remove link to survey

Author: joselynn_wallace@brown.edu

notebooks/_book/Intro.html

@@ -697,7 +697,7 @@ <h3 data-number="2.6.4" class="anchored" data-anchor-id="running-sctransform"><s
 <span id="cb44-3"><a href="#cb44-3" aria-hidden="true" tabindex="-1"></a>end.time <span class="ot">&lt;-</span> <span class="fu">Sys.time</span>()</span>
 <span id="cb44-4"><a href="#cb44-4" aria-hidden="true" tabindex="-1"></a>end.time <span class="sc">-</span> start.time</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Time difference of 18.36337 secs</code></pre>
+<pre><code>Time difference of 19.10482 secs</code></pre>
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 <p>Then run PCA</p>
@@ -836,7 +836,7 @@ <h3 data-number="2.7.4" class="anchored" data-anchor-id="harmony-integration"><s
 <span id="cb49-7"><a href="#cb49-7" aria-hidden="true" tabindex="-1"></a>end.time <span class="ot">&lt;-</span> <span class="fu">Sys.time</span>()</span>
 <span id="cb49-8"><a href="#cb49-8" aria-hidden="true" tabindex="-1"></a>end.time <span class="sc">-</span> start.time</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Time difference of 10.7184 secs</code></pre>
+<pre><code>Time difference of 11.29752 secs</code></pre>
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@@ -849,7 +849,7 @@ <h3 data-number="2.7.4" class="anchored" data-anchor-id="harmony-integration"><s
 <span id="cb51-7"><a href="#cb51-7" aria-hidden="true" tabindex="-1"></a>end.time <span class="ot">&lt;-</span> <span class="fu">Sys.time</span>()</span>
 <span id="cb51-8"><a href="#cb51-8" aria-hidden="true" tabindex="-1"></a>end.time <span class="sc">-</span> start.time</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Time difference of 8.304569 secs</code></pre>
+<pre><code>Time difference of 8.645848 secs</code></pre>
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@@ -866,7 +866,7 @@ <h3 data-number="2.7.4" class="anchored" data-anchor-id="harmony-integration"><s
 <div class="sourceCode cell-code" id="cb55"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb55-1"><a href="#cb55-1" aria-hidden="true" tabindex="-1"></a>end.time <span class="ot">&lt;-</span> <span class="fu">Sys.time</span>()</span>
 <span id="cb55-2"><a href="#cb55-2" aria-hidden="true" tabindex="-1"></a>end.time <span class="sc">-</span> start.time</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Time difference of 1.150598 secs</code></pre>
+<pre><code>Time difference of 1.208647 secs</code></pre>
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@@ -879,7 +879,7 @@ <h3 data-number="2.7.4" class="anchored" data-anchor-id="harmony-integration"><s
 <span id="cb57-7"><a href="#cb57-7" aria-hidden="true" tabindex="-1"></a>end.time <span class="ot">&lt;-</span> <span class="fu">Sys.time</span>()</span>
 <span id="cb57-8"><a href="#cb57-8" aria-hidden="true" tabindex="-1"></a>end.time <span class="sc">-</span> start.time</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Time difference of 10.10729 secs</code></pre>
+<pre><code>Time difference of 10.72018 secs</code></pre>
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 </div>
 </section>
@@ -985,16 +985,16 @@ <h2 data-number="2.8" class="anchored" data-anchor-id="clustering"><span class="
 This message will be shown once per session</code></pre>
 </div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:07 UMAP embedding parameters a = 0.9922 b = 1.112</code></pre>
+<pre><code>13:30:15 UMAP embedding parameters a = 0.9922 b = 1.112</code></pre>
 </div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:07 Read 1456 rows and found 10 numeric columns</code></pre>
+<pre><code>13:30:15 Read 1456 rows and found 10 numeric columns</code></pre>
 </div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:07 Using Annoy for neighbor search, n_neighbors = 30</code></pre>
+<pre><code>13:30:15 Using Annoy for neighbor search, n_neighbors = 30</code></pre>
 </div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:07 Building Annoy index with metric = cosine, n_trees = 50</code></pre>
+<pre><code>13:30:15 Building Annoy index with metric = cosine, n_trees = 50</code></pre>
 </div>
 <div class="cell-output cell-output-stderr">
 <pre><code>0%   10   20   30   40   50   60   70   80   90   100%</code></pre>
@@ -1004,86 +1004,86 @@ <h2 data-number="2.8" class="anchored" data-anchor-id="clustering"><span class="
 </div>
 <div class="cell-output cell-output-stderr">
 <pre><code>**************************************************|
-08:50:08 Writing NN index file to temp file /tmp/Rtmp3GlxL6/file2f29163dab174d
-08:50:08 Searching Annoy index using 1 thread, search_k = 3000
-08:50:08 Annoy recall = 100%
-08:50:09 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
-08:50:10 Initializing from normalized Laplacian + noise (using RSpectra)
