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<h1 id="testing">Testing<a class="headerlink" href="#testing" title="Permanent link">&para;</a></h1>
<p>The following is a simple guide to run RAPIDS&rsquo; tests. All files necessary for testing are stored in the <code>./tests/</code> directory</p>
<h2 id="steps-for-testing">Steps for Testing<a class="headerlink" href="#steps-for-testing" title="Permanent link">&para;</a></h2>
<details class="check"><summary><strong>Testing Overview</strong></summary><ol>
<li>You have to create a single four day test dataset for the sensor you are working on. </li>
<li>You will adjust your dataset with <code>tests/script/assign_test_timestamps.py</code> to fit <code>Fri March 6th 2020 - Mon March 9th 2020</code> and <code>Fri Oct 30th 2020 - Mon Nov 2nd 2020</code>. We test daylight saving times with these dates.</li>
<li>We have one test participant per platform (<code>pids</code>: <code>android</code>, <code>ios</code>, <code>fitbit</code>, <code>empatica</code>, <code>empty</code>). The data <code>device_id</code> should be equal to the <code>pid</code>.</li>
<li>We will run this test dataset against six test pipelines, three for <code>frequency</code>, <code>periodic</code>, and <code>event</code> time segments in a <code>single</code> time zone, and the same three in <code>multiple</code> time zones.</li>
<li>You will have to create your test data to cover as many corner cases as possible. These cases depend on the sensor you are working on.</li>
<li>The time segments and time zones to be tested are:</li>
</ol>
<details class="example"><summary>Frequency</summary><ul>
<li>30 minutes (<code>30min,30</code>)</li>
</ul>
</details>
<details class="example"><summary>Periodic</summary><ul>
<li>morning (<code>morning,06:00:00,5H 59M 59S,every_day,0</code>)</li>
<li>daily (<code>daily,00:00:00,23H 59M 59S,every_day,0</code>)</li>
<li>three-day segments that repeat every day (<code>threeday,00:00:00,71H 59M 59S,every_day,0</code>)</li>
<li>three-day segments that repeat every Friday (<code>weekend,00:00:00,71H 59M 59S,wday,5</code>)</li>
</ul>
</details>
<details class="example"><summary>Event</summary><ul>
<li>A segment that starts 3 hour before an event (Sat Mar 07 2020 19:00:00 EST) and lasts for 22 hours. Note that the last part of this segment will happen during a daylight saving change on Sunday at 2am when the clock moves forward and the period 2am-3am does not exist. In this case, the segment would start on Sat Mar 07 2020 16:00:00 EST (timestamp: 1583614800000) and end on Sun Mar 08 2020 15:00:00 EST (timestamp: 1583694000000). (<code>beforeMarchEvent,1583625600000,22H,3H,-1,android</code>)</li>
<li>A segment that starts 3 hour before an event (Sat Oct 31 2020 19:00:00 EST) and lasts for 22 hours. Note that the last part of this segment will happen during a daylight saving change on Sunday at 2am when the clock moves back and the period 1am-2am exists twice. In this case, the segment would start on Sat Oct 31 2020 16:00:00 EST (timestamp: 1604174400000) and end on Sun Nov 01 2020 13:00:00 EST (timestamp: 1604253600000). (<code>beforeNovemberEvent,1604185200000,22H,3H,-1,android</code>)</li>
</ul>
</details>
<details class="example"><summary>Single time zone to test</summary><p>America/New_York</p>
</details>
<details class="example"><summary>Multi time zones to test</summary><ul>
<li>America/New_York starting at <code>0</code></li>
<li>America/Los_Angeles starting at <code>1583600400000</code> (Sat Mar 07 2020 12:00:00 EST)</li>
<li>America/New_York starting at <code>1583683200000</code> (Sun Mar 08 2020 12:00:00 EST)</li>
<li>America/Los_Angeles starting at <code>1604160000000</code> (Sat Oct 31 2020 12:00:00 EST)</li>
<li>America/New_York starting at <code>1604250000000</code> (Sun Nov 01 2020 12:00:00 EST)</li>
</ul>
</details>
<details class="hint"><summary>Understanding event segments with multi timezones</summary><p><figure>
<img src="../../img/testing_eventsegments_mtz.png" max-width="100%" />
</figure></p>
</details>
</details>
<details class="check"><summary><strong>Document your tests</strong></summary><ul>
<li>Before you start implementing any test data you need to document your tests. </li>
<li>The documentation of your tests should be added to <code>docs/developers/test-cases.md</code> under the corresponding sensor. </li>
<li>You will need to add two subsections <code>Description</code> and the <code>Checklist</code></li>
<li>The amount of data you need depends on each sensor but you can be efficient by creating data that covers corner cases in more than one time segment. For example, a battery episode from 11am to 1pm, covers the case when an episode has to be split for 30min frequency segments and for morning segments.</li>
