:49:21.524833Z","shell.execute_reply":"2025-12-23T13:49:21.533623Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"We are provided with our train and test data, as well as metadata with additional information about the buildings (including maps) where the data collection took place.\n\nNote that the data is organized by the sites and floors. How many sites do we have in this dataset?\n","metadata":{}},{"cell_type":"code","source":"train_sites = os.listdir(dataset_path/\"train\")\nprint(f'There are {len(train_sites)} sites in the training set')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:24.392504Z","iopub.execute_input":"2025-12-23T13:49:24.392852Z","iopub.status.idle":"2025-12-23T13:49:24.405009Z","shell.execute_reply.started":"2025-12-23T13:49:24.392825Z","shell.execute_reply":"2025-12-23T13:49:24.403662Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Each site folder is organized by the floor (a variable to predict!):","metadata":{}},{"cell_type":"code","source":"example_site = os.listdir(dataset_path/\"train\")[10]\nexample_site_path = dataset_path/\"train\"/example_site\nprint('Floors for example site:')\nprint(os.listdir(example_site_path))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:26.761323Z","iopub.execute_input":"2025-12-23T13:49:26.761720Z","iopub.status.idle":"2025-12-23T13:49:26.770999Z","shell.execute_reply.started":"2025-12-23T13:49:26.761683Z","shell.execute_reply":"2025-12-23T13:49:26.770026Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"floors_per_site = []\nfor i in os.listdir(dataset_path/\"train\"): floors_per_site.append(len(os.listdir(dataset_path/\"train\"/i)))\nprint(f'There are a total of {sum(floors_per_site)} floors. On average, each site has {np.mean(floors_per_site)} floors')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:28.936020Z","iopub.execute_input":"2025-12-23T13:49:28.936346Z","iopub.status.idle":"2025-12-23T13:49:29.517727Z","shell.execute_reply.started":"2025-12-23T13:49:28.936319Z","shell.execute_reply":"2025-12-23T13:49:29.516883Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"So every site has about 5 floors.\n\nIn each floor are the path trace text files with the data:","metadata":{}},{"cell_type":"code","source":"print('Path text files for example floor:')\nprint(os.listdir(example_site_path/'B1'))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:34.943600Z","iopub.execute_input":"2025-12-23T13:49:34.943932Z","iopub.status.idle":"2025-12-23T13:49:34.953195Z","shell.execute_reply.started":"2025-12-23T13:49:34.943904Z","shell.execute_reply":"2025-12-23T13:49:34.952100Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"How many total training path files are there?","metadata":{}},{"cell_type":"code","source":"print(f\"There are {len(list((dataset_path/'train').rglob('*.txt')))} path text files in the training set\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:49:36.886615Z","iopub.execute_input":"2025-12-23T13:49:36.886944Z","iopub.status.idle":"2025-12-23T13:49:56.524529Z","shell.execute_reply.started":"2025-12-23T13:49:36.886910Z","shell.execute_reply":"2025-12-23T13:49:56.523478Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"To summarize, this is how the training data is structured:\n\n```\n└───train                                                        //raw data from two sites\n      └───site1\n      |     └───B1                                               //traces from one floor\n      |     |   └───5dda14a2c5b77e0006b17533.txt                 //trace file                             \n      |     |   | ...\n      |     |\n      |     |\n      |     └───F1\n      |     | ...\n      |\n      └───site2\n```","metadata":{}},{"cell_type":"markdown","source":"Let's now move on to the test set. The test set simply is a collection of path text files:","metadata":{}},{"cell_type":"code","source":"print(f\"There are {len(os.listdir(dataset_path/'test'))} path text files in the test set\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:03.185660Z","iopub.execute_input":"2025-12-23T13:50:03.186020Z","iopub.status.idle":"2025-12-23T13:50:03.203260Z","shell.execute_reply.started":"2025-12-23T13:50:03.185990Z","shell.execute_reply":"2025-12-23T13:50:03.202186Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"2\"></a>\n## Metadata organization\n\nNow let's check the metadata. It's organized in the same way the training set is organized. ","metadata":{}},{"cell_type":"code","source":"print(f'There