rapids/config.yaml

########################################################################################################################
#                                              GLOBAL CONFIGURATION                                                    #
########################################################################################################################

# See https://www.rapids.science/latest/setup/configuration/#participant-files
PIDS: [p01]

# See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files
CREATE_PARTICIPANT_FILES:
  CSV_FILE_PATH: "data/external/example_participants.csv" # see docs for required format
  PHONE_SECTION:
    ADD: True
    IGNORED_DEVICE_IDS: []
  FITBIT_SECTION:
    ADD: True
    IGNORED_DEVICE_IDS: []
  EMPATICA_SECTION:
    ADD: True
    IGNORED_DEVICE_IDS: []

# See https://www.rapids.science/latest/setup/configuration/#time-segments
TIME_SEGMENTS: &time_segments
  TYPE: PERIODIC # FREQUENCY, PERIODIC, EVENT
  FILE: "data/external/timesegments_periodic.csv"
  INCLUDE_PAST_PERIODIC_SEGMENTS: FALSE # Only relevant if TYPE=PERIODIC, see docs

# See https://www.rapids.science/latest/setup/configuration/#timezone-of-your-study
TIMEZONE: 
    TYPE: SINGLE
    SINGLE:
      TZCODE: Europe/Ljubljana
    MULTIPLE:
      TZCODES_FILE: data/external/multiple_timezones_example.csv
      IF_MISSING_TZCODE: USE_DEFAULT
      DEFAULT_TZCODE: Europe/Ljubljana
      FITBIT: 
        ALLOW_MULTIPLE_TZ_PER_DEVICE: False
        INFER_FROM_SMARTPHONE_TZ: False

########################################################################################################################
#                                                 PHONE                                                                #
########################################################################################################################

# See https://www.rapids.science/latest/setup/configuration/#data-stream-configuration
PHONE_DATA_STREAMS:
  USE: aware_csv
  
  # AVAILABLE:
  aware_mysql: 
    DATABASE_GROUP: MY_GROUP

  aware_csv:
    FOLDER: data/external/aware_csv
  
  aware_influxdb: 
    DATABASE_GROUP: MY_GROUP

# Sensors ------

# https://www.rapids.science/latest/features/phone-accelerometer/
PHONE_ACCELEROMETER:
  CONTAINER: accelerometer
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
      SRC_SCRIPT: src/features/phone_accelerometer/rapids/main.py
    
    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_SCRIPT: src/features/phone_accelerometer/panda/main.py

# See https://www.rapids.science/latest/features/phone-activity-recognition/
PHONE_ACTIVITY_RECOGNITION:
  CONTAINER: 
    ANDROID: plugin_google_activity_recognition
    IOS: plugin_ios_activity_recognition
  EPISODE_THRESHOLD_BETWEEN_ROWS: 5 # minutes. Max time difference for two consecutive rows to be considered within the same AR episode.
  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_SCRIPT: src/features/phone_activity_recognition/rapids/main.py

# See https://www.rapids.science/latest/features/phone-applications-crashes/
PHONE_APPLICATIONS_CRASHES:
  CONTAINER: applications_crashes
  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
  PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD

