all_data_foreground.py (**** No longer required ****) Description: Outputs totals, means, no. of devices, mins, maxs and medians of devices hourly averages for all app foreground instances and all data demand rx and tx. Args:

  1. Device ids csv file
  2. Path of device files Output files:
  3. total_out/all_totals_hourly.csv
  4. total_out/all_means_hourly.csv
  5. total_out/all_deviceNo_hourly.csv
  6. total_out/all_mins_hourly.csv
  7. total_out/all_maxs_hourly.csv
  8. total_out/all_meds_hourly.csv
  9. total_out/all_hourly.csv

app_use_time.py Description: Outputs totals, means, no. of devices, mins, maxs and medians of devices hourly averages for foreground app instances whilst the screen is on and unlocked or other. It also outputs the same calculations for devices hourly averages of use durations and no. of uses, i.e. time screen was on. App use is also summarised into practice use for both foreground app instances whilst the screen is on and unlocked or other Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. use_out/device_use_hourly.csv
  5. use_out/app_foreground_use_hourly.csv
  6. use_out/app_use_totals_hourly.csv
  7. use_out/app_use_means_hourly.csv
  8. use_out/app_use_deviceNo_hourly.csv
  9. use_out/app_use_mins_hourly.csv
  10. use_out/app_use_maxs_hourly.csv
  11. use_out/app_use_meds_hourly.csv
  12. use_out/app_foreground_other_hourly.csv
  13. use_out/app_other_totals_hourly.csv
  14. use_out/app_other_means_hourly.csv
  15. use_out/app_other_deviceNo_hourly.csv
  16. use_out/app_other_mins_hourly.csv
  17. use_out/app_other_maxs_hourly.csv
  18. use_out/app_other_meds_hourly.csv
  19. use_out/practice_hourly_use_summaries_foreground.csv
  20. use_out/practice_hourly_use_summaries_other.csv

day_of_week_totals.py: Description: Outputs the average daily totals of data demand for each day of the week, alongside weekdays and weekend average totals. Rx, tx and both outputted for each day, weekdays, and weekend. Contributions are also outputted for the number of devices which sent data, received data, and both sent and received data. Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. day_totals_output/contribution.csv
  5. day_totals_output/days_of_week_demand_rx.csv
  6. day_totals_output/days_of_week_demand_tx.csv
  7. day_totals_output/days_of_week_demand_all.csv
  8. day_totals_output/weekday_weekend_demand.csv

data_sms_phonecalls.py Description: Outputs totals, means, no. of devices, mins, maxs and medians of devices hourly averages for data demand rx and tx, SMS sent and received, no. of phone calls and duration of phone calls. Args:

  1. Device ids csv file
  2. Path of device files
  3. app-greater50-installs-on-devices-at-least-14-days.csv Output files:
  4. out/sms_summary.csv
  5. out/phone_calls_summary.csv
  6. out/app_hourly_summaries.csv
  7. out/app_hourly_totals.csv
  8. out/app_hourly_means.csv
  9. out/app_hourly_devicesNo.csv
  10. out/app_hourly_mins.csv
  11. out/app_hourly_maxs.csv
  12. out/app_hourly_meds.csv

overall_summary.py Description: Helps give an idea of what percentage of the dataset we're representing overall and per category with the Cambridge app list (apps installed on 50 devices or more). Outputs the number of devices that contribute to: overall data, overall demand of categories, overall use of categories, demand of each category and use of each category (contribution, practice_demand_contribution, practice_use_contribution). Also outputs hourly data summed for devices and categories (all_practice_data, all_practice_rx, all_practice_tx, all_practice_use). Also outputs daily data summed for devices and categories with percentages (daily_practice_data, daily_practice_use). Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. overall_summary/all_practice_data.csv
  5. overall_summary/all_practice_rx.csv
  6. overall_summary/all_practice_tx.csv
  7. overall_summary/all_practice_use.csv
  8. overall_summary/all_totals.csv
  9. overall_summary/contribution.csv
  10. overall_summary/practice_demand_contribution.csv
  11. overall_summary/practice_use_contribution.csv
  12. overall_summary/daily_practice_data.csv
  13. overall_summary/daily_practice_use.csv

parse_everything.py Description: Same as overall_summary.py but also outputs sms and phone calls like data_sms_phonecalls.py. Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. everything/all_practice_data.csv
  5. everything/all_practice_rx.csv
  6. everything/all_practice_tx.csv
  7. everything/all_practice_use.csv
  8. everything/all_totals.csv
  9. everything/contribution.csv
  10. everything/practice_demand_contribution.csv
  11. everything/practice_use_contribution.csv
  12. everything/daily_practice_data.csv
  13. everything/daily_practice_use.csv
  14. everything/sms_summary.csv
  15. everything/phone_calls_summary.csv

stats_summary.py Description: Outputs the daily average data demand for each user for each practice in bytes (user by practice table). Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. stats/user_practices_stats.csv

practice_data_demand.py Description: Outputs hourly totals of data demand per practice, i.e. totals of hourly app averages based on devices hourly app averages. Args:

  1. Device ids csv file
  2. Path of device files
  3. Greater50InstallsApps.csv Output files:
  4. out/practice_hourly_summaries.csv