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<!DOCTYPE html>
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<article class="h-entry post-text" itemscope="itemscope" itemtype="http://schema.org/Article"><header><h1 class="p-name entry-title"><a href="blog/untitled/" class="u-url">Test notebook</a></h1>
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<p class="byline author vcard"><span class="byline-name fn" itemprop="author">
Sergey B Kirpichev
</span></p>
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<a href="blog/untitled/" rel="bookmark">
<time class="published dt-published" datetime="2019-02-22T13:22:30+03:00" itemprop="datePublished" title="2019-02-22 13:22">2019-02-22 13:22</time></a>
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<p>Write your post here.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">diofant</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">diofant.abc</span> <span class="k">import</span> <span class="n">x</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">p</span> <span class="o">=</span> <span class="n">x</span><span class="o">**</span><span class="mi">7</span> <span class="o">+</span> <span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">*</span><span class="n">x</span> <span class="o">-</span> <span class="n">I</span>
<span class="n">r1</span> <span class="o">=</span> <span class="n">RootOf</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">r1</span><span class="o">.</span><span class="n">is_real</span>
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\begin{equation}\mathrm{False}\end{equation}
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">r1</span><span class="o">.</span><span class="n">is_imaginary</span>
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\begin{equation}\mathrm{False}\end{equation}
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<p>... it's a complex number</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">r1</span><span class="o">.</span><span class="n">evalf</span><span class="p">()</span>
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\begin{equation}-0.938939892790381 - 0.622375271319501 i\end{equation}
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">nroots</span><span class="p">(</span><span class="n">p</span><span class="p">)</span>
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\begin{equation}\left [ -0.966114667772369 + 0.416533257705247 i, \quad -0.938939892790381 - 0.622375271319501 i, \quad -0.111375557241875 + 0.779695119900266 i, \quad - 1.14770621257202 i, \quad 0.111375557241875 + 0.779695119900266 i, \quad 0.938939892790381 - 0.622375271319501 i, \quad 0.966114667772369 + 0.416533257705247 i\right ]\end{equation}
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">str</span><span class="p">(</span><span class="n">_5</span><span class="p">)</span> <span class="ow">in</span> <span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">_</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="n">_6</span><span class="p">]</span>
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\begin{equation}\mathrm{True}\end{equation}
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<p>Now some plots</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span><span class="k">matplotlib</span> inline
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plot</span><span class="p">(</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">/</span><span class="n">x</span><span class="p">,</span> <span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="o">*</span><span class="n">pi</span><span class="p">))</span>
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<pre>/usr/lib/python3/dist-packages/numpy/__init__.py:1: RuntimeWarning: invalid value encountered in double_scalars
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">
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<div class="output_area">
<div class="prompt output_prompt">Out[9]:</div>
<div class="output_text output_subarea output_execute_result">
<pre><diofant.plotting.plot.Plot at 0x7fa1d7d2cac8></pre>
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<div class="prompt input_prompt">In [ ]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span>
</pre></div>
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</article><article class="h-entry post-text" itemscope="itemscope" itemtype="http://schema.org/Article"><header><h1 class="p-name entry-title"><a href="posts/test-post/" class="u-url">Test post</a></h1>
<div class="metadata">
<p class="byline author vcard"><span class="byline-name fn" itemprop="author">
Sergey B Kirpichev
</span></p>
<p class="dateline">
<a href="posts/test-post/" rel="bookmark">
<time class="published dt-published" datetime="2015-01-20T17:50:51+03:00" itemprop="datePublished" title="2015-01-20 17:50">2015-01-20 17:50</time></a>
</p>
<p class="commentline">
</p>
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</header><div class="e-content entry-content">
<div>
<p>Write your post here.</p>
<p>Some list:</p>
<ul class="simple">
<li>one</li>
<li>two</li>
<li><span class="math">\(\lim\limits_{n\to\infty} \left(1 + \frac{1}{n}\right)^n = e\)</span></li>
<li><span class="math">\(e^{ix} = \cos x + i\sin x\)</span></li>
<li>xxx</li>
</ul>
</div>
</div>
</article>
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