# See https://www.rapids.science/latest/features/phone-applications-foreground/
PHONE_APPLICATIONS_FOREGROUND:
  CONTAINER: applications_foreground
  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
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      INCLUDE_EPISODE_FEATURES: False
      SINGLE_CATEGORIES: ["all", "email"]
      MULTIPLE_CATEGORIES:
        social: ["socialnetworks", "socialmediatools"]
        entertainment: ["entertainment", "gamingknowledge", "gamingcasual", "gamingadventure", "gamingstrategy", "gamingtoolscommunity", "gamingroleplaying", "gamingaction", "gaminglogic", "gamingsports", "gamingsimulation"]
      CUSTOM_CATEGORIES:
        social_media: ["com.google.android.youtube", "com.snapchat.android", "com.instagram.android", "com.zhiliaoapp.musically", "com.facebook.katana"]
        dating: ["com.tinder", "com.relance.happycouple", "com.kiwi.joyride"]
      SINGLE_APPS: ["top1global", "com.facebook.moments", "com.google.android.youtube", "com.twitter.android"] # There's no entropy for single apps
      EXCLUDED_CATEGORIES: []
      EXCLUDED_APPS: ["com.fitbit.FitbitMobile", "com.aware.plugin.upmc.cancer"]
      FEATURES: 
        APP_EVENTS: ["countevent", "timeoffirstuse", "timeoflastuse", "frequencyentropy"]
        APP_EPISODES: ["countepisode", "minduration", "maxduration", "meanduration", "sumduration"]
      IGNORE_EPISODES_SHORTER_THAN: 0 # in minutes, set to 0 to disable
      IGNORE_EPISODES_LONGER_THAN: 300 # in minutes, set to 0 to disable
      SRC_SCRIPT: src/features/phone_applications_foreground/rapids/main.py

# See https://www.rapids.science/latest/features/phone-applications-notifications/
PHONE_APPLICATIONS_NOTIFICATIONS:
  CONTAINER: applications_notifications
  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
  PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD

# See https://www.rapids.science/latest/features/phone-battery/
PHONE_BATTERY:
  CONTAINER: battery
  EPISODE_THRESHOLD_BETWEEN_ROWS: 30 # minutes. Max time difference for two consecutive rows to be considered within the same battery episode.
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["countdischarge", "sumdurationdischarge", "countcharge", "sumdurationcharge", "avgconsumptionrate", "maxconsumptionrate"]
      SRC_SCRIPT: src/features/phone_battery/rapids/main.py

# See https://www.rapids.science/latest/features/phone-bluetooth/
PHONE_BLUETOOTH:
  CONTAINER: bluetooth
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
      SRC_SCRIPT: src/features/phone_bluetooth/rapids/main.R

    DORYAB:
      COMPUTE: False
      FEATURES: 
        ALL: 
            DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
            SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
            SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
        OWN: 
            DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
            SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
            SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
        OTHERS:
            DEVICES: ["countscans", "uniquedevices", "meanscans", "stdscans"]
            SCANS_MOST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
            SCANS_LEAST_FREQUENT_DEVICE: ["withinsegments", "acrosssegments", "acrossdataset"]
      SRC_SCRIPT: src/features/phone_bluetooth/doryab/main.py

# See https://www.rapids.science/latest/features/phone-calls/
PHONE_CALLS:
  CONTAINER: calls.csv
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES_TYPE: EPISODES # EVENTS or EPISODES
      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_SCRIPT: src/features/phone_calls/rapids/main.R

# See https://www.rapids.science/latest/features/phone-conversation/
PHONE_CONVERSATION:
  CONTAINER: 
    ANDROID: plugin_studentlife_audio_android
    IOS: plugin_studentlife_audio
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["minutessilence", "minutesnoise", "minutesvoice", "minutesunknown","sumconversationduration","avgconversationduration",
    "sdconversationduration","minconversationduration","maxconversationduration","timefirstconversation","timelastconversation","noisesumenergy",
    "noiseavgenergy","noisesdenergy","noiseminenergy","noisemaxenergy","voicesumenergy",
    "voiceavgenergy","voicesdenergy","voiceminenergy","voicemaxenergy","silencesensedfraction","noisesensedfraction",
    "voicesensedfraction","unknownsensedfraction","silenceexpectedfraction","noiseexpectedfraction","voiceexpectedfraction",
    "unknownexpectedfraction","countconversation"]
      RECORDING_MINUTES: 1
      PAUSED_MINUTES : 3
      SRC_SCRIPT: src/features/phone_conversation/rapids/main.py

# See https://www.rapids.science/latest/features/phone-data-yield/
PHONE_DATA_YIELD:
  SENSORS: []
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: [ratiovalidyieldedminutes, ratiovalidyieldedhours]
      MINUTE_RATIO_THRESHOLD_FOR_VALID_YIELDED_HOURS: 0.5 # 0 to 1, minimum percentage of valid minutes in an hour to be considered valid.
      SRC_SCRIPT: src/features/phone_data_yield/rapids/main.R

