--- /srv/rebuilderd/tmp/rebuilderdv2t3i6/inputs/python-numpy-doc_2.2.4+ds-1_all.deb
+++ /srv/rebuilderd/tmp/rebuilderdv2t3i6/out/python-numpy-doc_2.2.4+ds-1_all.deb
├── file list
│ @@ -1,3 +1,3 @@
│  -rw-r--r--   0        0        0        4 2025-04-01 19:45:23.000000 debian-binary
│ --rw-r--r--   0        0        0    64868 2025-04-01 19:45:23.000000 control.tar.xz
│ --rw-r--r--   0        0        0  5748876 2025-04-01 19:45:23.000000 data.tar.xz
│ +-rw-r--r--   0        0        0    64884 2025-04-01 19:45:23.000000 control.tar.xz
│ +-rw-r--r--   0        0        0  5748940 2025-04-01 19:45:23.000000 data.tar.xz
├── control.tar.xz
│ ├── control.tar
│ │ ├── ./md5sums
│ │ │ ├── ./md5sums
│ │ │ │┄ Files differ
├── data.tar.xz
│ ├── data.tar
│ │ ├── file list
│ │ │ @@ -2578,15 +2578,15 @@
│ │ │  -rw-r--r--   0 root         (0) root         (0)    42758 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    47423 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    45546 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    82403 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    45982 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    89078 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    35540 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ --rw-r--r--   0 root         (0) root         (0)    44354 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ +-rw-r--r--   0 root         (0) root         (0)    44350 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    52723 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    38070 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    41915 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    45998 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    50957 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    27535 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    54450 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ @@ -2755,15 +2755,15 @@
│ │ │  -rw-r--r--   0 root         (0) root         (0)    31655 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    32348 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    32865 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.3-notes.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    32016 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.4-notes.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    13407 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    90990 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    12397 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ --rw-r--r--   0 root         (0) root         (0)  2687918 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ +-rw-r--r--   0 root         (0) root         (0)  2687952 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │  -rw-r--r--   0 root         (0) root         (0)   177614 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    64100 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │  -rw-r--r--   0 root         (0) root         (0)    18746 2025-04-01 19:45:23.000000 ./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">1.28 ms +- 15.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ -<span class="go">2.24 ms +- 23.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">1.39 ms +- 38.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">2.58 ms +- 168 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">626 us +- 7.21 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ -<span class="go">1.56 ms +- 15.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">675 us +- 116 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">1.97 ms +- 151 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">2.3 ms +- 8.81 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ -<span class="go">4.41 ms +- 9.56 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">2.75 ms +- 162 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ +<span class="go">5.22 ms +- 427 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([0.20603939, 0.47061387, 0.86256701])</span>
│ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.27516724, 0.24118272, 0.86169933])</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([0.18358761, 0.15874952, 0.03037512], dtype=float32)</span>
│ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.6148415 , 0.18180382, 0.2537861 ], 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([217,  76,  75], dtype=uint8)</span>
│ │ │ +<span class="gh">Out[9]: </span><span class="go">array([159, 110, 234], 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([0.05299698, 0.2293819 ])</span>
│ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.76927745, 0.26405331])</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">[0.05299698 0.2293819  0.         0.        ]</span>
│ │ │ +<span class="go">[0.76927745 0.26405331 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([[ 1,  2,  3,  0,  1],</span>
│ │ │ -<span class="go">       [ 5,  6,  7,  4,  5],</span>
│ │ │ -<span class="go">       [ 9, 10, 11,  8,  9]])</span>
│ │ │ +<span class="go">array([[ 2,  1,  2,  0,  2],</span>
│ │ │ +<span class="go">       [ 6,  5,  6,  4,  6],</span>
│ │ │ +<span class="go">       [10,  9, 10,  8, 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,  2,  0,  1],</span>
│ │ │ -<span class="go">       [ 7,  6,  4,  5],</span>
│ │ │ -<span class="go">       [11, 10,  8,  9]])</span>
│ │ │ +<span class="go">array([[ 1,  2,  3,  0],</span>
│ │ │ +<span class="go">       [ 5,  6,  7,  4],</span>
│ │ │ +<span class="go">       [ 9, 10, 11,  8]])</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)
│ │ │ │     ...:
│ │ │ │ -1.28 ms +- 15.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -2.24 ms +- 23.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +1.39 ms +- 38.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +2.58 ms +- 168 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)
│ │ │ │     ...:
│ │ │ │ -626 us +- 7.21 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -1.56 ms +- 15.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +675 us +- 116 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +1.97 ms +- 151 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)
│ │ │ │     ...:
│ │ │ │ -2.3 ms +- 8.81 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -4.41 ms +- 9.56 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +2.75 ms +- 162 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +5.22 ms +- 427 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([0.20603939, 0.47061387, 0.86256701])
│ │ │ │ +Out[7]: array([0.27516724, 0.24118272, 0.86169933])
│ │ │ │  
│ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ -Out[8]: array([0.18358761, 0.15874952, 0.03037512], dtype=float32)
│ │ │ │ +Out[8]: array([0.6148415 , 0.18180382, 0.2537861 ], dtype=float32)
│ │ │ │  
│ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ -Out[9]: array([217,  76,  75], dtype=uint8)
│ │ │ │ +Out[9]: array([159, 110, 234], 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([0.05299698, 0.2293819 ])
│ │ │ │ +Out[12]: array([0.76927745, 0.26405331])
│ │ │ │  
│ │ │ │  In [13]: print(existing)
│ │ │ │ -[0.05299698 0.2293819  0.         0.        ]
│ │ │ │ +[0.76927745 0.26405331 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([[ 1,  2,  3,  0,  1],
│ │ │ │ -       [ 5,  6,  7,  4,  5],
│ │ │ │ -       [ 9, 10, 11,  8,  9]])
│ │ │ │ +array([[ 2,  1,  2,  0,  2],
│ │ │ │ +       [ 6,  5,  6,  4,  6],
│ │ │ │ +       [10,  9, 10,  8, 10]])
│ │ │ │  
│ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │  
│ │ │ │  In [19]: a
│ │ │ │  Out[19]:
│ │ │ │ -array([[ 3,  2,  0,  1],
│ │ │ │ -       [ 7,  6,  4,  5],
│ │ │ │ -       [11, 10,  8,  9]])
│ │ │ │ +array([[ 1,  2,  3,  0],
│ │ │ │ +       [ 5,  6,  7,  4],
│ │ │ │ +       [ 9, 10, 11,  8]])
