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<section id="numpy-benchmarks">
<h1>NumPy benchmarks<a class="headerlink" href="#numpy-benchmarks" title="Link to this heading">#</a></h1>
<p>Benchmarking NumPy with Airspeed Velocity.</p>
<section id="usage">
<h2>Usage<a class="headerlink" href="#usage" title="Link to this heading">#</a></h2>
<p>Airspeed Velocity manages building and Python virtualenvs by itself,
unless told otherwise. To run the benchmarks, you do not need to install a
development version of NumPy to your current Python environment.</p>
<p>Before beginning, ensure that <em>airspeed velocity</em> is installed.
By default, <em class="xref py py-obj">asv</em> ships with support for anaconda and virtualenv:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">asv</span>
<span class="n">pip</span> <span class="n">install</span> <span class="n">virtualenv</span>
</pre></div>
</div>
<p>After contributing new benchmarks, you should test them locally before
submitting a pull request.</p>
<p>To run all benchmarks, navigate to the root NumPy directory at
the command line and execute:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">spin</span> <span class="n">bench</span>
</pre></div>
</div>
<p>This builds NumPy and runs all available benchmarks
defined in <code class="docutils literal notranslate"><span class="pre">benchmarks/</span></code>. (Note: this could take a while. Each
benchmark is run multiple times to measure the distribution in
execution times.)</p>
<p>For <strong>testing</strong> benchmarks locally, it may be better to run these without
replications:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>cd benchmarks/
export REGEXP="bench.*Ufunc"
asv run --dry-run --show-stderr --python=same --quick -b $REGEXP
</pre></div>
</div>
<p>Where the regular expression used to match benchmarks is stored in <code class="docutils literal notranslate"><span class="pre">$REGEXP</span></code>,
and <em class="xref py py-obj">–quick</em> is used to avoid repetitions.</p>
<p>To run benchmarks from a particular benchmark module, such as
<code class="docutils literal notranslate"><span class="pre">bench_core.py</span></code>, simply append the filename without the extension:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">spin</span> <span class="n">bench</span> <span class="o">-</span><span class="n">t</span> <span class="n">bench_core</span>
</pre></div>
</div>
<p>To run a benchmark defined in a class, such as <code class="docutils literal notranslate"><span class="pre">MeshGrid</span></code>
from <code class="docutils literal notranslate"><span class="pre">bench_creation.py</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">spin</span> <span class="n">bench</span> <span class="o">-</span><span class="n">t</span> <span class="n">bench_creation</span><span class="o">.</span><span class="n">MeshGrid</span>
</pre></div>
</div>
<p>Compare changes in benchmark results to another version/commit/branch, use the
<code class="docutils literal notranslate"><span class="pre">--compare</span></code> option (or the equivalent <code class="docutils literal notranslate"><span class="pre">-c</span></code>):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">spin</span> <span class="n">bench</span> <span class="o">--</span><span class="n">compare</span> <span class="n">v1</span><span class="mf">.6.2</span> <span class="o">-</span><span class="n">t</span> <span class="n">bench_core</span>
<span class="n">spin</span> <span class="n">bench</span> <span class="o">--</span><span class="n">compare</span> <span class="mi">20</span><span class="n">d03bcfd</span> <span class="o">-</span><span class="n">t</span> <span class="n">bench_core</span>
<span class="n">spin</span> <span class="n">bench</span> <span class="o">-</span><span class="n">c</span> <span class="n">main</span> <span class="o">-</span><span class="n">t</span> <span class="n">bench_core</span>
</pre></div>
</div>
<p>All of the commands above display the results in plain text in
the console, and the results are not saved for comparison with
future commits. For greater control, a graphical view, and to
have results saved for future comparison you can run ASV commands
(record results and generate HTML):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">cd</span> <span class="n">benchmarks</span>
<span class="n">asv</span> <span class="n">run</span> <span class="o">-</span><span class="n">n</span> <span class="o">-</span><span class="n">e</span> <span class="o">--</span><span class="n">python</span><span class="o">=</span><span class="n">same</span>
<span class="n">asv</span> <span class="n">publish</span>
<span class="n">asv</span> <span class="n">preview</span>
</pre></div>
</div>
<p>More on how to use <code class="docutils literal notranslate"><span class="pre">asv</span></code> can be found in <a class="reference external" href="https://asv.readthedocs.io/">ASV documentation</a>
Command-line help is available as usual via <code class="docutils literal notranslate"><span class="pre">asv</span> <span class="pre">--help</span></code> and
<code class="docutils literal notranslate"><span class="pre">asv</span> <span class="pre">run</span> <span class="pre">--help</span></code>.</p>
</section>
<section id="benchmarking-versions">
<h2>Benchmarking versions<a class="headerlink" href="#benchmarking-versions" title="Link to this heading">#</a></h2>
<p>To benchmark or visualize only releases on different machines locally, the tags with their commits can be generated, before being run with <code class="docutils literal notranslate"><span class="pre">asv</span></code>, that is:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>cd benchmarks
# Get commits for tags
# delete tag_commits.txt before re-runs
for gtag in $(git tag --list --sort taggerdate | grep "^v"); do
git log $gtag --oneline -n1 --decorate=no | awk '{print $1;}' >> tag_commits.txt
done
# Use the last 20
tail --lines=20 tag_commits.txt > 20_vers.txt
asv run HASHFILE:20_vers.txt
# Publish and view
asv publish
asv preview
</pre></div>
</div>
<p>For details on contributing these, see the <a class="reference external" href="https://github.com/HaoZeke/asv-numpy">benchmark results repository</a>.</p>
</section>
<section id="writing-benchmarks">
<h2>Writing benchmarks<a class="headerlink" href="#writing-benchmarks" title="Link to this heading">#</a></h2>
<p>See <a class="reference external" href="https://asv.readthedocs.io/">ASV documentation</a> for basics on how to write benchmarks.</p>
<p>Some things to consider:</p>
<ul class="simple">
<li><p>The benchmark suite should be importable with any NumPy version.</p></li>
<li><p>The benchmark parameters etc. should not depend on which NumPy version
is installed.</p></li>
<li><p>Try to keep the runtime of the benchmark reasonable.</p></li>
<li><p>Prefer ASV’s <code class="docutils literal notranslate"><span class="pre">time_</span></code> methods for benchmarking times rather than cooking up
time measurements via <code class="docutils literal notranslate"><span class="pre">time.clock</span></code>, even if it requires some juggling when
writing the benchmark.</p></li>
<li><p>Preparing arrays etc. should generally be put in the <code class="docutils literal notranslate"><span class="pre">setup</span></code> method rather
than the <code class="docutils literal notranslate"><span class="pre">time_</span></code> methods, to avoid counting preparation time together with
the time of the benchmarked operation.</p></li>
<li><p>Be mindful that large arrays created with <code class="docutils literal notranslate"><span class="pre">np.empty</span></code> or <code class="docutils literal notranslate"><span class="pre">np.zeros</span></code> might
not be allocated in physical memory until the memory is accessed. If this is
desired behaviour, make sure to comment it in your setup function. If
you are benchmarking an algorithm, it is unlikely that a user will be
executing said algorithm on a newly created empty/zero array. One can force
pagefaults to occur in the setup phase either by calling <code class="docutils literal notranslate"><span class="pre">np.ones</span></code> or
<code class="docutils literal notranslate"><span class="pre">arr.fill(value)</span></code> after creating the array.</p></li>
</ul>
</section>
</section>
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