# See https://www.rapids.science/latest/features/phone-keyboard/
PHONE_KEYBOARD:
  CONTAINER: keyboard
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["sessioncount","averageinterkeydelay","averagesessionlength","changeintextlengthlessthanminusone","changeintextlengthequaltominusone","changeintextlengthequaltoone","changeintextlengthmorethanone","maxtextlength","lastmessagelength","totalkeyboardtouches"]
      SRC_SCRIPT: src/features/phone_keyboard/rapids/main.py

# See https://www.rapids.science/latest/features/phone-light/
PHONE_LIGHT:
  CONTAINER: light
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["count", "maxlux", "minlux", "avglux", "medianlux", "stdlux"]
      SRC_SCRIPT: src/features/phone_light/rapids/main.py

# See https://www.rapids.science/latest/features/phone-locations/
PHONE_LOCATIONS:
  CONTAINER: locations
  LOCATIONS_TO_USE: ALL_RESAMPLED # ALL, GPS, ALL_RESAMPLED, 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
  ACCURACY_LIMIT: 100 # meters, drops location coordinates with an accuracy equal or higher than this. This number means there's a 68% probability the true location is within this radius

  PROVIDERS:
    DORYAB:
      COMPUTE: False
      FEATURES: ["locationvariance","loglocationvariance","totaldistance","avgspeed","varspeed", "numberofsignificantplaces","numberlocationtransitions","radiusgyration","timeattop1location","timeattop2location","timeattop3location","movingtostaticratio","outlierstimepercent","maxlengthstayatclusters","minlengthstayatclusters","avglengthstayatclusters","stdlengthstayatclusters","locationentropy","normalizedlocationentropy","timeathome", "homelabel"]
      DBSCAN_EPS: 100 # meters
      DBSCAN_MINSAMPLES: 5
      THRESHOLD_STATIC : 1 # km/h
      MAXIMUM_ROW_GAP: 300 # seconds
      MINUTES_DATA_USED: False
      CLUSTER_ON: PARTICIPANT_DATASET # PARTICIPANT_DATASET, TIME_SEGMENT, TIME_SEGMENT_INSTANCE
      INFER_HOME_LOCATION_STRATEGY: DORYAB_STRATEGY # DORYAB_STRATEGY, SUN_LI_VEGA_STRATEGY
      MINIMUM_DAYS_TO_DETECT_HOME_CHANGES: 3
      CLUSTERING_ALGORITHM: DBSCAN # DBSCAN, OPTICS
      RADIUS_FOR_HOME: 100
      SRC_SCRIPT: src/features/phone_locations/doryab/main.py

    BARNETT:
      COMPUTE: False
      FEATURES: ["hometime","disttravelled","rog","maxdiam","maxhomedist","siglocsvisited","avgflightlen","stdflightlen","avgflightdur","stdflightdur","probpause","siglocentropy","circdnrtn","wkenddayrtn"]
      IF_MULTIPLE_TIMEZONES: USE_MOST_COMMON
      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_SCRIPT: src/features/phone_locations/barnett/main.R

# See https://www.rapids.science/latest/features/phone-log/
PHONE_LOG:
  CONTAINER: 
    ANDROID: aware_log
    IOS: ios_aware_log
  PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD

# See https://www.rapids.science/latest/features/phone-messages/
PHONE_MESSAGES:
  CONTAINER: messages
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      MESSAGES_TYPES : [received, sent]
      FEATURES: 
        received: [count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
        sent: [count, distinctcontacts, timefirstmessage, timelastmessage, countmostfrequentcontact]
      SRC_SCRIPT: src/features/phone_messages/rapids/main.R

# See https://www.rapids.science/latest/features/phone-screen/
PHONE_SCREEN:
  CONTAINER: screen
  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: 360 # 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_SCRIPT: src/features/phone_screen/rapids/main.py