│ │ │ │      * 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([ 1.33339157, -1.74432687])</span>
│ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 0.97479468, -0.47053287])</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([4.2559352 , 6.00026207], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([3.91604321, 4.38657608], 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([-1.74432687,  1.33339157], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.47053287,  0.97479468], 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([ 1.33339157, -1.74432687])
│ │ │ │ +Out[4]: array([ 0.97479468, -0.47053287])
│ │ │ │  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([4.2559352 , 6.00026207], domain=[0., 9.], window=[-1.,
│ │ │ │ +Out[6]: Polynomial([3.91604321, 4.38657608], 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([-1.74432687,  1.33339157], domain=[-1.,  1.], window=[-1.,
│ │ │ │ +Out[7]: Polynomial([-0.47053287,  0.97479468], 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 {}
│ │ │ │ @@ -32314,15 +32314,14 @@
│ │ │ │          "00010001": [140, 146],
│ │ │ │          "00011100": 146,
│ │ │ │          "00011101": 144,
│ │ │ │          "00012": 137,
│ │ │ │          "00016403": 1640,
│ │ │ │          "0001e10": [91, 548],
│ │ │ │          "0002": 2607,
│ │ │ │ -        "00026207": 2488,
│ │ │ │          "0003": [1596, 1653, 1710, 1767, 1824, 1879, 1893, 2607],
│ │ │ │          "0003163943736596009": 2315,
│ │ │ │          "00032805": 1697,
│ │ │ │          "000e": [410, 2658],
│ │ │ │          "000j": 1335,
│ │ │ │          "001": [335, 420, 947, 1541, 1596, 1602, 1653, 1659, 1710, 1716, 1767, 1773, 1824, 1830, 1879, 1886, 1893, 2160],
│ │ │ │          "0010": 1519,
│ │ │ │ @@ -32370,15 +32369,14 @@
│ │ │ │          "02654825": 1891,
│ │ │ │          "02658058e": 2666,
│ │ │ │          "02755911": 2666,
│ │ │ │          "027559113243068367": 2666,
│ │ │ │          "02785049": 1867,
│ │ │ │          "02i": [513, 2644],
│ │ │ │          "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2658],
│ │ │ │ -        "03037512": 2461,
│ │ │ │          "03125": [1585, 2491],
│ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │          "0361": 2607,
│ │ │ │          "03703704": 1809,
│ │ │ │          "03943254e": 2104,
│ │ │ │          "03968254": [1113, 1543],
│ │ │ │          "0396842": 680,
│ │ │ │ @@ -32391,15 +32389,14 @@
│ │ │ │          "04551152e": 2104,
│ │ │ │          "04719755": 1911,
│ │ │ │          "05": [55, 91, 163, 410, 548, 669, 896, 1095, 1871, 2083, 2173, 2353, 2400, 2450, 2648],
│ │ │ │          "0500": 360,
│ │ │ │          "05093587": 2635,
│ │ │ │          "05208333": 1585,
│ │ │ │          "05263157894736836": 2257,
│ │ │ │ -        "05299698": 2461,
│ │ │ │          "0549999999999997": 2083,
│ │ │ │          "055": 2083,
│ │ │ │          "0596779": 1153,
│ │ │ │          "06": [55, 566, 2083, 2508],
│ │ │ │          "0614962j": [439, 453],
│ │ │ │          "0625": [418, 624, 1645],
│ │ │ │          "06369197489564249": 2458,
│ │ │ │ @@ -32587,15 +32584,15 @@
│ │ │ │          "10_qbz5n2kfra8p0": 42,
│ │ │ │          "10j": 2665,
│ │ │ │          "10n": 2336,
│ │ │ │          "10th": [87, 88, 100, 101, 102, 103, 104, 106, 125, 126, 129, 131, 533, 670, 671, 672],
│ │ │ │          "10x": [2594, 2602, 2616, 2622],
│ │ │ │          "10x100": 652,
│ │ │ │          "11": [8, 38, 42, 47, 54, 55, 58, 59, 60, 61, 62, 73, 79, 98, 107, 108, 135, 137, 138, 140, 141, 250, 270, 296, 336, 354, 364, 366, 367, 375, 435, 513, 520, 530, 628, 653, 664, 880, 893, 905, 941, 963, 1069, 1083, 1107, 1114, 1122, 1123, 1124, 1131, 1143, 1159, 1160, 1161, 1164, 1166, 1167, 1193, 1194, 1195, 1204, 1205, 1206, 1212, 1213, 1218, 1228, 1229, 1236, 1240, 1247, 1249, 1301, 1312, 1455, 1466, 1510, 1557, 1580, 1601, 1618, 1640, 1644, 1654, 1656, 1658, 1675, 1697, 1715, 1732, 1754, 1759, 1762, 1772, 1789, 1811, 1818, 1829, 1846, 1867, 1885, 1912, 1975, 1986, 2080, 2083, 2089, 2091, 2115, 2125, 2180, 2184, 2204, 2205, 2206, 2208, 2209, 2210, 2225, 2237, 2240, 2246, 2248, 2316, 2333, 2336, 2342, 2353, 2361, 2377, 2379, 2390, 2400, 2408, 2424, 2426, 2438, 2450, 2457, 2461, 2491, 2513, 2519, 2520, 2522, 2535, 2539, 2547, 2554, 2560, 2571, 2576, 2577, 2578, 2579, 2580, 2581, 2587, 2588, 2590, 2591, 2592, 2593, 2594, 2595, 2596, 2597, 2598, 2599, 2600, 2601, 2602, 2622, 2627, 2635, 2637, 2638, 2641, 2645, 2648, 2657, 2665, 2666],
