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mhostetter · Sep 6, 2024 · cc67fca · cc67fca
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diff --git a/v0.0.x/.doctrees/api/sdr.bec.doctree b/v0.0.x/.doctrees/api/sdr.bec.doctree
diff --git a/v0.0.x/.doctrees/api/sdr.bsc.doctree b/v0.0.x/.doctrees/api/sdr.bsc.doctree
diff --git a/v0.0.x/.doctrees/api/sdr.dmc.doctree b/v0.0.x/.doctrees/api/sdr.dmc.doctree
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diff --git a/v0.0.x/.doctrees/environment.pickle b/v0.0.x/.doctrees/environment.pickle
diff --git a/v0.0.x/.doctrees/release-notes/v0.0.doctree b/v0.0.x/.doctrees/release-notes/v0.0.doctree
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diff --git a/v0.0.x/_sources/release-notes/v0.0.md.txt b/v0.0.x/_sources/release-notes/v0.0.md.txt
@@ -4,6 +4,18 @@ tocdepth: 2
 
 # v0.0
 
+## v0.0.24
+
+*Released September 5, 2024*
+
+### Changes
+
+- Added support for NumPy 2.1.
+
+### Contributors
+
+- Matt Hostetter ([@mhostetter](https://github.com/mhostetter))
+
 ## v0.0.23
 
 *Released July 28, 2024*

diff --git a/v0.0.x/api/detection/index.html b/v0.0.x/api/detection/index.html
@@ -14479,13 +14479,13 @@ <h2 id="detectors">Detectors<a class="headerlink" href="#detectors" title="Link
 <h2 id="theoretical-performance">Theoretical performance<a class="headerlink" href="#theoretical-performance" title="Link to this heading">¶</a></h2>
 <dl class="py function summary objdesc">
 <dt class="sig sig-object highlight py">
-<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.h0/" title="sdr.h0 (Python function) — Computes the statistical distribution under the null hypothesis $mathcal{H}_0$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">h0</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h0/#p-sigma2" title="sdr.h0.sigma2 (Python parameter) — The noise variance $sigma^2$ in linear units."><span class="n"><span class="pre">sigma2</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><code class="code python default_value docutils literal highlight highlight-python"><span class="mf">1.0</span></code></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><a class="reference external" href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.html#scipy.stats.rv_continuous" title="(in SciPy v1.14.0)"><span class="pre">rv_continuous</span></a></span></span></span></dt>
+<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.h0/" title="sdr.h0 (Python function) — Computes the statistical distribution under the null hypothesis $mathcal{H}_0$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">h0</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h0/#p-sigma2" title="sdr.h0.sigma2 (Python parameter) — The noise variance $sigma^2$ in linear units."><span class="n"><span class="pre">sigma2</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><code class="code python default_value docutils literal highlight highlight-python"><span class="mf">1.0</span></code></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><a class="reference external" href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.html#scipy.stats.rv_continuous" title="(in SciPy v1.14.1)"><span class="pre">rv_continuous</span></a></span></span></span></dt>
 <dd><p>Computes the statistical distribution under the null hypothesis <span class="math notranslate nohighlight">\(\mathcal{H}_0\)</span>.</p>
 </dd></dl>
 