# See https://www.rapids.science/latest/features/phone-wifi-connected/
PHONE_WIFI_CONNECTED:
  CONTAINER: sensor_wifi
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
      SRC_SCRIPT: src/features/phone_wifi_connected/rapids/main.R

# See https://www.rapids.science/latest/features/phone-wifi-visible/
PHONE_WIFI_VISIBLE:
  CONTAINER: wifi
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["countscans", "uniquedevices", "countscansmostuniquedevice"]
      SRC_SCRIPT: src/features/phone_wifi_visible/rapids/main.R



########################################################################################################################
#                                                 FITBIT                                                               #
########################################################################################################################

# See https://www.rapids.science/latest/setup/configuration/#data-stream-configuration
FITBIT_DATA_STREAMS:
  USE: fitbitjson_mysql
  
  # AVAILABLE:
  fitbitjson_mysql: 
    DATABASE_GROUP: MY_GROUP
    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).
  
  fitbitparsed_mysql: 
    DATABASE_GROUP: MY_GROUP
    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).
  
  fitbitjson_csv: 
    FOLDER: data/external/fitbit_csv
    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).

  fitbitparsed_csv: 
    FOLDER: data/external/fitbit_csv
    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).

# Sensors ------

# See https://www.rapids.science/latest/features/fitbit-calories-intraday/
FITBIT_CALORIES_INTRADAY:
  CONTAINER: fitbit_data
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      EPISODE_TYPE: [sedentary, lightlyactive, fairlyactive, veryactive, mvpa, lowmet, highmet]
      EPISODE_TIME_THRESHOLD: 5 # minutes
      EPISODE_MET_THRESHOLD: 3
      EPISODE_MVPA_CATEGORIES: [fairlyactive, veryactive]
      EPISODE_REFERENCE_TIME: MIDNIGHT # or START_OF_THE_SEGMENT
      FEATURES: [count, sumduration, avgduration, minduration, maxduration, stdduration, starttimefirst, endtimefirst, starttimelast, endtimelast, starttimelongest, endtimelongest, summet, avgmet, maxmet, minmet, stdmet, sumcalories, avgcalories, maxcalories, mincalories, stdcalories]
      SRC_SCRIPT: src/features/fitbit_calories_intraday/rapids/main.R

# See https://www.rapids.science/latest/features/fitbit-data-yield/
FITBIT_DATA_YIELD:
  SENSOR: FITBIT_HEARTRATE_INTRADAY
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: [ratiovalidyieldedminutes, ratiovalidyieldedhours]
      MINUTE_RATIO_THRESHOLD_FOR_VALID_YIELDED_HOURS: 0.5 #  0 to 1, minimum percentage of valid minutes in an hour to be considered valid.
      SRC_SCRIPT: src/features/fitbit_data_yield/rapids/main.R


# See https://www.rapids.science/latest/features/fitbit-heartrate-summary/
FITBIT_HEARTRATE_SUMMARY:
  CONTAINER: heartrate_summary
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["maxrestinghr", "minrestinghr", "avgrestinghr", "medianrestinghr", "moderestinghr", "stdrestinghr", "diffmaxmoderestinghr", "diffminmoderestinghr", "entropyrestinghr"] # 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"]
      SRC_SCRIPT: src/features/fitbit_heartrate_summary/rapids/main.py

# See https://www.rapids.science/latest/features/fitbit-heartrate-intraday/
FITBIT_HEARTRATE_INTRADAY:
  CONTAINER: heartrate_intraday
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["maxhr", "minhr", "avghr", "medianhr", "modehr", "stdhr", "diffmaxmodehr", "diffminmodehr", "entropyhr", "minutesonoutofrangezone", "minutesonfatburnzone", "minutesoncardiozone", "minutesonpeakzone"]
      SRC_SCRIPT: src/features/fitbit_heartrate_intraday/rapids/main.py