-08:50:10 Commencing optimization for 500 epochs, with 55744 positive edges
-08:50:10 Using rng type: pcg
-08:50:13 Optimization finished</code></pre>
+13:30:15 Writing NN index file to temp file /tmp/RtmpXqTft1/file1e66443af80802
+13:30:15 Searching Annoy index using 1 thread, search_k = 3000
+13:30:16 Annoy recall = 100%
+13:30:17 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
+13:30:18 Initializing from normalized Laplacian + noise (using RSpectra)
+13:30:18 Commencing optimization for 500 epochs, with 55744 positive edges
+13:30:18 Using rng type: pcg
+13:30:21 Optimization finished</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb89"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb89-1"><a href="#cb89-1" aria-hidden="true" tabindex="-1"></a>all_data_sub <span class="ot">&lt;-</span> <span class="fu">RunUMAP</span>(all_data_sub, <span class="at">reduction =</span> <span class="st">"integrated.cca"</span>, <span class="at">dims =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>, <span class="at">reduction.name =</span> <span class="st">"umap.cca"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:13 UMAP embedding parameters a = 0.9922 b = 1.112
-08:50:13 Read 1456 rows and found 10 numeric columns
-08:50:13 Using Annoy for neighbor search, n_neighbors = 30
-08:50:13 Building Annoy index with metric = cosine, n_trees = 50
+<pre><code>13:30:21 UMAP embedding parameters a = 0.9922 b = 1.112
+13:30:21 Read 1456 rows and found 10 numeric columns
+13:30:21 Using Annoy for neighbor search, n_neighbors = 30
+13:30:21 Building Annoy index with metric = cosine, n_trees = 50
 0%   10   20   30   40   50   60   70   80   90   100%
 [----|----|----|----|----|----|----|----|----|----|
 **************************************************|
-08:50:13 Writing NN index file to temp file /tmp/Rtmp3GlxL6/file2f291636acb517
-08:50:13 Searching Annoy index using 1 thread, search_k = 3000
-08:50:13 Annoy recall = 100%
-08:50:14 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
-08:50:16 Initializing from normalized Laplacian + noise (using RSpectra)
-08:50:16 Commencing optimization for 500 epochs, with 58396 positive edges
-08:50:16 Using rng type: pcg
-08:50:18 Optimization finished</code></pre>
+13:30:21 Writing NN index file to temp file /tmp/RtmpXqTft1/file1e66445b9bacb2
+13:30:21 Searching Annoy index using 1 thread, search_k = 3000
+13:30:21 Annoy recall = 100%
+13:30:22 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
+13:30:24 Initializing from normalized Laplacian + noise (using RSpectra)
+13:30:24 Commencing optimization for 500 epochs, with 58396 positive edges
+13:30:24 Using rng type: pcg
+13:30:26 Optimization finished</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb91"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb91-1"><a href="#cb91-1" aria-hidden="true" tabindex="-1"></a>all_data_sub <span class="ot">&lt;-</span> <span class="fu">RunUMAP</span>(all_data_sub, <span class="at">reduction =</span> <span class="st">"integrated.jpca"</span>, <span class="at">dims =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>, <span class="at">reduction.name =</span> <span class="st">"umap.jpca"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:18 UMAP embedding parameters a = 0.9922 b = 1.112
-08:50:18 Read 1456 rows and found 10 numeric columns
-08:50:18 Using Annoy for neighbor search, n_neighbors = 30
-08:50:18 Building Annoy index with metric = cosine, n_trees = 50
+<pre><code>13:30:26 UMAP embedding parameters a = 0.9922 b = 1.112
+13:30:26 Read 1456 rows and found 10 numeric columns
+13:30:26 Using Annoy for neighbor search, n_neighbors = 30
+13:30:26 Building Annoy index with metric = cosine, n_trees = 50
 0%   10   20   30   40   50   60   70   80   90   100%
 [----|----|----|----|----|----|----|----|----|----|
 **************************************************|
-08:50:18 Writing NN index file to temp file /tmp/Rtmp3GlxL6/file2f29161a5c0631
-08:50:18 Searching Annoy index using 1 thread, search_k = 3000
-08:50:18 Annoy recall = 100%
-08:50:19 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
-08:50:21 Initializing from normalized Laplacian + noise (using RSpectra)
-08:50:21 Commencing optimization for 500 epochs, with 58918 positive edges
-08:50:21 Using rng type: pcg
-08:50:23 Optimization finished</code></pre>
+13:30:27 Writing NN index file to temp file /tmp/RtmpXqTft1/file1e66442972fd80
+13:30:27 Searching Annoy index using 1 thread, search_k = 3000
+13:30:27 Annoy recall = 100%
+13:30:28 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
+13:30:30 Initializing from normalized Laplacian + noise (using RSpectra)
+13:30:30 Commencing optimization for 500 epochs, with 58918 positive edges
+13:30:30 Using rng type: pcg
