569 lines
29 KiB
YAML
569 lines
29 KiB
YAML
########################################################################################################################
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# GLOBAL CONFIGURATION #
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########################################################################################################################
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# See https://www.rapids.science/latest/setup/configuration/#participant-files
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PIDS: [android, ios, fitbit, empatica, empty]
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# See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files
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CREATE_PARTICIPANT_FILES:
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CSV_FILE_PATH: "data/external/example_participants.csv" # see docs for required format
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PHONE_SECTION:
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ADD: True
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DEVICE_ID_COLUMN: device_id # column name
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IGNORED_DEVICE_IDS: []
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FITBIT_SECTION:
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ADD: True
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DEVICE_ID_COLUMN: fitbit_id # column name
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IGNORED_DEVICE_IDS: []
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EMPATICA_SECTION:
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ADD: True
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DEVICE_ID_COLUMN: empatica_id # column name
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IGNORED_DEVICE_IDS: []
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# See https://www.rapids.science/latest/setup/configuration/#time-segments
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TIME_SEGMENTS: &time_segments
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TYPE: FREQUENCY # FREQUENCY, PERIODIC, EVENT
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FILE: "tests/data/external/timesegments_frequency.csv"
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INCLUDE_PAST_PERIODIC_SEGMENTS: FALSE # Only relevant if TYPE=PERIODIC, see docs
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# See https://www.rapids.science/latest/setup/configuration/#timezone-of-your-study
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TIMEZONE:
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TYPE: MULTIPLE
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SINGLE:
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TZCODE: America/New_York
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MULTIPLE:
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TZCODES_FILE: tests/data/external/multiple_timezones.csv
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IF_MISSING_TZCODE: STOP
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DEFAULT_TZCODE: America/New_York
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FITBIT:
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ALLOW_MULTIPLE_TZ_PER_DEVICE: True
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INFER_FROM_SMARTPHONE_TZ: False
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########################################################################################################################
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# PHONE #
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########################################################################################################################
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# See https://www.rapids.science/latest/setup/configuration/#data-stream-configuration
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PHONE_DATA_STREAMS:
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USE: aware_csv
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# AVAILABLE:
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aware_mysql:
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DATABASE_GROUP: MY_GROUP
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aware_csv:
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FOLDER: tests/data/external/aware_csv
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aware_influxdb:
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DATABASE_GROUP: MY_GROUP
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# Sensors ------
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# https://www.rapids.science/latest/features/phone-accelerometer/
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PHONE_ACCELEROMETER:
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CONTAINER: phone_accelerometer_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
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SRC_SCRIPT: src/features/phone_accelerometer/rapids/main.py
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PANDA:
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COMPUTE: True
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VALID_SENSED_MINUTES: False
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FEATURES:
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exertional_activity_episode: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
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nonexertional_activity_episode: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
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SRC_SCRIPT: src/features/phone_accelerometer/panda/main.py
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# See https://www.rapids.science/latest/features/phone-activity-recognition/
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PHONE_ACTIVITY_RECOGNITION:
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CONTAINER:
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ANDROID: plugin_google_activity_recognition_raw.csv
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IOS: plugin_ios_activity_recognition_raw.csv
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EPISODE_THRESHOLD_BETWEEN_ROWS: 5 # minutes. Max time difference for two consecutive rows to be considered within the same AR episode.
