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26
0.3/change-log/index.html
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</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
<a href="#v032" class="md-nav__link">
v0.3.2
</a>
</li>
<li class="md-nav__item">
<a href="#v031" class="md-nav__link">
v0.3.1
@ -1143,6 +1150,13 @@
</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
<a href="#v032" class="md-nav__link">
v0.3.2
</a>
</li>
<li class="md-nav__item">
<a href="#v031" class="md-nav__link">
v0.3.1
@ -1231,6 +1245,18 @@
<h1 id="change-log">Change Log<a class="headerlink" href="#change-log" title="Permanent link">&para;</a></h1>
<h2 id="v032">v0.3.2<a class="headerlink" href="#v032" title="Permanent link">&para;</a></h2>
<ul>
<li>Update docker and linux instructions to use RSPM binary repo for for faster installation</li>
<li>Update CI to create a release on a tagged push that passes the tests</li>
<li>Clarify in DB credential configuration that we only support MySQL</li>
<li>Add Windows installation instructions</li>
<li>Fix bugs in the create_participants_file script</li>
<li>Fix bugs in Fitbit data parsing.</li>
<li>Fixed Doryab location features context of clustering.</li>
<li>Fixed the wrong shifting while calculating distance in Doryab location features.</li>
<li>Refactored the haversine function</li>
</ul>
<h2 id="v031">v0.3.1<a class="headerlink" href="#v031" title="Permanent link">&para;</a></h2>
<ul>
<li>Update installation docs for RAPIDS&rsquo; docker container</li>

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0.3/features/phone-locations/index.html
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@ -1312,7 +1312,7 @@ For a detailed description of how this is calculated, see <a href="../../citatio
- data/processed/features/<span class="o">{</span>pid<span class="o">}</span>/phone_locations.csv
</code></pre></div>
</div>
<p>Parameters description for <code>[PHONE_LOCATIONS][PROVIDERS][BARNETT]</code>:</p>
<p>Parameters description for <code>[PHONE_LOCATIONS][PROVIDERS][DORYAB]</code>:</p>
<table>
<thead>
<tr>
@ -1353,9 +1353,13 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<td><code>[SAMPLING_FREQUENCY]</code></td>
<td>Expected time difference between any two location rows in minutes. If set to <code>0</code>, the sampling frequency will be inferred automatically as the median of all the differences between any two consecutive row timestamps (recommended if you are using <code>FUSED_RESAMPLED</code> data). This parameter impacts all the time calculations.</td>
</tr>
<tr>
<td><code>[CLUSTER_ON]</code></td>
<td>Set this flag to <code>PARTICIPANT_DATASET</code> to create clusters based on the entire participant&rsquo;s dataset or to <code>TIME_SEGMENT</code> to create clusters based on all the instances of the corresponding time segment (e.g. all mornings).</td>
</tr>
</tbody>
</table>
<p>Features description for <code>[PHONE_LOCATIONS][PROVIDERS][BARNETT]</code>:</p>
<p>Features description for <code>[PHONE_LOCATIONS][PROVIDERS][DORYAB]</code>:</p>
<table>
<thead>
<tr>
@ -1428,12 +1432,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<tr>
<td>movingtostaticratio</td>
<td>-</td>
<td>Ratio between the number of rows labeled Moving versus Static</td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
</tr>
<tr>
<td>outlierstimepercent</td>
<td>-</td>
<td>Ratio between the number of rows that belong to non-significant clusters divided by the total number of rows in a time segment.</td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
</tr>
<tr>
<td>maxlengthstayatclusters</td>

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0.3/setup/configuration/index.html
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@ -1316,12 +1316,15 @@
</code></pre></div></p>
</div>
<div class="admonition hint">
<p class="admonition-title">Hint<p>If you are using RAPIDS&rsquo; docker container and Docker-for-mac or Docker-for-Windows 18.03+, connect to your MySQL database using the host <code>host.docker.internal</code> instead of <code>127.0.0.1</code></p>
<p class="admonition-title">Hint<p>If you are using RAPIDS&rsquo; docker container and Docker-for-mac or Docker-for-Windows 18.03+, you can connect to a MySQL database in your host machine using the <code>host.docker.internal</code> instead of <code>127.0.0.1</code> or <code>localhost</code></p>
</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>You can ignore this step if you are only processing Fitbit data in CSV files.</p>
<ul>
