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AmbulatoryAssessmentAnalysis.jl\n\n[![Build Status](https://github.com/CarlBittendorf/AmbulatoryAssessmentAnalysis.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/CarlBittendorf/AmbulatoryAssessmentAnalysis.jl/actions/workflows/CI.yml?query=branch%3Amain)\n[![Aqua](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)\n\n## Installation\n\nFollow the instructions on [https://julialang.org/install/](https://julialang.org/install/) to download and install Julia (if you have not already).\n\nType `]` in the Julia REPL to enter the package manager REPL mode und run\n\n```\npkg\u003e add https://github.com/CarlBittendorf/AmbulatoryAssessmentAnalysis.jl\n```\n\n## Examples\n\n```julia\nusing AmbulatoryAssessmentAnalysis\nusing Dates\n\n# replace with your own credentials\nstudyid = \"12345\"\napikey = \"abcdefghijklmnopqrstuvwxyz\"\n\n# download mobile sensing data from movisensXS and save it to \"path/to/dir\"\ndownload(\"path/to/dir\", MovisensXSUnisens, studyid, apikey)\n\n# load the physical activity data of all participants as a DataFrame\ndf = gather(\"path/to/dir\", MovisensXSPhysicalActivity)\n\n# calculate aggregated variables at the daily level\naggregate(df, MovisensXSPhysicalActivity, Day(1))\n```\n\n## Acknowledgements\n\nFunded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – GRK2739/1 – Project Nr. 447089431 – Research Training Group: KD²School – Designing Adaptive Systems for Economic Decisions","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcarlbittendorf%2Fambulatoryassessmentanalysis.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcarlbittendorf%2Fambulatoryassessmentanalysis.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcarlbittendorf%2Fambulatoryassessmentanalysis.jl/lists"}