+13:30:32 Optimization finished</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb93"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb93-1"><a href="#cb93-1" aria-hidden="true" tabindex="-1"></a>all_data_sub <span class="ot">&lt;-</span> <span class="fu">RunUMAP</span>(all_data_sub, <span class="at">reduction =</span> <span class="st">"harmony"</span>, <span class="at">dims =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>, <span class="at">reduction.name =</span> <span class="st">"umap.harmony"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:23 UMAP embedding parameters a = 0.9922 b = 1.112
-08:50:23 Read 1456 rows and found 10 numeric columns
-08:50:23 Using Annoy for neighbor search, n_neighbors = 30
-08:50:23 Building Annoy index with metric = cosine, n_trees = 50
+<pre><code>13:30:32 UMAP embedding parameters a = 0.9922 b = 1.112
+13:30:32 Read 1456 rows and found 10 numeric columns
+13:30:32 Using Annoy for neighbor search, n_neighbors = 30
+13:30:32 Building Annoy index with metric = cosine, n_trees = 50
 0%   10   20   30   40   50   60   70   80   90   100%
 [----|----|----|----|----|----|----|----|----|----|
 **************************************************|
-08:50:23 Writing NN index file to temp file /tmp/Rtmp3GlxL6/file2f29163f7a3d75
-08:50:23 Searching Annoy index using 1 thread, search_k = 3000
-08:50:24 Annoy recall = 100%
-08:50:24 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
-08:50:26 Initializing from normalized Laplacian + noise (using RSpectra)
-08:50:26 Commencing optimization for 500 epochs, with 57540 positive edges
-08:50:26 Using rng type: pcg
-08:50:28 Optimization finished</code></pre>
+13:30:32 Writing NN index file to temp file /tmp/RtmpXqTft1/file1e66441abc6662
+13:30:32 Searching Annoy index using 1 thread, search_k = 3000
+13:30:33 Annoy recall = 100%
+13:30:33 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
+13:30:35 Initializing from normalized Laplacian + noise (using RSpectra)
+13:30:35 Commencing optimization for 500 epochs, with 57540 positive edges
+13:30:35 Using rng type: pcg
+13:30:37 Optimization finished</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb95"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb95-1"><a href="#cb95-1" aria-hidden="true" tabindex="-1"></a>all_data_sub <span class="ot">&lt;-</span> <span class="fu">RunUMAP</span>(all_data_sub, <span class="at">reduction =</span> <span class="st">"integrated.rpca"</span>, <span class="at">dims =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>, <span class="at">reduction.name =</span> <span class="st">"umap.rpca"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>08:50:28 UMAP embedding parameters a = 0.9922 b = 1.112
-08:50:28 Read 1456 rows and found 10 numeric columns
-08:50:28 Using Annoy for neighbor search, n_neighbors = 30
-08:50:28 Building Annoy index with metric = cosine, n_trees = 50
+<pre><code>13:30:38 UMAP embedding parameters a = 0.9922 b = 1.112
+13:30:38 Read 1456 rows and found 10 numeric columns
+13:30:38 Using Annoy for neighbor search, n_neighbors = 30
+13:30:38 Building Annoy index with metric = cosine, n_trees = 50
 0%   10   20   30   40   50   60   70   80   90   100%
 [----|----|----|----|----|----|----|----|----|----|
 **************************************************|
-08:50:28 Writing NN index file to temp file /tmp/Rtmp3GlxL6/file2f2916195a7045
-08:50:28 Searching Annoy index using 1 thread, search_k = 3000
-08:50:29 Annoy recall = 100%
-08:50:30 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
-08:50:31 Initializing from normalized Laplacian + noise (using RSpectra)
-08:50:31 Commencing optimization for 500 epochs, with 57330 positive edges
-08:50:31 Using rng type: pcg
-08:50:33 Optimization finished</code></pre>
+13:30:38 Writing NN index file to temp file /tmp/RtmpXqTft1/file1e664421291c83
+13:30:38 Searching Annoy index using 1 thread, search_k = 3000
+13:30:38 Annoy recall = 100%
+13:30:39 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
+13:30:41 Initializing from normalized Laplacian + noise (using RSpectra)
+13:30:41 Commencing optimization for 500 epochs, with 57330 positive edges
+13:30:41 Using rng type: pcg
+13:30:43 Optimization finished</code></pre>
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+This is XeTeX, Version 3.141592653-2.6-0.999994 (TeX Live 2022) (preloaded format=xelatex 2023.2.9)  26 SEP 2025 13:33
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notebooks/_book/index.html

@@ -12,8 +12,3 @@ execute:
   cache: true
 ---
 
-Please fill out this form so we know who is attending DSCOV, using the link or the QR code.
-
-![](image/DSCoVAttendanceForm.png){width=50%}
-[https://bit.ly/4nghyWw](https://docs.google.com/forms/d/e/1FAIpQLSeyXnwcBBgzT8C2o9p4DkupVaQDLNIx7lIvyoyOUgW_YIdsHA/viewform?pli=1)
-Thank you!