<li>You can ignore this step if you are only processing Fitbit data in CSV files.</li>
<li>RAPIDS only supports MySQL/MariaDB databases. If you would like to add support for a different database engine get in touch and we can discuss how to implement it.</li>
</ul>
</div>
<hr />
<h2 id="timezone-of-your-study">Timezone of your study<a class="headerlink" href="#timezone-of-your-study" title="Permanent link">&para;</a></h2>

64
0.3/setup/installation/index.html
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@ -1061,15 +1061,15 @@
<h1 id="installation">Installation<a class="headerlink" href="#installation" title="Permanent link">&para;</a></h1>
<p>You can install RAPIDS using Docker (the fastest), or native instructions for MacOS and Ubuntu</p>
<div class="tabbed-set" data-tabs="1:3"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><label for="__tabbed_1_1">Docker</label><div class="tabbed-content">
<p>You can install RAPIDS using Docker (the fastest), or native instructions for MacOS and Linux (Ubuntu). Windows is supported through Docker or WSL.</p>
<div class="tabbed-set" data-tabs="1:4"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><label for="__tabbed_1_1">Docker</label><div class="tabbed-content">
<ol>
<li>
<p>Install <a href="https://docs.docker.com/desktop/">Docker</a></p>
</li>
<li>
<p>Pull our RAPIDS container
<div class="highlight"><pre><span></span><code>docker pull moshiresearch/rapids:latest<span class="sb">`</span>
<div class="highlight"><pre><span></span><code>docker pull moshiresearch/rapids:latest
</code></pre></div></p>
</li>
<li>
@ -1108,6 +1108,10 @@
</details>
</li>
</ol>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>If you installed RAPIDS using Docker for Windows on Windows 10, the container will have <a href="https://stackoverflow.com/questions/43460770/docker-windows-container-memory-limit">limits</a> on the amount of RAM it can use. If you find that RAPIDS crashes due to running out of memory, <a href="https://stackoverflow.com/a/56583203/6030343">increase</a> this limit.</p>
</div>
</div>
<input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><label for="__tabbed_1_2">MacOS</label><div class="tabbed-content">
<p>We tested these instructions in Catalina</p>
@ -1169,13 +1173,14 @@ snakemake -j1 renv_restore
</ol>
</div>
<input id="__tabbed_1_3" name="__tabbed_1" type="radio" /><label for="__tabbed_1_3">Ubuntu</label><div class="tabbed-content">
<p>We tested on Ubuntu 18.04 &amp; 20.04</p>
<p>We tested RAPIDS on Ubuntu 18.04 &amp; 20.04. Note that the necessary Python and R packages are available in other Linux distributions, so if you decide to give it a try, let us know and we can update these docs.</p>
<ol>
<li>
<p>Install dependencies</p>
<div class="highlight"><pre><span></span><code>sudo apt install libcurl4-openssl-dev
sudo apt install libssl-dev
sudo apt install libxml2-dev
sudo apt install libglpk40
</code></pre></div>
</li>
<li>
@ -1191,18 +1196,15 @@ sudo apt install mysql-server
</li>
<li>
<p>Add R&rsquo;s repository</p>
<ol>
<li>
<p>For 18.04 <br />
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/&#39;</span>
</code></pre></div></p>
</li>
<li>
<p>For 20.04
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/&#39;</span>
</code></pre></div></p>
</li>
</ol>
<div class="tabbed-set" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><label for="__tabbed_2_1">Ubuntu 18.04 Bionic</label><div class="tabbed-content">
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/&#39;</span>
</code></pre></div>
</div>
<input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><label for="__tabbed_2_2">Ubuntu 20.04 Focal</label><div class="tabbed-content">
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/&#39;</span>
</code></pre></div>
</div>
</div>
</li>
<li>
<p>Install R 4.0. If you have other instances of R, we recommend uninstalling them</p>
@ -1240,10 +1242,28 @@ conda activate MY_ENV_NAME
</code></pre></div>
</li>
<li>
<p>Install R packages and virtual environment:</p>
<p>Install the R virtual environment management package (renv)</p>
<div class="highlight"><pre><span></span><code>snakemake -j1 renv_install
snakemake -j1 renv_restore
</code></pre></div>
</li>
<li>
<p>Restore the R virtual environment</p>
<div class="tabbed-set" data-tabs="3:3"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><label for="__tabbed_3_1">Ubuntu 18.04 Bionic (fast)</label><div class="tabbed-content">
<p>Run the following command to restore the R virtual environment using <a href="https://packagemanager.rstudio.com/client/#/repos/1/overview">RSPM</a> binaries
