Add aware_influxdb in beta

pull/128/head
JulioV 2021-03-14 13:33:43 -04:00
parent e38d1fa8ba
commit 42cee67664
7 changed files with 445 additions and 2 deletions

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@ -54,6 +54,10 @@ PHONE_DATA_STREAMS:
aware_csv: aware_csv:
FOLDER: data/external/aware_csv FOLDER: data/external/aware_csv
aware_influxdb:
DATABASE_GROUP: MY_GROUP
# Sensors ------ # Sensors ------
# https://www.rapids.science/latest/features/phone-accelerometer/ # https://www.rapids.science/latest/features/phone-accelerometer/

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@ -4,7 +4,7 @@
- Add a new [Overview](../setup/overview/) page. - Add a new [Overview](../setup/overview/) page.
- You can [extend](../datastreams/add-new-data-streams/) RAPIDS with your own [data streams](../datastreams/data-streams-introduction/). Data streams are data collected with other sensing apps besides AWARE (like Beiwe, mindLAMP), and stored in other data containers (databases, files) besides MySQL. - You can [extend](../datastreams/add-new-data-streams/) RAPIDS with your own [data streams](../datastreams/data-streams-introduction/). Data streams are data collected with other sensing apps besides AWARE (like Beiwe, mindLAMP), and stored in other data containers (databases, files) besides MySQL.
- Support to analyze Empatica wearable data (thanks to Joe Kim and Brinnae Bent from the [DBDP](https://dbdp.org/)) - Support to analyze Empatica wearable data (thanks to Joe Kim and Brinnae Bent from the [DBDP](https://dbdp.org/))
- Support to analyze AWARE data stored in [CSV files](../datastreams/aware-csv/) and InfluxDB databases (the latter thanks to Neil Singh) - Support to analyze AWARE data stored in [CSV files](../datastreams/aware-csv/) and [InfluxDB](../datastreams/aware-influxdb/) databases (the latter thanks to Neil Singh)
- Support to analyze data collected over [multiple time zones](../setup/configuration/#multiple-timezones) - Support to analyze data collected over [multiple time zones](../setup/configuration/#multiple-timezones)
- Support for [sleep intraday features](../features/fitbit-sleep-intraday/) from the core team and also from the community (thanks to Stephen Price) - Support for [sleep intraday features](../features/fitbit-sleep-intraday/) from the core team and also from the community (thanks to Stephen Price)
- Add RAPIDS new logo - Add RAPIDS new logo

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@ -0,0 +1,18 @@
# `aware_influxdb (beta)`
!!! warning
This data stream is being released in beta while we test it thoroughly.
This [data stream](../../datastreams/data-streams-introduction) handles iOS and Android sensor data collected with the [AWARE Framework](https://awareframework.com/) and stored in an InfluxDB database.
## Container
An InfluxDB database with a table per sensor, each containing the data for all participants.
The script to connect and download data from this container is at:
```bash
src/data/streams/aware_influxdb/container.R
```
## Format
--8<---- "docs/snippets/aware_format.md"

