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# Participants to include in the analysis
# You must create a file for each participant named pXXX containing their device_id. This can be done manually or automatically
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PIDS : [ test03, test04,test05, test06]
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# Global var with common day segments
DAY_SEGMENTS : &day_segments
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TYPE : FREQUENCY # FREQUENCY, PERIODIC, EVENT
FILE : "data/external/daysegments_frequency.csv"
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INCLUDE_PAST_PERIODIC_SEGMENTS : FALSE # Only relevant if TYPE=PERIODIC, if set to TRUE we consider day segments back enough in the past as to include the first day of data
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# Use tz codes from https://en.wikipedia.org/wiki/List_of_tz_database_time_zones. Double check your code, for example EST is not US Eastern Time.
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TIMEZONE : &timezone
America/New_York
DATABASE_GROUP : &database_group
MY_GROUP
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# config section for the script that creates participant files automatically
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PARTICIPANT_FILES : # run snakemake -j1 -R parse_participant_files
PHONE_SECTION :
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ADD : FALSE
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PARSED_FROM : AWARE_DEVICE_TABLE #AWARE_DEVICE_TABLE or CSV_FILE
PARSED_SOURCE: *database_group # DB credentials group or CSV file path. If CSV file, it should have : device_id, pid (optional), label (optional), start_date (optional), end_date (optional)
IGNORED_DEVICE_IDS : [ ]
FITBIT_SECTION :
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ADD : FALSE
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SAME_AS_PHONE : FALSE # If TRUE, all config below is ignored
PARSED_FROM : CSV_FILE
PARSED_SOURCE : "external/my_fitbit_participants.csv" # CSV file should have: device_id, pid (optional), label (optional), start_date (optional), end_date (optional)
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SENSOR_DATA :
PHONE :
SOURCE :
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TYPE : DATABASE # Phone only supports DATABASE for now
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DATABASE_GROUP : *database_group
DEVICE_ID_COLUMN : device_id # column name
TIMEZONE :
TYPE : SINGLE # SINGLE or MULTIPLE
VALUE : *timezone # IF TYPE=SINGLE, timezone code (e.g. America/New_York, see attribute TIMEZONE above). If TYPE=MULTIPLE, a table in your database with two columns (timestamp, timezone) where timestamp is a unix timestamp and timezone is one of https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
FITBIT :
SOURCE :
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TYPE : DATABASE # DATABASE or FILES (set each FITBIT_SENSOR TABLE attribute accordingly with a table name or a file path)
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DATABASE_GROUP : *database_group
DEVICE_ID_COLUMN : device_id # column name
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TIMEZONE :
TYPE : SINGLE # Fitbit only supports SINGLE timezones
VALUE : *timezone # timezone code (e.g. America/New_York, see attribute TIMEZONE above and https://en.wikipedia.org/wiki/List_of_tz_database_time_zones)
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PHONE_VALID_SENSED_BINS :
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COMPUTE : False # This flag is automatically ignored (set to True) if you are extracting PHONE_VALID_SENSED_DAYS or screen or Barnett's location features
BIN_SIZE : &bin_size 5 # (in minutes)
# Add as many PHONE sensors as you have, they all improve the computation of PHONE_VALID_SENSED_BINS and PHONE_VALID_SENSED_DAYS.
# If you are extracting screen or Barnett/Doryab location features, PHONE_SCREEN and PHONE_LOCATIONS tables are mandatory.
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# You can choose any of the keys shown below, just make sure its TABLE exists in your database!