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["count", "mostcommonactivity", "countuniqueactivities", "durationstationary", "durationmobile", "durationvehicle"]
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ACTIVITY_CLASSES:
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STATIONARY: ["still", "tilting"]
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MOBILE: ["on_foot", "walking", "running", "on_bicycle"]
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VEHICLE: ["in_vehicle"]
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SRC_SCRIPT: src/features/phone_activity_recognition/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-applications-crashes/
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PHONE_APPLICATIONS_CRASHES:
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CONTAINER: applications_crashes
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APPLICATION_CATEGORIES:
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CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
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CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD
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# See https://www.rapids.science/latest/features/phone-applications-foreground/
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PHONE_APPLICATIONS_FOREGROUND:
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CONTAINER: phone_applications_foreground_raw.csv
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APPLICATION_CATEGORIES:
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CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
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CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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INCLUDE_EPISODE_FEATURES: True
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SINGLE_CATEGORIES: ["all", "email"]
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MULTIPLE_CATEGORIES:
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social: ["socialnetworks", "socialmediatools"]
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entertainment: ["entertainment", "gamingknowledge", "gamingcasual", "gamingadventure", "gamingstrategy", "gamingtoolscommunity", "gamingroleplaying", "gamingaction", "gaminglogic", "gamingsports", "gamingsimulation"]
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CUSTOM_CATEGORIES:
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social_media: ['com.google.android.youtube','com.snapchat.android','com.instagram.android','com.zhiliaoapp.musically','com.facebook.katana']
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dating: ['com.tinder','com.relance.happycouple','com.kiwi.joyride']
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SINGLE_APPS: ["top1global", "com.facebook.moments", "com.google.android.youtube", "com.twitter.android"] # There's no entropy for single apps
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EXCLUDED_CATEGORIES: []
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EXCLUDED_APPS: ["com.fitbit.FitbitMobile", "com.aware.plugin.upmc.cancer"]
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FEATURES:
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APP_EVENTS: ["countevent", "timeoffirstuse", "timeoflastuse", "frequencyentropy"]
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APP_EPISODES: ["countepisode", "minduration", "maxduration", "meanduration", "sumduration"]
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IGNORE_EPISODES_SHORTER_THAN: 0 # in minutes, set to 0 to disable
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IGNORE_EPISODES_LONGER_THAN: 300 # in minutes, set to 0 to disable
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SRC_SCRIPT: src/features/phone_applications_foreground/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-applications-notifications/
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PHONE_APPLICATIONS_NOTIFICATIONS:
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CONTAINER: applications_notifications
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APPLICATION_CATEGORIES:
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CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
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CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD
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# See https://www.rapids.science/latest/features/phone-battery/
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PHONE_BATTERY:
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CONTAINER: phone_battery_raw.csv
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EPISODE_THRESHOLD_BETWEEN_ROWS: 30 # minutes. Max time difference for two consecutive rows to be considered within the same battery episode.
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["countdischarge", "sumdurationdischarge", "countcharge", "sumdurationcharge", "avgconsumptionrate", "maxconsumptionrate"]
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SRC_SCRIPT: src/features/phone_battery/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-bluetooth/
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PHONE_BLUETOOTH:
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CONTAINER: phone_bluetooth_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: FALSE
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FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
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SRC_SCRIPT: src/features/phone_bluetooth/rapids/main.R
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DORYAB:
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COMPUTE: True
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FEATURES:
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ALL:
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DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
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SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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OWN:
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DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
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SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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OTHERS:
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DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
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SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
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SRC_SCRIPT: src/features/phone_bluetooth/doryab/main.py
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# See https://www.rapids.science/latest/features/phone-calls/
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PHONE_CALLS:
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CONTAINER: phone_calls_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES_TYPE: EPISODES
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CALL_TYPES: [missed, incoming, outgoing]
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FEATURES:
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missed: [count, distinctcontacts, timefirstcall, timelastcall, countmostfrequentcontact]
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incoming: [count, distinctcontacts, meanduration, sumduration, minduration, maxduration, stdduration, modeduration, entropyduration, timefirstcall, timelastcall, countmostfrequentcontact]
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outgoing: [count, distinctcontacts, meanduration, sumduration, minduration, maxduration, stdduration, modeduration, entropyduration, timefirstcall, timelastcall, countmostfrequentcontact]
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SRC_SCRIPT: src/features/phone_calls/rapids/main.R
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# See https://www.rapids.science/latest/features/phone-conversation/
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PHONE_CONVERSATION:
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CONTAINER:
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ANDROID: phone_conversation_raw.csv
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IOS: phone_conversation_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["minutessilence", "minutesnoise", "minutesvoice", "minutesunknown","sumconversationduration","avgconversationduration",
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"sdconversationduration","minconversationduration","maxconversationduration","timefirstconversation","timelastconversation","noisesumenergy",
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"noiseavgenergy","noisesdenergy","noiseminenergy","noisemaxenergy","voicesumenergy",
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"voiceavgenergy","voicesdenergy","voiceminenergy","voicemaxenergy","silencesensedfraction","noisesensedfraction",
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"voicesensedfraction","unknownsensedfraction","silenceexpectedfraction","noiseexpectedfraction","voiceexpectedfraction",
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"unknownexpectedfraction","countconversation"]
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RECORDING_MINUTES: 1
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PAUSED_MINUTES : 3
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SRC_SCRIPT: src/features/phone_conversation/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-data-yield/
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PHONE_DATA_YIELD:
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SENSORS: [PHONE_SCREEN, PHONE_LIGHT]
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PROVIDERS:
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RAPIDS:
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COMPUTE: TRUE
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FEATURES: [ratiovalidyieldedminutes, ratiovalidyieldedhours]
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MINUTE_RATIO_THRESHOLD_FOR_VALID_YIELDED_HOURS: 0.5 # 0 to 1, minimum percentage of valid minutes in an hour to be considered valid.
