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new sugar articles: all, any, diff
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‎_posts/2012-12-23-sugar-all.md

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---
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title: Using Sugar Function all()
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author: Ross Bennett
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license: GPL (>= 2)
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tags: sugar
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summary: Illustrates the use of sugar function all()
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layout: post
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src: 2012-12-23-sugar-all.cpp
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---
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The sugar function all() answers the question, "Are all of the values ... ?".
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The all_sug() function takes a LogicalVector as an argument and allows one to
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enter an expression for the argument as shown in the R examples. In this example,
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it is simply wrapper around the sugar function all() and includes is_true to
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return a boolean.
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Note that when comparing two vectors, it is an element-wise comparison.
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(i.e. `x[0] > y[0]`, ..., `x[n] > y[n]`)
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{% highlight cpp %}
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#include <Rcpp.h>
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using namespace Rcpp;
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// [[Rcpp::export]]
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bool all_sug(LogicalVector x) {
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// Note the use of is_true to return a bool type.
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return is_true(all(x == TRUE));
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}
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{% endhighlight %}
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While the above function may seem trivial, it can be easy to forget is_true() when
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using all() and will result in a compile error. The check_equal() function below
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is an example of a simple utility function to check two vectors for equality
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using the all_sug() function defined above.
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{% highlight cpp %}
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// [[Rcpp::export]]
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void check_equal(NumericVector x, NumericVector y) {
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if(all_sug(x == y)) {
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Rcout << "Success! The input vectors are equal" << std::endl;
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// do something
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} else {
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Rcout << "Fail! The input vectors are not equal" << std::endl;
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// do something else
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}
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}
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{% endhighlight %}
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{% highlight r %}
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x <- c(3, 9, 0, 2, 7, 5, 6)
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y <- c(0, 0, 0, 0, 0, 0, 0)
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all_sug(x < 10)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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all_sug(x != 3)
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{% endhighlight %}
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<pre class="output">
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[1] FALSE
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</pre>
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{% highlight r %}
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all_sug(x >= y)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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all_sug(y == 0)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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check_equal(x, y)
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{% endhighlight %}
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<pre class="output">
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Fail! The input vectors are not equal
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</pre>
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<pre class="output">
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NULL
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</pre>
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{% highlight r %}
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check_equal(x, c(3, 9, 0, 2, 7, 5, 6))
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{% endhighlight %}
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<pre class="output">
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Success! The input vectors are equal
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</pre>
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<pre class="output">
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NULL
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</pre>
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‎_posts/2012-12-23-sugar-any.md

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---
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title: Using Sugar Function any()
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author: Ross Bennett
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license: GPL (>= 2)
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tags: sugar
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summary: Illustrates the use of sugar function any()
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layout: post
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src: 2012-12-23-sugar-any.cpp
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---
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The sugar function any() answers the question, "Are any of the values ... ?".
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The any_sug() function takes a LogicalVector as an argument and allows one to
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enter an expression for the argument as shown in the R examples. In this
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example, it is simply wrapper around the sugar function any() and includes
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is_true to return a boolean.
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Note that when comparing two vectors, it is an element-wise comparison.
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(i.e. `x[0] > y[0]`, ..., `x[n] > y[n]`)
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{% highlight cpp %}
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#include <Rcpp.h>
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using namespace Rcpp;
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// [[Rcpp::export]]
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bool any_sug(LogicalVector x){
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// Note the use of is_true to return a bool type
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return is_true(any(x == TRUE));
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}
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{% endhighlight %}
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While the above function may seem trivial, it can be easy to forget is_true()
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when using any() and will result in a compile error. The check_negative()
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function below is an example of a simple utility function to check if a
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vector contains negative values using the any_sug() function defined above.
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{% highlight cpp %}
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// [[Rcpp::export]]
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void check_negative(NumericVector x) {
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if(any_sug(x < 0)) {
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Rcout << "The vector contains negative numbers" << std::endl;
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// do something
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} else {
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Rcout << "The vector does not contain negative numbers" << std::endl;
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// do something else
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}
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}
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{% endhighlight %}
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{% highlight r %}
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x <- c(3, 9, 0, 2, 7, -1, 6)
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y <- c(8, 3, 2, 6, 1, 5, 0)
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any_sug(x < 10)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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any_sug(x != 3)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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any_sug(x >= y)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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any_sug(y == 0)
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{% endhighlight %}
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<pre class="output">
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[1] TRUE
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</pre>
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{% highlight r %}
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check_negative(x)
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{% endhighlight %}
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<pre class="output">
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The vector contains negative numbers
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</pre>
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<pre class="output">
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NULL
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</pre>
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{% highlight r %}
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check_negative(y)
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{% endhighlight %}
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<pre class="output">
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The vector does not contain negative numbers
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</pre>
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<pre class="output">
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NULL
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</pre>
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‎_posts/2012-12-23-sugar-diff.md

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---
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title: Using Sugar Function diff()
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author: Ross Bennett
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license: GPL (>= 2)
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tags: sugar
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summary: Illustrates the use of sugar function diff()
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layout: post
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src: 2012-12-23-sugar-diff.cpp
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---
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The sugar function diff() computes the difference of consecutive elements
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(i.e. lag = 1) of the input vector. Note that the size of the vector returned
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is one less than the input vector. The sugar function diff() works the same
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way as the diff() function in base R, except the lag is not specified.
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{% highlight cpp %}
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#include <Rcpp.h>
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using namespace Rcpp;
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// [[Rcpp::export]]
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NumericVector diff_sug(NumericVector x){
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return diff(x);
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}
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{% endhighlight %}
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One can use the diff() function to compute one period simple returns of stock
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prices.
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{% highlight cpp %}
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// [[Rcpp::export]]
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NumericVector ret_simple(NumericVector x) {
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NumericVector vec_diff = diff(x);
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NumericVector res(x.size());
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// pad the front with an NA
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res[0] = NA_REAL;
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for(int i = 1; i < res.size(); i++) {
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res[i] = vec_diff[i-1] / x[i-1];
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}
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return res;
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}
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{% endhighlight %}
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{% highlight r %}
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x <- rnorm(10)
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# Close prices of S&P 500
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y <- c(1418.55, 1427.84, 1428.48, 1419.45, 1413.58,
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1430.36, 1446.79, 1435.81, 1443.69, 1430.15)
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diff_sug(x)
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{% endhighlight %}
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<pre class="output">
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[1] 1.78889 -1.48820 0.05878 1.58578 -1.25415 -1.72598 0.57821 0.24119
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[9] 1.66974
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</pre>
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{% highlight r %}
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# base R function
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diff(x)
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{% endhighlight %}
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<pre class="output">
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[1] 1.78889 -1.48820 0.05878 1.58578 -1.25415 -1.72598 0.57821 0.24119
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[9] 1.66974
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</pre>
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{% highlight r %}
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ret_simple(y)
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{% endhighlight %}
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<pre class="output">
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[1] NA 0.0065489 0.0004482 -0.0063214 -0.0041354 0.0118706
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[7] 0.0114866 -0.0075892 0.0054882 -0.0093787
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</pre>
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