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# PHONE_MESSAGES, PHONE_CALLS, PHONE_LOCATIONS, PHONE_BLUETOOTH, PHONE_ACTIVITY_RECOGNITION, PHONE_BATTERY, PHONE_SCREEN, PHONE_LIGHT,
# PHONE_ACCELEROMETER, PHONE_APPLICATIONS_FOREGROUND, PHONE_WIFI_VISIBLE, PHONE_WIFI_CONNECTED, PHONE_CONVERSATION
PHONE_SENSORS : [ ]
PHONE_VALID_SENSED_DAYS :
COMPUTE : False
MIN_VALID_HOURS_PER_DAY : &min_valid_hours_per_day [ 16 ] # (out of 24) MIN_HOURS_PER_DAY
MIN_VALID_BINS_PER_HOUR : &min_valid_bins_per_hour [ 6 ] # (out of 60min/BIN_SIZE bins)
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# Communication SMS features config, TYPES and FEATURES keys need to match
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PHONE_MESSAGES :
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TABLE : messages
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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MESSAGES_TYPES : [ received, sent]
FEATURES :
received : [ count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
sent : [ count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
SRC_LANGUAGE : "r"
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SRC_FOLDER : "rapids" # inside src/features/phone_messages
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# Communication call features config, TYPES and FEATURES keys need to match
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PHONE_CALLS :
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TABLE : calls
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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CALL_TYPES : [ missed, incoming, outgoing]
FEATURES :
missed : [ count, distinctcontacts, timefirstcall, timelastcall, countmostfrequentcontact]
incoming : [ count, distinctcontacts, meanduration, sumduration, minduration, maxduration, stdduration, modeduration, entropyduration, timefirstcall, timelastcall, countmostfrequentcontact]
outgoing : [ count, distinctcontacts, meanduration, sumduration, minduration, maxduration, stdduration, modeduration, entropyduration, timefirstcall, timelastcall, countmostfrequentcontact]
SRC_LANGUAGE : "r"
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SRC_FOLDER : "rapids" # inside src/features/phone_calls
PHONE_LOCATIONS :
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TABLE : locations
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LOCATIONS_TO_USE : FUSED_RESAMPLED # ALL, GPS OR FUSED_RESAMPLED
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
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
PROVIDERS :
DORYAB :
COMPUTE : False
FEATURES : [ "locationvariance" , "loglocationvariance" , "totaldistance" , "averagespeed" , "varspeed" , "circadianmovement" , "numberofsignificantplaces" , "numberlocationtransitions" , "radiusgyration" , "timeattop1location" , "timeattop2location" , "timeattop3location" , "movingtostaticratio" , "outlierstimepercent" , "maxlengthstayatclusters" , "minlengthstayatclusters" , "meanlengthstayatclusters" , "stdlengthstayatclusters" , "locationentropy" , "normalizedlocationentropy" ]
DBSCAN_EPS : 10 # meters
DBSCAN_MINSAMPLES : 5
THRESHOLD_STATIC : 1 # km/h
MAXIMUM_GAP_ALLOWED : 300
MINUTES_DATA_USED : False
SAMPLING_FREQUENCY : 0
SRC_FOLDER : "doryab" # inside src/features/phone_locations
SRC_LANGUAGE : "python"
BARNETT :
COMPUTE : False
FEATURES : [ "hometime" , "disttravelled" , "rog" , "maxdiam" , "maxhomedist" , "siglocsvisited" , "avgflightlen" , "stdflightlen" , "avgflightdur" , "stdflightdur" , "probpause" , "siglocentropy" , "circdnrtn" , "wkenddayrtn" ]
ACCURACY_LIMIT : 51 # 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
TIMEZONE : *timezone
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
SRC_FOLDER : "barnett" # inside src/features/phone_locations
SRC_LANGUAGE : "r"
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PHONE_BLUETOOTH :
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TABLE : bluetooth
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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FEATURES : [ "countscans" , "uniquedevices" , "countscansmostuniquedevice" ]
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SRC_FOLDER : "rapids" # inside src/features/phone_bluetooth
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SRC_LANGUAGE : "r"
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PHONE_ACTIVITY_RECOGNITION :
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TABLE :
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ANDROID : plugin_google_activity_recognition
IOS : plugin_ios_activity_recognition
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EPISODE_THRESHOLD_BETWEEN_ROWS : 5 # minutes. Max time difference for two consecutive rows to be considered within the same battery episode.