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SRC_SCRIPT: src/features/phone_data_yield/rapids/main.R
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# See https://www.rapids.science/latest/features/phone-keyboard/
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PHONE_KEYBOARD:
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CONTAINER: phone_keyboard_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["sessioncount","averageinterkeydelay","averagesessionlength","changeintextlengthlessthanminusone","changeintextlengthequaltominusone","changeintextlengthequaltoone","changeintextlengthmorethanone","maxtextlength","lastmessagelength","totalkeyboardtouches"]
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SRC_SCRIPT: src/features/phone_keyboard/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-light/
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PHONE_LIGHT:
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CONTAINER: phone_light_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["count", "maxlux", "minlux", "avglux", "medianlux", "stdlux"]
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SRC_SCRIPT: src/features/phone_light/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-locations/
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PHONE_LOCATIONS:
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CONTAINER: phone_locations_raw.csv
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LOCATIONS_TO_USE: GPS # ALL, GPS, ALL_RESAMPLED, OR FUSED_RESAMPLED
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FUSED_RESAMPLED_CONSECUTIVE_THRESHOLD: 30 # minutes, only replicate location samples to the next sensed bin if the phone did not stop collecting data for more than this threshold
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FUSED_RESAMPLED_TIME_SINCE_VALID_LOCATION: 720 # minutes, only replicate location samples to consecutive sensed bins if they were logged within this threshold after a valid location row
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ACCURACY_LIMIT: 100 # meters, drops location coordinates with an accuracy higher than this. This number means there's a 68% probability the true location is within this radius
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PROVIDERS:
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DORYAB:
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COMPUTE: True
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FEATURES: ["locationvariance","loglocationvariance","totaldistance","avgspeed","varspeed", "numberofsignificantplaces","numberlocationtransitions","radiusgyration","timeattop1location","timeattop2location","timeattop3location","movingtostaticratio","outlierstimepercent","maxlengthstayatclusters","minlengthstayatclusters","avglengthstayatclusters","stdlengthstayatclusters","locationentropy","normalizedlocationentropy","timeathome"]
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DBSCAN_EPS: 10 # meters
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DBSCAN_MINSAMPLES: 3
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THRESHOLD_STATIC : 1 # km/h
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MAXIMUM_ROW_GAP: 300 # seconds
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MINUTES_DATA_USED: False
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CLUSTER_ON: PARTICIPANT_DATASET # PARTICIPANT_DATASET, TIME_SEGMENT, TIME_SEGMENT_INSTANCE
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INFER_HOME_LOCATION_STRATEGY: DORYAB_STRATEGY # DORYAB_STRATEGY, SUN_LI_VEGA_STRATEGY
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MINIMUM_DAYS_TO_DETECT_HOME_CHANGES: 3
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CLUSTERING_ALGORITHM: DBSCAN # DBSCAN, OPTICS
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RADIUS_FOR_HOME: 100
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SRC_SCRIPT: src/features/phone_locations/doryab/main.py
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BARNETT:
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COMPUTE: False
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FEATURES: ["hometime","disttravelled","rog","maxdiam","maxhomedist","siglocsvisited","avgflightlen","stdflightlen","avgflightdur","stdflightdur","probpause","siglocentropy","circdnrtn","wkenddayrtn"]
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IF_MULTIPLE_TIMEZONES: USE_MOST_COMMON
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MINUTES_DATA_USED: False # Use this for quality control purposes, how many minutes of data (location coordinates gruped by minute) were used to compute features
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SRC_SCRIPT: src/features/phone_locations/barnett/main.R
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# See https://www.rapids.science/latest/features/phone-log/
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PHONE_LOG:
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CONTAINER:
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ANDROID: aware_log
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IOS: ios_aware_log
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PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD
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# See https://www.rapids.science/latest/features/phone-messages/
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PHONE_MESSAGES:
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CONTAINER: phone_messages_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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MESSAGES_TYPES : [received, sent]
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FEATURES:
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received: [count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
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sent: [count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
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SRC_SCRIPT: src/features/phone_messages/rapids/main.R
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# See https://www.rapids.science/latest/features/phone-screen/
