--- /srv/reproducible-results/rbuild-debian/r-b-build.F9txe52m/b1/numpy_2.2.4+ds-1.2_arm64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.F9txe52m/b2/numpy_2.2.4+ds-1.2_arm64.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - 37ce51f86fc5e40101cd7ff77cf6dab8 5808024 doc optional python-numpy-doc_2.2.4+ds-1.2_all.deb
│ + 941cae68e0b88139e7d93f48e0c98209 5807872 doc optional python-numpy-doc_2.2.4+ds-1.2_all.deb
│   11c761cb3614185a39b982f88823a78f 14207256 debug optional python3-numpy-dbgsym_2.2.4+ds-1.2_arm64.deb
│   c0cbd4b003ff88afdbfa668cce7cae5d 138484 python optional python3-numpy-dev_2.2.4+ds-1.2_arm64.deb
│   8a68428d1b00e098c3b18a8d1908d801 3619724 python optional python3-numpy_2.2.4+ds-1.2_arm64.deb
├── python-numpy-doc_2.2.4+ds-1.2_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2025-09-05 09:56:25.000000 debian-binary
│ │ --rw-r--r--   0        0        0    64952 2025-09-05 09:56:25.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5742880 2025-09-05 09:56:25.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0    64948 2025-09-05 09:56:25.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0  5742732 2025-09-05 09:56:25.000000 data.tar.xz
│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./md5sums
│ │ │ │ ├── ./md5sums
│ │ │ │ │┄ Files differ
│ ├── data.tar.xz
│ │ ├── data.tar
│ │ │ ├── file list
│ │ │ │ @@ -2611,15 +2611,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    24350 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.matlib.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26240 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.other.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    37407 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials-package.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46787 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.chebyshev.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51499 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.classes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42945 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43480 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite_e.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    47585 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    47589 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42872 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.laguerre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42653 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.legendre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28625 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.poly1d.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41718 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polynomial.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26512 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polyutils.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26749 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.rec.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26398 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/reference/routines.set.html
│ │ │ │ @@ -2756,15 +2756,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    31655 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32348 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32865 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release/2.2.3-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32016 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release/2.2.4-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    13407 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    90894 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12397 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2368719 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2368702 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   177610 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64099 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    18647 2025-09-05 09:56:25.000000 ./usr/share/doc/python-numpy/html/user/basics.html
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ @@ -536,30 +536,30 @@
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [1]: </span><span class="kn">import</span> <span class="nn">numpy.random</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [2]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">939 us +- 44.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">2.42 ms +- 36.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.03 ms +- 39.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.43 ms +- 41.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">796 us +- 18.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">1.69 ms +- 22 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">851 us +- 18 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.7 ms +- 34.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [5]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_gamma(3.0, 100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_gamma(3.0, 100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">2.92 ms +- 1.41 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">4.1 ms +- 28.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.46 ms +- 34.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.1 ms +- 20.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p><a class="reference internal" href="generated/numpy.random.Generator.integers.html#numpy.random.Generator.integers" title="numpy.random.Generator.integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">integers</span></code></a> is now the canonical way to generate integer
│ │ │ │  random numbers from a discrete uniform distribution. This replaces both
│ │ │ │  <a class="reference internal" href="generated/numpy.random.randint.html#numpy.random.randint" title="numpy.random.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a> and the deprecated <a class="reference internal" href="generated/numpy.random.random_integers.html#numpy.random.random_integers" title="numpy.random.random_integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random_integers</span></code></a>.</p></li>
│ │ │ │  <li><p>The <a class="reference internal" href="generated/numpy.random.rand.html#numpy.random.rand" title="numpy.random.rand"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rand</span></code></a> and <a class="reference internal" href="generated/numpy.random.randn.html#numpy.random.randn" title="numpy.random.randn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randn</span></code></a> methods are only available through the legacy
│ │ │ │ @@ -586,21 +586,21 @@
│ │ │ │  <li><p>Standard Exponentials (<a class="reference internal" href="generated/numpy.random.Generator.standard_exponential.html#numpy.random.Generator.standard_exponential" title="numpy.random.Generator.standard_exponential"><code class="xref py py-obj docutils literal notranslate"><span class="pre">standard_exponential</span></code></a>)</p></li>
│ │ │ │  </ul>
│ │ │ │  </li>
│ │ │ │  </ul>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [6]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [7]: </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[7]: </span><span class="go">array([0.55792744, 0.10045431, 0.39091772])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.12730094, 0.86732915, 0.29751739])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [8]: </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[8]: </span><span class="go">array([0.7786327 , 0.44079942, 0.11658084], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.07399744, 0.87415296, 0.9917921 ], dtype=float32)</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [9]: </span><span class="n">rng</span><span class="o">.</span><span class="n">integers</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">256</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[9]: </span><span class="go">array([192, 232, 195], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([217, 193, 195], dtype=uint8)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul>
│ │ │ │  <li><p>Optional <code class="docutils literal notranslate"><span class="pre">out</span></code> argument that allows existing arrays to be filled for
│ │ │ │  select distributions</p>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Uniforms (<a class="reference internal" href="generated/numpy.random.Generator.random.html#numpy.random.Generator.random" title="numpy.random.Generator.random"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random</span></code></a>)</p></li>
│ │ │ │ @@ -613,18 +613,18 @@
│ │ │ │  </li>