│ │ │ │ -        "110": [38, 136, 409, 523, 542, 968, 969, 2666],
│ │ │ │ +        "110": [38, 136, 409, 523, 542, 968, 969, 2461, 2666],
│ │ │ │          "1100": [140, 1519],
│ │ │ │          "1101": 2463,
│ │ │ │          "1109": 457,
│ │ │ │          "110m": 409,
│ │ │ │          "111": [2463, 2637],
│ │ │ │          "11100": 146,
│ │ │ │          "11101": [138, 144],
│ │ │ │ @@ -32625,15 +32622,15 @@
│ │ │ │          "114": 2463,
│ │ │ │          "11407192": 1822,
│ │ │ │          "1142": [2353, 2400, 2450],
│ │ │ │          "1149": 2612,
│ │ │ │          "115": [1654, 2463],
│ │ │ │          "1151": 657,
│ │ │ │          "11525": 2547,
│ │ │ │ -        "116": 2463,
│ │ │ │ +        "116": [2461, 2463],
│ │ │ │          "11625": [2543, 2544, 2545, 2546],
│ │ │ │          "11647": 2543,
│ │ │ │          "11648": 2543,
│ │ │ │          "11657": 2543,
│ │ │ │          "11659149": [2345, 2391, 2439],
│ │ │ │          "11661": 2543,
│ │ │ │          "11665": 2543,
│ │ │ │ @@ -32984,15 +32981,15 @@
│ │ │ │          "1500000": 2635,
│ │ │ │          "15006": 2588,
│ │ │ │          "15012": 2560,
│ │ │ │          "15028c96": 2668,
│ │ │ │          "15038": 2559,
│ │ │ │          "15067": 2559,
│ │ │ │          "15068": 2560,
│ │ │ │ -        "151": [2358, 2405, 2455, 2463],
│ │ │ │ +        "151": [2358, 2405, 2455, 2461, 2463],
│ │ │ │          "15113": 2560,
│ │ │ │          "15118": 2566,
│ │ │ │          "15119": 2566,
│ │ │ │          "15121": 2572,
│ │ │ │          "15158": 2561,
│ │ │ │          "15159": 2561,
│ │ │ │          "15161": 2561,
│ │ │ │ @@ -33056,19 +33053,18 @@
│ │ │ │          "1582": 55,
│ │ │ │          "15840": 2566,
│ │ │ │          "15844": 2588,
│ │ │ │          "15852": 2572,
│ │ │ │          "15867": 2566,
│ │ │ │          "15870": 2566,
│ │ │ │          "15872": 2566,
│ │ │ │ -        "15874952": 2461,
│ │ │ │          "15882": 2566,
│ │ │ │          "15886": 2572,
│ │ │ │          "15888336": 680,
│ │ │ │ -        "159": 2463,
│ │ │ │ +        "159": [2461, 2463],
│ │ │ │          "15900": 2572,
│ │ │ │          "15916": 2563,
│ │ │ │          "15929": 2563,
│ │ │ │          "15930": 2563,
│ │ │ │          "15954": 2563,
│ │ │ │          "1597": 28,
│ │ │ │          "1599": 1643,
│ │ │ │ @@ -33098,15 +33094,15 @@
│ │ │ │          "16128": 2566,
│ │ │ │          "16132": 2564,
│ │ │ │          "16134": 2572,
│ │ │ │          "16153": 2566,
│ │ │ │          "16154": 2594,
│ │ │ │          "16156": 2572,
│ │ │ │          "16161": 2572,
│ │ │ │ -        "162": 2463,
│ │ │ │ +        "162": [2461, 2463],
│ │ │ │          "16200": 2572,
│ │ │ │          "1621": [1913, 2236],
│ │ │ │          "1622776601683795": 637,
│ │ │ │          "16232": 2572,
│ │ │ │          "16236208e": 2104,
│ │ │ │          "16350": 2572,
│ │ │ │          "16354": 2660,
│ │ │ │ @@ -33152,15 +33148,15 @@
│ │ │ │          "16772": 2567,
│ │ │ │          "16776": 2567,
│ │ │ │          "16779": 2567,
│ │ │ │          "1678": 55,
│ │ │ │          "16780": 2567,
│ │ │ │          "16784": 2567,
│ │ │ │          "16795": 2567,
│ │ │ │ -        "168": 2463,
│ │ │ │ +        "168": [2461, 2463],
│ │ │ │          "16815": 2572,
│ │ │ │          "16830": 2588,
│ │ │ │          "16832": 2567,
│ │ │ │          "16841": 2572,
│ │ │ │          "16872": 2567,
│ │ │ │          "16875": 2567,
│ │ │ │          "16904": 2567,
│ │ │ │ @@ -33264,14 +33260,15 @@
│ │ │ │          "18036": 2571,
│ │ │ │          "1805": [2328, 2477],
