forked from swcarpentry/r-novice-inflammation
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path03-supp-loops-in-depth.html
357 lines (353 loc) · 22.3 KB
/
03-supp-loops-in-depth.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="generator" content="pandoc">
<title>Software Carpentry: Programming with R</title>
<link rel="shortcut icon" type="image/x-icon" href="/favicon.ico" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="stylesheet" type="text/css" href="css/bootstrap/bootstrap.css" />
<link rel="stylesheet" type="text/css" href="css/bootstrap/bootstrap-theme.css" />
<link rel="stylesheet" type="text/css" href="css/swc.css" />
<link rel="alternate" type="application/rss+xml" title="Software Carpentry Blog" href="http://software-carpentry.org/feed.xml"/>
<meta charset="UTF-8" />
<!-- HTML5 shim, for IE6-8 support of HTML5 elements -->
<!--[if lt IE 9]>
<script src="http://html5shim.googlecode.com/svn/trunk/html5.js"></script>
<![endif]-->
</head>
<body class="lesson">
<div class="container card">
<div class="banner">
<a href="http://software-carpentry.org" title="Software Carpentry">
<img alt="Software Carpentry banner" src="img/software-carpentry-banner.png" />
</a>
</div>
<article>
<div class="row">
<div class="col-md-10 col-md-offset-1">
<a href="index.html"><h1 class="title">Programming with R</h1></a>
<h2 class="subtitle">Loops in R</h2>
<section class="objectives panel panel-warning">
<div class="panel-heading">
<h2 id="learning-objectives"><span class="glyphicon glyphicon-certificate"></span>Learning Objectives</h2>
</div>
<div class="panel-body">
<ul>
<li>Compare loops and vectorized operations</li>
<li>Use the apply family of functions</li>
</ul>
</div>
</section>
<p>In R you have multiple options when repeating calculations: vectorized operations, <code>for</code> loops, and <code>apply</code> functions.</p>
<p>This lesson is an extension of <a href="03-loops-R.html">Analyzing Multiple Data Sets</a>. In that lesson, we introduced how to run a custom function, <code>analyze</code>, over multiple data files:</p>
<pre class="sourceCode r"><code class="sourceCode r">analyze <-<span class="st"> </span>function(filename) {
<span class="co"># Plots the average, min, and max inflammation over time.</span>
<span class="co"># Input is character string of a csv file.</span>
dat <-<span class="st"> </span><span class="kw">read.csv</span>(<span class="dt">file =</span> filename, <span class="dt">header =</span> <span class="ot">FALSE</span>)
avg_day_inflammation <-<span class="st"> </span><span class="kw">apply</span>(dat, <span class="dv">2</span>, mean)
<span class="kw">plot</span>(avg_day_inflammation)
max_day_inflammation <-<span class="st"> </span><span class="kw">apply</span>(dat, <span class="dv">2</span>, max)
<span class="kw">plot</span>(max_day_inflammation)
min_day_inflammation <-<span class="st"> </span><span class="kw">apply</span>(dat, <span class="dv">2</span>, min)
<span class="kw">plot</span>(min_day_inflammation)
}</code></pre>
<pre class="sourceCode r"><code class="sourceCode r">filenames <-<span class="st"> </span><span class="kw">list.files</span>(<span class="dt">path =</span> <span class="st">"data"</span>, <span class="dt">pattern =</span> <span class="st">"inflammation"</span>, <span class="dt">full.names =</span> <span class="ot">TRUE</span>)</code></pre>
<h3 id="vectorized-operations">Vectorized Operations</h3>
<p>A key difference between R and many other languages is a topic known as vectorization. When you wrote the <code>total</code> function, we mentioned that R already has <code>sum</code> to do this; <code>sum</code> is <em>much</em> faster than the interpreted <code>for</code> loop because <code>sum</code> is coded in C to work with a vector of numbers. Many of R’s functions work this way; the loop is hidden from you in C. Learning to use vectorized operations is a key skill in R.</p>
<p>For example, to add pairs of numbers contained in two vectors</p>
<pre class="sourceCode r"><code class="sourceCode r">a <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">10</span>
b <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">10</span></code></pre>
<p>You could loop over the pairs adding each in turn, but that would be very inefficient in R.</p>
<p>Instead of using <code>i in a</code> to make our loop variable, we use the function <code>seq_along</code> to generate indices for each element <code>a</code> contains.</p>
<pre class="sourceCode r"><code class="sourceCode r">res <-<span class="st"> </span><span class="kw">numeric</span>(<span class="dt">length =</span> <span class="kw">length</span>(a))
for (i in <span class="kw">seq_along</span>(a)) {