 <dl class="py function summary objdesc">
 <dt class="sig sig-object highlight py">
-<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.h1/" title="sdr.h1 (Python function) — Computes the statistical distribution under the alternative hypothesis $mathcal{H}_1$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">h1</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h1/#p-snr" title="sdr.h1.snr (Python parameter) — The signal-to-noise ratio $S / sigma^2$ in dB."><span class="n"><span class="pre">snr</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span></em>, </span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h1/#p-sigma2" title="sdr.h1.sigma2 (Python parameter) — The noise variance $sigma^2$ in linear units."><span class="n"><span class="pre">sigma2</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><code class="code python default_value docutils literal highlight highlight-python"><span class="mf">1.0</span></code></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><a class="reference external" href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.html#scipy.stats.rv_continuous" title="(in SciPy v1.14.0)"><span class="pre">rv_continuous</span></a></span></span></span></dt>
+<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.h1/" title="sdr.h1 (Python function) — Computes the statistical distribution under the alternative hypothesis $mathcal{H}_1$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">h1</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h1/#p-snr" title="sdr.h1.snr (Python parameter) — The signal-to-noise ratio $S / sigma^2$ in dB."><span class="n"><span class="pre">snr</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span></em>, </span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.h1/#p-sigma2" title="sdr.h1.sigma2 (Python parameter) — The noise variance $sigma^2$ in linear units."><span class="n"><span class="pre">sigma2</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><span class="pre">float</span></a></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><code class="code python default_value docutils literal highlight highlight-python"><span class="mf">1.0</span></code></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><a class="reference external" href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.html#scipy.stats.rv_continuous" title="(in SciPy v1.14.1)"><span class="pre">rv_continuous</span></a></span></span></span></dt>
 <dd><p>Computes the statistical distribution under the alternative hypothesis <span class="math notranslate nohighlight">\(\mathcal{H}_1\)</span>.</p>
 </dd></dl>
 

diff --git a/v0.0.x/api/measurement/index.html b/v0.0.x/api/measurement/index.html
@@ -14486,7 +14486,7 @@ <h2 id="distance">Distance<a class="headerlink" href="#distance" title="Link to
 
 <dl class="py function summary objdesc">
 <dt class="sig sig-object highlight py">
-<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.hamming/" title="sdr.hamming (Python function) — Measures the Hamming distance between two signals $x[n]$ and $y[n]$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">hamming</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.hamming/#p-x" title="sdr.hamming.x (Python parameter) — The time-domain signal $x[n]$."><span class="n"><span class="pre">x</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><span class="pre">NDArray</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.int_" title="(in NumPy v2.0)"><span class="pre">int_</span></a><span class="p"><span class="pre">]</span></span></span></span></em>, </span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.hamming/#p-y" title="sdr.hamming.y (Python parameter) — The time-domain signal $y[n]$."><span class="n"><span class="pre">y</span></span></a></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><span class="pre">NDArray</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.int_" title="(in NumPy v2.0)"><span class="pre">int_</span></a><span class="p"><span class="pre">]</span></span></span></span></span></dt>
+<span class="sig-prename descclassname"><span class="pre">sdr.</span></span><a class="sig-name descname pseudo-toc-entry reference internal" href="../sdr.hamming/" title="sdr.hamming (Python function) — Measures the Hamming distance between two signals $x[n]$ and $y[n]$."><span class="sig-name descname pseudo-toc-entry"><span class="pre">hamming</span></span></a><span class="sig-paren">(</span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.hamming/#p-x" title="sdr.hamming.x (Python parameter) — The time-domain signal $x[n]$."><span class="n"><span class="pre">x</span></span></a><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="desctype"><span class="pre">NDArray</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.int_" title="(in NumPy v2.1)"><span class="pre">int_</span></a><span class="p"><span class="pre">]</span></span></span></span></em>, </span><span class="sig-param-decl"><em class="sig-param"><a class="n reference internal" href="../sdr.hamming/#p-y" title="sdr.hamming.y (Python parameter) — The time-domain signal $y[n]$."><span class="n"><span class="pre">y</span></span></a></em>, </span><span class="sig-param-decl"><em class="sig-param"><span class="p"><span class="pre">...</span></span></em></span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="desctype"><span class="pre">NDArray</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.int_" title="(in NumPy v2.1)"><span class="pre">int_</span></a><span class="p"><span class="pre">]</span></span></span></span></span></dt>
 <dd><p>Measures the Hamming distance between two signals <span class="math notranslate nohighlight">\(x[n]\)</span> and <span class="math notranslate nohighlight">\(y[n]\)</span>.</p>
 </dd></dl>