are {len(os.listdir(dataset_path/\"metadata\"))} sites in the metadata, just like the training set')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:05.405655Z","iopub.execute_input":"2025-12-23T13:50:05.405985Z","iopub.status.idle":"2025-12-23T13:50:05.415919Z","shell.execute_reply.started":"2025-12-23T13:50:05.405957Z","shell.execute_reply":"2025-12-23T13:50:05.414888Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Let's look at a single floor of a single site:","metadata":{}},{"cell_type":"code","source":"metadata_example_site = os.listdir(dataset_path/\"metadata\")[10]\nmetadata_example_site_path = dataset_path/\"metadata\"/metadata_example_site\nmetadata_example_floor_path = dataset_path/\"metadata\"/metadata_example_site/os.listdir(metadata_example_site_path)[0]\nprint(os.listdir(metadata_example_floor_path))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:07.953467Z","iopub.execute_input":"2025-12-23T13:50:07.953824Z","iopub.status.idle":"2025-12-23T13:50:07.964969Z","shell.execute_reply.started":"2025-12-23T13:50:07.953791Z","shell.execute_reply":"2025-12-23T13:50:07.964047Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Each floor has metadata with a floor map, floor information, and geographic information.","metadata":{}},{"cell_type":"code","source":"Image.open(metadata_example_floor_path/'floor_image.png')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:10.231998Z","iopub.execute_input":"2025-12-23T13:50:10.232327Z","iopub.status.idle":"2025-12-23T13:50:10.357700Z","shell.execute_reply.started":"2025-12-23T13:50:10.232300Z","shell.execute_reply":"2025-12-23T13:50:10.356677Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"with open(metadata_example_floor_path/'geojson_map.json') as geojson_map:\n    data = json.load(geojson_map)\n    geojson_map.close()\nprint(data)","metadata":{"_kg_hide-output":true,"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:15.014456Z","iopub.execute_input":"2025-12-23T13:50:15.014829Z","iopub.status.idle":"2025-12-23T13:50:15.028873Z","shell.execute_reply.started":"2025-12-23T13:50:15.014791Z","shell.execute_reply":"2025-12-23T13:50:15.027714Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"with open(metadata_example_floor_path/'floor_info.json') as floor_info:\n    data = json.load(floor_info)\n    floor_info.close()\nprint(data)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:22.515722Z","iopub.execute_input":"2025-12-23T13:50:22.516079Z","iopub.status.idle":"2025-12-23T13:50:22.525087Z","shell.execute_reply.started":"2025-12-23T13:50:22.516047Z","shell.execute_reply":"2025-12-23T13:50:22.524263Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"3\"></a>\n## Path text files\n\nLet's look more closely at the path text files and how to process them.\n\nThe [GitHub README](https://github.com/location-competition/indoor-location-competition-20) provides more information about the text file format:\n\n> The first column is Unix Time in millisecond. In specific, we use SensorEvent.timestamp for sensor data and system time for WiFi and Bluetooth scans.\n> \n>The second column is the data type (ten in total).\n>\n>TYPE_ACCELEROMETER\n>\n>TYPE_MAGNETIC_FIELD\n>\n>TYPE_GYROSCOPE\n>\n>TYPE_ROTATION_VECTOR\n>\n>TYPE_MAGNETIC_FIELD_UNCALIBRATED\n>TYPE_GYROSCOPE_UNCALIBRATED\n>\n>TYPE_ACCELEROMETER_UNCALIBRATED\n>\n>TYPE_WIFI\n>\n>TYPE_BEACON\n>\n>TYPE_WAYPOINT: ground truth location labeled by the surveyor\n>\n>Data values start from the third column.\n>\n>Column 3-5 of TYPE_ACCELEROMETER、TYPE_ACCELEROMETER、TYPE_GYROSCOPE、TYPE_ROTATION_VECTOR are SensorEvent.values[0-2] from the callback function onSensorChanged(). Column 6 is SensorEvent.accuracy.\n>\n>Column 3-8 of TYPE_ACCELEROMETER_UNCALIBRATED、TYPE_GYROSCOPE_UNCALIBRATED、TYPE_MAGNETIC_FIELD_UNCALIBRATED are SensorEvent.values[0-5] from the callback function onSensorChanged(). Column 9 is SensorEvent.accuracy.","metadata":{}},{"cell_type":"code","source":"example_floor_path = example_site_path/'B1'\nexample_txt_path = example_floor_path/os.listdir(example_floor_path)[0]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:29.051905Z","iopub.execute_input":"2025-12-23T13:50:29.052229Z","iopub.status.idle":"2025-12-23T13:50:29.058685Z","shell.execute_reply.started":"2025-12-23T13:50:29.052202Z","shell.execute_reply":"2025-12-23T13:50:29.057866Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"with