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README.md
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README.md
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In this folder you can find 4 scripts that can be used to transfrom 24/7 .cwa accelerometer data to intensity plots. The methods are based on the Rowland et al. 2018 article 'Beyond Cut Points: Accelerometer Metrics that Capture the Physical Activity Profile.
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In this folder you can find 4 scripts that can be used to transfrom 24/7 .csv accelerometer data to intensity plots. The methods are based on the Rowland et al. 2018 article 'Beyond Cut Points: Accelerometer Metrics that Capture the Physical Activity Profile.
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The scripts should be run in the following order:
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1. DailyCutter.py - ...
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1. DailyCutter.py - This script is used to transform single week .csv files (input) into individual day-files (output)
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The WeekPath should be set to the folder containing the week-files of the patient
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The ScriptPath should be set to the folder containing the 'formules.py' script. This script holds
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all functions used in the analysis.
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2. plotter.py - This is the second script used in the analysis and is the script that performs the most.
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Before getting started, the os.chdir(___) should be set to the 'formules.py' pathway
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The rootdir should be set to the folder containing 7 individual .csv day-files
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The PtName variable should be set accordingly to the name of the files used. This possibly changes
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between different weeks/different patients.
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Finally, the CheckWeel.to_csv(___) should be filled with the used weeknumber, to save the
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parameters of the trendline for each different week.
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After changing these variables to your liking, the script should run automatically, using the
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folder with individual days as input and saving the plots for individual days as well as an
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overview of the entire week as output.
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3. Totalplotter.py - After running the plotter.py script you should have ended up with 6 .csv files with parameters
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of the trendlines. Make sure that these files are saved within the same folder and set the path
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of this folder as the rootdir in this script.
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Change the names in the plt.title(___) and plt.savefig(___) commands accordingly and run the scripts
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The output will be a plot of all 6 weeks in one figure.
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2. plotter.py - ...
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3. Totalplotter.py - ...
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