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore(repos = c(CRAN = &quot;https://packagemanager.rstudio.com/all/__linux__/bionic/latest&quot;))&#39;</span>
</code></pre></div></p>
</div>
<input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><label for="__tabbed_3_2">Ubuntu 20.04 Focal (fast)</label><div class="tabbed-content">
<p>Run the following command to restore the R virtual environment using <a href="https://packagemanager.rstudio.com/client/#/repos/1/overview">RSPM</a> binaries
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore(repos = c(CRAN = &quot;https://packagemanager.rstudio.com/all/__linux__/focal/latest&quot;))&#39;</span>
</code></pre></div></p>
</div>
<input id="__tabbed_3_3" name="__tabbed_3" type="radio" /><label for="__tabbed_3_3">Ubuntu (slow)</label><div class="tabbed-content">
<p>If the fast installation command failed for some reason, you can restore the R virtual environment from source:
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore()&#39;</span>
</code></pre></div></p>
</div>
</div>
<div class="admonition note">
<p class="admonition-title">Note<p>This step could take several minutes to complete, especially if you have less than 3Gb of RAM or packages need to be compiled from source. Please be patient and let it run until completion.</p>
</p>
@ -1261,6 +1281,14 @@ snakemake -j1 renv_restore
</li>
</ol>
</div>
<input id="__tabbed_1_4" name="__tabbed_1" type="radio" /><label for="__tabbed_1_4">Windows</label><div class="tabbed-content">
<p>There are several options varying in complexity:</p>
<ul>
<li>You can use our Docker instructions (tested)</li>
<li>You can use our Ubuntu 20.04 instructions on <a href="https://docs.microsoft.com/en-us/windows/wsl/install-win10">WSL2</a> (not tested but it will likely work)</li>
<li>Native installation (experimental). If you would like to contribute to RAPIDS you could try to install MySQL, miniconda, Python, and R 4.0+ in Windows and restore the Python and R virtual environments using steps 6 and 7 of the instructions for Mac. You can <a href="../../team">get in touch</a> if you would like to discuss this with the team.</li>
</ul>
</div>
</div>

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latest/change-log/index.html
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@ -1024,6 +1024,13 @@
</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
<a href="#v032" class="md-nav__link">
v0.3.2
</a>
</li>
<li class="md-nav__item">
<a href="#v031" class="md-nav__link">
v0.3.1
@ -1143,6 +1150,13 @@
</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
<a href="#v032" class="md-nav__link">
v0.3.2
</a>
</li>
<li class="md-nav__item">
<a href="#v031" class="md-nav__link">
v0.3.1
@ -1231,6 +1245,18 @@
<h1 id="change-log">Change Log<a class="headerlink" href="#change-log" title="Permanent link">&para;</a></h1>
<h2 id="v032">v0.3.2<a class="headerlink" href="#v032" title="Permanent link">&para;</a></h2>
<ul>
<li>Update docker and linux instructions to use RSPM binary repo for for faster installation</li>
<li>Update CI to create a release on a tagged push that passes the tests</li>
<li>Clarify in DB credential configuration that we only support MySQL</li>
<li>Add Windows installation instructions</li>
<li>Fix bugs in the create_participants_file script</li>
<li>Fix bugs in Fitbit data parsing.</li>
<li>Fixed Doryab location features context of clustering.</li>
<li>Fixed the wrong shifting while calculating distance in Doryab location features.</li>
<li>Refactored the haversine function</li>
</ul>
<h2 id="v031">v0.3.1<a class="headerlink" href="#v031" title="Permanent link">&para;</a></h2>
<ul>
<li>Update installation docs for RAPIDS&rsquo; docker container</li>

12
latest/features/phone-locations/index.html
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@ -1312,7 +1312,7 @@ For a detailed description of how this is calculated, see <a href="../../citatio
- data/processed/features/<span class="o">{</span>pid<span class="o">}</span>/phone_locations.csv
</code></pre></div>
</div>
<p>Parameters description for <code>[PHONE_LOCATIONS][PROVIDERS][BARNETT]</code>:</p>
<p>Parameters description for <code>[PHONE_LOCATIONS][PROVIDERS][DORYAB]</code>:</p>
<table>
<thead>
<tr>
@ -1353,9 +1353,13 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<td><code>[SAMPLING_FREQUENCY]</code></td>
