Build(deps): Update numpy requirement from ^1.26.3 to ^2.0.0 (#163)

Updates the requirements on [numpy](https://github.com/numpy/numpy) to
permit the latest version.
<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>v2.0.0</h2>
<h1>NumPy 2.0.0 Release Notes</h1>
<p>NumPy 2.0.0 is the first major release since 2006. It is the result
of
11 months of development since the last feature release and is the work
of 212 contributors spread over 1078 pull requests. It contains a large
number of exciting new features as well as changes to both the Python
and C APIs.</p>
<p>This major release includes breaking changes that could not happen in
a
regular minor (feature) release - including an ABI break, changes to
type promotion rules, and API changes which may not have been emitting
deprecation warnings in 1.26.x. Key documents related to how to adapt to
changes in NumPy 2.0, in addition to these release notes, include:</p>
<ul>
<li>The <a
href="https://numpy.org/devdocs/numpy_2_0_migration_guide.html">numpy-2-migration-guide</a></li>
<li>The Numpy 2.0-specific advice in <a
href="https://numpy.org/devdocs/dev/depending_on_numpy.html">for
dpwmstream package authors</a></li>
</ul>
<h2>Highlights</h2>
<p>Highlights of this release include:</p>
<ul>
<li>New features:
<ul>
<li>A new variable-length string dtype,
<code>numpy.dtypes.StringDType</code> and a new
<code>numpy.strings</code> namespace with performant ufuncs for string
operations,</li>
<li>Support for <code>float32</code> and <code>longdouble</code> in all
<code>numpy.fft</code> functions,</li>
<li>Support for the array API standard in the main <code>numpy</code>
namespace.</li>
</ul>
</li>
<li>Performance improvements:
<ul>
<li>Sorting functions <code>sort</code>, <code>argsort</code>,
<code>partition</code>, <code>argpartition</code> have been
accelerated through the use of the Intel x86-simd-sort and
Google Highway libraries, and may see large (hardware-specific)
speedups,</li>
<li>macOS Accelerate support and binary wheels for macOS &gt;=14, with
significant performance improvements for linear algebra
operations on macOS, and wheels that are about 3 times smaller,</li>
<li><code>numpy.char</code> fixed-length string operations have
been accelerated by implementing ufuncs that also support
<code>numpy.dtypes.StringDType</code> in addition to the
fixed-length string dtypes,</li>
<li>A new tracing and introspection API,
<code>numpy.lib.introspect.opt_func_info</code>, to determine
which hardware-specific kernels are available and will be
dispatched to.</li>
<li><code>numpy.save</code> now uses pickle protocol version 4 for
saving
arrays with object dtype, which allows for pickle objects larger
than 4GB and improves saving speed by about 5% for large arrays.</li>
</ul>
</li>
<li>Python API improvements:</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="https://github.com/numpy/numpy/commit/1d49c7f7ff527c696fc26ab2278ad51632a66660"><code>1d49c7f</code></a>
Merge pull request <a
href="https://redirect.github.com/numpy/numpy/issues/26698">#26698</a>
from charris/prepare-2.0.0</li>
<li><a
href="https://github.com/numpy/numpy/commit/2103511c0fa1b336f38d43920e3eb5440af9ea15"><code>2103511</code></a>
DOC: Remove duplicate in author list.</li>
<li><a
href="https://github.com/numpy/numpy/commit/db8030e9bb082466f89714c9a97c87f99dabb60d"><code>db8030e</code></a>
BUG: Change cibuildwheel version [wheel build]</li>
<li><a
href="https://github.com/numpy/numpy/commit/1a68264bb5f6859fc85c985984fc682034320503"><code>1a68264</code></a>
REL: Prepare for the NumPy 2.0.0 release [wheel build]</li>
<li><a
href="https://github.com/numpy/numpy/commit/c8665baa495d13e40eee0d39db841b0cbfde04a1"><code>c8665ba</code></a>
Merge pull request <a
href="https://redirect.github.com/numpy/numpy/issues/26696">#26696</a>
from charris/backport-26582</li>
<li><a
href="https://github.com/numpy/numpy/commit/103f4dd40725bcf610b3ff19a324e1ca099a47c4"><code>103f4dd</code></a>
Merge pull request <a
href="https://redirect.github.com/numpy/numpy/issues/26697">#26697</a>
from charris/backport-25963</li>
<li><a
href="https://github.com/numpy/numpy/commit/c193dcd1dcd01989088475349e1b717d2b82b07b"><code>c193dcd</code></a>
Merge pull request <a
href="https://redirect.github.com/numpy/numpy/issues/26695">#26695</a>
from charris/backport-26667</li>
<li><a
href="https://github.com/numpy/numpy/commit/8fa81913477d19c78b5f8660830615b31a95a7de"><code>8fa8191</code></a>
BUG: Fix bug in numpy.pad() (<a
href="https://redirect.github.com/numpy/numpy/issues/25963">#25963</a>)</li>
<li><a
href="https://github.com/numpy/numpy/commit/ece3559d4c0b9fc22c2d272d07cef1d62b4b65b2"><code>ece3559</code></a>
BUG: weighted nanpercentile, nanquantile and multi-dim q (<a
href="https://redirect.github.com/numpy/numpy/issues/26582">#26582</a>)</li>
<li><a
href="https://github.com/numpy/numpy/commit/b31e19550fbb374efc6246e2f114124eee6a3714"><code>b31e195</code></a>
BUG: Adds asanyarray to start of linalg.cross (<a
href="https://redirect.github.com/numpy/numpy/issues/26667">#26667</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/numpy/numpy/compare/v1.26.3...v2.0.0">compare
view</a></li>
</ul>
</details>
<br />


Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.

[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)

---

<details>
<summary>Dependabot commands and options</summary>
<br />

You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)


</details>

pyproject.toml

@@ -57,7 +57,7 @@ classifiers = [
 python = "^3.10,<3.12"
 arcade = "^3.0.0.dev25"
 # grpcio = "^1.60.0"
-numpy = "^1.26.3"
+numpy = "^2.0.0"
 shapely = "^2.0.2"
 torch = "^2.1.2"
 # tensorflow = "~2.11.0"  # Last known version with Windows support