res[i] <-<span class="st"> </span>a[i] +<span class="st"> </span>b[i]
}
res</code></pre>
<pre class="output"><code> [1] 2 4 6 8 10 12 14 16 18 20
</code></pre>
<p>Instead, <code>+</code> is a <em>vectorized</em> function which can operate on entire vectors at once</p>
<pre class="sourceCode r"><code class="sourceCode r">res2 <-<span class="st"> </span>a +<span class="st"> </span>b
<span class="kw">all.equal</span>(res, res2)</code></pre>
<pre class="output"><code>[1] TRUE
</code></pre>
<h3 id="vector-recycling">Vector Recycling</h3>
<p>When performing vector operations in R, it is important to know about recycling. If you perform an operation on two or more vectors of unequal length, R will recycle elements of the shorter vector(s) to match the longest vector. For example:</p>
<pre class="sourceCode r"><code class="sourceCode r">a <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">10</span>
b <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">5</span>
a +<span class="st"> </span>b</code></pre>
<pre class="output"><code> [1] 2 4 6 8 10 7 9 11 13 15
</code></pre>
<p>The elements of <code>a</code> and <code>b</code> are added together starting from the first element of both vectors. When R reaches the end of the shorter vector <code>b</code>, it starts again at the first element of <code>b</code> and contines until it reaches the last element of the longest vector <code>a</code>. This behaviour may seem crazy at first glance, but it is very useful when you want to perform the same operation on every element of a vector. For example, say we want to multiply every element of our vector <code>a</code> by 5:</p>
<pre class="sourceCode r"><code class="sourceCode r">a <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">10</span>
b <-<span class="st"> </span><span class="dv">5</span>
a *<span class="st"> </span>b</code></pre>
<pre class="output"><code> [1] 5 10 15 20 25 30 35 40 45 50
</code></pre>
<p>Remember there are no scalars in R, so <code>b</code> is actually a vector of length 1; in order to add its value to every element of <code>a</code>, it is <em>recycled</em> to match the length of <code>a</code>.</p>
<p>When the length of the longer object is a multiple of the shorter object length (as in our example above), the recycling occurs silently. When the longer object length is not a multiple of the shorter object length, a warning is given:</p>
<pre class="sourceCode r"><code class="sourceCode r">a <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">10</span>
b <-<span class="st"> </span><span class="dv">1</span>:<span class="dv">7</span>
a +<span class="st"> </span>b</code></pre>
<pre class="error"><code>Warning in a + b: longer object length is not a multiple of shorter object
length
</code></pre>
<pre class="output"><code> [1] 2 4 6 8 10 12 14 9 11 13
</code></pre>
<h3 id="for-or-apply"><code>for</code> or <code>apply</code>?</h3>
<p>A <code>for</code> loop is used to apply the same function calls to a collection of objects. R has a family of functions, the <code>apply</code> family, which can be used in much the same way. You’ve already used one of the family, <code>apply</code> in the first <a href="01-starting-with-data.html">lesson</a>. The <code>apply</code> family members include</p>
<ul>
<li><code>apply</code> - apply over the margins of an array (e.g. the rows or columns of a matrix)</li>
<li><code>lapply</code> - apply over an object and return list</li>
<li><code>sapply</code> - apply over an object and return a simplified object (an array) if possible</li>
<li><code>vapply</code> - similar to <code>sapply</code> but you specify the type of object returned by the iterations</li>
</ul>
<p>Each of these has an argument <code>FUN</code> which takes a function to apply to each element of the object. Instead of looping over <code>filenames</code> and calling <code>analyze</code>, as you did earlier, you could <code>sapply</code> over <code>filenames</code> with <code>FUN = analyze</code>:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">sapply</span>(filenames, <span class="dt">FUN =</span> analyze)</code></pre>
<p>Deciding whether to use <code>for</code> or one of the <code>apply</code> family is really personal preference. Using an <code>apply</code> family function forces to you encapsulate your operations as a function rather than separate calls with <code>for</code>. <code>for</code> loops are often more natural in some circumstances; for several related operations, a <code>for</code> loop will avoid you having to pass in a lot of extra arguments to your function.</p>
<h3 id="loops-in-r-are-slow">Loops in R Are Slow</h3>
<p>No, they are not! <em>If</em> you follow some golden rules:</p>