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@ -6,7 +6,7 @@ For example, the `aware_mysql` data stream handles smartphone data (**device**)
If you want to process a data stream using RAPIDS, make sure that your data is stored in a supported **format** and **container** (see table below). If you want to process a data stream using RAPIDS, make sure that your data is stored in a supported **format** and **container** (see table below).
If RAPIDS doesn't support your data stream yet (e.g. Beiwe data stored in PostgreSQL, or AWARE data stored in InfluxDB), you can always [implement a new data stream](../add-new-data-streams). If it's something you think other people might be interested on, we will be happy to include your new data stream in RAPIDS, so get in touch!. If RAPIDS doesn't support your data stream yet (e.g. Beiwe data stored in PostgreSQL, or AWARE data stored in SQLite), you can always [implement a new data stream](../add-new-data-streams). If it's something you think other people might be interested on, we will be happy to include your new data stream in RAPIDS, so get in touch!.
!!! hint !!! hint
Currently, you can add new data streams for smartphones, Fitbit, and Empatica devices. If you need RAPIDS to process data from **other devices**, like Oura Rings or Actigraph wearables, get in touch. It is a more complicated process that could take a couple of days to implement for someone familiar with R or Python, but we would be happy to work on it together. Currently, you can add new data streams for smartphones, Fitbit, and Empatica devices. If you need RAPIDS to process data from **other devices**, like Oura Rings or Actigraph wearables, get in touch. It is a more complicated process that could take a couple of days to implement for someone familiar with R or Python, but we would be happy to work on it together.
@ -17,6 +17,7 @@ For reference, these are the data streams we currently support:
|--|--|--|--|--| |--|--|--|--|--|
| `aware_mysql`| Phone | AWARE app | MySQL | [link](../aware-mysql) | `aware_mysql`| Phone | AWARE app | MySQL | [link](../aware-mysql)
| `aware_csv`| Phone | AWARE app | CSV files | [link](../aware-csv) | `aware_csv`| Phone | AWARE app | CSV files | [link](../aware-csv)
| `aware_influxdb` (beta)| Phone | AWARE app | InfluxDB | [link](../aware-influxdb)
| `fitbitjson_mysql`| Fitbit | JSON (per [Fitbit's API](https://dev.fitbit.com/build/reference/web-api/)) | MySQL | [link](../fitbitjson-mysql) | `fitbitjson_mysql`| Fitbit | JSON (per [Fitbit's API](https://dev.fitbit.com/build/reference/web-api/)) | MySQL | [link](../fitbitjson-mysql)
| `fitbitjson_csv`| Fitbit | JSON (per [Fitbit's API](https://dev.fitbit.com/build/reference/web-api/)) | CSV files | [link](../fitbitjson-csv) | `fitbitjson_csv`| Fitbit | JSON (per [Fitbit's API](https://dev.fitbit.com/build/reference/web-api/)) | CSV files | [link](../fitbitjson-csv)
| `fitbitparsed_mysql`| Fitbit | Parsed (parsed API data) | MySQL | [link](../fitbitparsed-mysql) | `fitbitparsed_mysql`| Fitbit | Parsed (parsed API data) | MySQL | [link](../fitbitparsed-mysql)

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@ -84,6 +84,7 @@ nav:
- Phone: - Phone:
- aware_mysql: datastreams/aware-mysql.md - aware_mysql: datastreams/aware-mysql.md
- aware_csv: datastreams/aware-csv.md - aware_csv: datastreams/aware-csv.md
- aware_influxdb (beta): datastreams/aware-influxdb.md
- Mandatory Phone Format: datastreams/mandatory-phone-format.md - Mandatory Phone Format: datastreams/mandatory-phone-format.md
- Fitbit: - Fitbit:
- fitbitjson_mysql: datastreams/fitbitjson-mysql.md - fitbitjson_mysql: datastreams/fitbitjson-mysql.md