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PHONE_SCREEN:
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CONTAINER: phone_screen_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: False
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REFERENCE_HOUR_FIRST_USE: 0
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IGNORE_EPISODES_SHORTER_THAN: 0 # in minutes, set to 0 to disable
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IGNORE_EPISODES_LONGER_THAN: 0 # in minutes, set to 0 to disable
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FEATURES: ["countepisode", "sumduration", "maxduration", "minduration", "avgduration", "stdduration", "firstuseafter"] # "episodepersensedminutes" needs to be added later
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EPISODE_TYPES: ["unlock"]
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SRC_SCRIPT: src/features/phone_screen/rapids/main.py
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# See https://www.rapids.science/latest/features/phone-wifi-connected/
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PHONE_WIFI_CONNECTED:
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CONTAINER: phone_wifi_connected_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
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SRC_SCRIPT: src/features/phone_wifi_connected/rapids/main.R
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# See https://www.rapids.science/latest/features/phone-wifi-visible/
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PHONE_WIFI_VISIBLE:
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CONTAINER: phone_wifi_visible_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
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SRC_SCRIPT: src/features/phone_wifi_visible/rapids/main.R
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########################################################################################################################
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# FITBIT #
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########################################################################################################################
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# See https://www.rapids.science/latest/setup/configuration/#data-stream-configuration
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FITBIT_DATA_STREAMS:
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USE: fitbitparsed_csv
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# AVAILABLE:
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fitbitjson_mysql:
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DATABASE_GROUP: MY_GROUP
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SLEEP_SUMMARY_LAST_NIGHT_END: 660 # a number ranged from 0 (midnight) to 1439 (23:59) which denotes number of minutes after midnight. By default, 660 (11:00).
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fitbitparsed_mysql:
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DATABASE_GROUP: MY_GROUP
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SLEEP_SUMMARY_LAST_NIGHT_END: 660 # a number ranged from 0 (midnight) to 1439 (23:59) which denotes number of minutes after midnight. By default, 660 (11:00).
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fitbitjson_csv:
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FOLDER: data/external/fitbit_csv
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SLEEP_SUMMARY_LAST_NIGHT_END: 660 # a number ranged from 0 (midnight) to 1439 (23:59) which denotes number of minutes after midnight. By default, 660 (11:00).
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fitbitparsed_csv:
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FOLDER: tests/data/external/aware_csv
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SLEEP_SUMMARY_LAST_NIGHT_END: 660 # a number ranged from 0 (midnight) to 1439 (23:59) which denotes number of minutes after midnight. By default, 660 (11:00).
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# Sensors ------
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FITBIT_CALORIES_INTRADAY:
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CONTAINER: fitbit_calories_intraday_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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EPISODE_TYPE: [sedentary, lightlyactive, fairlyactive, veryactive, mvpa, lowmet, highmet]
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EPISODE_TIME_THRESHOLD: 5 # minutes
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EPISODE_MET_THRESHOLD: 3
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EPISODE_MVPA_CATEGORIES: [fairlyactive, veryactive]
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EPISODE_REFERENCE_TIME: MIDNIGHT # MIDNIGHT or START_OF_THE_SEGMENT
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FEATURES: [count, sumduration, avgduration, minduration, maxduration, stdduration, starttimefirst, endtimefirst, starttimelast, endtimelast, starttimelongest, endtimelongest, summet, avgmet, maxmet, minmet, stdmet, sumcalories, avgcalories, maxcalories, mincalories, stdcalories]
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SRC_SCRIPT: src/features/fitbit_calories_intraday/rapids/main.R
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# See https://www.rapids.science/latest/features/fitbit-data-yield/
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FITBIT_DATA_YIELD:
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SENSOR: FITBIT_HEARTRATE_INTRADAY
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PROVIDERS:
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RAPIDS:
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COMPUTE: TRUE
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FEATURES: [ratiovalidyieldedminutes, ratiovalidyieldedhours]
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MINUTE_RATIO_THRESHOLD_FOR_VALID_YIELDED_HOURS: 0.5 # 0 to 1, minimum percentage of valid minutes in an hour to be considered valid.