<td>Expected time difference between any two location rows in minutes. If set to <code>0</code>, the sampling frequency will be inferred automatically as the median of all the differences between any two consecutive row timestamps (recommended if you are using <code>FUSED_RESAMPLED</code> data). This parameter impacts all the time calculations.</td>
</tr>
<tr>
<td><code>[CLUSTER_ON]</code></td>
<td>Set this flag to <code>PARTICIPANT_DATASET</code> to create clusters based on the entire participant&rsquo;s dataset or to <code>TIME_SEGMENT</code> to create clusters based on all the instances of the corresponding time segment (e.g. all mornings).</td>
</tr>
</tbody>
</table>
<p>Features description for <code>[PHONE_LOCATIONS][PROVIDERS][BARNETT]</code>:</p>
<p>Features description for <code>[PHONE_LOCATIONS][PROVIDERS][DORYAB]</code>:</p>
<table>
<thead>
<tr>
@ -1428,12 +1432,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<tr>
<td>movingtostaticratio</td>
<td>-</td>
<td>Ratio between the number of rows labeled Moving versus Static</td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
</tr>
<tr>
<td>outlierstimepercent</td>
<td>-</td>
<td>Ratio between the number of rows that belong to non-significant clusters divided by the total number of rows in a time segment.</td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
</tr>
<tr>
<td>maxlengthstayatclusters</td>

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@ -1316,12 +1316,15 @@
</code></pre></div></p>
</div>
<div class="admonition hint">
<p class="admonition-title">Hint<p>If you are using RAPIDS&rsquo; docker container and Docker-for-mac or Docker-for-Windows 18.03+, connect to your MySQL database using the host <code>host.docker.internal</code> instead of <code>127.0.0.1</code></p>
<p class="admonition-title">Hint<p>If you are using RAPIDS&rsquo; docker container and Docker-for-mac or Docker-for-Windows 18.03+, you can connect to a MySQL database in your host machine using the <code>host.docker.internal</code> instead of <code>127.0.0.1</code> or <code>localhost</code></p>
</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>You can ignore this step if you are only processing Fitbit data in CSV files.</p>
<ul>
<li>You can ignore this step if you are only processing Fitbit data in CSV files.</li>
<li>RAPIDS only supports MySQL/MariaDB databases. If you would like to add support for a different database engine get in touch and we can discuss how to implement it.</li>
</ul>
</div>
<hr />
<h2 id="timezone-of-your-study">Timezone of your study<a class="headerlink" href="#timezone-of-your-study" title="Permanent link">&para;</a></h2>

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@ -1061,15 +1061,15 @@
<h1 id="installation">Installation<a class="headerlink" href="#installation" title="Permanent link">&para;</a></h1>
<p>You can install RAPIDS using Docker (the fastest), or native instructions for MacOS and Ubuntu</p>
<div class="tabbed-set" data-tabs="1:3"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><label for="__tabbed_1_1">Docker</label><div class="tabbed-content">
<p>You can install RAPIDS using Docker (the fastest), or native instructions for MacOS and Linux (Ubuntu). Windows is supported through Docker or WSL.</p>
<div class="tabbed-set" data-tabs="1:4"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><label for="__tabbed_1_1">Docker</label><div class="tabbed-content">
<ol>
<li>
<p>Install <a href="https://docs.docker.com/desktop/">Docker</a></p>
</li>
<li>
<p>Pull our RAPIDS container
<div class="highlight"><pre><span></span><code>docker pull moshiresearch/rapids:latest<span class="sb">`</span>
<div class="highlight"><pre><span></span><code>docker pull moshiresearch/rapids:latest
</code></pre></div></p>
</li>
<li>
@ -1108,6 +1108,10 @@
</details>
</li>
</ol>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>If you installed RAPIDS using Docker for Windows on Windows 10, the container will have <a href="https://stackoverflow.com/questions/43460770/docker-windows-container-memory-limit">limits</a> on the amount of RAM it can use. If you find that RAPIDS crashes due to running out of memory, <a href="https://stackoverflow.com/a/56583203/6030343">increase</a> this limit.</p>
</div>
</div>
<input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><label for="__tabbed_1_2">MacOS</label><div class="tabbed-content">
<p>We tested these instructions in Catalina</p>
@ -1169,13 +1173,14 @@ snakemake -j1 renv_restore
</ol>
</div>
<input id="__tabbed_1_3" name="__tabbed_1" type="radio" /><label for="__tabbed_1_3">Ubuntu</label><div class="tabbed-content">