# See https://www.rapids.science/latest/features/fitbit-sleep-summary/
FITBIT_SLEEP_SUMMARY:
  CONTAINER: sleep_summary
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["firstwaketime", "lastwaketime", "firstbedtime", "lastbedtime", "countepisode", "avgefficiency", "sumdurationafterwakeup", "sumdurationasleep", "sumdurationawake", "sumdurationtofallasleep", "sumdurationinbed", "avgdurationafterwakeup", "avgdurationasleep", "avgdurationawake", "avgdurationtofallasleep", "avgdurationinbed"]
      SLEEP_TYPES: ["main", "nap", "all"]
      SRC_SCRIPT: src/features/fitbit_sleep_summary/rapids/main.py

# See https://www.rapids.science/latest/features/fitbit-sleep-intraday/
FITBIT_SLEEP_INTRADAY:
  CONTAINER: sleep_intraday
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES:
        LEVELS_AND_TYPES: [countepisode, sumduration, maxduration, minduration, avgduration, medianduration, stdduration]
        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]
      SRC_SCRIPT: src/features/fitbit_sleep_intraday/rapids/main.py
  
    PRICE:
      COMPUTE: False
      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: steps_summary
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      FEATURES: ["maxsumsteps", "minsumsteps", "avgsumsteps", "mediansumsteps", "stdsumsteps"]
      SRC_SCRIPT: src/features/fitbit_steps_summary/rapids/main.py

# See https://www.rapids.science/latest/features/fitbit-steps-intraday/
FITBIT_STEPS_INTRADAY:
  CONTAINER: steps_intraday
  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: False
      FEATURES:
        STEPS: ["sum", "max", "min", "avg", "std", "firststeptime", "laststeptime"]
        SEDENTARY_BOUT: ["countepisode", "sumduration", "maxduration", "minduration", "avgduration", "stdduration"]
        ACTIVE_BOUT: ["countepisode", "sumduration", "maxduration", "minduration", "avgduration", "stdduration"]
      REFERENCE_HOUR: 0
      THRESHOLD_ACTIVE_BOUT: 10 # steps
      INCLUDE_ZERO_STEP_ROWS: False
      SRC_SCRIPT: src/features/fitbit_steps_intraday/rapids/main.py

########################################################################################################################
#                                                 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: True
      FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
      SRC_SCRIPT: src/features/empatica_accelerometer/dbdp/main.py
    CR:
      COMPUTE: True
      FEATURES: ["fqHighestPeakFreqs", "fqHighestPeaks", "fqEnergyFeat", "fqEntropyFeat", "fqHistogramBins","fqAbsMean", "fqSkewness", "fqKurtosis", "fqInterquart", # Freq features
                  "meanLow", "areaLow", "totalAbsoluteAreaBand", "totalMagnitudeBand", "entropyBand", "skewnessBand", "kurtosisBand", 
                  "postureDistanceLow", "absoluteMeanBand", "absoluteAreaBand", "quartilesBand", "interQuartileRangeBand", "varianceBand", 
                  "coefficientOfVariationBand", "amplitudeBand", "totalEnergyBand", "dominantFrequencyEnergyBand", "meanCrossingRateBand", 
                  "correlationBand", "quartilesMagnitudesBand", "interQuartileRangeMagnitudesBand", "areaUnderAccelerationMagnitude", 
                  "peaksDataLow", "sumPerComponentBand", "velocityBand", "meanKineticEnergyBand", "totalKineticEnergyBand", "squareSumOfComponent", 
                  "sumOfSquareComponents", "averageVectorLength", "averageVectorLengthPower", "rollAvgLow", "pitchAvgLow", "rollStdDevLow", 
                  "pitchStdDevLow", "rollMotionAmountLow", "rollMotionRegularityLow", "manipulationLow", "rollPeaks", "pitchPeaks", "rollPitchCorrelation"] # Acc features
      WINDOWS:
        COMPUTE: True
        WINDOW_LENGTH: 10 # specify window length in seconds
        SECOND_ORDER_FEATURES: ['mean', 'median', 'sd', 'max', 'min']
      SRC_SCRIPT: src/features/empatica_accelerometer/cr/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: True
      FEATURES: ["maxtemp", "mintemp", "avgtemp", "mediantemp", "modetemp", "stdtemp", "diffmaxmodetemp", "diffminmodetemp", "entropytemp"]
      SRC_SCRIPT: src/features/empatica_temperature/dbdp/main.py
    CR:
      COMPUTE: True
      FEATURES: ["autocorrelations", "countAboveMean", "countBelowMean", "maximum", "minimum", "meanAbsChange", "longestStrikeAboveMean", 
                  "longestStrikeBelowMean", "stdDev", "median", "meanChange", "numberOfZeroCrossings", "absEnergy", "linearTrendSlope", 
                  "ratioBeyondRSigma", "binnedEntropy", "numOfPeaksAutocorr", "numberOfZeroCrossingsAutocorr", "areaAutocorr",
                  "calcMeanCrossingRateAutocorr", "countAboveMeanAutocorr", "sumPer", "sumSquared", "squareSumOfComponent", 
                  "sumOfSquareComponents"]
      WINDOWS:
        COMPUTE: True
        WINDOW_LENGTH: 600 # specify window length in seconds
        SECOND_ORDER_FEATURES: ['mean', 'median', 'sd', 'max', 'min']
      SRC_SCRIPT: src/features/empatica_temperature/cr/main.py