open(example_txt_path) as example_txt:\n    data = example_txt.read()\n    example_txt.close()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:30.928035Z","iopub.execute_input":"2025-12-23T13:50:30.928386Z","iopub.status.idle":"2025-12-23T13:50:30.951424Z","shell.execute_reply.started":"2025-12-23T13:50:30.928353Z","shell.execute_reply":"2025-12-23T13:50:30.950554Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Here is an example text file (unhide the output, it's very long):","metadata":{}},{"cell_type":"code","source":"print(data)","metadata":{"_kg_hide-output":true,"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:32.971494Z","iopub.execute_input":"2025-12-23T13:50:32.971867Z","iopub.status.idle":"2025-12-23T13:50:33.030800Z","shell.execute_reply.started":"2025-12-23T13:50:32.971834Z","shell.execute_reply":"2025-12-23T13:50:33.029683Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"The organizers have thankfully provided some code for processing the text files over [here](https://github.com/location-competition/indoor-location-competition-20/blob/master/io_f.py). We will use that code to process our data (code is hidden):","metadata":{}},{"cell_type":"code","source":"@dataclass\nclass ReadData:\n    acce: np.ndarray\n    acce_uncali: np.ndarray\n    gyro: np.ndarray\n    gyro_uncali: np.ndarray\n    magn: np.ndarray\n    magn_uncali: np.ndarray\n    ahrs: np.ndarray\n    wifi: np.ndarray\n    ibeacon: np.ndarray\n    waypoint: np.ndarray\n\n\ndef read_data_file(data_filename):\n    acce = []\n    acce_uncali = []\n    gyro = []\n    gyro_uncali = []\n    magn = []\n    magn_uncali = []\n    ahrs = []\n    wifi = []\n    ibeacon = []\n    waypoint = []\n\n    with open(data_filename, 'r', encoding='utf-8') as file:\n        lines = file.readlines()\n\n    for line_data in lines:\n        line_data = line_data.strip()\n        if not line_data or line_data[0] == '#':\n            continue\n\n        line_data = line_data.split('\\t')\n\n        if line_data[1] == 'TYPE_ACCELEROMETER':\n            acce.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_ACCELEROMETER_UNCALIBRATED':\n            acce_uncali.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_GYROSCOPE':\n            gyro.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_GYROSCOPE_UNCALIBRATED':\n            gyro_uncali.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_MAGNETIC_FIELD':\n            magn.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_MAGNETIC_FIELD_UNCALIBRATED':\n            magn_uncali.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_ROTATION_VECTOR':\n            ahrs.append([int(line_data[0]), float(line_data[2]), float(line_data[3]), float(line_data[4])])\n            continue\n\n        if line_data[1] == 'TYPE_WIFI':\n            sys_ts = line_data[0]\n            ssid = line_data[2]\n            bssid = line_data[3]\n            rssi = line_data[4]\n            lastseen_ts = line_data[6]\n            wifi_data = [sys_ts, ssid, bssid, rssi, lastseen_ts]\n            wifi.append(wifi_data)\n            continue\n\n        if line_data[1] == 'TYPE_BEACON':\n            ts = line_data[0]\n            uuid = line_data[2]\n            major = line_data[3]\n            minor = line_data[4]\n            rssi = line_data[6]\n            ibeacon_data = [ts, '_'.join([uuid, major, minor]), rssi]\n            ibeacon.append(ibeacon_data)\n            continue\n\n        if line_data[1] == 'TYPE_WAYPOINT':\n            waypoint.append([int(line_data[0]), float(line_data[2]), float(line_data[3])])\n\n    acce = np.array(acce)\n    acce_uncali = np.array(acce_uncali)\n    gyro = np.array(gyro)\n    gyro_uncali = np.array(gyro_uncali)\n    magn = np.array(magn)\n    magn_uncali = np.array(magn_uncali)\n    ahrs = np.array(ahrs)\n    wifi = np.array(wifi)\n    ibeacon = np.array(ibeacon)\n    waypoint = np.array(waypoint)\n\n    return ReadData(acce, acce_uncali, gyro, gyro_uncali, magn, magn_uncali, ahrs, wifi, ibeacon, waypoint)","metadata":{"_kg_hide-input":true,"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:49.456442Z","iopub.execute_input":"2025-12-23T13:50:49.456779Z","iopub.status.idle":"2025-12-23T13:50:49.474180Z","shell.execute_reply.started":"2025-12-23T13:50:49.456750Z","shell.execute_reply":"2025-12-23T13:50:49.473019Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"example_data = read_data_file(example_txt_path)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:52.308997Z","iopub.execute_input":"2025-12-23T13:50:52.309321Z","iopub.status.idle":"2025-12-23T13:50:52.432913Z","shell.execute_reply.started":"2025-12-23T13:50:52.309294Z","shell.execute_reply":"2025-12-23T13:50:52.431983Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Let's see the shape of the data:","metadata":{}},{"cell_type":"code","source":"print(example_data.acce.shape)\nprint(example_data.acce_uncali.shape)\nprint(example_data.gyro.shape)\nprint(example_data.gyro_uncali.shape)\nprint(example_data.magn.shape)\nprint(example_data.magn_uncali.shape)\nprint(example_data.ahrs.shape)\nprint(example_data.wifi.shape)\nprint(example_data.ibeacon.shape)\nprint(example_data.waypoint.shape)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:50:55.060497Z","iopub.execute_input":"2025-12-23T13:50:55.060840Z","iopub.status.idle":"2025-12-23T13:50:55.067712Z","shell.execute_reply.started":"2025-12-23T13:50:55.060812Z","shell.execute_reply":"2025-12-23T13:50:55.066735Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Here we have 9 features and the target:\n\n`acce` - accelerometer data \n\n`acce_uncali` - uncalibrated accelerometer data\n\n`gyro` - gyroscope data\n\n`gyro_uncali` - uncalibrated gyroscope data\n\n`magn` - magnetometer data\n\n`magn_uncali` - uncalibrated magnetometer data\n\n`ahrs` - rotation vector data\n\n`wifi` - WiFi data\n\n`ibeacon` - iBeacon data (sometimes can be missing)\n\n`waypoint` - position, target\n\n\nLet's look at the distribution of the number of datapoint for the features in the training data (code is hidden):","metadata":{}},{"cell_type":"code","source":"acce_shape = []\nacce_uncali_shape = []\ngyro_shape = []\ngyro_uncali_shape = []\nmagn_shape = []\nmagn_uncali_shape = []\nahrs_shape = []\nwifi_shape = []\nibeacon_shape = []\ntrain_files = list((dataset_path/'train').rglob('*.txt'))[:1000] #take a subset for now\nfor i in tqdm(train_files):\n    train_data = read_data_file(i)\n    acce_shape.append(train_data.acce.shape)\n    acce_uncali_shape.append(train_data.acce_uncali.shape)\n    gyro_shape.append(train_data.gyro.shape)\n    gyro_uncali_shape.append(train_data.gyro_uncali.shape)\n    magn_shape.append(train_data.magn.shape)\n    magn_uncali_shape.append(train_data.magn_uncali.shape)\n    ahrs_shape.append(train_data.ahrs.shape)\n    wifi_shape.append(train_data.wifi.shape)\n    ibeacon_shape.append(train_data.ibeacon.shape)\n","metadata":{"_kg_hide-input":true,"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:53:27.945910Z","iopub.execute_input":"2025-12-23T13:53:27.946249Z","iopub.status.idle":"2025-12-23T13:55:00.104801Z","shell.execute_reply.started":"2025-12-23T13:53:27.946222Z","shell.execute_reply":"2025-12-23T13:55:00.103878Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in acce_shape])\n_ = plt.title('accelerometer # data points training set histogram')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:52:45.875765Z","iopub.execute_input":"2025-12-23T13:52:45.876190Z","iopub.status.idle":"2025-12-23T13:52:46.027957Z","shell.execute_reply.started":"2025-12-23T13:52:45.876142Z","shell.execute_reply":"2025-12-23T13:52:46.026933Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in ahrs_shape])\n_ = plt.title('rotation vector # data points training set histogram')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-23T13:52:46.029336Z","iopub.execute_input":"2025-12-23T13:52:46.029817Z","iopub.status.idle":"2025-12-23T13:52:46.181398Z","shell.execute_reply.started":"2025-12-23T13:52:46.029746Z","shell.execute_reply":"2025-12-23T13:52:46.180611Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in wifi_shape])\n_ = plt.title('WiFi # data points training set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in ibeacon_shape])\n_ = plt.title('iBeacon # data points training set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Also, let's look for missing iBeacon data:","metadata":{}},{"cell_type":"code","source":"print(f'{sum([i == (0,) for i in ibeacon_shape])} of the training samples are missing iBeacon data')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"We can see that the shape of the arrays for the accelerometer, gyroscope, and magnetometer measuements are the same, likely because they are coming from the smartphone and sampled simultaneously. Interestingly, this sample is missing iBeacon data, so it looks like sometimes the iBeacon data is not present.