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SRC_SCRIPT: src/features/fitbit_data_yield/rapids/main.R
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# See https://www.rapids.science/latest/features/fitbit-heartrate-summary/
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FITBIT_HEARTRATE_SUMMARY:
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CONTAINER: fitbit_heartrate_summary_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["maxrestinghr", "minrestinghr", "avgrestinghr", "medianrestinghr", "moderestinghr", "stdrestinghr", "diffmaxmoderestinghr", "diffminmoderestinghr", "entropyrestinghr", "sumcaloriesoutofrange", "maxcaloriesoutofrange", "mincaloriesoutofrange", "avgcaloriesoutofrange", "mediancaloriesoutofrange", "stdcaloriesoutofrange", "entropycaloriesoutofrange", "sumcaloriesfatburn", "maxcaloriesfatburn", "mincaloriesfatburn", "avgcaloriesfatburn", "mediancaloriesfatburn", "stdcaloriesfatburn", "entropycaloriesfatburn", "sumcaloriescardio", "maxcaloriescardio", "mincaloriescardio", "avgcaloriescardio", "mediancaloriescardio", "stdcaloriescardio", "entropycaloriescardio", "sumcaloriespeak", "maxcaloriespeak", "mincaloriespeak", "avgcaloriespeak", "mediancaloriespeak", "stdcaloriespeak", "entropycaloriespeak"] # calories features' accuracy depend on the accuracy of the participants fitbit profile (e.g. height, weight) use these with care: ["sumcaloriesoutofrange", "maxcaloriesoutofrange", "mincaloriesoutofrange", "avgcaloriesoutofrange", "mediancaloriesoutofrange", "stdcaloriesoutofrange", "entropycaloriesoutofrange", "sumcaloriesfatburn", "maxcaloriesfatburn", "mincaloriesfatburn", "avgcaloriesfatburn", "mediancaloriesfatburn", "stdcaloriesfatburn", "entropycaloriesfatburn", "sumcaloriescardio", "maxcaloriescardio", "mincaloriescardio", "avgcaloriescardio", "mediancaloriescardio", "stdcaloriescardio", "entropycaloriescardio", "sumcaloriespeak", "maxcaloriespeak", "mincaloriespeak", "avgcaloriespeak", "mediancaloriespeak", "stdcaloriespeak", "entropycaloriespeak"]
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SRC_SCRIPT: src/features/fitbit_heartrate_summary/rapids/main.py
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# See https://www.rapids.science/latest/features/fitbit-heartrate-intraday/
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FITBIT_HEARTRATE_INTRADAY:
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CONTAINER: fitbit_heartrate_intraday_raw.csv
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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FEATURES: ["maxhr", "minhr", "avghr", "medianhr", "modehr", "stdhr", "diffmaxmodehr", "diffminmodehr", "entropyhr", "minutesonoutofrangezone", "minutesonfatburnzone", "minutesoncardiozone", "minutesonpeakzone"]
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SRC_SCRIPT: src/features/fitbit_heartrate_intraday/rapids/main.py
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# See https://www.rapids.science/latest/features/fitbit-sleep-summary/
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|
FITBIT_SLEEP_SUMMARY:
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CONTAINER: fitbit_sleep_summary_raw.csv
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|
PROVIDERS:
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RAPIDS:
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COMPUTE: True
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|
FEATURES: ["firstwaketime", "lastwaketime", "firstbedtime", "lastbedtime", "countepisode", "avgefficiency", "sumdurationafterwakeup", "sumdurationasleep", "sumdurationawake", "sumdurationtofallasleep", "sumdurationinbed", "avgdurationafterwakeup", "avgdurationasleep", "avgdurationawake", "avgdurationtofallasleep", "avgdurationinbed"]
