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@ -2052,14 +2052,14 @@
<td>RAPIDS</td>
<td>Y</td>
<td>Y</td>
<td>N</td>
<td>Y</td>
</tr>
<tr>
<td>Phone Conversation</td>
<td>RAPIDS</td>
<td>Y</td>
<td>Y</td>
<td>N</td>
<td>Y</td>
</tr>
<tr>
<td>Phone Data Yield</td>
@ -2100,22 +2100,22 @@
<td>Phone Screen</td>
<td>RAPIDS</td>
<td>Y</td>
<td>N</td>
<td>N</td>
<td>Y</td>
<td>Y</td>
</tr>
<tr>
<td>Phone WiFi Connected</td>
<td>RAPIDS</td>
<td>Y</td>
<td>Y</td>
<td>N</td>
<td>Y</td>
</tr>
<tr>
<td>Phone WiFi Visible</td>
<td>RAPIDS</td>
<td>Y</td>
<td>Y</td>
<td>N</td>
<td>Y</td>
</tr>
<tr>
<td>Fitbit Calories Intraday</td>
@ -2200,40 +2200,190 @@
iOS for testing empty data files</li>
</ul>
<h2 id="calls">Calls<a class="headerlink" href="#calls" title="Permanent link">&para;</a></h2>
<p>Due to the difference in the format of the raw call data for iOS and Android the following is the expected results the <code>calls_with_datetime_unified.csv</code>. This would give a better idea of the use cases being tested since the <code>calls_with_datetime_unified.csv</code> would make both the iOS and Android data comparable.</p>
<p>Due to the difference in the format of the raw data for iOS and Android the following is the expected results
the <code>phone_calls.csv</code>. </p>
<p>Description:</p>
<ul>
<li>The call data would contain data for 2 days.</li>
<li>The data for the first day contains 6 records for every <code>epoch</code>.</li>
<li>The second day's data contains 6 records for each of only 2
<code>epoch</code> (currently <code>morning</code> and <code>evening</code>)</li>
<li>The call data contains records for all <code>call_types</code> (i.e.
<code>incoming</code>, <code>outgoing</code> and <code>missed</code>) in both days in all epochs.
The number records with each of the <code>call_types</code> per epoch is
randomly distributed. There is at least one records with each
<code>call_types</code> per epoch.</li>
<li>There is one call data file each, as described above, for testing
both iOS and Android data.</li>
<li>There is also an additional empty data file for both android and
iOS for testing empty data files</li>
<li>One missed episode, one outgoing episode and one incoming episode on Friday night, morning, afternoon and evening</li>
<li>There is at least one episode of each type of phone calls on each day</li>
<li>One incoming episode crossing two 30-mins segments</li>
<li>One outgoing episode crossing two 30-mins segments </li>
<li>One missed episode before, during and after the <code>event</code></li>
<li>There is one incoming episode before, during or after the <code>event</code></li>
<li>There is one outcoming episode before, during or after the <code>event</code></li>
<li>There is one missed episode before, during or after the <code>event</code></li>
</ul>
<p>Data format:</p>
<table>
<thead>
<tr>
<th>Device</th>
<th>Missed</th>
<th>Outgoing</th>
<th>Incoming</th>
</tr>
</thead>
<tbody>
<tr>
<td>iOS</td>
<td>3</td>
<td>2</td>
<td>1</td>
</tr>
<tr>
<td>Android</td>
<td>1,4 or 3,4</td>
<td>3,2,4</td>
<td>1,2,4</td>
</tr>
</tbody>
</table>
<p>Note:
When generating test data, all traces for iOS device need to be unique otherwise the episode with duplicate trace will be dropped </p>
<p>Checklist:</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
</tbody>
</table>
<h2 id="screen">Screen<a class="headerlink" href="#screen" title="Permanent link">&para;</a></h2>
<p>Due to the difference in the format of the raw screen data for iOS and Android the following is the expected results the <code>screen_deltas.csv</code>. This would give a better idea of the use cases being tested since the <code>screen_eltas.csv</code> would make both the iOS and Android data comparable These files are used to calculate the features for the screen sensor</p>