│ │ │ │  </ul>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [10]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [11]: </span><span class="n">existing</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [12]: </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">out</span><span class="o">=</span><span class="n">existing</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span>
│ │ │ │ -<span class="gh">Out[12]: </span><span class="go">array([0.81716537, 0.98353266])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.23968024, 0.57921891])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [13]: </span><span class="nb">print</span><span class="p">(</span><span class="n">existing</span><span class="p">)</span>
│ │ │ │ -<span class="go">[0.81716537 0.98353266 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.23968024 0.57921891 0.         0.        ]</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Optional <code class="docutils literal notranslate"><span class="pre">axis</span></code> argument for methods like <a class="reference internal" href="generated/numpy.random.Generator.choice.html#numpy.random.Generator.choice" title="numpy.random.Generator.choice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">choice</span></code></a>,
│ │ │ │  <a class="reference internal" href="generated/numpy.random.Generator.permutation.html#numpy.random.Generator.permutation" title="numpy.random.Generator.permutation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">permutation</span></code></a> and <a class="reference internal" href="generated/numpy.random.Generator.shuffle.html#numpy.random.Generator.shuffle" title="numpy.random.Generator.shuffle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">shuffle</span></code></a> that controls which
│ │ │ │  axis an operation is performed over for multi-dimensional arrays.</p></li>
│ │ │ │  </ul>
│ │ │ │ @@ -636,25 +636,25 @@
│ │ │ │  <span class="gh">Out[16]: </span>
│ │ │ │  <span class="go">array([[ 0,  1,  2,  3],</span>
│ │ │ │  <span class="go">       [ 4,  5,  6,  7],</span>
│ │ │ │  <span class="go">       [ 8,  9, 10, 11]])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [17]: </span><span class="n">rng</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
│ │ │ │  <span class="gh">Out[17]: </span>
│ │ │ │ -<span class="go">array([[ 2,  3,  2,  3,  1],</span>
│ │ │ │ -<span class="go">       [ 6,  7,  6,  7,  5],</span>
│ │ │ │ -<span class="go">       [10, 11, 10, 11,  9]])</span>
│ │ │ │ +<span class="go">array([[ 1,  3,  1,  1,  2],</span>
│ │ │ │ +<span class="go">       [ 5,  7,  5,  5,  6],</span>
│ │ │ │ +<span class="go">       [ 9, 11,  9,  9, 10]])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [18]: </span><span class="n">rng</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>        <span class="c1"># Shuffle in-place</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [19]: </span><span class="n">a</span>
│ │ │ │  <span class="gh">Out[19]: </span>
│ │ │ │ -<span class="go">array([[ 3,  0,  2,  1],</span>
│ │ │ │ -<span class="go">       [ 7,  4,  6,  5],</span>
│ │ │ │ -<span class="go">       [11,  8, 10,  9]])</span>
│ │ │ │ +<span class="go">array([[ 0,  1,  2,  3],</span>
│ │ │ │ +<span class="go">       [ 4,  5,  6,  7],</span>
│ │ │ │ +<span class="go">       [ 8,  9, 10, 11]])</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Added a method to sample from the complex normal distribution
│ │ │ │  (<em class="xref py py-obj">complex_normal</em>)</p></li>
│ │ │ │  </ul>
│ │ │ │  </section>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -102,26 +102,26 @@
│ │ │ │ │  In [1]: import numpy.random
│ │ │ │ │  
│ │ │ │ │  In [2]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [3]: %timeit -n 1 rng.standard_normal(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_normal(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -939 us +- 44.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -2.42 ms +- 36.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.03 ms +- 39.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.43 ms +- 41.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │  In [4]: %timeit -n 1 rng.standard_exponential(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_exponential(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -796 us +- 18.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -1.69 ms +- 22 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +851 us +- 18 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.7 ms +- 34.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │  In [5]: %timeit -n 1 rng.standard_gamma(3.0, 100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_gamma(3.0, 100000)
│ │ │ │ │     ...:
│ │ │ │ │ -2.92 ms +- 1.41 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -4.1 ms +- 28.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.46 ms +- 34.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.1 ms +- 20.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │      * _i_n_t_e_g_e_r_s is now the canonical way to generate integer random numbers from
│ │ │ │ │        a discrete uniform distribution. This replaces both _r_a_n_d_i_n_t and the
│ │ │ │ │        deprecated _r_a_n_d_o_m___i_n_t_e_g_e_r_s.
│ │ │ │ │      * The _r_a_n_d and _r_a_n_d_n methods are only available through the legacy
│ │ │ │ │        _R_a_n_d_o_m_S_t_a_t_e.
│ │ │ │ │      * _G_e_n_e_r_a_t_o_r_._r_a_n_d_o_m is now the canonical way to generate floating-point
│ │ │ │ │        random numbers, which replaces _R_a_n_d_o_m_S_t_a_t_e_._r_a_n_d_o_m___s_a_m_p_l_e, _s_a_m_p_l_e, and
│ │ │ │ │ @@ -140,38 +140,38 @@
│ │ │ │ │            o Uniforms (_r_a_n_d_o_m and _i_n_t_e_g_e_r_s)
│ │ │ │ │            o Normals (_s_t_a_n_d_a_r_d___n_o_r_m_a_l)
│ │ │ │ │            o Standard Gammas (_s_t_a_n_d_a_r_d___g_a_m_m_a)
│ │ │ │ │            o Standard Exponentials (_s_t_a_n_d_a_r_d___e_x_p_o_n_e_n_t_i_a_l)
│ │ │ │ │  In [6]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [7]: rng.random(3, dtype=np.float64)
│ │ │ │ │ -Out[7]: array([0.55792744, 0.10045431, 0.39091772])
│ │ │ │ │ +Out[7]: array([0.12730094, 0.86732915, 0.29751739])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.7786327 , 0.44079942, 0.11658084], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.07399744, 0.87415296, 0.9917921 ], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([192, 232, 195], dtype=uint8)
│ │ │ │ │ +Out[9]: array([217, 193, 195], dtype=uint8)
│ │ │ │ │      * Optional out argument that allows existing arrays to be filled for select
│ │ │ │ │        distributions
│ │ │ │ │            o Uniforms (_r_a_n_d_o_m)
│ │ │ │ │            o Normals (_s_t_a_n_d_a_r_d___n_o_r_m_a_l)
│ │ │ │ │            o Standard Gammas (_s_t_a_n_d_a_r_d___g_a_m_m_a)
│ │ │ │ │            o Standard Exponentials (_s_t_a_n_d_a_r_d___e_x_p_o_n_e_n_t_i_a_l)
│ │ │ │ │        This allows multithreading to fill large arrays in chunks using suitable
│ │ │ │ │        BitGenerators in parallel.
│ │ │ │ │  In [10]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [11]: existing = np.zeros(4)
│ │ │ │ │  
│ │ │ │ │  In [12]: rng.random(out=existing[:2])
│ │ │ │ │ -Out[12]: array([0.81716537, 0.98353266])
│ │ │ │ │ +Out[12]: array([0.23968024, 0.57921891])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.81716537 0.98353266 0.         0.        ]
│ │ │ │ │ +[0.23968024 0.57921891 0.         0.        ]
│ │ │ │ │      * Optional axis argument for methods like _c_h_o_i_c_e, _p_e_r_m_u_t_a_t_i_o_n and _s_h_u_f_f_l_e
│ │ │ │ │        that controls which axis an operation is performed over for multi-
│ │ │ │ │        dimensional arrays.
│ │ │ │ │  In [14]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [15]: a = np.arange(12).reshape((3, 4))
│ │ │ │ │  
│ │ │ │ │ @@ -179,25 +179,25 @@
│ │ │ │ │  Out[16]:
│ │ │ │ │  array([[ 0,  1,  2,  3],
│ │ │ │ │         [ 4,  5,  6,  7],
│ │ │ │ │         [ 8,  9, 10, 11]])
│ │ │ │ │  
│ │ │ │ │  In [17]: rng.choice(a, axis=1, size=5)
│ │ │ │ │  Out[17]:
│ │ │ │ │ -array([[ 2,  3,  2,  3,  1],
│ │ │ │ │ -       [ 6,  7,  6,  7,  5],
│ │ │ │ │ -       [10, 11, 10, 11,  9]])
│ │ │ │ │ +array([[ 1,  3,  1,  1,  2],
│ │ │ │ │ +       [ 5,  7,  5,  5,  6],
│ │ │ │ │ +       [ 9, 11,  9,  9, 10]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 3,  0,  2,  1],
│ │ │ │ │ -       [ 7,  4,  6,  5],
│ │ │ │ │ -       [11,  8, 10,  9]])
│ │ │ │ │ +array([[ 0,  1,  2,  3],
│ │ │ │ │ +       [ 4,  5,  6,  7],
│ │ │ │ │ +       [ 8,  9, 10, 11]])
│ │ │ │ │      * Added a method to sample from the complex normal distribution
│ │ │ │ │        (ccoommpplleexx__nnoorrmmaall)
│ │ │ │ │  _p_r_e_v_i_o_u_s
│ │ │ │ │  _M_u_l_t_i_t_h_r_e_a_d_e_d_ _g_e_n_e_r_a_t_i_o_n
│ │ │ │ │  _n_e_x_t
│ │ │ │ │  _P_e_r_f_o_r_m_a_n_c_e
│ │ │ │ │  © Copyright 2008-2025, NumPy Developers.