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PROVIDERS :
RAPIDS :
COMPUTE : False
FEATURES : [ "count" , "mostcommonactivity" , "countuniqueactivities" , "durationstationary" , "durationmobile" , "durationvehicle" ]
ACTIVITY_CLASSES :
STATIONARY : [ "still" , "tilting" ]
MOBILE : [ "on_foot" , "walking" , "running" , "on_bicycle" ]
VEHICLE : [ "in_vehicle" ]
SRC_FOLDER : "rapids" # inside src/features/phone_activity_recognition
SRC_LANGUAGE : "python"
PHONE_BATTERY :
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TABLE : battery
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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 :
RAPIDS :
COMPUTE : False
FEATURES : [ "countdischarge" , "sumdurationdischarge" , "countcharge" , "sumdurationcharge" , "avgconsumptionrate" , "maxconsumptionrate" ]
SRC_FOLDER : "rapids" # inside src/features/phone_battery
SRC_LANGUAGE : "python"
PHONE_SCREEN :
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TABLE : screen
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PROVIDERS :
RAPIDS :
COMPUTE : False
REFERENCE_HOUR_FIRST_USE : 0
IGNORE_EPISODES_SHORTER_THAN : 0 # in minutes, set to 0 to disable
IGNORE_EPISODES_LONGER_THAN : 0 # in minutes, set to 0 to disable
FEATURES : [ "countepisode" , "sumduration" , "maxduration" , "minduration" , "avgduration" , "stdduration" , "firstuseafter" ] # "episodepersensedminutes" needs to be added later
EPISODE_TYPES : [ "unlock" ]
SRC_FOLDER : "rapids" # inside src/features/phone_screen
SRC_LANGUAGE : "python"
PHONE_LIGHT :
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TABLE : light
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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FEATURES : [ "count" , "maxlux" , "minlux" , "avglux" , "medianlux" , "stdlux" ]
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SRC_FOLDER : "rapids" # inside src/features/phone_light
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SRC_LANGUAGE : "python"
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PHONE_ACCELEROMETER :
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TABLE : accelerometer
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PROVIDERS :
RAPIDS :
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COMPUTE : False
FEATURES : [ "maxmagnitude" , "minmagnitude" , "avgmagnitude" , "medianmagnitude" , "stdmagnitude" ]
SRC_FOLDER : "rapids" # inside src/features/phone_accelerometer
SRC_LANGUAGE : "python"
PANDA :
COMPUTE : False
VALID_SENSED_MINUTES : False
FEATURES :
exertional_activity_episode : [ "sumduration" , "maxduration" , "minduration" , "avgduration" , "medianduration" , "stdduration" ]
nonexertional_activity_episode : [ "sumduration" , "maxduration" , "minduration" , "avgduration" , "medianduration" , "stdduration" ]
SRC_FOLDER : "panda" # inside src/features/phone_accelerometer
SRC_LANGUAGE : "python"
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PHONE_APPLICATIONS_FOREGROUND :
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TABLE : applications_foreground
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APPLICATION_CATEGORIES :
CATALOGUE_SOURCE : FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
CATALOGUE_FILE : "data/external/stachl_application_genre_catalogue.csv"
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
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 :
RAPIDS :
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COMPUTE : TRUE
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SINGLE_CATEGORIES : [ "all" , "email" ]
MULTIPLE_CATEGORIES :
social : [ "socialnetworks" , "socialmediatools" ]
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entertainment : [ "entertainment" , "gamingstrategy" ]
SINGLE_APPS : [ "top1global" , "com.facebook.moments" ] # There's no entropy for single apps
EXCLUDED_CATEGORIES : [ "systemapp" , "tvvideoapps" ]
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EXCLUDED_APPS : [ "com.fitbit.FitbitMobile" , "com.aware.plugin.upmc.cancer" ]
FEATURES : [ "count" , "timeoffirstuse" , "timeoflastuse" , "frequencyentropy" ]
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SRC_FOLDER : "rapids" # inside src/features/phone_applications_foreground
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SRC_LANGUAGE : "python"
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PHONE_WIFI_VISIBLE :
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TABLE : "wifi"
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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FEATURES : [ "countscans" , "uniquedevices" , "countscansmostuniquedevice" ]
SRC_FOLDER : "rapids" # inside src/features/phone_wifi_visible
SRC_LANGUAGE : "r"
PHONE_WIFI_CONNECTED :
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TABLE : "sensor_wifi"
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PROVIDERS :
RAPIDS :
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COMPUTE : TRUE
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FEATURES : [ "countscans" , "uniquedevices" , "countscansmostuniquedevice" ]
SRC_FOLDER : "rapids" # inside src/features/phone_wifi_connected
SRC_LANGUAGE : "r"
PHONE_CONVERSATION :
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TABLE :
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ANDROID : plugin_studentlife_audio_android
IOS : plugin_studentlife_audio
PROVIDERS :
RAPIDS :
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COMPUTE : False
