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<title>Policies Have Sensible Defaults</title>
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<div class="titlepage"><div><div><h3 class="title">
<a name="math_toolkit.pol_tutorial.policy_tut_defaults"></a><a class="link" href="policy_tut_defaults.html" title="Policies Have Sensible Defaults">Policies
Have Sensible Defaults</a>
</h3></div></div></div>
<p>
Most of the time you can just ignore the policy framework.
</p>
<p>
<span class="emphasis"><em>*The defaults for the various policies are as follows, if these
work OK for you then you can stop reading now!</em></span>
</p>
<div class="variablelist">
<p class="title"><b></b></p>
<dl class="variablelist">
<dt><span class="term">Domain Error</span></dt>
<dd><p>
Throws a <code class="computeroutput"><span class="identifier">std</span><span class="special">::</span><span class="identifier">domain_error</span></code> exception.
</p></dd>
<dt><span class="term">Pole Error</span></dt>
<dd><p>
Occurs when a function is evaluated at a pole: throws a <code class="computeroutput"><span class="identifier">std</span><span class="special">::</span><span class="identifier">domain_error</span></code> exception.
</p></dd>
<dt><span class="term">Overflow Error</span></dt>
<dd><p>
Throws a <code class="computeroutput"><span class="identifier">std</span><span class="special">::</span><span class="identifier">overflow_error</span></code> exception.
</p></dd>
<dt><span class="term">Underflow</span></dt>
<dd><p>
Ignores the underflow, and returns zero.
</p></dd>
<dt><span class="term">Denormalised Result</span></dt>
<dd><p>
Ignores the fact that the result is denormalised, and returns it.
</p></dd>
<dt><span class="term">Rounding Error</span></dt>
<dd><p>
Throws a <code class="computeroutput"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">rounding_error</span></code> exception.
</p></dd>
<dt><span class="term">Internal Evaluation Error</span></dt>
<dd><p>
Throws a <code class="computeroutput"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">evaluation_error</span></code> exception.
</p></dd>
<dt><span class="term">Indeterminate Result Error</span></dt>
<dd><p>
Returns a result that depends on the function where the error occurred.
</p></dd>
<dt><span class="term">Promotion of float to double</span></dt>
<dd><p>
Does occur by default - gives full float precision results.
</p></dd>
<dt><span class="term">Promotion of double to long double</span></dt>
<dd><p>
Does occur by default if long double offers more precision than double.
</p></dd>
<dt><span class="term">Precision of Approximation Used</span></dt>
<dd><p>
By default uses an approximation that will result in the lowest level
of error for the type of the result.
</p></dd>
<dt><span class="term">Behaviour of Discrete Quantiles</span></dt>
<dd>
<p>
The quantile function will by default return an integer result that
has been <span class="emphasis"><em>rounded outwards</em></span>. That is to say lower
quantiles (where the probability is less than 0.5) are rounded downward,
and upper quantiles (where the probability is greater than 0.5) are
rounded upwards. This behaviour ensures that if an X% quantile is requested,
then <span class="emphasis"><em>at least</em></span> the requested coverage will be present
in the central region, and <span class="emphasis"><em>no more than</em></span> the requested
coverage will be present in the tails.
</p>
<p>
This behaviour can be changed so that the quantile functions are rounded
differently, or even return a real-valued result using <a class="link" href="../pol_overview.html" title="Policy Overview">Policies</a>.
It is strongly recommended that you read the tutorial <a class="link" href="understand_dis_quant.html" title="Understanding Quantiles of Discrete Distributions">Understanding
Quantiles of Discrete Distributions</a> before using the quantile
function on a discrete distribution. The <a class="link" href="../pol_ref/discrete_quant_ref.html" title="Discrete Quantile Policies">reference
docs</a> describe how to change the rounding policy for these distributions.
</p>
</dd>
</dl>
</div>
<p>
What's more, if you define your own policy type, then it automatically inherits
the defaults for any policies not explicitly set, so given:
</p>
<pre class="programlisting"><span class="keyword">using</span> <span class="keyword">namespace</span> <span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">policies</span><span class="special">;</span>
<span class="comment">//</span>
<span class="comment">// Define a policy that sets ::errno on overflow, and does</span>
<span class="comment">// not promote double to long double internally:</span>
<span class="comment">//</span>
<span class="keyword">typedef</span> <span class="identifier">policy</span><span class="special"><</span><span class="identifier">domain_error</span><span class="special"><</span><span class="identifier">errno_on_error</span><span class="special">>,</span> <span class="identifier">promote_double</span><span class="special"><</span><span class="keyword">false</span><span class="special">></span> <span class="special">></span> <span class="identifier">mypolicy</span><span class="special">;</span>
</pre>
<p>
then <code class="computeroutput"><span class="identifier">mypolicy</span></code> defines a policy
where only the overflow error handling and <code class="computeroutput"><span class="keyword">double</span></code>-promotion
policies differ from the defaults.
</p>
</div>
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<td align="right"><div class="copyright-footer">Copyright © 2006-2010, 2012-2014 Nikhar Agrawal,
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Holin, Bruno Lalande, John Maddock, Johan Råde, Gautam Sewani, Benjamin Sobotta,
Thijs van den Berg, Daryle Walker and Xiaogang Zhang<p>
Distributed under the Boost Software License, Version 1.0. (See accompanying
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