<p>Due to the difference in the format of the raw screen data for iOS and Android the following is the expected results the <code>phone_screen.csv</code>. </p>
<p>Description:</p>
<ul>
<li>The screen delta data file contains data for 1 day.</li>
<li>The screen delta data contains 1 record to represent an <code>unlock</code>
<li>The screen data file contains data for 4 days.</li>
<li>The screen data contains 1 record to represent an <code>unlock</code>
episode that falls within an <code>epoch</code> for every <code>epoch</code>.</li>
<li>The screen delta data contains 1 record to represent an <code>unlock</code>
<li>The screen data contains 1 record to represent an <code>unlock</code>
episode that falls across the boundary of 2 epochs. Namely the
<code>unlock</code> episode starts in one epoch and ends in the next, thus
there is a record for <code>unlock</code> episodes that fall across <code>night</code>
to <code>morning</code>, <code>morning</code> to <code>afternoon</code> and finally <code>afternoon</code> to
<code>night</code></li>
<li>The testing is done for <code>unlock</code> episode_type.</li>
<li>There is one screen data file each for testing both iOS and
Android data formats.</li>
<li>There is also an additional empty data file for both android and
iOS for testing empty data files</li>
<li>One episode that crossing two <code>30-min</code> segments</li>
</ul>
<p>Data format:</p>
<table>
<thead>
<tr>
<th>Device</th>
<th>unlock</th>
</tr>
</thead>
<tbody>
<tr>
<td>Android</td>
<td>3, 0</td>
</tr>
<tr>
<td>iOS</td>
<td>3, 2</td>
</tr>
</tbody>
</table>
<p>Checklist</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>Android, iOS</td>
</tr>
</tbody>
</table>
<h2 id="battery">Battery<a class="headerlink" href="#battery" title="Permanent link">&para;</a></h2>
<p>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 <code>battery_deltas.csv</code>. This would give a better idea of the use cases being tested since the <code>battery_deltas.csv</code> would make both the iOS and Android data comparable. These files are used to calculate the features for the battery sensor.</p>
<ul>
@ -2272,27 +2422,126 @@
iOS for testing empty data files.</li>
</ul>
<h2 id="wifi">WIFI<a class="headerlink" href="#wifi" title="Permanent link">&para;</a></h2>
<p>There are two wifi features (<code>phone wifi connected</code> and <code>phone wifi visible</code>). The raw test data are seperatly stored in the <code>phone_wifi_connected_raw.csv</code> and <code>phone_wifi_visible_raw.csv</code>.</p>
<p>Description: </p>
<ul>
<li>There are 2 data files (<code>wifi_raw.csv</code> and <code>sensor_wifi_raw.csv</code>)
for each fake participant for each phone platform. </li>
<li>The raw WIFI data files contain data for 1 day.</li>
<li>The <code>sensor_wifi_raw.csv</code> data contains at least 2 records for
each <code>epoch</code>. Each <code>epoch</code> has a record with a <code>timestamp</code> for the
beginning boundary for that <code>epoch</code> and a record with a
<code>timestamp</code> for the ending boundary for that <code>epoch</code>. (e.g. For
the <code>morning</code> epoch there is a record with a <code>timestamp</code> for
<code>6:00AM</code> and another record with a <code>timestamp</code> for <code>11:59:59AM</code>.
These are to test edge cases)</li>
<li>The <code>wifi_raw.csv</code> data contains 3 records with random timestamps
for each <code>epoch</code> to represent visible broadcasting WIFI network.