# See https://www.rapids.science/latest/features/empatica-electrodermal-activity/
EMPATICA_ELECTRODERMAL_ACTIVITY:
  CONTAINER: EDA
  PROVIDERS:
    DBDP:
      COMPUTE: True
      FEATURES: ["maxeda", "mineda", "avgeda", "medianeda", "modeeda", "stdeda", "diffmaxmodeeda", "diffminmodeeda", "entropyeda"]
      SRC_SCRIPT: src/features/empatica_electrodermal_activity/dbdp/main.py
    CR:
      COMPUTE: True
      FEATURES: ['mean', 'std', 'q25', 'q75', 'qd', 'deriv', 'power', 'numPeaks', 'ratePeaks', 'powerPeaks', 'sumPosDeriv', 'propPosDeriv', 'derivTonic', 
                  'sigTonicDifference', 'freqFeats','maxPeakAmplitudeChangeBefore', 'maxPeakAmplitudeChangeAfter', 'avgPeakAmplitudeChangeBefore', 
                  'avgPeakAmplitudeChangeAfter', 'avgPeakChangeRatio', 'maxPeakIncreaseTime', 'maxPeakDecreaseTime', 'maxPeakDuration', 'maxPeakChangeRatio',
                  'avgPeakIncreaseTime', 'avgPeakDecreaseTime', 'avgPeakDuration', 'maxPeakResponseSlopeBefore', 'maxPeakResponseSlopeAfter', 
                  'signalOverallChange', 'changeDuration', 'changeRate', 'significantIncrease', 'significantDecrease']
      WINDOWS:
        COMPUTE: True
        WINDOW_LENGTH: 300 # specify window length in seconds
        SECOND_ORDER_FEATURES: ['mean', 'median', 'sd', 'max', 'min']
      SRC_SCRIPT: src/features/empatica_electrodermal_activity/cr/main.py

# See https://www.rapids.science/latest/features/empatica-blood-volume-pulse/
EMPATICA_BLOOD_VOLUME_PULSE:
  CONTAINER: BVP
  PROVIDERS:
    DBDP:
      COMPUTE: True
      FEATURES: ["maxbvp", "minbvp", "avgbvp", "medianbvp", "modebvp", "stdbvp", "diffmaxmodebvp", "diffminmodebvp", "entropybvp"]
      SRC_SCRIPT: src/features/empatica_blood_volume_pulse/dbdp/main.py
    CR:
      COMPUTE: True
      FEATURES: ['meanHr', 'ibi', 'sdnn', 'sdsd', 'rmssd', 'pnn20', 'pnn50', 'sd', 'sd2', 'sd1/sd2', 'numRR', # Time features
                  'VLF', 'LF', 'LFnorm', 'HF', 'HFnorm', 'LF/HF', 'fullIntegral'] # Freq features
      WINDOWS:
        COMPUTE: True
        WINDOW_LENGTH: 300 # specify window length in seconds
        SECOND_ORDER_FEATURES: ['mean', 'median', 'sd', 'max', 'min']
      SRC_SCRIPT: src/features/empatica_blood_volume_pulse/cr/main.py