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SLEEP_TYPES: ["main", "nap", "all"]
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SRC_SCRIPT: src/features/fitbit_sleep_summary/rapids/main.py
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# See https://www.rapids.science/latest/features/fitbit-sleep-intraday/
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|
FITBIT_SLEEP_INTRADAY:
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|
CONTAINER: fitbit_sleep_intraday_raw.csv
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PROVIDERS:
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|
RAPIDS:
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|
COMPUTE: True
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|
FEATURES:
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|
LEVELS_AND_TYPES: [countepisode, sumduration, maxduration, minduration, avgduration, medianduration, stdduration]
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|
RATIOS_TYPE: [count, duration]
|
|
RATIOS_SCOPE: [ACROSS_LEVELS, ACROSS_TYPES, WITHIN_LEVELS, WITHIN_TYPES]
|
|
SLEEP_LEVELS:
|
|
INCLUDE_ALL_GROUPS: True
|
|
CLASSIC: [awake, restless, asleep]
|
|
STAGES: [wake, deep, light, rem]
|
|
UNIFIED: [awake, asleep]
|
|
SLEEP_TYPES: [main, nap, all]
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|
SRC_SCRIPT: src/features/fitbit_sleep_intraday/rapids/main.py
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|
|
|
PRICE:
|
|
COMPUTE: True
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|
FEATURES: [avgduration, avgratioduration, avgstarttimeofepisodemain, avgendtimeofepisodemain, avgmidpointofepisodemain, stdstarttimeofepisodemain, stdendtimeofepisodemain, stdmidpointofepisodemain, socialjetlag, rmssdmeanstarttimeofepisodemain, rmssdmeanendtimeofepisodemain, rmssdmeanmidpointofepisodemain, rmssdmedianstarttimeofepisodemain, rmssdmedianendtimeofepisodemain, rmssdmedianmidpointofepisodemain]
|
|
SLEEP_LEVELS:
|
|
INCLUDE_ALL_GROUPS: True
|
|
CLASSIC: [awake, restless, asleep]
|
|
STAGES: [wake, deep, light, rem]
|
|
UNIFIED: [awake, asleep]
|
|
DAY_TYPES: [WEEKEND, WEEK, ALL]
|
|
LAST_NIGHT_END: 660 # number of minutes after midnight (11:00) 11*60
|
|
SRC_SCRIPT: src/features/fitbit_sleep_intraday/price/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/fitbit-steps-summary/
|
|
FITBIT_STEPS_SUMMARY:
|
|
CONTAINER: fitbit_steps_summary_raw.csv
|
|
PROVIDERS:
|
|
RAPIDS:
|
|
COMPUTE: True
|
|
FEATURES: ["maxsumsteps", "minsumsteps", "avgsumsteps", "mediansumsteps", "stdsumsteps"]
|
|
SRC_SCRIPT: src/features/fitbit_steps_summary/rapids/main.py
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|
|
|
# See https://www.rapids.science/latest/features/fitbit-steps-intraday/
|
|
FITBIT_STEPS_INTRADAY:
|
|
CONTAINER: fitbit_steps_intraday_raw.csv
|
|
EXCLUDE_SLEEP: # you can exclude step data that was logged during sleep periods
|
|
TIME_BASED:
|
|
EXCLUDE: False
|
|
START_TIME: "23:00"
|
|
END_TIME: "07:00"
|
|
FITBIT_BASED:
|
|
EXCLUDE: False
|
|
PROVIDERS:
|
|
RAPIDS:
|
|
COMPUTE: True
|
|
FEATURES:
|
|
STEPS: ["sum", "max", "min", "avg", "std"]
|
|
SEDENTARY_BOUT: ["countepisode", "sumduration", "maxduration", "minduration", "avgduration", "stdduration"]
|
|
ACTIVE_BOUT: ["countepisode", "sumduration", "maxduration", "minduration", "avgduration", "stdduration"]
|
|
THRESHOLD_ACTIVE_BOUT: 10 # steps
|
|
INCLUDE_ZERO_STEP_ROWS: False
|
|
SRC_SCRIPT: src/features/fitbit_steps_intraday/rapids/main.py
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|
|
|
########################################################################################################################
|
|
# EMPATICA #
|
|
########################################################################################################################
|
|
|
|
EMPATICA_DATA_STREAMS:
