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    "info": {
        "author": "Marko Seslija",
        "author_email": "marko.seslija@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3"
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        "description": "# TiltX\n\n#### Feature extraction from mobile phone motion sensor data\n\nThis repository implements a method which extracts some of the key features from mobile phone motion sensor data.\n\nAt `t=0` a visual stimulus appears on the screen. As the response, a participant (person holding the phone) is required to tilt the phone in a specific direction (left, right, up, or down). Once the roll or picth angle reaches 0.5 radians (`t=T>0`), the movement is completed. `T` is the event time registered by the app. The rotaion along the third axis (yaw) *does not* affect the outcome of the task, hence it is neglected.\n\nThe features extracted by TiltX are: reaction time, L1 norms, maximal deviation, number of turning points, and sample entropy.\n\n## Usage\nThese steps introduce how to use `TiltX`.\n\n### Input data\nThe `DataGenerator` is a utility class that generates sample datasets. \n\n```python\nfrom tiltx.data_generator import DataGenerator\nt, alpha, beta = DataGenerator.example(1)\n```\n>  Note: `t`, `alpha`, and `beta` need to be equal length arrays.\n\n### Extract features\nThe `FeatureExtractor` extracts key features from the data.\n```python\nfrom tiltx.feature_extractor import FeatureExtractor\nfeatures = FeatureExtractor(t,alpha,beta,RT_method='cumsum',correct='up')\n```\n> Note: `cumsum` is a method for reaction time detection and `correct` is the direction in which the phone should be tilted in order to successfully complete the task.\n\n```python\nprint('Reaction time: %.3f'%(features.RT))\nprint('L1-norm of the triggering axis: %.3f'%(features.L1_x))\nprint('L1-norm of the remaining (non-triggering) axis: %.3f'%(features.L1_y))\n\nReaction time: 0.669\nL1-norm of the triggering axis: 0.492\nL1-norm of the remaining (non-triggering) axis: 0.006\n```\n### Visualize\nBy calling `plot()` function in `FeatureExtractor`, we plot the roll and pitch angles from the moment the stimulus appears till the moment when the app registers the move as completed.\n\n```python\nfeatures.plot()\n```\n![](figures/figure_1.png)\n\n- `x` is a triggering angle (the one which reaches 0.5 radians first)\n- `y` is the remaining (non-triggering) angle\n- the shaded regions are proportional to L1 norms\n- the black dotted line marks the begining of the reaction\n\n### Documentation\nFor a tutorial and a brief note on signal features, check out [the notebooks folder](/notebooks).\n\n",
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