<ol style="list-style-type: decimal">
<li>Don’t use a loop when a vectorised alternative exists</li>
<li>Don’t grow objects (via <code>c</code>, <code>cbind</code>, etc) during the loop - R has to create a new object and copy across the information just to add a new element or row/column</li>
<li>Allocate an object to hold the results and fill it in during the loop</li>
</ol>
<p>As an example, we’ll create a new version of <code>analyze</code> that will return the mean inflammation per day (column) of each file.</p>
<pre class="sourceCode r"><code class="sourceCode r">analyze2 <-<span class="st"> </span>function(filenames) {
for (f in <span class="kw">seq_along</span>(filenames)) {
fdata <-<span class="st"> </span><span class="kw">read.csv</span>(filenames[f], <span class="dt">header =</span> <span class="ot">FALSE</span>)
res <-<span class="st"> </span><span class="kw">apply</span>(fdata, <span class="dv">2</span>, mean)
if (f ==<span class="st"> </span><span class="dv">1</span>) {
out <-<span class="st"> </span>res
} else {
<span class="co"># The loop is slowed by this call to cbind that grows the object</span>
out <-<span class="st"> </span><span class="kw">cbind</span>(out, res)
}
}
<span class="kw">return</span>(out)
}
<span class="kw">system.time</span>(avg2 <-<span class="st"> </span><span class="kw">analyze2</span>(filenames))</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="output"><code> user system elapsed
0.101 0.006 0.113
</code></pre>
<p>Note how we add a new column to <code>out</code> at each iteration? This is a cardinal sin of writing a <code>for</code> loop in R.</p>
<p>Instead, we can create an empty matrix with the right dimensions (rows/columns) to hold the results. Then we loop over the files but this time we fill in the <code>f</code>th column of our results matrix <code>out</code>. This time there is no copying/growing for R to deal with.</p>
<pre class="sourceCode r"><code class="sourceCode r">analyze3 <-<span class="st"> </span>function(filenames) {
out <-<span class="st"> </span><span class="kw">matrix</span>(<span class="dt">ncol =</span> <span class="kw">length</span>(filenames), <span class="dt">nrow =</span> <span class="dv">40</span>) ## assuming 40 here from files
for (f in <span class="kw">seq_along</span>(filenames)) {
fdata <-<span class="st"> </span><span class="kw">read.csv</span>(filenames[f], <span class="dt">header =</span> <span class="ot">FALSE</span>)
out[, f] <-<span class="st"> </span><span class="kw">apply</span>(fdata, <span class="dv">2</span>, mean)
}
<span class="kw">return</span>(out)
}
<span class="kw">system.time</span>(avg3 <-<span class="st"> </span><span class="kw">analyze3</span>(filenames))</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="error"><code>Warning in scan(file, what, nmax, sep, dec, quote, skip, nlines,
na.strings, : EOF within quoted string
</code></pre>
<pre class="error"><code>Warning in scan(file = file, what = what, sep = sep, quote = quote, dec =
dec, : embedded nul(s) found in input
</code></pre>
<pre class="error"><code>Warning in mean.default(newX[, i], ...): argument is not numeric or
logical: returning NA
</code></pre>
<pre class="output"><code> user system elapsed
0.110 0.003 0.117
</code></pre>
<p>In this simple example there is little difference in the compute time of <code>analyze2</code> and <code>analyze3</code>. This is because we are only iterating over 12 files and hence we only incur 12 copy/grow operations. If we were doing this over more files or the data objects we were growing were larger, the penalty for copying/growing would be much larger.</p>
<p>Note that <code>apply</code> handles these memory allocation issues for you, but then you have to write the loop part as a function to pass to <code>apply</code>. At its heart, <code>apply</code> is just a <code>for</code> loop with extra convenience.</p>
</div>
</div>
</article>
<div class="footer">
<a class="label swc-blue-bg" href="http://software-carpentry.org">Software Carpentry</a>
<a class="label swc-blue-bg" href="https://github.com/swcarpentry/r-novice-inflammation">Source</a>
<a class="label swc-blue-bg" href="mailto:[email protected]">Contact</a>
<a class="label swc-blue-bg" href="LICENSE.html">License</a>
</div>
</div>
<!-- Javascript placed at the end of the document so the pages load faster -->
<script src="http://software-carpentry.org/v5/js/jquery-1.9.1.min.js"></script>
<script src="css/bootstrap/bootstrap-js/bootstrap.js"></script>
<script src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></script>
<script>
(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-37305346-2', 'auto');
ga('send', 'pageview');
</script>
</body>
</html>