<li>As a rule of thumb think about corner cases for 30min segments as they will give you the most flexibility.</li>
<li>Only add tests for iOS if the raw data format is different than Android&rsquo;s (for example for screen)</li>
<li>Create specific tests for Sunday before and after 02:00. These will test daylight saving switches, in March 02:00 to 02:59 do not exist, and in November 01:00 to 01:59 exist twice (read below how <code>tests/script/assign_test_timestamps.py</code> handles this)</li>
</ul>
<details class="example"><summary>Example of Description</summary><p><code>Description</code> is a list and every item describes the different scenarios your test data is covering. For example, if we are testing PHONE_BATTERY:</p>
<div class="highlight"><pre><span></span><code>- We test 24 discharge episodes, 24 charge episodes and 2 episodes with a 0 discharge rate
- One episode is shorter than 30 minutes (`start timestamp` to `end timestamp`)
- One episode is 120 minutes long from 11:00 to 13:00 (`start timestamp` to `end timestamp`). This one covers the case when an episode has to be chunked for 30min frequency segments and for morning segments
- One episode is 60 minutes long from 23:30 to 00:30 (`start timestamp` to `end timestamp`). This one covers the case when an episode has to be chunked for 30min frequency segments and for daly segments (overnight)
- One 0 discharge rate episode 10 minutes long that happens within a 30-minute segment (10:00 to 10:29) (`start timestamp` to `end timestamp`)
- Three discharge episodes that happen between during beforeMarchEvent (start/end timestamps of those discharge episodes)
- Three charge episodes that happen between during beforeMarchEvent (start/end timestamps of those charge episodes)
- One discharge episode that happen between 00:30 and 04:00 to test for daylight saving times in March and Novemeber 2020.
- ... any other test corner cases you can think of
</code></pre></div>
<p>Describe your test cases in as much detail as possible so in the future if we find a bug in RAPIDS, we know what test case we did not include and should add.</p>
</details>
<details class="example"><summary>Example of Checklist</summary><p><code>Checklist</code> is a table where you confirm you have verified the output of your dataset for the different time segments and time zones</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 and iOS</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>android and iOS</td>
</tr>
</tbody>
</table>
</details>
</details>
<details class="check"><summary><strong>Add raw input data.</strong></summary><ol>
<li>Add the raw test data to the corresponding sensor CSV file in <code>tests/data/manual/aware_csv/SENSOR_raw.csv</code>. Create the CSV if it does not exist.</li>
<li>The test data you create will have the same columns as normal raw data except <code>test_time</code> replaces <code>timestamp</code>. To make your life easier, you can place a test data row in time using the <code>test_time</code> column with the following format: <code>Day HH:MM:SS.XXX</code>, for example <code>Fri 22:54:30.597</code>.</li>
<li>
<p>You can convert your manual test data to actual raw test data with the following commands:</p>
<ul>
<li>
<p>For the selected files: (It could be a single file name or multiple file names separated by whitespace(s))
<div class="highlight"><pre><span></span><code>python tests/scripts/assign_test_timestamps.py -f file_name_1 file_name_2
</code></pre></div></p>
</li>
<li>
<p>For all files under the <code>tests/data/manual/aware_csv</code> folder:
<div class="highlight"><pre><span></span><code>python tests/scripts/assign_test_timestamps.py -a
</code></pre></div></p>
</li>
</ul>
</li>
<li>
<p>The script <code>assign_test_timestamps.py</code> converts you <code>test_time</code> column into a <code>timestamp</code>. For example, <code>Fri 22:54:30.597</code> is converted to <code>1583553270597</code> (<code>Fri Mar 06 2020 22:54:30 GMT-0500</code>) and to <code>1604112870597</code> (<code>Fri Oct 30 2020 22:54:30 GMT-0400</code>). Note you can include milliseconds.</p>
</li>
<li>The <code>device_id</code> should be the same as <code>pid</code>.</li>
</ol>
<details class="example"><summary>Example of test data you need to create</summary><p>The <code>test_time</code> column will be automatically converted to a timestamp that fits our testing periods in March and November by <code>tests/script/assign_test_timestamps.py</code></p>
<div class="highlight"><pre><span></span><code>test_time,device_id,battery_level,battery_scale,battery_status
Fri 01:00:00.000,ios,90,100,4
Fri 01:00:30.500,ios,89,100,4
Fri 01:01:00.000,ios,80,100,4
Fri 01:01:45.500,ios,79,100,4
...
