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changed core feature to use change in voltage, maintenance cleanup
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| # Sphinx build info version 1 | ||
| # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
| config: a34f014baffc3a18f2e4451097838d56 | ||
| config: 1986480a93c54f2f17e09825d323461e | ||
| tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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docs/_downloads/45db2a75d199d40435fefaab0063e78d/plot_find_audio_events.ipynb
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%matplotlib inline" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "\n# Use Audio to Align Video Data\nIn this example, we use ``pd-parser`` to find audio events using the same\nalgorithm for matching with time-stamps and rejecting misaligned\naudio, but applied using the onset of an audio deflection instead of detecting\nphotodiode events based on their square wave shape.\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Authors: Alex Rockhill <[email protected]>\n#\n# License: BSD (3-clause)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Load in a video with audio:\n\nIn this example, we'll use audio and instead of aligning electrophysiology\ndata, we'll align a video. This example data is from a task where movements\nare played on a monitor for the participant to mirror and the video recording\nis synchronized by playing a pre-recorded clap. This clap sound, or a similar\nsound, is recommended for synchronizing audio because the onset is clear and\nallows good precision in synchronizing events.\n\nNote that the commands that require ffmpeg are pre-computed and commented\nout because ffmpeg must be installed to use them and it is not required by\n``pd-parser``.\n\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import os\nimport os.path as op\nimport numpy as np\nfrom scipy.io import wavfile\nfrom subprocess import call\n# from subprocess import run, PIPE, STDOUT\n# import datetime\n\nimport mne\nfrom mne.utils import _TempDir\n\nimport pd_parser\nfrom pd_parser.parse_pd import _load_data # , _read_tsv\n\n# get the data\nout_dir = _TempDir()\ncall(['curl -L https://raw.githubusercontent.com/alexrockhill/pd-parser/'\n 'master/pd_parser/tests/data/test_video.mp4 '\n '-o ' + op.join(out_dir, 'test_video.mp4')], shell=True, env=os.environ)\ncall(['curl -L https://raw.githubusercontent.com/alexrockhill/pd-parser/'\n 'master/pd_parser/tests/data/test_video.wav '\n '-o ' + op.join(out_dir, 'test_video.wav')], shell=True, env=os.environ)\ncall(['curl -L https://raw.githubusercontent.com/alexrockhill/pd-parser/'\n 'master/pd_parser/tests/data/test_video_beh.tsv '\n '-o ' + op.join(out_dir, 'test_video_beh.tsv')],\n shell=True, env=os.environ)\n\n# navigate to the example video\nvideo_fname = op.join(out_dir, 'test_video.mp4')\n\naudio_fname = video_fname.replace('mp4', 'wav') # pre-computed\n# extract audio (requires ffmpeg)\n# run(['ffmpeg', '-i', video_fname, audio_fname])\n\nfs, data = wavfile.read(audio_fname)\ndata = data.mean(axis=1) # stereo audio but only need one source\ninfo = mne.create_info(['audio'], fs, ['stim'])\nraw = mne.io.RawArray(data[np.newaxis], info)\n\n# find audio-visual time offset\noffset = 0 # pre-computed value for this video\n'''\nresult = run(['ffprobe', '-show_entries', 'stream=codec_type,start_time',\n '-v', '0', '-of', 'compact=p=1:nk=0', video_fname],\n stdout=PIPE, stderr=STDOUT)\noutput = result.stdout.decode('utf-8').split('\\n')\noffset = float(output[0].strip('stream|codec_type=video|start_time')) - \\\n float(output[1].strip('stream|codec_type=audio|start_time'))\n'''\n\n# save to disk as required by ``pd-parser``, raw needs a filename\nfname = op.join(out_dir, 'sub-1_task-mytask_raw.fif')\nraw.save(fname)\n\n# navigate to corresponding behavior\nbehf = op.join(out_dir, 'test_video_beh.tsv')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Run the parser:\n\nNow we'll call the main function to automatically parse the audio events.\n\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "pd_parser.parse_audio(fname, beh=behf, beh_key='tone_onset_time',\n audio_ch_names=['audio'], zscore=10)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Load the results:\n\nFinally, we'll load the events and use them to crop the video although it\nrequires ffmpeg so it is commented out.\n\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "annot = _load_data(fname)[0]\nprint('Here are the event times: ', annot.onset)\n\n# Crop the videos with ffmpeg\n'''\nbeh = _read_tsv(behf)\nfor i in range(annot.onset.size): # skip the first video\n action_time = (beh['tone_onset'][i] - beh['action_onset'][i]) / 1000\n run(['ffmpeg', '-i', f'{video_fname}', '-ss',\n str(datetime.timedelta(\n seconds=annot.onset[i] - action_time - offset)),\n '-to', str(datetime.timedelta(seconds=annot.onset[i] - offset)),\n op.join(out_dir, 'movement-{}+action_type-{}.mp4'.format(\n beh['movement'][i], beh['action_type'][i]))])\n'''" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.9.1" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 0 | ||
| } |
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