This file is empty for the iOS phone testing data.</li>
<li>An option of 10 access point devices is randomly distributed
throughout the data records. 5 each for <code>sensor_wifi_raw.csv</code> and
<code>wifi_raw.csv</code>.</li>
<li>There data files for testing both iOS and Android data formats.</li>
<li>There are also additional empty data files for both android and
iOS for testing empty data files.</li>
<li>One episode for each <code>epoch</code> (<code>night</code>, <code>morining</code>, <code>afternoon</code> and <code>evening</code>)</li>
<li>Two two episodes in the same time segment (<code>daily</code> and <code>30-min</code>)</li>
<li>Two episodes around the transition of <code>epochs</code> (e.g. one at the end of <code>night</code> and one at the beginning of <code>morning</code>) </li>
<li>One episode before and after the time switch on Sunday</li>
</ul>
<p>phone wifi connected:</p>
<p>Checklist</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
</tbody>
</table>
<p>phone wifi visible</p>
<p>Checklist</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
</tbody>
</table>
<h2 id="light">Light<a class="headerlink" href="#light" title="Permanent link">&para;</a></h2>
<ul>
<li>The raw light data file contains data for 1 day.</li>
@ -2347,26 +2596,96 @@
iOS for testing empty data files.</li>
</ul>
<h2 id="conversation">Conversation<a class="headerlink" href="#conversation" title="Permanent link">&para;</a></h2>
<ul>
<li>The raw conversation data file contains data for 2 day.</li>
<li>The raw conversation data contains records with a sample of both
<code>datatypes</code> (i.e. <code>voice/noise</code> = <code>0</code>, and <code>conversation</code> = <code>2</code> )
as well as rows with for samples of each of the <code>inference</code> values
(i.e. <code>silence</code> = <code>0</code>, <code>noise</code> = <code>1</code>, <code>voice</code> = <code>2</code>, and <code>unknown</code>
= <code>3</code>) for each <code>epoch</code>. The different <code>datatype</code> and <code>inference</code>
records are randomly distributed throughout the <code>epoch</code>.</li>
<li>Additionally there are 2 - 5 records for conversations (<code>datatype</code>
= 2, and <code>inference</code> = -1) in each <code>epoch</code> and for each <code>epoch</code>
except night, there is a conversation record that has a
<code>double_convo_start</code> <code>timestamp</code> that is from the previous
<code>epoch</code>. This is to test the calculations of features across
<code>epochs</code>.</li>
<li>There is a raw conversation data file for both android and iOS
platforms (<code>plugin_studentlife_audio_android_raw.csv</code> and
<code>plugin_studentlife_audio_raw.csv</code> respectively).</li>
<li>Finally, there are also additional empty data files for both
android and iOS for testing empty data files</li>
</ul>
<p>The 4-day raw conversation data is contained in <code>phone_conversation_raw.csv</code>. The different <code>inference</code> records are
randomly distributed throughout the <code>epoch</code>. </p>
<p>Description:
- One episode for each daily segment (<code>night</code>, <code>morning</code>, <code>afternoon</code> and <code>evening</code>) on each day
- Two episodes near the transition of the daily segment, one starts at the end of the afternoon, <code>Fri 17:10:00</code> and another one starts at the beginning of the evening, <code>Fri 18:01:00</code>
- One episode across two segments, <code>daily</code> and <code>30-mins</code>, (from <code>Fri 05:55:00</code> to <code>Fri 06:00:41</code>)
- Two episodes locate in the same daily segment (<code>Sat 12:45:36</code> and <code>Sat 16:48:22</code>)
- One episode before the time switch, <code>Sun 00:15:06</code>, and one episode after the time switch, <code>Sun 06:01:00</code></p>
<p>Data format:</p>
<table>
<thead>
<tr>
<th>inference</th>
<th>type</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>silence</td>
</tr>
<tr>
<td>1</td>
<td>noise</td>
</tr>
<tr>
<td>2</td>
<td>voice</td>
</tr>
<tr>
<td>3</td>
<td>unknown</td>
</tr>
</tbody>
</table>
<p>Checklist</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>android</td>
</tr>
</tbody>
</table>
<h2 id="keyboard">Keyboard<a class="headerlink" href="#keyboard" title="Permanent link">&para;</a></h2>
<ul>
<li>The raw keyboard data file contains data for 4 days.</li>

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