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<div class="title">RAND Uniform Random Number Generator </div> </div>
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<div class="textblock"><p>Section: <a class="el" href="sec_random.html">Random Number Generation</a> </p>
<h1><a class="anchor" id="Usage"></a>
Usage</h1>
<p>Creates an array of pseudo-random numbers of the specified size. The numbers are uniformly distributed on <code>[0,1)</code>. Two seperate syntaxes are possible. The first syntax specifies the array dimensions as a sequence of scalar dimensions: </p>
<pre class="fragment"> y = rand(d1,d2,...,dn).
</pre><p> The resulting array has the given dimensions, and is filled with random numbers. The type of <code>y</code> is <code>double</code>, a 64-bit floating point array. To get arrays of other types, use the typecast functions.</p>
<p>The second syntax specifies the array dimensions as a vector, where each element in the vector specifies a dimension length: </p>
<pre class="fragment"> y = rand([d1,d2,...,dn]).
</pre><p> This syntax is more convenient for calling <code>rand</code> using a variable for the argument.</p>
<p>Finally, <code>rand</code> supports two additional forms that allow you to manipulate the state of the random number generator. The first retrieves the state </p>
<pre class="fragment"> y = rand('state')
</pre><p> which is a 625 length integer vector. The second form sets the state </p>
<pre class="fragment"> rand('state',y)
</pre><p> or alternately, you can reset the random number generator with </p>
<pre class="fragment"> rand('state',0)
</pre> <h1><a class="anchor" id="Example"></a>
Example</h1>
<p>The following example demonstrates an example of using the first form of the <code>rand</code> function.</p>
<pre class="fragment">--> rand(2,2,2)
ans =
(:,:,1) =
0.8539 0.1733
0.0415 0.1300
(:,:,2) =
0.7163 0.5752
0.5953 0.3728
</pre><p>The second example demonstrates the second form of the <code>rand</code> function.</p>
<pre class="fragment">--> rand([2,2,2])
ans =
(:,:,1) =
0.4992 0.2797
0.6513 0.3209
(:,:,2) =
0.6244 0.7774
0.0934 0.1820
</pre><p>The third example computes the mean and variance of a large number of uniform random numbers. Recall that the mean should be <code>1/2</code>, and the variance should be <code>1/12 ~ 0.083</code>.</p>
<pre class="fragment">--> x = rand(1,10000);
--> mean(x)
ans =
0.4952
--> var(x)
ans =
0.0845
</pre><p>Now, we use the state manipulation functions of <code>rand</code> to exactly reproduce a random sequence. Note that unlike using <code>seed</code>, we can exactly control where the random number generator starts by saving the state.</p>
<pre class="fragment">--> rand('state',0) % restores us to startup conditions
--> a = rand(1,3) % random sequence 1
a =
0.3759 0.0183 0.9134
--> b = rand('state'); % capture the state vector
--> c = rand(1,3) % random sequence 2
c =
0.3580 0.7604 0.8077
--> rand('state',b); % restart the random generator so...
--> c = rand(1,3) % we get random sequence 2 again
c =
0.3580 0.7604 0.8077
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