\n\nThis function also works with the test files. The test files provide all the same information, except the waypoint, which is the target.","metadata":{}},{"cell_type":"code","source":"example_test_data = read_data_file(dataset_path/'test'/os.listdir(dataset_path/'test')[0])","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(example_test_data.acce.shape)\nprint(example_test_data.acce_uncali.shape)\nprint(example_test_data.gyro.shape)\nprint(example_test_data.gyro_uncali.shape)\nprint(example_test_data.magn.shape)\nprint(example_test_data.magn_uncali.shape)\nprint(example_test_data.ahrs.shape)\nprint(example_test_data.wifi.shape)\nprint(example_test_data.ibeacon.shape)\nprint(example_test_data.waypoint.shape) # will be zero because this is target","metadata":{"_kg_hide-input":false,"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Like we did for the training data, let's look at the shape of the test data (code is hidden):","metadata":{}},{"cell_type":"code","source":"acce_shape = []\nacce_uncali_shape = []\ngyro_shape = []\ngyro_uncali_shape = []\nmagn_shape = []\nmagn_uncali_shape = []\nahrs_shape = []\nwifi_shape = []\nibeacon_shape = []\ntest_files = os.listdir(dataset_path/'test')\nfor i in tqdm(range(len(test_files))):\n    test_data = read_data_file(dataset_path/'test'/test_files[i])\n    acce_shape.append(test_data.acce.shape)\n    acce_uncali_shape.append(test_data.acce_uncali.shape)\n    gyro_shape.append(test_data.gyro.shape)\n    gyro_uncali_shape.append(test_data.gyro_uncali.shape)\n    magn_shape.append(test_data.magn.shape)\n    magn_uncali_shape.append(test_data.magn_uncali.shape)\n    ahrs_shape.append(test_data.ahrs.shape)\n    wifi_shape.append(test_data.wifi.shape)\n    ibeacon_shape.append(test_data.ibeacon.shape)\n","metadata":{"_kg_hide-input":true,"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in acce_shape])\n_ = plt.title('accelerometer # data points test set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in ahrs_shape])\n_ = plt.title('rotation vector # data points test set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in wifi_shape])\n_ = plt.title('WiFi # data points test set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"_ = plt.hist([i[0] for i in ibeacon_shape])\n_ = plt.title('iBeacon # data points test set histogram')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Also, let's look for missing iBeacon data:","metadata":{}},{"cell_type":"code","source":"print(f'{sum([i == (0,) for i in ibeacon_shape])} of the test samples are missing iBeacon data')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"4\"></a>\n## Submission CSV and evaluation\n\nLastly, let's look at the submission CSV and figure out what we need to predict and how our results are evaluated.","metadata":{}},{"cell_type":"code","source":"sample_df = pd.read_csv(dataset_path/'sample_submission.csv')","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"sample_df.head(10)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"We see that we are given the name of the path trace files and we are supposed to predict the floor number, as well as the position (x,y). The name of the path trace file provides the ID for the site as well as the path ID and UNIX timestamp. We can see that the sites in the test site are also present in the training set.","metadata":{}},{"cell_type":"code","source":"unique_test_sites = list(set([j[0] for j in [i.split('_') for i in list(sample_df.site_path_timestamp)]]))\nlen(list(set(unique_test_sites) & set(train_sites))) == len(unique_test_sites)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Let's look at how our submission is evaluated:\n\n> ![image.png](attachment:image.png)\n\nNote that the floor numbers are mapped to integers for the submission file. The above-ground floors are mapped as the floor number minue one. For example F1 would be mapped to 0, F2 to 1, F3 to 2, etc. The below-ground floors are mapped to negative floor numbers. For example B1 is -1, B2 is -2, B3 is -3, etc. There are non-traditional floor numbers in the training set (ex: LG2, LM, etc.) but those are not in the test set.","metadata":{},"attachments":{"image.png":{"image/png":"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"}}},{"cell_type":"code","source":"sample_df.to_csv('submission.csv',index=False)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**THE END**\n\nPlease upvote if you found this notebook useful!","metadata":{}}]}