<p>We tested on Ubuntu 18.04 &amp; 20.04</p>
<p>We tested RAPIDS on Ubuntu 18.04 &amp; 20.04. Note that the necessary Python and R packages are available in other Linux distributions, so if you decide to give it a try, let us know and we can update these docs.</p>
<ol>
<li>
<p>Install dependencies</p>
<div class="highlight"><pre><span></span><code>sudo apt install libcurl4-openssl-dev
sudo apt install libssl-dev
sudo apt install libxml2-dev
sudo apt install libglpk40
</code></pre></div>
</li>
<li>
@ -1191,18 +1196,15 @@ sudo apt install mysql-server
</li>
<li>
<p>Add R&rsquo;s repository</p>
<ol>
<li>
<p>For 18.04 <br />
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/&#39;</span>
</code></pre></div></p>
</li>
<li>
<p>For 20.04
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/&#39;</span>
</code></pre></div></p>
</li>
</ol>
<div class="tabbed-set" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><label for="__tabbed_2_1">Ubuntu 18.04 Bionic</label><div class="tabbed-content">
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/&#39;</span>
</code></pre></div>
</div>
<input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><label for="__tabbed_2_2">Ubuntu 20.04 Focal</label><div class="tabbed-content">
<div class="highlight"><pre><span></span><code>sudo add-apt-repository <span class="s1">&#39;deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/&#39;</span>
</code></pre></div>
</div>
</div>
</li>
<li>
<p>Install R 4.0. If you have other instances of R, we recommend uninstalling them</p>
@ -1240,10 +1242,28 @@ conda activate MY_ENV_NAME
</code></pre></div>
</li>
<li>
<p>Install R packages and virtual environment:</p>
<p>Install the R virtual environment management package (renv)</p>
<div class="highlight"><pre><span></span><code>snakemake -j1 renv_install
snakemake -j1 renv_restore
</code></pre></div>
</li>
<li>
<p>Restore the R virtual environment</p>
<div class="tabbed-set" data-tabs="3:3"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><label for="__tabbed_3_1">Ubuntu 18.04 Bionic (fast)</label><div class="tabbed-content">
<p>Run the following command to restore the R virtual environment using <a href="https://packagemanager.rstudio.com/client/#/repos/1/overview">RSPM</a> binaries
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore(repos = c(CRAN = &quot;https://packagemanager.rstudio.com/all/__linux__/bionic/latest&quot;))&#39;</span>
</code></pre></div></p>
</div>
<input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><label for="__tabbed_3_2">Ubuntu 20.04 Focal (fast)</label><div class="tabbed-content">
<p>Run the following command to restore the R virtual environment using <a href="https://packagemanager.rstudio.com/client/#/repos/1/overview">RSPM</a> binaries
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore(repos = c(CRAN = &quot;https://packagemanager.rstudio.com/all/__linux__/focal/latest&quot;))&#39;</span>
</code></pre></div></p>
</div>
<input id="__tabbed_3_3" name="__tabbed_3" type="radio" /><label for="__tabbed_3_3">Ubuntu (slow)</label><div class="tabbed-content">
<p>If the fast installation command failed for some reason, you can restore the R virtual environment from source:
<div class="highlight"><pre><span></span><code>R -e <span class="s1">&#39;renv::restore()&#39;</span>
</code></pre></div></p>
</div>
</div>
<div class="admonition note">
<p class="admonition-title">Note<p>This step could take several minutes to complete, especially if you have less than 3Gb of RAM or packages need to be compiled from source. Please be patient and let it run until completion.</p>
</p>
@ -1261,6 +1281,14 @@ snakemake -j1 renv_restore
</li>
</ol>
</div>
<input id="__tabbed_1_4" name="__tabbed_1" type="radio" /><label for="__tabbed_1_4">Windows</label><div class="tabbed-content">
<p>There are several options varying in complexity:</p>
<ul>
<li>You can use our Docker instructions (tested)</li>
<li>You can use our Ubuntu 20.04 instructions on <a href="https://docs.microsoft.com/en-us/windows/wsl/install-win10">WSL2</a> (not tested but it will likely work)</li>
<li>Native installation (experimental). If you would like to contribute to RAPIDS you could try to install MySQL, miniconda, Python, and R 4.0+ in Windows and restore the Python and R virtual environments using steps 6 and 7 of the instructions for Mac. You can <a href="../../team">get in touch</a> if you would like to discuss this with the team.</li>
</ul>
</div>
</div>

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