Minimal Working Example¶

This is a quick guide for creating and running a simple pipeline to extract missing, outgoing, and incoming call features for daily and night epochs of one participant monitored on the US East coast.

Install RAPIDS and make sure your conda environment is active (see Installation)

Make the changes listed below for the corresponding Configuration step (we provide an example of what the relevant sections in your config.yml will look like after you are done)

Things to change on each configuration step

1. Setup your database connection credentials in .env. We assume your credentials group is called MY_GROUP.

2. America/New_York should be the default timezone

3. Create a participant file p01.yaml based on one of your participants and add p01 to [PIDS] in config.yaml. The following would be the content of your p01.yaml participant file:

PHONE:
    DEVICE_IDS: [aaaaaaaa-1111-bbbb-2222-cccccccccccc] # your participant's AWARE device id
    PLATFORMS: [android] # or ios
    LABEL: MyTestP01 # any string
    START_DATE: 2020-01-01 # this can also be empty
    END_DATE: 2021-01-01 # this can also be empty

4. [TIME_SEGMENTS][TYPE] should be the default PERIODIC. Change [TIME_SEGMENTS][FILE] with the path of a file containing the following lines:

label,start_time,length,repeats_on,repeats_value
daily,00:00:00,23H 59M 59S,every_day,0
night,00:00:00,5H 59M 59S,every_day,0

5. If you collected data with AWARE you won’t need to modify the attributes of [DEVICE_DATA][PHONE]

6. Set [PHONE_CALLS][PROVIDERS][RAPIDS][COMPUTE] to True

Example of the config.yaml sections after the changes outlined above

PIDS: [p01]

TIMEZONE: &timezone
America/New_York

DATABASE_GROUP: &database_group
MY_GROUP

# ... other irrelevant sections

TIME_SEGMENTS: &time_segments
    TYPE: PERIODIC
    FILE: "data/external/timesegments_periodic.csv" # make sure the three lines specified above are in the file
    INCLUDE_PAST_PERIODIC_SEGMENTS: FALSE

# No need to change this if you collected AWARE data on a database and your credentials are grouped under `MY_GROUP` in `.env`
DEVICE_DATA:
    PHONE:
        SOURCE: 
            TYPE: DATABASE
            DATABASE_GROUP: *database_group
            DEVICE_ID_COLUMN: device_id # column name
        TIMEZONE: 
            TYPE: SINGLE # SINGLE or MULTIPLE
            VALUE: *timezone 


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

# ... other irrelevant sections

# Communication call features config, TYPES and FEATURES keys need to match
PHONE_CALLS:
    TABLE: calls # change if your calls table has a different name
    PROVIDERS:
        RAPIDS:
            COMPUTE: True # set this to True!
            CALL_TYPES: ...

Run RAPIDS
```
./rapids -j1
```
The call features for daily and morning time segments will be in
```
/data/processed/features/p01/phone_calls.csv
```