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ @@ -609,31 +609,31 @@
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span> <span class="o">+</span> <span class="n">rng</span><span class="o">.</span><span class="n">standard_normal</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>With the legacy polynomial module, a linear fit (i.e. polynomial of degree 1)
│ │ │ │  could be applied to these data with <a class="reference internal" href="generated/numpy.polyfit.html#numpy.polyfit" title="numpy.polyfit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">polyfit</span></code></a>:</p>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[4]: </span><span class="go">array([0.83003832, 0.81698516])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 1.03419431, -0.3995521 ])</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>With the new polynomial API, the <a class="reference internal" href="generated/numpy.polynomial.polynomial.Polynomial.fit.html#numpy.polynomial.polynomial.Polynomial.fit" title="numpy.polynomial.polynomial.Polynomial.fit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fit</span></code></a>
│ │ │ │  class method is preferred:</p>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [5]: </span><span class="n">p_fitted</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polynomial</span><span class="o">.</span><span class="n">Polynomial</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [6]: </span><span class="n">p_fitted</span>
│ │ │ │ -<span class="gh">Out[6]: </span><span class="go">Polynomial([4.55215758, 3.73517242], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.25432228, 4.65387438], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>Note that the coefficients are given <em>in the scaled domain</em> defined by the
│ │ │ │  linear mapping between the <code class="docutils literal notranslate"><span class="pre">window</span></code> and <code class="docutils literal notranslate"><span class="pre">domain</span></code>.
│ │ │ │  <a class="reference internal" href="generated/numpy.polynomial.polynomial.Polynomial.convert.html#numpy.polynomial.polynomial.Polynomial.convert" title="numpy.polynomial.polynomial.Polynomial.convert"><code class="xref py py-obj docutils literal notranslate"><span class="pre">convert</span></code></a> can be used to get the
│ │ │ │  coefficients in the unscaled data domain.</p>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [7]: </span><span class="n">p_fitted</span><span class="o">.</span><span class="n">convert</span><span class="p">()</span>
│ │ │ │ -<span class="gh">Out[7]: </span><span class="go">Polynomial([0.81698516, 0.83003832], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.3995521 ,  1.03419431], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  </section>
│ │ │ │  </section>
│ │ │ │  <section id="documentation-for-the-polynomial-package">
│ │ │ │  <h2>Documentation for the <a class="reference internal" href="routines.polynomials-package.html#module-numpy.polynomial" title="numpy.polynomial"><code class="xref py py-obj docutils literal notranslate"><span class="pre">polynomial</span></code></a> package<a class="headerlink" href="#documentation-for-the-polynomial-package" title="Link to this heading">#</a></h2>
│ │ │ │  <p>In addition to standard power series polynomials, the polynomial package
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -150,26 +150,26 @@
│ │ │ │ │  
│ │ │ │ │  In [2]: x = np.arange(10)
│ │ │ │ │  
│ │ │ │ │  In [3]: y = np.arange(10) + rng.standard_normal(10)
│ │ │ │ │  With the legacy polynomial module, a linear fit (i.e. polynomial of degree 1)
│ │ │ │ │  could be applied to these data with _p_o_l_y_f_i_t:
│ │ │ │ │  In [4]: np.polyfit(x, y, deg=1)
│ │ │ │ │ -Out[4]: array([0.83003832, 0.81698516])
│ │ │ │ │ +Out[4]: array([ 1.03419431, -0.3995521 ])
│ │ │ │ │  With the new polynomial API, the _f_i_t class method is preferred:
│ │ │ │ │  In [5]: p_fitted = np.polynomial.Polynomial.fit(x, y, deg=1)
│ │ │ │ │  
│ │ │ │ │  In [6]: p_fitted
│ │ │ │ │ -Out[6]: Polynomial([4.55215758, 3.73517242], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.25432228, 4.65387438], domain=[0., 9.], window=[-1.,
│ │ │ │ │  1.], symbol='x')
│ │ │ │ │  Note that the coefficients are given iinn tthhee ssccaalleedd ddoommaaiinn defined by the linear
│ │ │ │ │  mapping between the window and domain. _c_o_n_v_e_r_t can be used to get the
│ │ │ │ │  coefficients in the unscaled data domain.
│ │ │ │ │  In [7]: p_fitted.convert()
│ │ │ │ │ -Out[7]: Polynomial([0.81698516, 0.83003832], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.3995521 ,  1.03419431], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │  1.], symbol='x')
│ │ │ │ │  ********** DDooccuummeennttaattiioonn ffoorr tthhee _pp_oo_ll_yy_nn_oo_mm_ii_aa_ll ppaacckkaaggee_## **********
│ │ │ │ │  In addition to standard power series polynomials, the polynomial package
│ │ │ │ │  provides several additional kinds of polynomials including Chebyshev, Hermite
│ │ │ │ │  (two subtypes), Laguerre, and Legendre polynomials. Each of these has an
│ │ │ │ │  associated ccoonnvveenniieennccee ccllaassss available from the _n_u_m_p_y_._p_o_l_y_n_o_m_i_a_l namespace that
│ │ │ │ │  provides a consistent interface for working with polynomials regardless of
│ │ │ ├── ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ ├── js-beautify {}
│ │ │ │ │ @@ -32368,17 +32368,18 @@
│ │ │ │ │          "0253": 2652,
│ │ │ │ │          "02654825": 1891,
│ │ │ │ │          "02658058e": 2666,
│ │ │ │ │          "02755911": 2666,
│ │ │ │ │          "027559113243068367": 2666,
│ │ │ │ │          "02785049": 1867,
