Bump numpy from 2.1.2 to 2.1.3 (#117)

Bumps [numpy](https://github.com/numpy/numpy) from 2.1.2 to 2.1.3.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/numpy/numpy/releases">numpy's releases</a>.</em></p>
<blockquote>
<h2>2.1.3 (Nov 2, 2024)</h2>
<h1>NumPy 2.1.3 Release Notes</h1>
<p>NumPy 2.1.3 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.2 release. This release also adds support
for free threaded Python 3.13 on Windows.</p>
<p>The Python versions supported by this release are 3.10-3.13.</p>
<h2>Improvements</h2>
<ul>
<li>
<p>Fixed a number of issues around promotion for string ufuncs with
StringDType arguments. Mixing StringDType and the fixed-width DTypes
using the string ufuncs should now generate much more uniform
results.</p>
<p>(<a href="https://redirect.github.com/numpy/numpy/pull/27636">gh-27636</a>)</p>
</li>
</ul>
<h2>Changes</h2>
<ul>
<li>
<p><code>numpy.fix</code> now won't perform casting to a floating
data-type for integer and boolean data-type input arrays.</p>
<p>(<a href="https://redirect.github.com/numpy/numpy/pull/26766">gh-26766</a>)</p>
</li>
</ul>
<h2>Contributors</h2>
<p>A total of 15 people contributed to this release. People with a &quot;+&quot; by
their names contributed a patch for the first time.</p>
<ul>
<li>Abhishek Kumar +</li>
<li>Austin +</li>
<li>Benjamin A. Beasley +</li>
<li>Charles Harris</li>
<li>Christian Lorentzen</li>
<li>Marcel Telka +</li>
<li>Matti Picus</li>
<li>Michael Davidsaver +</li>
<li>Nathan Goldbaum</li>
<li>Peter Hawkins</li>
<li>Raghuveer Devulapalli</li>
<li>Ralf Gommers</li>
<li>Sebastian Berg</li>
<li>dependabot[bot]</li>
<li>kp2pml30 +</li>
</ul>
<h2>Pull requests merged</h2>
<p>A total of 21 pull requests were merged for this release.</p>
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</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a href="https://github.com/numpy/numpy/commit/98464cc0cbc1f211482a0756ded305bed1599f18"><code>98464cc</code></a> Merge pull request <a href="https://redirect.github.com/numpy/numpy/issues/27690">#27690</a> from charris/prepare-2.1.3</li>
<li><a href="https://github.com/numpy/numpy/commit/cbda85b3551910a8e0d80b89c727b62d66aec20f"><code>cbda85b</code></a> REL: Prepare for the NumPy 2.1.3 release [wheel build]</li>
<li><a href="https://github.com/numpy/numpy/commit/daa8699a4145299ea8ff850b94de31c1c208cb65"><code>daa8699</code></a> Merge pull request <a href="https://redirect.github.com/numpy/numpy/issues/27672">#27672</a> from charris/backport-27666</li>
<li><a href="https://github.com/numpy/numpy/commit/614ca19a3ae5469ed2b19cf1ebbc22ba81606b7d"><code>614ca19</code></a> Merge pull request <a href="https://redirect.github.com/numpy/numpy/issues/27673">#27673</a> from charris/backport-27636</li>
<li><a href="https://github.com/numpy/numpy/commit/e6b02d7ba6d8a34b169113f9874d015ef875d67e"><code>e6b02d7</code></a> DOC: add release note</li>
<li><a href="https://github.com/numpy/numpy/commit/54fd7291022e8e8c0cc80d651ebf7afd4dd152b3"><code>54fd729</code></a> BUG: substantially simplify and fix issue with justification promoter</li>
<li><a href="https://github.com/numpy/numpy/commit/a90fe7cc6e52be410321b5fffe4e85e76acedb0a"><code>a90fe7c</code></a> BUG: fix more issues with string ufunc promotion</li>
<li><a href="https://github.com/numpy/numpy/commit/a121864b22b6fe5da2d2ae8924b58a31d1b67bf0"><code>a121864</code></a> BUG: fixes for StringDType/unicode promoters</li>
<li><a href="https://github.com/numpy/numpy/commit/f055fb97531bd89ab0d97f3a5a9f6a11dab4b6ec"><code>f055fb9</code></a> BUG: Fix a reference count leak in npy_find_descr_for_scalar.</li>
<li><a href="https://github.com/numpy/numpy/commit/5895c021934b3321dd9abb6be979bf6d2abbc8a4"><code>5895c02</code></a> Merge pull request <a href="https://redirect.github.com/numpy/numpy/issues/27669">#27669</a> from charris/backport-27663</li>
<li>Additional commits viewable in <a href="https://github.com/numpy/numpy/compare/v2.1.2...v2.1.3">compare view</a></li>
</ul>
</details>
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</details>

requirements.txt

@@ -1,5 +1,5 @@
 networkx==3.4.2
-numpy==2.1.2
+numpy==2.1.3
 pandas==2.2.3
 scikit-learn==1.5.2
 scipy==1.14.1