fix doc rendering; simplify travis; check-in RStudio project

.gitignore

@@ -1,7 +1,9 @@
 .Rhistory
-*.Rproj
 .Rproj.user
 .DS_Store
+
+docs/*/*_cache
+
 inst/examples/*/*
 !inst/examples/*/*.R
 !inst/examples/*/*.Rmd

LDAvis.Rproj

@@ -0,0 +1,17 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source

Makefile

@@ -1,2 +1,9 @@
+all: site
+
+clean:
+	rm -r docs/*/vis
+	rm docs/*/*.html
+	rm docs/*/*.md
+
 site:
-	cd docs && Rscript knit_examples.R && cd ..
+	cd docs && Rscript render.R && cd ..

docs/AP/AP.html

@@ -207,21 +207,11 @@ <h1>Associated Press</h1>
 
 <pre><code class="r">library(&quot;LDAvis&quot;)
 data(AP, package = &quot;LDAvisData&quot;)
+json &lt;- with(AP, createJSON(phi, theta, doc.length, vocab, term.frequency))
+serVis(json, out.dir = &#39;vis&#39;, open.browser = FALSE)
 </code></pre>
 
-<pre><code>## Error in find.package(package, lib.loc, verbose = verbose): there is no package called &#39;LDAvisData&#39;
-</code></pre>
-
-<pre><code class="r">json &lt;- with(AP, createJSON(phi, theta, doc.length, vocab, term.frequency))
-</code></pre>
-
-<pre><code>## Error in with(AP, createJSON(phi, theta, doc.length, vocab, term.frequency)): object &#39;AP&#39; not found
-</code></pre>
-
-<pre><code class="r">serVis(json, out.dir = &#39;vis&#39;, open.browser = FALSE)
-</code></pre>
-
-<pre><code>## Error in cat(json, file = file.path(out.dir, &quot;lda.json&quot;)): object &#39;json&#39; not found
+<pre><code>## Loading required namespace: servr
 </code></pre>
 
 </body>

docs/AP/AP.md

@@ -7,24 +7,10 @@ Associated Press
 ```r
 library("LDAvis")
 data(AP, package = "LDAvisData")
-```
-
-```
-## Error in find.package(package, lib.loc, verbose = verbose): there is no package called 'LDAvisData'
-```
-
-```r
 json <- with(AP, createJSON(phi, theta, doc.length, vocab, term.frequency))
-```
-
-```
-## Error in with(AP, createJSON(phi, theta, doc.length, vocab, term.frequency)): object 'AP' not found
-```
-
-```r
 serVis(json, out.dir = 'vis', open.browser = FALSE)
 ```
 
 ```
-## Error in cat(json, file = file.path(out.dir, "lda.json")): object 'json' not found
+## Loading required namespace: servr
 ```

docs/Jeopardy/Jeopardy.html

@@ -207,21 +207,8 @@ <h1>Jeopardy Data</h1>
 
 <pre><code class="r">library(&quot;LDAvis&quot;)
 data(Jeopardy, package = &quot;LDAvisData&quot;)
-</code></pre>
-
-<pre><code>## Error in find.package(package, lib.loc, verbose = verbose): there is no package called &#39;LDAvisData&#39;
-</code></pre>
-
-<pre><code class="r">json &lt;- with(Jeopardy, createJSON(phi, theta, doc.length, vocab, term.frequency))
-</code></pre>
-
-<pre><code>## Error in with(Jeopardy, createJSON(phi, theta, doc.length, vocab, term.frequency)): object &#39;Jeopardy&#39; not found
-</code></pre>
-
-<pre><code class="r">serVis(json, out.dir = &#39;vis&#39;, open.browser = FALSE)
-</code></pre>
-
-<pre><code>## Error in cat(json, file = file.path(out.dir, &quot;lda.json&quot;)): object &#39;json&#39; not found
+json &lt;- with(Jeopardy, createJSON(phi, theta, doc.length, vocab, term.frequency))
+serVis(json, out.dir = &#39;vis&#39;, open.browser = FALSE)
 </code></pre>
 
 </body>

docs/Jeopardy/Jeopardy.md

@@ -7,24 +7,6 @@ Jeopardy Data
 ```r
 library("LDAvis")
 data(Jeopardy, package = "LDAvisData")
-```
-
-```
-## Error in find.package(package, lib.loc, verbose = verbose): there is no package called 'LDAvisData'
-```
-
-```r
 json <- with(Jeopardy, createJSON(phi, theta, doc.length, vocab, term.frequency))
-```
-
-```
-## Error in with(Jeopardy, createJSON(phi, theta, doc.length, vocab, term.frequency)): object 'Jeopardy' not found
-```
-
-```r
 serVis(json, out.dir = 'vis', open.browser = FALSE)
 ```
-
-```
-## Error in cat(json, file = file.path(out.dir, "lda.json")): object 'json' not found
-```

docs/knit_examples.R → docs/render.R

@@ -7,7 +7,7 @@ knit_examples <- function() {
   # navigate intp each example and knit individually
   for (i in dirs) {
     setwd(i)
-    e <- try(knitr::knit2html(input = paste0(i, ".Rmd"), envir = new.env()))
+    knitr::knit2html(input = paste0(i, ".Rmd"), envir = new.env())
     setwd(old)
   }
 }

