Test Cases¶

Along with the continued development and the addition of new sensors and features to the RAPIDS pipeline, tests for the currently available sensors and features are being implemented. Since this is a Work In Progress this page will be updated with the list of sensors and features for which testing is available. For each of the sensors listed a description of the data used for testing (test cases) are outline. Currently for all intent and testing purposes the tests/data/raw/test01/ contains all the test data files for testing android data formats and tests/data/raw/test02/ contains all the test data files for testing iOS data formats. It follows that the expected (verified output) are contained in the tests/data/processed/test01/ and tests/data/processed/test02/ for Android and iOS respectively. tests/data/raw/test03/ and tests/data/raw/test04/ contain data files for testing empty raw data files for android and iOS respectively.

The following is a list of the sensors that testing is currently available.

Messages (SMS)¶

The raw message data file contains data for 2 separate days.
The data for the first day contains records 5 records for every epoch.
The second day's data contains 6 records for each of only 2 epoch (currently morning and evening)
The raw message data contains records for both message_types (i.e. recieved and sent) in both days in all epochs. The number records with each message_types per epoch is randomly distributed There is at least one records with each message_types per epoch.
There is one raw message data file each, as described above, for testing both iOS and Android data.
There is also an additional empty data file for both android and iOS for testing empty data files

Calls¶

Due to the difference in the format of the raw call data for iOS and Android the following is the expected results the calls_with_datetime_unified.csv. This would give a better idea of the use cases being tested since the calls_with_datetime_unified.csv would make both the iOS and Android data comparable.

The call data would contain data for 2 days.
The data for the first day contains 6 records for every epoch.
The second day's data contains 6 records for each of only 2 epoch (currently morning and evening)
The call data contains records for all call_types (i.e. incoming, outgoing and missed) in both days in all epochs. The number records with each of the call_types per epoch is randomly distributed. There is at least one records with each call_types per epoch.
There is one call data file each, as described above, for testing both iOS and Android data.
There is also an additional empty data file for both android and iOS for testing empty data files

Screen¶

Due to the difference in the format of the raw screen data for iOS and Android the following is the expected results the screen_deltas.csv. This would give a better idea of the use cases being tested since the screen_eltas.csv would make both the iOS and Android data comparable These files are used to calculate the features for the screen sensor

The screen delta data file contains data for 1 day.
The screen delta data contains 1 record to represent an unlock episode that falls within an epoch for every epoch.
The screen delta data contains 1 record to represent an unlock episode that falls across the boundary of 2 epochs. Namely the unlock episode starts in one epoch and ends in the next, thus there is a record for unlock episodes that fall across night to morning, morning to afternoon and finally afternoon to night
The testing is done for unlock episode_type.
There is one screen data file each for testing both iOS and Android data formats.
There is also an additional empty data file for both android and iOS for testing empty data files

Battery¶

Due to the difference in the format of the raw battery data for iOS and Android as well as versions of iOS the following is the expected results the battery_deltas.csv. This would give a better idea of the use cases being tested since the battery_deltas.csv would make both the iOS and Android data comparable. These files are used to calculate the features for the battery sensor.

The battery delta data file contains data for 1 day.
The battery delta data contains 1 record each for a charging and discharging episode that falls within an epoch for every epoch. Thus, for the daily epoch there would be multiple charging and discharging episodes
Since either a charging episode or a discharging episode and not both can occur across epochs, in order to test episodes that occur across epochs alternating episodes of charging and discharging episodes that fall across night to morning, morning to afternoon and finally afternoon to night are present in the battery delta data. This starts with a discharging episode that begins in night and end in morning.
There is one battery data file each, for testing both iOS and Android data formats.
There is also an additional empty data file for both android and iOS for testing empty data files

Bluetooth¶

The raw Bluetooth data file contains data for 1 day.
The raw Bluetooth data contains at least 2 records for each epoch. Each epoch has a record with a timestamp for the beginning boundary for that epoch and a record with a timestamp for the ending boundary for that epoch. (e.g. For the morning epoch there is a record with a timestamp for 6:00AM and another record with a timestamp for 11:59:59AM. These are to test edge cases)
An option of 5 Bluetooth devices are randomly distributed throughout the data records.
There is one raw Bluetooth data file each, for testing both iOS and Android data formats.
There is also an additional empty data file for both android and iOS for testing empty data files.

WIFI¶

There are 2 data files (wifi_raw.csv and sensor_wifi_raw.csv) for each fake participant for each phone platform.
The raw WIFI data files contain data for 1 day.
The sensor_wifi_raw.csv data contains at least 2 records for each epoch. Each epoch has a record with a timestamp for the beginning boundary for that epoch and a record with a timestamp for the ending boundary for that epoch. (e.g. For the morning epoch there is a record with a timestamp for 6:00AM and another record with a timestamp for 11:59:59AM. These are to test edge cases)
The wifi_raw.csv data contains 3 records with random timestamps for each epoch to represent visible broadcasting WIFI network. This file is empty for the iOS phone testing data.
An option of 10 access point devices is randomly distributed throughout the data records. 5 each for sensor_wifi_raw.csv and wifi_raw.csv.
There data files for testing both iOS and Android data formats.
There are also additional empty data files for both android and iOS for testing empty data files.

Light¶

The raw light data file contains data for 1 day.
The raw light data contains 3 or 4 rows of data for each epoch except night. The single row of data for night is for testing features for single values inputs. (Example testing the standard deviation of one input value)
Since light is only available for Android there is only one file that contains data for Android. All other files (i.e. for iPhone) are empty data files.

Application Foreground¶

The raw application foreground data file contains data for 1 day.
The raw application foreground data contains 7 - 9 rows of data for each epoch. The records for each epoch contains apps that are randomly selected from a list of apps that are from the MULTIPLE_CATEGORIES and SINGLE_CATEGORIES (See testing_config.yaml). There are also records in each epoch that have apps randomly selected from a list of apps that are from the EXCLUDED_CATEGORIES and EXCLUDED_APPS. This is to test that these apps are actually being excluded from the calculations of features. There are also records to test SINGLE_APPS calculations.
Since application foreground is only available for Android there is only one file that contains data for Android. All other files (i.e. for iPhone) are empty data files.

Activity Recognition¶

The raw Activity Recognition data file contains data for 1 day.
The raw Activity Recognition data each epoch period contains rows that records 2 - 5 different activity_types. The is such that durations of activities can be tested. Additionally, there are records that mimic the duration of an activity over the time boundary of neighboring epochs. (For example, there a set of records that mimic the participant in_vehicle from afternoon into evening)
There is one file each with raw Activity Recognition data for testing both iOS and Android data formats. (plugin_google_activity_recognition_raw.csv for android and plugin_ios_activity_recognition_raw.csv for iOS)
There is also an additional empty data file for both android and iOS for testing empty data files.

Conversation¶

The raw conversation data file contains data for 2 day.
The raw conversation data contains records with a sample of both datatypes (i.e. voice/noise = 0, and conversation = 2 ) as well as rows with for samples of each of the inference values (i.e. silence = 0, noise = 1, voice = 2, and unknown = 3) for each epoch. The different datatype and inference records are randomly distributed throughout the epoch.
Additionally there are 2 - 5 records for conversations (datatype = 2, and inference = -1) in each epoch and for each epoch except night, there is a conversation record that has a double_convo_start timestamp that is from the previous epoch. This is to test the calculations of features across epochs.
There is a raw conversation data file for both android and iOS platforms (plugin_studentlife_audio_android_raw.csv and plugin_studentlife_audio_raw.csv respectively).
Finally, there are also additional empty data files for both android and iOS for testing empty data files