│ │ │ │ │          "02i": [513, 2644],
│ │ │ │ │ -        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2658],
│ │ │ │ │ +        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2461, 2658],
│ │ │ │ │          "03125": [1585, 2491],
│ │ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │ │ +        "03419431": 2488,
│ │ │ │ │          "0361": 2607,
│ │ │ │ │          "03703704": 1809,
│ │ │ │ │          "03943254e": 2104,
│ │ │ │ │          "03968254": [1113, 1543],
│ │ │ │ │          "0396842": 680,
│ │ │ │ │          "03t13": 55,
│ │ │ │ │          "04": [54, 55, 164, 410, 547, 1586, 2463, 2594, 2659],
│ │ │ │ │ @@ -32401,14 +32402,15 @@
│ │ │ │ │          "0625": [418, 624, 1645],
│ │ │ │ │          "06369197489564249": 2458,
│ │ │ │ │          "06381726": 349,
│ │ │ │ │          "0660": [302, 2131],
│ │ │ │ │          "06959433e": [420, 947],
│ │ │ │ │          "07": [55, 164, 547, 896, 897, 1335, 2170, 2508],
│ │ │ │ │          "07106781e": 514,
│ │ │ │ │ +        "07399744": 2461,
│ │ │ │ │          "07407407": 1809,
│ │ │ │ │          "07779185": 2458,
│ │ │ │ │          "07937323": 524,
│ │ │ │ │          "07944154": [657, 2655],
│ │ │ │ │          "08": [55, 91, 147, 410, 523, 548, 896, 1095, 2322, 2366, 2413, 2525, 2659],
│ │ │ │ │          "0800": 2525,
│ │ │ │ │          "08187135": 54,
│ │ │ │ │ @@ -32492,15 +32494,14 @@
│ │ │ │ │          "100000": [2327, 2336, 2337, 2346, 2354, 2357, 2372, 2379, 2380, 2392, 2401, 2404, 2419, 2426, 2427, 2441, 2451, 2454, 2461],
│ │ │ │ │          "1000000": [357, 359, 2338, 2344, 2346, 2349, 2351, 2353, 2381, 2386, 2392, 2396, 2398, 2400, 2428, 2433, 2441, 2446, 2448, 2450],
│ │ │ │ │          "10000000": [2312, 2460],
│ │ │ │ │          "10000000000": [896, 897],
│ │ │ │ │          "1000000000000000000": 2648,
│ │ │ │ │          "1000j": 514,
│ │ │ │ │          "1001": 2535,
│ │ │ │ │ -        "10045431": 2461,
│ │ │ │ │          "100_000": [669, 2588],
│ │ │ │ │          "100j": 1909,
│ │ │ │ │          "100x5": 652,
│ │ │ │ │          "101": [86, 137, 138, 143, 145, 570, 1325, 2077, 2463, 2666],
│ │ │ │ │          "1010": [145, 1519, 2077],
│ │ │ │ │          "10100": [143, 570],
│ │ │ │ │          "1015": 2592,
│ │ │ │ │ @@ -32628,15 +32629,14 @@
│ │ │ │ │          "1151": 657,
│ │ │ │ │          "11525": 2547,
│ │ │ │ │          "116": 2463,
│ │ │ │ │          "11625": [2543, 2544, 2545, 2546],
│ │ │ │ │          "11647": 2543,
│ │ │ │ │          "11648": 2543,
│ │ │ │ │          "11657": 2543,
│ │ │ │ │ -        "11658084": 2461,
│ │ │ │ │          "11659149": [2345, 2391, 2439],
│ │ │ │ │          "11661": 2543,
│ │ │ │ │          "11665": 2543,
│ │ │ │ │          "11675684e": 1586,
│ │ │ │ │          "11682": 2543,
│ │ │ │ │          "11698": 2543,
│ │ │ │ │          "11700": 2543,
│ │ │ │ │ @@ -32726,14 +32726,15 @@
│ │ │ │ │          "125": [470, 660, 1114, 1142, 1645, 1651, 1899, 1900, 2239, 2339, 2382, 2429, 2460, 2491, 2659, 2666],
│ │ │ │ │          "12589991e": 645,
│ │ │ │ │          "126": [863, 1048, 1116, 1904],
│ │ │ │ │          "1261": 2612,
│ │ │ │ │          "12658": 2560,
│ │ │ │ │          "12697628": 2635,
│ │ │ │ │          "127": [62, 66, 514, 863, 1048, 1102, 1116, 1904, 2301, 2302, 2462, 2463, 2464, 2583, 2639],
│ │ │ │ │ +        "12730094": 2461,
│ │ │ │ │          "12736": [2548, 2549],
│ │ │ │ │          "12767": 2548,
│ │ │ │ │          "12768": 2548,
│ │ │ │ │          "12769": 2548,
│ │ │ │ │          "12773": 2548,
│ │ │ │ │          "128": [56, 62, 69, 114, 514, 863, 1048, 1098, 1116, 1335, 1904, 2091, 2162, 2270, 2275, 2280, 2285, 2290, 2299, 2300, 2301, 2302, 2303, 2348, 2458, 2462, 2463, 2464, 2525, 2535, 2566, 2583, 2622, 2639, 2648],
│ │ │ │ │          "12811363": [349, 2457, 2639],
│ │ │ │ │ @@ -33374,22 +33375,22 @@
│ │ │ │ │          "19062": 2583,
│ │ │ │ │          "1908": [2353, 2400, 2450],
│ │ │ │ │          "19083": 2583,
│ │ │ │ │          "19135": 2583,
│ │ │ │ │          "19151": 2583,
│ │ │ │ │          "191614240": 95,
│ │ │ │ │          "1918": 2612,
│ │ │ │ │ -        "192": [69, 669, 1519, 2461, 2463],
│ │ │ │ │ +        "192": [69, 669, 1519, 2463],
│ │ │ │ │          "19211": 2583,
│ │ │ │ │          "192163377": 2098,
│ │ │ │ │          "19226": 2588,
│ │ │ │ │          "1923875335537315": [2352, 2389, 2399, 2436, 2449],
│ │ │ │ │          "19249760": [420, 947],
│ │ │ │ │          "19259": 2583,
│ │ │ │ │ -        "193": [2463, 2637],
│ │ │ │ │ +        "193": [2461, 2463, 2637],
│ │ │ │ │          "19311": 2577,
│ │ │ │ │          "1932": [2359, 2406, 2456],
│ │ │ │ │          "19324": 2577,
│ │ │ │ │          "19330": 2577,
│ │ │ │ │          "19342": 2577,
│ │ │ │ │          "19343": 2577,
│ │ │ │ │          "19347": 2577,
│ │ │ │ │ @@ -33515,15 +33516,15 @@
│ │ │ │ │          "1l_0": 1822,
│ │ │ │ │          "1rc1": 577,
│ │ │ │ │          "1st": [36, 74, 642, 2616, 2637, 2641],
│ │ │ │ │          "1th": [661, 2168],
│ │ │ │ │          "1type": 2554,
│ │ │ │ │          "1xn": 2665,