|
|
USE: empatica_zip
|
|
|
|
# AVAILABLE:
|
|
empatica_zip:
|
|
FOLDER: data/external/empatica
|
|
|
|
# Sensors ------
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-accelerometer/
|
|
EMPATICA_ACCELEROMETER:
|
|
CONTAINER: ACC
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
|
|
SRC_SCRIPT: src/features/empatica_accelerometer/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-heartrate/
|
|
EMPATICA_HEARTRATE:
|
|
CONTAINER: HR
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxhr", "minhr", "avghr", "medianhr", "modehr", "stdhr", "diffmaxmodehr", "diffminmodehr", "entropyhr"]
|
|
SRC_SCRIPT: src/features/empatica_heartrate/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-temperature/
|
|
EMPATICA_TEMPERATURE:
|
|
CONTAINER: TEMP
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxtemp", "mintemp", "avgtemp", "mediantemp", "modetemp", "stdtemp", "diffmaxmodetemp", "diffminmodetemp", "entropytemp"]
|
|
SRC_SCRIPT: src/features/empatica_temperature/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-electrodermal-activity/
|
|
EMPATICA_ELECTRODERMAL_ACTIVITY:
|
|
CONTAINER: EDA
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxeda", "mineda", "avgeda", "medianeda", "modeeda", "stdeda", "diffmaxmodeeda", "diffminmodeeda", "entropyeda"]
|
|
SRC_SCRIPT: src/features/empatica_electrodermal_activity/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-blood-volume-pulse/
|
|
EMPATICA_BLOOD_VOLUME_PULSE:
|
|
CONTAINER: BVP
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxbvp", "minbvp", "avgbvp", "medianbvp", "modebvp", "stdbvp", "diffmaxmodebvp", "diffminmodebvp", "entropybvp"]
|
|
SRC_SCRIPT: src/features/empatica_blood_volume_pulse/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-inter-beat-interval/
|
|
EMPATICA_INTER_BEAT_INTERVAL:
|
|
CONTAINER: IBI
|
|
PROVIDERS:
|
|
DBDP:
|
|
COMPUTE: False
|
|
FEATURES: ["maxibi", "minibi", "avgibi", "medianibi", "modeibi", "stdibi", "diffmaxmodeibi", "diffminmodeibi", "entropyibi"]
|
|
SRC_SCRIPT: src/features/empatica_inter_beat_interval/dbdp/main.py
|
|
|
|
# See https://www.rapids.science/latest/features/empatica-tags/
|
|
EMPATICA_TAGS:
|
|
CONTAINER: TAGS
|
|
PROVIDERS: # None implemented yet
|
|
|
|
|
|
########################################################################################################################
|
|
# PLOTS #
|
|
########################################################################################################################
|
|
|
|
# Data quality ------
|
|
|
|
# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#1-histograms-of-phone-data-yield
|
|
HISTOGRAM_PHONE_DATA_YIELD:
|
|
PLOT: False
|
|
|
|
# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#2-heatmaps-of-overall-data-yield
|
|
HEATMAP_PHONE_DATA_YIELD_PER_PARTICIPANT_PER_TIME_SEGMENT:
|
|
PLOT: False
|
|
TIME: ABSOLUTE_TIME # ABSOLUTE_TIME or RELATIVE_TIME
|
|
|
|
# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#3-heatmap-of-recorded-phone-sensors
|
|
HEATMAP_SENSORS_PER_MINUTE_PER_TIME_SEGMENT:
|
|
PLOT: False
|
|
|
|
# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#4-heatmap-of-sensor-row-count
|
|
HEATMAP_SENSOR_ROW_COUNT_PER_TIME_SEGMENT:
|
|
PLOT: False
|
|
SENSORS: [PHONE_ACCELEROMETER, PHONE_ACTIVITY_RECOGNITION, PHONE_APPLICATIONS_FOREGROUND, PHONE_BATTERY, PHONE_BLUETOOTH, PHONE_CALLS, PHONE_CONVERSATION, PHONE_LIGHT, PHONE_LOCATIONS, PHONE_MESSAGES, PHONE_SCREEN, PHONE_WIFI_CONNECTED, PHONE_WIFI_VISIBLE]
|
|
|
|
# Features ------
|
|
|
|
# See https://www.rapids.science/latest/visualizations/feature-visualizations/#1-heatmap-correlation-matrix
|
|
HEATMAP_FEATURE_CORRELATION_MATRIX:
|
|
PLOT: False
|
|
MIN_ROWS_RATIO: 0.5
|
|
CORR_THRESHOLD: 0.1
|
|
CORR_METHOD: "pearson" # choose from {"pearson", "kendall", "spearman"}
|
|
|