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@ -0,0 +1,104 @@
# if you need a new package, you should add it with renv::install(package) so your renv venv is updated
library(influxdbr)
library(tidyverse)
library(yaml)
#' @description
#' Auxiliary function to parse the connection credentials from a specifc group in ./credentials.yaml
#' You can reause most of this function if you are connection to a DB or Web API.
#' It's OK to delete this function if you don't need credentials, e.g., you are pulling data from a CSV for example.
#' @param group the yaml key containing the credentials to connect to a database
#' @preturn dbEngine a database engine (connection) ready to perform queries
get_db_engine <- function(group){
# The working dir is aways RAPIDS root folder, so your credentials file is always /credentials.yaml
credentials <- read_yaml("./credentials.yaml")
if(!group %in% names(credentials))
stop(paste("The credentials group",group, "does not exist in ./credentials.yaml. The only groups that exist in that file are:", paste(names(credentials), collapse = ",")))
#replace with credentials values
conn_object <- influx_connection(host=credentials[[group]][["host"]],
user=credentials[[group]][["user"]],
pass=credentials[[group]][["password"]],
port= credentials[[group]][["port"]])
return(conn_object)
}
# This file gets executed for each PHONE_SENSOR of each participant
# If you are connecting to a database the env file containing its credentials is available at "./.env"
# If you are reading a CSV file instead of a DB table, the @param sensor_container wil contain the file path as set in config.yaml
# You are not bound to databases or files, you can query a web API or whatever data source you need.
#' @description
#' RAPIDS allows users to use the keyword "infer" (previously "multiple") to automatically infer the mobile Operative System a device was running.
#' If you have a way to infer the OS of a device ID, implement this function. For example, for AWARE data we use the "aware_device" table.
#'
#' If you don't have a way to infer the OS, call stop("Error Message") so other users know they can't use "infer" or the inference failed,
#' and they have to assign the OS manually in the participant file
#'
#' @param stream_parameters The PHONE_STREAM_PARAMETERS key in config.yaml. If you need specific parameters add them there.
#' @param device A device ID string
#' @return The OS the device ran, "android" or "ios"
infer_device_os <- function(stream_parameters, device){
dbEngine <- get_db_engine(stream_parameters$SOURCE$DATABASE_GROUP)
#need to re-fetch the YAML for the DB name
credentials <- read_yaml("./credentials.yaml")
message(paste0("Utilizing the Influx query for: ", device))
#execute query string
query_object <- influx_select(dbEngine,
db = credentials[[stream_parameters$SOURCE$DATABASE_GROUP]][["database"]],
field_keys="device_id,brand",
measurement="aware_device",
where= paste0("device_id = '",device,"'"),
return_xts = FALSE)
#fetches the table from the query_object, filtering rows with ALL n/a
#a behavior of influxdbr is that one all NA row will be returned with no matches
os <- query_object[[1]] %>% filter_all(any_vars(!is.na(.))) %>% select(c('device_id','brand','time'))
if(nrow(os) > 0)
return(os %>% mutate(os = ifelse(brand == "iPhone", "ios", "android")) %>% pull(os))
else
stop(paste("We cannot infer the OS of the following device id because it does not exist in the aware_device table:", device))
return(os)
}
#' @description
#' Gets the sensor data for a specific device id from a database table, file or whatever source you want to query
#'
#' @param stream_parameters The PHONE_STREAM_PARAMETERS key in config.yaml. If you need specific parameters add them there.
#' @param device A device ID string
#' @param sensor_container database table or file containing the sensor data for all participants. This is the PHONE_SENSOR[CONTAINER] key in config.yaml
#' @param columns the columns needed from this sensor (we recommend to only return these columns instead of every column in sensor_container)
#' @return A dataframe with the sensor data for device
pull_data <- function(stream_parameters, device, sensor, sensor_container, columns){
dbEngine <- get_db_engine(stream_parameters$SOURCE$DATABASE_GROUP)
#need to re-fetch the YAML for the DB name
credentials <- read_yaml("./credentials.yaml")
# Letting the user know what we are doing
message(paste0("Executing an Influx query for: ", device, " ", sensor, ". Extracting ", columns, " from ", sensor_container))
#execute query string
query_object <- influx_select(dbEngine,
db = credentials[[stream_parameters$SOURCE$DATABASE_GROUP]][["database"]],
field_keys=paste(columns, collapse = ","),
measurement=sensor_container,
where= paste0(columns$DEVICE_ID, " = '",device,"'"),
return_xts=FALSE)
#fetches the table from the query_object, filtering rows with ALL n/a
#a behavior of influxdbr is that one all NA row will be returned with no matches
sensor_data <- query_object[[1]] %>% filter_all(any_vars(!is.na(.))) %>% select(c('time',columns))
if(nrow(sensor_data) == 0)
warning(paste("The device '", device,"' did not have data in ", sensor_container))
return(sensor_data)
}