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│ │ │ │ │ +        "20": [0, 22, 24, 32, 38, 47, 54, 55, 57, 58, 59, 60, 74, 78, 90, 95, 98, 99, 113, 120, 121, 123, 124, 137, 141, 143, 160, 163, 270, 287, 336, 341, 342, 349, 354, 356, 358, 371, 420, 436, 438, 439, 441, 443, 444, 445, 446, 448, 449, 450, 451, 452, 453, 454, 455, 480, 481, 482, 483, 486, 487, 489, 513, 527, 534, 540, 548, 567, 568, 569, 570, 628, 653, 661, 667, 669, 820, 848, 851, 855, 857, 860, 864, 866, 870, 880, 893, 896, 897, 900, 901, 905, 906, 912, 913, 917, 933, 937, 940, 941, 947, 951, 956, 958, 965, 967, 977, 985, 986, 990, 1019, 1024, 1025, 1026, 1031, 1038, 1040, 1044, 1049, 1051, 1056, 1069, 1083, 1088, 1089, 1094, 1097, 1100, 1101, 1106, 1109, 1114, 1117, 1118, 1123, 1124, 1131, 1143, 1145, 1146, 1229, 1241, 1247, 1312, 1324, 1466, 1478, 1482, 1516, 1808, 1867, 1871, 1906, 1986, 1998, 2073, 2089, 2115, 2165, 2168, 2172, 2174, 2203, 2204, 2208, 2223, 2224, 2237, 2238, 2240, 2249, 2256, 2257, 2270, 2300, 2316, 2319, 2321, 2323, 2328, 2333, 2337, 2338, 2342, 2348, 2361, 2365, 2377, 2380, 2381, 2383, 2388, 2390, 2408, 2412, 2424, 2427, 2428, 2430, 2435, 2438, 2461, 2462, 2463, 2470, 2513, 2517, 2519, 2533, 2535, 2542, 2560, 2571, 2576, 2577, 2583, 2584, 2594, 2599, 2602, 2603, 2608, 2622, 2627, 2635, 2637, 2641, 2642, 2645, 2657, 2658, 2666],
│ │ │ │ │          "200": [441, 446, 2337, 2339, 2346, 2354, 2357, 2380, 2382, 2392, 2401, 2404, 2427, 2429, 2441, 2451, 2454, 2645, 2648, 2666],
│ │ │ │ │          "2000": [514, 526, 2525, 2613],
│ │ │ │ │          "20000": [2316, 2359, 2361, 2406, 2408, 2456, 2583],
│ │ │ │ │          "2000000": 2635,
│ │ │ │ │          "20000000e": 897,
│ │ │ │ │          "2001": [55, 2322, 2326, 2329, 2330, 2331, 2335, 2339, 2340, 2366, 2371, 2373, 2374, 2375, 2378, 2382, 2383, 2413, 2418, 2420, 2421, 2422, 2425, 2429, 2430],
│ │ │ │ │          "2002": [55, 360, 2316, 2323, 2353, 2361, 2367, 2400, 2408, 2414, 2450],
│ │ │ │ │ @@ -33733,14 +33734,15 @@
│ │ │ │ │          "2155": [305, 2134],
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│ │ │ │ │          "21627": 2594,
│ │ │ │ │          "21645": 2594,
│ │ │ │ │          "21663": 2588,
│ │ │ │ │ +        "217": 2461,
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│ │ │ │ │          "218": [566, 2463],
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│ │ │ │ │          "21868": 2589,
│ │ │ │ │ @@ -33749,15 +33751,15 @@
│ │ │ │ │          "219": 2463,
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│ │ │ │ │          "21949": 2589,
│ │ │ │ │          "21951": 2589,
│ │ │ │ │          "21952": 2589,
│ │ │ │ │          "21976": 2594,
│ │ │ │ │          "21995": 2594,
│ │ │ │ │ -        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 98, 107, 108, 109, 163, 270, 336, 378, 425, 485, 628, 658, 669, 880, 905, 1045, 1069, 1113, 1211, 1229, 1294, 1312, 1336, 1337, 1340, 1341, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1358, 1448, 1466, 1514, 1521, 1522, 1543, 1591, 1905, 1908, 1913, 1968, 1986, 2091, 2208, 2236, 2237, 2342, 2461, 2513, 2517, 2519, 2534, 2588, 2635, 2637, 2641, 2657, 2666],
│ │ │ │ │ +        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 98, 107, 108, 109, 163, 270, 336, 378, 425, 485, 628, 658, 669, 880, 905, 1045, 1069, 1113, 1211, 1229, 1294, 1312, 1336, 1337, 1340, 1341, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1358, 1448, 1466, 1514, 1521, 1522, 1543, 1591, 1905, 1908, 1913, 1968, 1986, 2091, 2208, 2236, 2237, 2342, 2513, 2517, 2519, 2534, 2588, 2635, 2637, 2641, 2657, 2666],
│ │ │ │ │          "220": [2238, 2576],
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│ │ │ │ │          "22030": 2590,
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│ │ │ │ │          "22032": 2590,
│ │ │ │ │          "22033": 2590,
│ │ │ │ │ @@ -33922,15 +33924,14 @@
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│ │ │ │ │          "23194": 2597,
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│ │ │ │ │ -        "232": 2461,
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│ │ │ │ │          "23207": 2597,
│ │ │ │ │          "23208": 2597,
│ │ │ │ │          "23221": 2597,
│ │ │ │ │          "23226": 2597,
│ │ │ │ │          "23229": 2599,
│ │ │ │ │ @@ -33989,14 +33990,15 @@
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│ │ │ │ │          "23936": 2622,
│ │ │ │ │          "2394691": 2312,
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│ │ │ │ │ +        "23968024": 2461,
│ │ │ │ │          "23994": 2598,
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│ │ │ │ │          "23e": 477,
│ │ │ │ │          "23e24": 477,
│ │ │ │ │          "24": [10, 38, 47, 54, 55, 56, 58, 59, 62, 67, 98, 107, 108, 355, 356, 358, 408, 409, 477, 528, 531, 541, 542, 567, 638, 661, 662, 664, 838, 905, 939, 964, 968, 969, 1010, 1133, 1144, 1546, 1577, 1607, 1664, 1721, 1778, 1835, 1864, 1883, 1902, 2100, 2114, 2168, 2175, 2200, 2208, 2223, 2225, 2226, 2230, 2237, 2247, 2342, 2463, 2513, 2519, 2543, 2555, 2622, 2623, 2635, 2641, 2645, 2649, 2652, 2657, 2659, 2666, 2668],
│ │ │ │ │          "240": [57, 363],
│ │ │ │ │          "24011": 2622,
│ │ │ │ │ @@ -34255,14 +34257,15 @@
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│ │ │ │ │          "25419": 2605,
│ │ │ │ │          "25420": 2605,
│ │ │ │ │          "25422": 2605,
│ │ │ │ │          "25428": 2605,
│ │ │ │ │ +        "25432228": 2488,
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│ │ │ │ │          "25452": 2605,
│ │ │ │ │          "25458": 2605,
│ │ │ │ │          "25463": 2622,
│ │ │ │ │          "25465": 2605,
│ │ │ │ │ @@ -34510,15 +34513,15 @@
│ │ │ │ │          "27t00": 360,
│ │ │ │ │          "27t01": 360,
│ │ │ │ │          "27t02": 360,
│ │ │ │ │          "27t04": 360,
│ │ │ │ │          "27t05": 360,
│ │ │ │ │          "27t06": 360,
│ │ │ │ │          "27t07": 360,
│ │ │ │ │ -        "28": [36, 54, 55, 146, 409, 661, 1695, 1704, 1707, 1862, 2168, 2208, 2225, 2461, 2463, 2513, 2538, 2539, 2540, 2543, 2629, 2641, 2649, 2657, 2659, 2666],
│ │ │ │ │ +        "28": [36, 54, 55, 146, 409, 661, 1695, 1704, 1707, 1862, 2168, 2208, 2225, 2463, 2513, 2538, 2539, 2540, 2543, 2629, 2641, 2649, 2657, 2659, 2666],
│ │ │ │ │          "28000000e": 1335,
│ │ │ │ │          "2800000e": 1335,
│ │ │ │ │          "28006": 2630,