# See https://www.rapids.science/latest/features/empatica-inter-beat-interval/
EMPATICA_INTER_BEAT_INTERVAL:
  CONTAINER: IBI
  PROVIDERS:
    DBDP:
      COMPUTE: True
      FEATURES: ["maxibi", "minibi", "avgibi", "medianibi", "modeibi", "stdibi", "diffmaxmodeibi", "diffminmodeibi", "entropyibi"]
      SRC_SCRIPT: src/features/empatica_inter_beat_interval/dbdp/main.py
    CR:
      COMPUTE: True
      FEATURES: ['meanHr', 'ibi', 'sdnn', 'sdsd', 'rmssd', 'pnn20', 'pnn50', 'sd', 'sd2', 'sd1/sd2', 'numRR', # Time features
                  'VLF', 'LF', 'LFnorm', 'HF', 'HFnorm', 'LF/HF', 'fullIntegral'] # Freq features
      WINDOWS:
        COMPUTE: True
        WINDOW_LENGTH: 300 # specify window length in seconds
        SECOND_ORDER_FEATURES: ['mean', 'median', 'sd', 'max', 'min']
      SRC_SCRIPT: src/features/empatica_inter_beat_interval/cr/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: RELATIVE_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: []

# 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"}


########################################################################################################################
#                                                    Data Cleaning                                                     #
########################################################################################################################

ALL_CLEANING_INDIVIDUAL:
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      IMPUTE_SELECTED_EVENT_FEATURES:
        COMPUTE: True
        MIN_DATA_YIELDED_MINUTES_TO_IMPUTE: 0.33
      COLS_NAN_THRESHOLD: 0.3 # set to 1 to disable
      COLS_VAR_THRESHOLD: True
      ROWS_NAN_THRESHOLD: 0.3 # set to 1 to disable
      DATA_YIELD_FEATURE: RATIO_VALID_YIELDED_HOURS # RATIO_VALID_YIELDED_HOURS or RATIO_VALID_YIELDED_MINUTES
      DATA_YIELD_RATIO_THRESHOLD: 0.5 # set to 0 to disable
      DROP_HIGHLY_CORRELATED_FEATURES:
        COMPUTE: True
        MIN_OVERLAP_FOR_CORR_THRESHOLD: 0.5
        CORR_THRESHOLD: 0.95
      SRC_SCRIPT: src/features/all_cleaning_individual/rapids/main.R

ALL_CLEANING_OVERALL:
  PROVIDERS:
    RAPIDS:
      COMPUTE: False
      IMPUTE_SELECTED_EVENT_FEATURES:
        COMPUTE: True
        MIN_DATA_YIELDED_MINUTES_TO_IMPUTE: 0.33
      COLS_NAN_THRESHOLD: 0.3 # set to 1 to disable
      COLS_VAR_THRESHOLD: True
      ROWS_NAN_THRESHOLD: 0.3 # set to 1 to disable
      DATA_YIELD_FEATURE: RATIO_VALID_YIELDED_HOURS # RATIO_VALID_YIELDED_HOURS or RATIO_VALID_YIELDED_MINUTES
      DATA_YIELD_RATIO_THRESHOLD: 0.5 # set to 0 to disable
      DROP_HIGHLY_CORRELATED_FEATURES:
        COMPUTE: True
        MIN_OVERLAP_FOR_CORR_THRESHOLD: 0.5
        CORR_THRESHOLD: 0.95
      SRC_SCRIPT: src/features/all_cleaning_overall/rapids/main.R