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@ -0,0 +1,315 @@
PHONE_ACCELEROMETER:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_VALUES_0: double_values_0
DOUBLE_VALUES_1: double_values_1
DOUBLE_VALUES_2: double_values_2
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_VALUES_0: double_values_0
DOUBLE_VALUES_1: double_values_1
DOUBLE_VALUES_2: double_values_2
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_ACTIVITY_RECOGNITION:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
ACTIVITY_NAME: activity_name
ACTIVITY_TYPE: activity_type
CONFIDENCE: confidence
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
ACTIVITY_NAME: FLAG_TO_MUTATE
ACTIVITY_TYPE: FLAG_TO_MUTATE
CONFIDENCE: FLAG_TO_MUTATE
MUTATION:
COLUMN_MAPPINGS:
ACTIVITIES: activities
CONFIDENCE: confidence
SCRIPTS: # List any python or r scripts that mutate your raw data
- "src/data/streams/mutations/phone/aware/activity_recogniton_ios_unification.R"
PHONE_APPLICATIONS_CRASHES:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
PACKAGE_NAME: package_name
APPLICATION_NAME: application_name
APPLICATION_VERSION: application_version
ERROR_SHORT: error_short
ERROR_LONG: error_long
ERROR_CONDITION: error_condition
IS_SYSTEM_APP: is_system_app
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_APPLICATIONS_FOREGROUND:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
PACKAGE_NAME: package_name
APPLICATION_NAME: application_name
IS_SYSTEM_APP: is_system_app
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_APPLICATIONS_NOTIFICATIONS:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
PACKAGE_NAME: package_name
APPLICATION_NAME: application_name
TEXT: text
SOUND: sound
VIBRATE: vibrate
DEFAULTS: defaults
FLAGS: flags
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_BATTERY:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
BATTERY_STATUS: battery_status
BATTERY_LEVEL: battery_level
BATTERY_SCALE: battery_scale
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
BATTERY_STATUS: FLAG_TO_MUTATE
BATTERY_LEVEL: battery_level
BATTERY_SCALE: battery_scale
MUTATION:
COLUMN_MAPPINGS:
BATTERY_STATUS: battery_status
SCRIPTS:
- "src/data/streams/mutations/phone/aware/battery_ios_unification.R"
PHONE_BLUETOOTH:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
BT_ADDRESS: bt_address
BT_NAME: bt_name
BT_RSSI: bt_rssi
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_CALLS:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
CALL_TYPE: call_type
CALL_DURATION: call_duration
TRACE: trace
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
CALL_TYPE: FLAG_TO_MUTATE
CALL_DURATION: call_duration
TRACE: trace
MUTATION:
COLUMN_MAPPINGS:
CALL_TYPE: call_type
SCRIPTS:
- "src/data/streams/mutations/phone/aware/calls_ios_unification.R"
PHONE_CONVERSATION:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_ENERGY: double_energy
INFERENCE: inference
DOUBLE_CONVO_START: double_convo_start
DOUBLE_CONVO_END: double_convo_end
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_ENERGY: double_energy
INFERENCE: inference
DOUBLE_CONVO_START: double_convo_start
DOUBLE_CONVO_END: double_convo_end
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
- "src/data/streams/mutations/phone/aware/conversation_ios_timestamp.R"
PHONE_KEYBOARD:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
PACKAGE_NAME: package_name
BEFORE_TEXT: before_text
CURRENT_TEXT: current_text
IS_PASSWORD: is_password
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_LIGHT:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_LIGHT_LUX: double_light_lux
ACCURACY: accuracy
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_LOCATIONS:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_LATITUDE: double_latitude
DOUBLE_LONGITUDE: double_longitude
DOUBLE_BEARING: double_bearing
DOUBLE_SPEED: double_speed
DOUBLE_ALTITUDE: double_altitude
PROVIDER: provider
ACCURACY: accuracy
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
DOUBLE_LATITUDE: double_latitude
DOUBLE_LONGITUDE: double_longitude
DOUBLE_BEARING: double_bearing
DOUBLE_SPEED: double_speed
DOUBLE_ALTITUDE: double_altitude
PROVIDER: provider
ACCURACY: accuracy
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_LOG:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
LOG_MESSAGE: log_message
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
LOG_MESSAGE: log_message
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_MESSAGES:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
MESSAGE_TYPE: message_type
TRACE: trace
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_SCREEN:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
SCREEN_STATUS: screen_status
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
SCREEN_STATUS: FLAG_TO_MUTATE
MUTATION:
COLUMN_MAPPINGS:
SCREEN_STATUS: screen_status
SCRIPTS: # List any python or r scripts that mutate your raw data
- "src/data/streams/mutations/phone/aware/screen_ios_unification.R"
PHONE_WIFI_CONNECTED:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
MAC_ADDRESS: mac_address
SSID: ssid
BSSID: bssid
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
IOS:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
MAC_ADDRESS: mac_address
SSID: ssid
BSSID: bssid
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data
PHONE_WIFI_VISIBLE:
ANDROID:
RAPIDS_COLUMN_MAPPINGS:
TIMESTAMP: timestamp
DEVICE_ID: device_id
SSID: ssid
BSSID: bssid
SECURITY: security
FREQUENCY: frequency
RSSI: rssi
MUTATION:
COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data