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│ │ │ │ │          "2801": 2613,
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│ │ │ │ │          "28044": 2630,
│ │ │ │ │ @@ -34613,14 +34616,15 @@
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│ │ │ │ │          "296": 669,
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│ │ │ │ │          "297": [438, 2477, 2666],
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│ │ │ │ │          "2973": 2614,
│ │ │ │ │          "29737120e": 566,
│ │ │ │ │ +        "29751739": 2461,
│ │ │ │ │          "298": [2300, 2666],
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│ │ │ │ │          "2983": 2614,
│ │ │ │ │          "2984": 2614,
│ │ │ │ │          "2985": 2614,
│ │ │ │ │          "2988071523335984": 1114,
│ │ │ │ │          "299": 2666,
│ │ │ │ │ @@ -34736,15 +34740,15 @@
│ │ │ │ │          "3340": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "3348": 2617,
│ │ │ │ │          "33486982e": 438,
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│ │ │ │ │          "3364": 2615,
│ │ │ │ │          "3373": 2615,
│ │ │ │ │          "33872321e": 2104,
│ │ │ │ │ -        "34": [12, 28, 144, 441, 1880, 1919, 2208, 2463, 2491, 2566, 2583, 2641, 2657, 2666],
│ │ │ │ │ +        "34": [12, 28, 144, 441, 1880, 1919, 2208, 2461, 2463, 2491, 2566, 2583, 2641, 2657, 2666],
│ │ │ │ │          "340": [2238, 2576],
│ │ │ │ │          "34132519": [680, 2659],
│ │ │ │ │          "3421": 2615,
│ │ │ │ │          "343": 2666,
│ │ │ │ │          "34317802": 1153,
│ │ │ │ │          "34376245": 2635,
│ │ │ │ │          "3456": 13,
│ │ │ │ │ @@ -34763,15 +34767,15 @@
│ │ │ │ │          "35": [409, 489, 669, 870, 1056, 2204, 2325, 2369, 2416, 2572, 2635, 2641, 2657, 2666],
│ │ │ │ │          "350": [544, 635],
│ │ │ │ │          "3504": 2617,
│ │ │ │ │          "3534857623790153": 666,
│ │ │ │ │          "35355339": 1636,
│ │ │ │ │          "3541": 2615,
│ │ │ │ │          "35489284e": 2104,
│ │ │ │ │ -        "36": [58, 137, 355, 1752, 1761, 2204, 2225, 2323, 2367, 2414, 2461, 2463, 2491, 2536, 2649, 2657, 2659, 2666],
│ │ │ │ │ +        "36": [58, 137, 355, 1752, 1761, 2204, 2225, 2323, 2367, 2414, 2463, 2491, 2536, 2649, 2657, 2659, 2666],
│ │ │ │ │          "360": [544, 2103, 2238, 2576],
│ │ │ │ │          "36045180e": 147,
│ │ │ │ │          "3608": 2615,
│ │ │ │ │          "361": [1344, 1346, 1522, 1908],
│ │ │ │ │          "362": 12,
│ │ │ │ │          "3628523": 2458,
│ │ │ │ │          "36363636": 136,
│ │ │ │ │ @@ -34807,26 +34811,26 @@
│ │ │ │ │          "3871": 2615,
│ │ │ │ │          "38777878e": [147, 1651],
│ │ │ │ │          "38791518e": [421, 948],
│ │ │ │ │          "38885": [2361, 2408],
│ │ │ │ │          "389056": 2642,
│ │ │ │ │          "3890561": [38, 2666],
│ │ │ │ │          "3891": 2642,
│ │ │ │ │ -        "39": [30, 58, 2208, 2463, 2641, 2657],
│ │ │ │ │ +        "39": [30, 58, 2208, 2461, 2463, 2641, 2657],
│ │ │ │ │          "390": [2270, 2300],
│ │ │ │ │          "3900": 2615,
│ │ │ │ │          "3900x": 2463,
│ │ │ │ │          "39015": 2316,
│ │ │ │ │ -        "39091772": 2461,
│ │ │ │ │          "39211752": 1153,
│ │ │ │ │          "39337286e": 1149,
│ │ │ │ │          "3971": 2615,
│ │ │ │ │          "39804426": 1153,
│ │ │ │ │          "3992": 2615,
│ │ │ │ │          "39924804": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │ +        "3995521": 2488,
│ │ │ │ │          "3_000": 669,
│ │ │ │ │          "3abcd": 513,
│ │ │ │ │          "3d": [63, 2513, 2621, 2635, 2637, 2657, 2666],
│ │ │ │ │          "3e": [357, 359, 1596, 1653, 1710, 1767, 1824, 1879, 1893, 1915, 2086],
│ │ │ │ │          "3ej": 2086,
│ │ │ │ │          "3int8": 2645,
│ │ │ │ │          "3j": [58, 374, 544, 647, 1157, 2108, 2572],
│ │ │ │ │ @@ -34879,15 +34883,15 @@
│ │ │ │ │          "4167": 1643,
│ │ │ │ │          "4170": 2617,
│ │ │ │ │          "4176": 2617,
│ │ │ │ │          "4181": [28, 2621],
│ │ │ │ │          "4187": 2617,
│ │ │ │ │          "4191": 2617,
│ │ │ │ │          "4197": 2617,
│ │ │ │ │ -        "42": [31, 58, 63, 147, 349, 669, 896, 897, 974, 1029, 2090, 2208, 2256, 2332, 2376, 2423, 2457, 2461, 2566, 2605, 2622, 2635, 2639, 2657, 2664, 2665, 2666],
│ │ │ │ │ +        "42": [31, 58, 63, 147, 349, 669, 896, 897, 974, 1029, 2090, 2208, 2256, 2332, 2376, 2423, 2457, 2566, 2605, 2622, 2635, 2639, 2657, 2664, 2665, 2666],
│ │ │ │ │          "420": [2238, 2576],
│ │ │ │ │          "42016704": 2666,
│ │ │ │ │          "4206": 2617,
│ │ │ │ │          "4220": 2617,
│ │ │ │ │          "4223": 2617,
│ │ │ │ │          "4225": 2617,
│ │ │ │ │          "423": 55,
│ │ │ │ │ @@ -34903,30 +34907,29 @@
│ │ │ │ │          "42667924": 1154,
│ │ │ │ │          "4267": 2617,
│ │ │ │ │          "4270": 2617,
│ │ │ │ │          "4276": 2617,
│ │ │ │ │          "429": 136,
│ │ │ │ │          "4294967293": 2639,
│ │ │ │ │          "4294967296": [196, 836, 1008, 1179, 1266, 1421, 1940],
│ │ │ │ │ -        "43": [2208, 2583, 2635, 2641, 2657, 2666],
│ │ │ │ │ +        "43": [2208, 2461, 2583, 2635, 2641, 2657, 2666],
│ │ │ │ │          "430148": 2635,
│ │ │ │ │          "43014843": 2635,
│ │ │ │ │          "43181166": 2458,
│ │ │ │ │          "4354": 2617,
│ │ │ │ │          "4359": 2617,
│ │ │ │ │          "4368": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4375": 2491,
│ │ │ │ │          "43857224": 1153,
│ │ │ │ │          "43887844": [349, 2457, 2639],
│ │ │ │ │          "43999999999998": 1114,
│ │ │ │ │ -        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2461, 2463, 2624, 2657, 2658, 2659, 2666],
│ │ │ │ │ +        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2463, 2624, 2657, 2658, 2659, 2666],