docs/reviews/reviews.html

@@ -304,9 +304,6 @@ <h3>Visualizing the fitted model with LDAvis</h3>
 
 <p>Now we&#39;re ready to call the <code>createJSON()</code> function in <strong>LDAvis</strong>. This function will return a character string representing a JSON object used to populate the visualization. The <code>createJSON()</code> function computes topic frequencies, inter-topic distances, and projects topics onto a two-dimensional plane to represent their similarity to each other. It also loops through a grid of values of a tuning parameter, \(0 \leq \lambda \leq 1\), that controls how the terms are ranked for each topic, where terms are listed in decreasing of <em>relevance</em>, where the relevance of term \(w\) to topic \(t\) is defined as \(\lambda \times p(w \mid t) + (1 - \lambda) \times p(w \mid t)/p(w)\). Values of \(\lambda\) near 1 give high relevance rankings to <em>frequent</em> terms within a given topic, whereas values of \(\lambda\) near zero give high relevance rankings to <em>exclusive</em> terms within a topic. The set of all terms which are ranked among the top-<code>R</code> most relevant terms for each topic are pre-computed by the <code>createJSON()</code> function and sent to the browser to be interactively visualized using D3 as part of the JSON object.</p>
 
-<pre><code>## Error in find.package(package, lib.loc, verbose = verbose): there is no package called &#39;LDAvisData&#39;
-</code></pre>
-
 <pre><code class="r">library(LDAvis)
 
 # create the JSON object to feed the visualization:
@@ -317,17 +314,11 @@ <h3>Visualizing the fitted model with LDAvis</h3>
                    term.frequency = MovieReviews$term.frequency)
 </code></pre>
 
-<pre><code>## Error in createJSON(phi = MovieReviews$phi, theta = MovieReviews$theta, : object &#39;MovieReviews&#39; not found
-</code></pre>
-
 <p>The <code>serVis()</code> function can take <code>json</code> and serve the result in a variety of ways. Here we&#39;ll write <code>json</code> to a file within the &#39;vis&#39; directory (along with other HTML and JavaScript required to render the page). You can see the result <a href="http://cpsievert.github.io/LDAvis/reviews/vis">here</a>.</p>
 
 <pre><code class="r">serVis(json, out.dir = &#39;vis&#39;, open.browser = FALSE)
 </code></pre>
 
-<pre><code>## Error in cat(json, file = file.path(out.dir, &quot;lda.json&quot;)): object &#39;json&#39; not found
-</code></pre>
-
 <p>If you discover something interesting in your data using <strong>LDAvis</strong>, you can share the result via a URL since the state of the visualization is stored in the URL at all times. For example, in the movie review data, you can quickly see that Topic 7 is broadly about comedies by linking directly to the state of LDAvis where the selected Topic is &ldquo;7&rdquo; and the value of \(\lambda\) is 0.6 with the following URL:</p>
 
 <p><a href="http://cpsievert.github.io/LDAvis/reviews/vis/#topic=7&amp;lambda=0.6&amp;term=">http://cpsievert.github.io/LDAvis/reviews/vis/#topic=7&amp;lambda=0.6&amp;term=</a></p>

docs/reviews/reviews.md

@@ -114,9 +114,6 @@ MovieReviews <- list(phi = phi,
 Now we're ready to call the `createJSON()` function in **LDAvis**. This function will return a character string representing a JSON object used to populate the visualization. The `createJSON()` function computes topic frequencies, inter-topic distances, and projects topics onto a two-dimensional plane to represent their similarity to each other. It also loops through a grid of values of a tuning parameter, $0 \leq \lambda \leq 1$, that controls how the terms are ranked for each topic, where terms are listed in decreasing of *relevance*, where the relevance of term $w$ to topic $t$ is defined as $\lambda \times p(w \mid t) + (1 - \lambda) \times p(w \mid t)/p(w)$. Values of $\lambda$ near 1 give high relevance rankings to *frequent* terms within a given topic, whereas values of $\lambda$ near zero give high relevance rankings to *exclusive* terms within a topic. The set of all terms which are ranked among the top-`R` most relevant terms for each topic are pre-computed by the `createJSON()` function and sent to the browser to be interactively visualized using D3 as part of the JSON object.
 
 
-```
-## Error in find.package(package, lib.loc, verbose = verbose): there is no package called 'LDAvisData'
-```
 
 
 ```r
@@ -130,21 +127,13 @@ json <- createJSON(phi = MovieReviews$phi,
                    term.frequency = MovieReviews$term.frequency)
 ```
 
-```
-## Error in createJSON(phi = MovieReviews$phi, theta = MovieReviews$theta, : object 'MovieReviews' not found
-```
-
 The `serVis()` function can take `json` and serve the result in a variety of ways. Here we'll write `json` to a file within the 'vis' directory (along with other HTML and JavaScript required to render the page). You can see the result [here](http://cpsievert.github.io/LDAvis/reviews/vis).
 
 
 ```r
 serVis(json, out.dir = 'vis', open.browser = FALSE)
 ```
 
-```
-## Error in cat(json, file = file.path(out.dir, "lda.json")): object 'json' not found
-```
-
 If you discover something interesting in your data using **LDAvis**, you can share the result via a URL since the state of the visualization is stored in the URL at all times. For example, in the movie review data, you can quickly see that Topic 7 is broadly about comedies by linking directly to the state of LDAvis where the selected Topic is "7" and the value of $\lambda$ is 0.6 with the following URL:
 
 [http://cpsievert.github.io/LDAvis/reviews/vis/#topic=7&lambda=0.6&term=](http://cpsievert.github.io/LDAvis/reviews/vis/#topic=7&lambda=0.6&term=)