Sat 08:00:00.000,ios,78,100,4
Sat 08:01:00.000,ios,50,100,4
Sat 08:02:00.000,ios,49,100,4
</code></pre></div>
</details>
</details>
<details class="check"><summary><strong>Add expected output data.</strong></summary><ol>
<li>Add or update the expected output feature file of the participant and sensor you are testing:
<div class="highlight"><pre><span></span><code>tests/data/processed/features/<span class="o">{</span>type_of_time_segment<span class="o">}</span>/<span class="o">{</span>pid<span class="o">}</span>/device_sensor.csv
<span class="c1"># this example is expected output data for battery tests for periodic segments in a single timezone</span>
tests/data/processed/features/stz_periodic/android/phone_sensor.csv
<span class="c1"># this example is expected output data for battery tests for periodic segments in multi timezones</span>
tests/data/processed/features/mtz_periodic/android/phone_sensor.csv
</code></pre></div></li>
</ol>
</details>
<details class="check"><summary><strong>Edit the config file(s).</strong></summary><ol>
<li>Activate the sensor provider you are testing if it isn&rsquo;t already. Set <code>[SENSOR][PROVIDER][COMPUTE]</code> to <code>TRUE</code> in the <code>config.yaml</code> of the time segments and time zones you are testing:
<div class="highlight"><pre><span></span><code><span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/stz_frequency_config.yaml</span> <span class="c1"># For single-timezone frequency time segments</span>
<span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/stz_periodic_config.yaml</span> <span class="c1"># For single-timezone periodic time segments</span>
<span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/stz_event_config.yaml</span> <span class="c1"># For single-timezone event time segments</span>
<span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/mtz_frequency_config.yaml</span> <span class="c1"># For multi-timezone frequency time segments</span>
<span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/mtz_periodic_config.yaml</span> <span class="c1"># For multi-timezone periodic time segments</span>
<span class="p p-Indicator">-</span> <span class="l l-Scalar l-Scalar-Plain">tests/settings/mtz_event_config.yaml</span> <span class="c1"># For multi-timezone event time segments</span>
</code></pre></div></li>
</ol>
</details>
<details class="check"><summary><strong>Run the pipeline and tests.</strong></summary><ol>
<li>You can run all six segment pipelines and their tests
<div class="highlight"><pre><span></span><code>bash tests/scripts/run_tests.sh -t all
</code></pre></div></li>
<li>You can run only the pipeline of a specific time segment and its tests
<div class="highlight"><pre><span></span><code>bash tests/scripts/run_tests.sh -t stz_frequency -a both <span class="c1"># swap stz_frequency for mtz_frequency, stz_event, mtz_event, etc</span>
</code></pre></div></li>
<li>Or, if you are working on your tests and you want to run a pipeline and its tests independently
<div class="highlight"><pre><span></span><code>bash tests/scripts/run_tests.sh -t stz_frequency -a run
bash tests/scripts/run_tests.sh -t stz_frequency -a <span class="nb">test</span>
</code></pre></div></li>
</ol>
<details class="hint"><summary>How does the test execution work?</summary><p>This bash script <code>tests/scripts/run_tests.sh</code> executes one or all test pipelines for different time segment types (<code>frequency</code>, <code>periodic</code>, and <code>events</code>) and single or multiple timezones.</p>
<p>The python script <code>tests/scripts/run_tests.py</code> runs the tests. It parses the involved participants and active sensor providers in the <code>config.yaml</code> file of the time segment type and time zone being tested. We test that the output file we expect exists and that its content matches the expected values.</p>
</details>
<details class="example"><summary>Output Example</summary><p>The following is a snippet of the output you should see after running your test.</p>
<div class="highlight"><pre><span></span><code>test_sensors_files_exist <span class="o">(</span>test_sensor_features.TestSensorFeatures<span class="o">)</span> ... stz_periodic
ok
test_sensors_features_calculations <span class="o">(</span>test_sensor_features.TestSensorFeatures<span class="o">)</span> ... stz_periodic
ok
test_sensors_files_exist <span class="o">(</span>test_sensor_features.TestSensorFeatures<span class="o">)</span> ... stz_frequency
ok
test_sensors_features_calculations <span class="o">(</span>test_sensor_features.TestSensorFeatures<span class="o">)</span> ... stz_frequency
FAIL
</code></pre></div>
<p>The results above show that the for stz_periodic, both <code>test_sensors_files_exist</code> and <code>test_sensors_features_calculations</code> passed. While for stz_frequency, the first test <code>test_sensors_files_exist</code> passed while <code>test_sensors_features_calculations</code> failed. Additionally, you should get the traceback of the failure (not shown here).</p>
</details>
</details>
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