│ │ │ │ │          "440": [10, 2520],
│ │ │ │ │          "4400": [409, 661, 2168],
│ │ │ │ │          "44069024": 349,
│ │ │ │ │ -        "44079942": 2461,
│ │ │ │ │          "4408": 2617,
│ │ │ │ │          "44089210e": 1527,
│ │ │ │ │          "4408921e": [1765, 2175],
│ │ │ │ │          "4409e": 2091,
│ │ │ │ │          "442": 2615,
│ │ │ │ │          "4428": 2617,
│ │ │ │ │          "4434142": 349,
│ │ │ │ │ @@ -34953,15 +34956,15 @@
│ │ │ │ │          "4532": [409, 661, 2168],
│ │ │ │ │          "4545724517479104": 2460,
│ │ │ │ │          "45560727e": 54,
│ │ │ │ │          "456": 1921,
│ │ │ │ │          "4567": 2644,
│ │ │ │ │          "45674898e": 566,
│ │ │ │ │          "45a3d84": 2521,
│ │ │ │ │ -        "46": [409, 523, 905, 1707, 2204, 2208, 2641, 2657],
│ │ │ │ │ +        "46": [409, 523, 905, 1707, 2204, 2208, 2461, 2641, 2657],
│ │ │ │ │          "460": [2238, 2576],
│ │ │ │ │          "46009194e": 566,
│ │ │ │ │          "4602": 2618,
│ │ │ │ │          "4610935": 457,
│ │ │ │ │          "4613": 2618,
│ │ │ │ │          "4628": 2618,
│ │ │ │ │          "46351241j": 2081,
│ │ │ │ │ @@ -35127,22 +35130,20 @@
│ │ │ │ │          "54959369": 2666,
│ │ │ │ │          "54999924": 1247,
│ │ │ │ │          "55": [28, 59, 60, 73, 893, 1083, 1143, 1525, 1905, 2090, 2204, 2240, 2622, 2657],
│ │ │ │ │          "55000000074505806": 1247,
│ │ │ │ │          "5510652": 2635,
│ │ │ │ │          "55111512e": 642,
│ │ │ │ │          "55131477": 1153,
│ │ │ │ │ -        "55215758": 2488,
│ │ │ │ │          "5524": 2621,
│ │ │ │ │          "55458479": 349,
│ │ │ │ │          "55490914e": 2666,
│ │ │ │ │          "5555555555555554": 1349,
│ │ │ │ │          "55627469": 349,
│ │ │ │ │          "55645993": 2635,
│ │ │ │ │ -        "55792744": 2461,
│ │ │ │ │          "5580": 2535,
│ │ │ │ │          "55914881e": 2104,
│ │ │ │ │          "56": [52, 55, 61, 544, 1764, 2204, 2463, 2657, 2659],
│ │ │ │ │          "5612": 2621,
│ │ │ │ │          "5614": 2522,
│ │ │ │ │          "562": [680, 2659],
│ │ │ │ │          "5620499351813308": 86,
│ │ │ │ │ @@ -35160,14 +35161,15 @@
│ │ │ │ │          "57136612e": 2173,
│ │ │ │ │          "57510612": 660,
│ │ │ │ │          "576": 2615,
│ │ │ │ │          "57721": [2326, 2371, 2418],
│ │ │ │ │          "5772156649015328606065120900824024310421": 76,
│ │ │ │ │          "5773": 2522,
│ │ │ │ │          "57860025": 1154,
│ │ │ │ │ +        "57921891": 2461,
│ │ │ │ │          "579365079365115": [1113, 1543],
│ │ │ │ │          "57x": 2594,
│ │ │ │ │          "58": [669, 1748, 1777, 2204, 2208, 2332, 2376, 2423, 2464, 2572, 2635, 2657],
│ │ │ │ │          "582892": 2635,
│ │ │ │ │          "58289208": 2635,
│ │ │ │ │          "584388": 55,
│ │ │ │ │          "585": [378, 1358, 1514, 2583],
│ │ │ │ │ @@ -35270,14 +35272,15 @@
│ │ │ │ │          "6526": 2522,
│ │ │ │ │          "6527": 2522,
│ │ │ │ │          "6530": 2522,
│ │ │ │ │          "6532": 2522,
│ │ │ │ │          "6536": 2522,
│ │ │ │ │          "6537": 2522,
│ │ │ │ │          "6538": 2522,
│ │ │ │ │ +        "65387438": 2488,
│ │ │ │ │          "6546": 2522,
│ │ │ │ │          "65465": [2335, 2378, 2425],
│ │ │ │ │          "6551": 2525,
│ │ │ │ │          "65522": [142, 546],
│ │ │ │ │          "6553": 2522,
│ │ │ │ │          "65535": [584, 2619, 2622],
│ │ │ │ │          "6556": 2522,
│ │ │ │ │ @@ -35364,15 +35367,15 @@
│ │ │ │ │          "6840": 2524,
│ │ │ │ │          "6843": 2524,
│ │ │ │ │          "68456316": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "68482974": 1153,
│ │ │ │ │          "6884": 2524,
│ │ │ │ │          "68862757": 660,
│ │ │ │ │          "6888893": [2352, 2399, 2449],
│ │ │ │ │ -        "69": [58, 431, 2461, 2657, 2666],
│ │ │ │ │ +        "69": [58, 431, 2657, 2666],
│ │ │ │ │          "6916": 2524,
│ │ │ │ │          "6922": 2524,
│ │ │ │ │          "6924": 2524,
│ │ │ │ │          "69312169": [1113, 1543],
│ │ │ │ │          "69314718": [76, 657, 2655],
│ │ │ │ │          "69314718055994529": 657,
│ │ │ │ │          "6931471805599453": 2257,
│ │ │ │ │ @@ -35427,15 +35430,14 @@
│ │ │ │ │          "729": 2666,
│ │ │ │ │          "72904971": 1153,
│ │ │ │ │          "72949656": 2635,
│ │ │ │ │          "73": [2463, 2657],
│ │ │ │ │          "7320508075688772j": 59,
│ │ │ │ │          "73472348e": 1816,
│ │ │ │ │          "73496154e": 1867,
│ │ │ │ │ -        "73517242": 2488,
│ │ │ │ │          "73603959e": 2666,
│ │ │ │ │          "73799541": 1153,
│ │ │ │ │          "74": [2463, 2513, 2514, 2657],
│ │ │ │ │          "74000000": 2635,
│ │ │ │ │          "7416573867739413": 653,
│ │ │ │ │          "74165739": 653,
│ │ │ │ │          "74499359e": [420, 947],
│ │ │ │ │ @@ -35498,15 +35500,14 @@
│ │ │ │ │          "7755575615628914e": 2648,
│ │ │ │ │          "77555756e": 1877,
│ │ │ │ │          "77598074": 349,
│ │ │ │ │          "77714685": 349,
│ │ │ │ │          "7774613834041182": 2315,
│ │ │ │ │          "7776": [99, 906],
│ │ │ │ │          "7778": 2527,
│ │ │ │ │ -        "7786327": 2461,
│ │ │ │ │          "7793": 2527,
│ │ │ │ │          "78": [2091, 2644, 2657],
│ │ │ │ │          "78096262": [2352, 2399, 2449],
│ │ │ │ │          "7816": 2527,
│ │ │ │ │          "7821": 2527,
│ │ │ │ │          "7824": 2527,
│ │ │ │ │          "7835": 2527,
│ │ │ │ │ @@ -35533,15 +35534,14 @@
│ │ │ │ │          "7939": 2527,
│ │ │ │ │          "79479508": [2345, 2391, 2439],
│ │ │ │ │          "795": 650,
│ │ │ │ │          "7953": 2527,
│ │ │ │ │          "7954": 2527,
│ │ │ │ │          "7955": 2527,
│ │ │ │ │          "79579319e": 1867,
│ │ │ │ │ -        "796": 2461,
