rapids/docs/workflow-examples/minimal.md

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.

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

2. 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)

   !!! info "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:
        ```yaml
        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\. `[DAY_SEGMENTS][TYPE]` should be the default `PERIODIC`. Change `[DAY_SEGMENTS][FILE]` with the path of a file containing the following lines:
         ```csv
         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 "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
   
    DAY_SEGMENTS: &day_segments
        TYPE: PERIODIC
        FILE: "data/external/daysegments_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: ...
    ```
   

3. Run RAPIDS

   ./rapids -j1
   

4. The call features for daily and morning day segments will be in

   /data/processed/features/p01/phone_calls.csv