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FEATURES : [ "minutessilence" , "minutesnoise" , "minutesvoice" , "minutesunknown" , "sumconversationduration" , "avgconversationduration" ,
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"sdconversationduration" , "minconversationduration" , "maxconversationduration" , "timefirstconversation" , "timelastconversation" , "sumenergy" ,
"avgenergy" , "sdenergy" , "minenergy" , "maxenergy" , "silencesensedfraction" , "noisesensedfraction" ,
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"voicesensedfraction" , "unknownsensedfraction" , "silenceexpectedfraction" , "noiseexpectedfraction" , "voiceexpectedfraction" ,
"unknownexpectedfraction" , "countconversation" ]
RECORDING_MINUTES : 1
PAUSED_MINUTES : 3
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SRC_FOLDER : "rapids" # inside src/features/phone_conversation
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SRC_LANGUAGE : "python"
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############## FITBIT ##########################################################
################################################################################
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FITBIT_HEARTRATE :
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TABLE_FORMAT : JSON # JSON or CSV
TABLE :
JSON : fitbit_heartrate
CSV :
SUMMARY : heartrate_summary.csv
INTRADAY : heartrate_intraday.csv
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PROVIDERS :
RAPIDS :
COMPUTE : False
SUMMARY_FEATURES : [ "restinghr" ] # calories features' accuracy depend on the accuracy of the participants fitbit profile (e.g. height, weight) use these with care : [ "caloriesoutofrange" , "caloriesfatburn" , "caloriescardio" , "caloriespeak" ]
INTRADAY_FEATURES : [ "maxhr" , "minhr" , "avghr" , "medianhr" , "modehr" , "stdhr" , "diffmaxmodehr" , "diffminmodehr" , "entropyhr" , "minutesonoutofrangezone" , "minutesonfatburnzone" , "minutesoncardiozone" , "minutesonpeakzone" ]
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FITBIT_STEPS :
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TABLE_FORMAT : JSON # JSON or CSV
TABLE :
JSON : fitbit_steps
CSV :
SUMMARY : steps_summary.csv
INTRADAY : steps_intraday.csv
EXCLUDE_SLEEP : # you can exclude sleep periods from the step features computation
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EXCLUDE : False
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TYPE : FIXED # FIXED OR FITBIT_BASED (configure FITBIT_SLEEP section)
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FIXED :
START : "23:00"
END : "07:00"
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PROVIDERS :
RAPIDS :
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COMPUTE : False
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FEATURES :
ALL_STEPS : [ "sumallsteps" , "maxallsteps" , "minallsteps" , "avgallsteps" , "stdallsteps" ]
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
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FITBIT_SLEEP :
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TABLE_FORMAT : JSON # JSON or CSV
TABLE :
JSON : fitbit_sleep
CSV :
SUMMARY : sleep_summary.csv
INTRADAY : sleep_intraday.csv
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PROVIDERS :
RAPIDS :
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COMPUTE : False
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SLEEP_TYPES : [ "main" , "nap" , "all" ]
SUMMARY_FEATURES : [ "sumdurationafterwakeup" , "sumdurationasleep" , "sumdurationawake" , "sumdurationtofallasleep" , "sumdurationinbed" , "avgefficiency" , "countepisode" ]
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FITBIT_CALORIES :
TABLE_FORMAT : JSON # JSON or CSV
TABLE :
JSON : fitbit_calories
CSV :
SUMMARY : calories_summary.csv
INTRADAY : calories_intraday.csv
PROVIDERS :
RAPIDS :
COMPUTE : False
FEATURES : [ ]
### Visualizations #############################################################
################################################################################
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HEATMAP_FEATURES_CORRELATIONS :
PLOT : False
MIN_ROWS_RATIO : 0.5
MIN_VALID_HOURS_PER_DAY : *min_valid_hours_per_day
MIN_VALID_BINS_PER_HOUR : *min_valid_bins_per_hour
PHONE_FEATURES : [ accelerometer, activity_recognition, applications_foreground, battery, calls_incoming, calls_missed, calls_outgoing, conversation, light, location_doryab, messages_received, messages_sent, screen]
FITBIT_FEATURES : [ fitbit_heartrate, fitbit_step, fitbit_sleep]
CORR_THRESHOLD : 0.1
CORR_METHOD : "pearson" # choose from {"pearson", "kendall", "spearman"}
HISTOGRAM_VALID_SENSED_HOURS :
PLOT : False
MIN_VALID_HOURS_PER_DAY : *min_valid_hours_per_day
MIN_VALID_BINS_PER_HOUR : *min_valid_bins_per_hour
HEATMAP_DAYS_BY_SENSORS :
PLOT : False
MIN_VALID_HOURS_PER_DAY : *min_valid_hours_per_day
MIN_VALID_BINS_PER_HOUR : *min_valid_bins_per_hour
EXPECTED_NUM_OF_DAYS : -1
DB_TABLES : [ accelerometer, applications_foreground, battery, bluetooth, calls, light, locations, messages, screen, wifi, sensor_wifi, plugin_google_activity_recognition, plugin_ios_activity_recognition, plugin_studentlife_audio_android, plugin_studentlife_audio]
HEATMAP_SENSED_BINS :
PLOT : False
BIN_SIZE : *bin_size
OVERALL_COMPLIANCE_HEATMAP :
PLOT : False
ONLY_SHOW_VALID_DAYS : False
EXPECTED_NUM_OF_DAYS : -1
BIN_SIZE : *bin_size
MIN_VALID_HOURS_PER_DAY : *min_valid_hours_per_day
MIN_VALID_BINS_PER_HOUR : *min_valid_bins_per_hour