│ │ │ │ │          "79694221e": 1586,
│ │ │ │ │          "7972": 2527,
│ │ │ │ │          "7976931348623157e": 1335,
│ │ │ │ │          "79769313e": 1335,
│ │ │ │ │          "79ff": [102, 125],
│ │ │ │ │          "7e": 669,
│ │ │ │ │          "7e13": 55,
│ │ │ │ │ @@ -35564,16 +35564,14 @@
│ │ │ │ │          "80b3a34": 2614,
│ │ │ │ │          "81": [1650, 1884, 2635, 2641, 2645, 2657, 2666],
│ │ │ │ │          "81299683": 2635,
│ │ │ │ │          "812997": 2635,
│ │ │ │ │          "813": [270, 880, 1069, 1229, 1312, 1466, 1986],
│ │ │ │ │          "81327024": 2635,
│ │ │ │ │          "81349206": [1113, 1543],
│ │ │ │ │ -        "81698516": 2488,
│ │ │ │ │ -        "81716537": 2461,
│ │ │ │ │          "81814867": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "8192": [72, 517, 2092, 2619],
│ │ │ │ │          "82": [1650, 2323, 2367, 2414, 2463, 2657, 2666],
│ │ │ │ │          "8207540608310198": [2353, 2400, 2450],
│ │ │ │ │          "82276161": 349,
│ │ │ │ │          "8230": [2353, 2400, 2450],
│ │ │ │ │          "82485143": 2635,
│ │ │ │ │ @@ -35582,15 +35580,14 @@
│ │ │ │ │          "826716f": 2521,
│ │ │ │ │          "82743037": 524,
│ │ │ │ │          "82770259": 2666,
│ │ │ │ │          "8277025938204418": 2666,
│ │ │ │ │          "827941": [514, 680, 2659],
│ │ │ │ │          "82842712": [642, 644],
│ │ │ │ │          "83": [2105, 2167, 2353, 2400, 2450, 2554, 2657],
│ │ │ │ │ -        "83003832": 2488,
│ │ │ │ │          "83314899": 1154,
│ │ │ │ │          "83333333": 1702,
│ │ │ │ │          "833333333333333": [893, 1083, 1143, 2240],
│ │ │ │ │          "8341": 2528,
│ │ │ │ │          "8346": 2528,
│ │ │ │ │          "83571711": 349,
│ │ │ │ │          "83697020e": [470, 1899, 1900],
│ │ │ │ │ @@ -35604,14 +35601,15 @@
│ │ │ │ │          "84147098j": 2666,
│ │ │ │ │          "841471": 2642,
│ │ │ │ │          "842523": 2515,
│ │ │ │ │          "84680802e": 2104,
│ │ │ │ │          "8480354764257312": 653,
│ │ │ │ │          "85": [409, 2657],
│ │ │ │ │          "85099543": 1822,
│ │ │ │ │ +        "851": 2461,
│ │ │ │ │          "85355339": 1756,
│ │ │ │ │          "85569": 2098,
│ │ │ │ │          "85602287": [2335, 2378, 2425],
│ │ │ │ │          "857": 410,
│ │ │ │ │          "8570331885190563e": [648, 653],
│ │ │ │ │          "85715698e": 2171,
│ │ │ │ │          "8577": 2539,
│ │ │ │ │ @@ -35621,17 +35619,19 @@
│ │ │ │ │          "8601": [55, 62, 67, 2613],
│ │ │ │ │          "86260211e": 54,
│ │ │ │ │          "8630830": 13,
│ │ │ │ │          "86399": 55,
│ │ │ │ │          "86400": 55,
│ │ │ │ │          "86401": 55,
│ │ │ │ │          "8660254": 2103,
│ │ │ │ │ +        "86732915": 2461,
│ │ │ │ │          "86820401": [2345, 2391, 2439],
│ │ │ │ │          "86864911e": 1586,
│ │ │ │ │          "87": [2616, 2657],
│ │ │ │ │ +        "87415296": 2461,
│ │ │ │ │          "875": [478, 2491],
│ │ │ │ │          "8755": [186, 827, 999, 1172, 1259, 1414, 1933],
│ │ │ │ │          "87649168120691": 674,
│ │ │ │ │          "8770": [2353, 2400, 2450],
│ │ │ │ │          "88": [408, 2462, 2463, 2657, 2659, 2668],
│ │ │ │ │          "8801": [99, 906],
│ │ │ │ │          "88031624": 2666,
│ │ │ │ │ @@ -35668,15 +35668,15 @@
│ │ │ │ │          "90476190e": 1816,
│ │ │ │ │          "90909091": 136,
│ │ │ │ │          "909297": 2642,
│ │ │ │ │          "90929743": 2666,
│ │ │ │ │          "91": 2657,
│ │ │ │ │          "91275558": 2635,
│ │ │ │ │          "916666666666666": 1240,
│ │ │ │ │ -        "92": [98, 2461, 2657, 2659],
│ │ │ │ │ +        "92": [98, 2657, 2659],
│ │ │ │ │          "921fb54442d18p": 2520,
│ │ │ │ │          "9223372036854775807": 2648,
│ │ │ │ │          "9223372036854775808": 2648,
│ │ │ │ │          "92346708": 349,
│ │ │ │ │          "92362781e": 2104,
│ │ │ │ │          "92387953": 642,
│ │ │ │ │          "92387953j": 642,
│ │ │ │ │ @@ -35704,15 +35704,14 @@
│ │ │ │ │          "9373": 2532,
│ │ │ │ │          "9374": 2532,
│ │ │ │ │          "9376": 2532,
│ │ │ │ │          "9377": 2532,
│ │ │ │ │          "93773029": 349,
│ │ │ │ │          "9378": 2532,
│ │ │ │ │          "9379": 2532,
│ │ │ │ │ -        "939": 2461,
│ │ │ │ │          "9390": [2533, 2534],
│ │ │ │ │          "94": [409, 669, 2635, 2657],
│ │ │ │ │          "940": 2587,
│ │ │ │ │          "941257": 2635,
│ │ │ │ │          "94125714": 2635,
│ │ │ │ │          "94708397920832": 2642,
│ │ │ │ │          "9475673279178444": 2348,
│ │ │ │ │ @@ -35771,15 +35770,14 @@
│ │ │ │ │          "9800": 2666,
│ │ │ │ │          "9801": 2666,
│ │ │ │ │          "9802": 2666,
│ │ │ │ │          "98024613": 680,
│ │ │ │ │          "9807642": 1153,
│ │ │ │ │          "981": 2592,
│ │ │ │ │          "98136677": 523,
│ │ │ │ │ -        "98353266": 2461,
│ │ │ │ │          "987": 28,
│ │ │ │ │          "987654321": 2393,
│ │ │ │ │          "98935825": 2666,
│ │ │ │ │          "9897": 2666,
│ │ │ │ │          "9898": 2666,
│ │ │ │ │          "9899": [105, 130, 2666],
│ │ │ │ │          "99": [12, 302, 408, 544, 672, 1096, 1906, 2131, 2460, 2635, 2657, 2658, 2666],
│ │ │ │ │ @@ -35789,14 +35787,15 @@
│ │ │ │ │          "9902": 2666,
│ │ │ │ │          "990278": 2635,
│ │ │ │ │          "99027828": 2635,
│ │ │ │ │          "99060736": 2666,
│ │ │ │ │          "99091858": [2345, 2391, 2439],
│ │ │ │ │          "99149989": [2345, 2391, 2439],
│ │ │ │ │          "9917": 2343,
│ │ │ │ │ +        "9917921": 2461,
│ │ │ │ │          "99256089": 349,
│ │ │ │ │          "99322285": [88, 101],
│ │ │ │ │          "99394529": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "99417356": 1754,
│ │ │ │ │          "99507202": 349,
│ │ │ │ │          "99734545": 1154,
│ │ │ │ │          "998": 2535,