Bump scipy from 1.11.4 to 1.12.0 (#95)

Bumps [scipy](https://github.com/scipy/scipy) from 1.11.4 to 1.12.0.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/scipy/scipy/releases">scipy's releases</a>.</em></p>
<blockquote>
<h1>SciPy 1.12.0 Release Notes</h1>
<p>SciPy <code>1.12.0</code> is the culmination of <code>6</code> months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with <code>python -Wd</code> and check for <code>DeprecationWarning</code> s).
Our development attention will now shift to bug-fix releases on the
1.12.x branch, and on adding new features on the main branch.</p>
<p>This release requires Python <code>3.9+</code> and NumPy <code>1.22.4</code> or greater.</p>
<p>For running on PyPy, PyPy3 <code>6.0+</code> is required.</p>
<h1>Highlights of this release</h1>
<ul>
<li>Experimental support for the array API standard has been added to part of
<code>scipy.special</code>, and to all of <code>scipy.fft</code> and <code>scipy.cluster</code>. There are
likely to be bugs and early feedback for usage with CuPy arrays, PyTorch
tensors, and other array API compatible libraries is appreciated. Use the
<code>SCIPY_ARRAY_API</code> environment variable for testing.</li>
<li>A new class, <code>ShortTimeFFT</code>, provides a more versatile implementation of the
short-time Fourier transform (STFT), its inverse (ISTFT) as well as the (cross-)
spectrogram. It utilizes an improved algorithm for calculating the ISTFT.</li>
<li>Several new constructors have been added for sparse arrays, and many operations
now additionally support sparse arrays, further facilitating the migration
from sparse matrices.</li>
<li>A large portion of the <code>scipy.stats</code> API now has improved support for handling
<code>NaN</code> values, masked arrays, and more fine-grained shape-handling. The
accuracy and performance of a number of <code>stats</code> methods have been improved,
and a number of new statistical tests and distributions have been added.</li>
</ul>
<h1>New features</h1>
<h1><code>scipy.cluster</code> improvements</h1>
<ul>
<li>Experimental support added for the array API standard; PyTorch tensors,
CuPy arrays and array API compatible array libraries are now accepted
(GPU support is limited to functions with pure Python implementations).
CPU arrays which can be converted to and from NumPy are supported
module-wide and returned arrays will match the input type.
This behaviour is enabled by setting the <code>SCIPY_ARRAY_API</code> environment
variable before importing <code>scipy</code>. This experimental support is still
under development and likely to contain bugs - testing is very welcome.</li>
</ul>
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</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a href="https://github.com/scipy/scipy/commit/4edfcaa3ce8a387450b6efce968572def71be089"><code>4edfcaa</code></a> REL: SciPy 1.12.0 release commit [wheel build]</li>
<li><a href="https://github.com/scipy/scipy/commit/e3cff26bd50498225023798d14573d129307b12a"><code>e3cff26</code></a> Merge pull request <a href="https://redirect.github.com/scipy/scipy/issues/19922">#19922</a> from tylerjereddy/treddy_1_12_0_final_prep</li>
<li><a href="https://github.com/scipy/scipy/commit/bf025825bc797f8ec6e06732b127467311334665"><code>bf02582</code></a> DOC: PR 19922 revisions [wheel build]</li>
<li><a href="https://github.com/scipy/scipy/commit/41ed3d6d8a4d0858c4605b978d6f08cd29b3e3b4"><code>41ed3d6</code></a> Revert &quot;ENH: stats.wasserstein_distance: multivariate Wasserstein distance/EM...</li>
<li><a href="https://github.com/scipy/scipy/commit/db2cb8c3bdc6b12150317772fb44081a22d8cab2"><code>db2cb8c</code></a> DOC: update 1.12.0 relnotes</li>
<li><a href="https://github.com/scipy/scipy/commit/c76bedfcf58aba43dfbd4190f74f37cdaa43b052"><code>c76bedf</code></a> BLD: ensure the name of the installed <code>scipy</code> package is lower-case</li>
<li><a href="https://github.com/scipy/scipy/commit/aedbb2ba3d8899ff37626c0bfd35e494b41e41ba"><code>aedbb2b</code></a> DEP: reflect extended deprecations also in release notes (<a href="https://redirect.github.com/scipy/scipy/issues/19903">#19903</a>)</li>
<li><a href="https://github.com/scipy/scipy/commit/0b4c8dc42d13dde861fb9c073faabe69cce250b4"><code>0b4c8dc</code></a> DEP: extend some announced deprecations due to out-of-band 1.13 release (<a href="https://redirect.github.com/scipy/scipy/issues/19892">#19892</a>)</li>
<li><a href="https://github.com/scipy/scipy/commit/82dddc5b829e4f9131bc30b98cbab52542a9f3f0"><code>82dddc5</code></a> DOC: 1.12 release notes tweaks (<a href="https://redirect.github.com/scipy/scipy/issues/19877">#19877</a>)</li>
<li><a href="https://github.com/scipy/scipy/commit/e22a5ffce5b89422d276d2318ef3b9cbf03a46e3"><code>e22a5ff</code></a> REL: 1.12.0 final unreleased</li>
<li>Additional commits viewable in <a href="https://github.com/scipy/scipy/compare/v1.11.4...v1.12.0">compare view</a></li>
</ul>
</details>
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</details>

requirements.txt

@@ -2,6 +2,6 @@ networkx==3.2.1
 numpy==1.26.3
 pandas==2.2.0
 scikit-learn==1.4.0
-scipy==1.11.4
+scipy==1.12.0
 seaborn==0.13.1
 geneticalgorithm==1.0.2