│ │ │ │          "18053": 2599,
│ │ │ │          "18070": 2576,
│ │ │ │          "181": 2327,
│ │ │ │          "18110": 2576,
│ │ │ │          "18114": 2571,
│ │ │ │ +        "18180382": 2461,
│ │ │ │          "18181818": 136,
│ │ │ │          "182": [1526, 2463],
│ │ │ │          "18249173": 1153,
│ │ │ │          "18306": 2573,
│ │ │ │          "18310": 2573,
│ │ │ │          "18322": 2576,
│ │ │ │          "18326": 2573,
│ │ │ │ @@ -33284,15 +33281,14 @@
│ │ │ │          "18345": 2573,
│ │ │ │          "18351": 2573,
│ │ │ │          "18352": 2573,
│ │ │ │          "18353": 2573,
│ │ │ │          "18354": 2573,
│ │ │ │          "18356": 2573,
│ │ │ │          "18357": 2573,
│ │ │ │ -        "18358761": 2461,
│ │ │ │          "18359": 2573,
│ │ │ │          "1837": 2611,
│ │ │ │          "1838": 2611,
│ │ │ │          "18382": 2574,
│ │ │ │          "184": [520, 2572],
│ │ │ │          "1843": 2611,
│ │ │ │          "18459": 2574,
│ │ │ │ @@ -33609,15 +33605,14 @@
│ │ │ │          "20495": 2581,
│ │ │ │          "20497": 2581,
│ │ │ │          "20500": 2588,
│ │ │ │          "2052": 2615,
│ │ │ │          "20580": 2588,
│ │ │ │          "20589": 2588,
│ │ │ │          "206": 2463,
│ │ │ │ -        "20603939": 2461,
│ │ │ │          "20613": 2581,
│ │ │ │          "20618": 2581,
│ │ │ │          "2063": 2612,
│ │ │ │          "207": 2463,
│ │ │ │          "20702": 2584,
│ │ │ │          "20703": 2584,
│ │ │ │          "20704": 2584,
│ │ │ │ @@ -33670,15 +33665,15 @@
│ │ │ │          "20985": 2585,
│ │ │ │          "20986": 2585,
│ │ │ │          "20992": 2585,
│ │ │ │          "20993": 2588,
│ │ │ │          "20_ver": 0,
│ │ │ │          "20count": 141,
│ │ │ │          "20d03bcfd": 0,
│ │ │ │ -        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2461, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2635, 2637, 2641, 2642, 2649, 2654, 2657, 2665, 2666, 2668],
│ │ │ │ +        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2635, 2637, 2641, 2642, 2649, 2654, 2657, 2665, 2666, 2668],
│ │ │ │          "210": 363,
│ │ │ │          "21001": 2588,
│ │ │ │          "21029": 2588,
│ │ │ │          "210306068529402873165736369884012333109": [2275, 2280],
│ │ │ │          "21048": 2586,
│ │ │ │          "211": 2491,
│ │ │ │          "21106": 2586,
│ │ │ │ @@ -33737,15 +33732,14 @@
│ │ │ │          "2155": [305, 2134],
│ │ │ │          "21595": 2594,
│ │ │ │          "216": 2666,
│ │ │ │          "21623": [2588, 2594],
│ │ │ │          "21627": 2594,
│ │ │ │          "21645": 2594,
│ │ │ │          "21663": 2588,
│ │ │ │ -        "217": 2461,
│ │ │ │          "21760": 2622,
│ │ │ │          "218": [566, 2463],
│ │ │ │          "21807": 2594,
│ │ │ │          "2184": 2225,
│ │ │ │          "21866": 2589,
│ │ │ │          "21867": 2589,
│ │ │ │          "21868": 2589,
│ │ │ │ @@ -33754,15 +33748,15 @@
│ │ │ │          "219": 2463,
│ │ │ │          "21925": 2594,
│ │ │ │          "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, 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, 2461, 2513, 2517, 2519, 2534, 2588, 2635, 2637, 2641, 2657, 2666],
│ │ │ │          "220": [2238, 2576],
│ │ │ │          "22004": 2594,
│ │ │ │          "22014": 2594,
│ │ │ │          "22030": 2590,
│ │ │ │          "22031": 2590,
│ │ │ │          "22032": 2590,
│ │ │ │          "22033": 2590,
│ │ │ │ @@ -33886,15 +33880,14 @@
│ │ │ │          "22867": 2595,
│ │ │ │          "22868": 2595,
│ │ │ │          "22875": 2595,
│ │ │ │          "22877": 2595,
│ │ │ │          "22883": 2595,
│ │ │ │          "22884": 2595,
│ │ │ │          "22887": 2595,
│ │ │ │ -        "2293819": 2461,
│ │ │ │          "22959": 2596,
│ │ │ │          "22963": 2599,
│ │ │ │          "22965": 2596,
│ │ │ │          "22966": 2596,
│ │ │ │          "22967": 2596,
│ │ │ │          "22968": 2596,
│ │ │ │          "22969": 2596,
│ │ │ │ @@ -33903,15 +33896,15 @@
│ │ │ │          "22972": 2596,
│ │ │ │          "22976": 2596,
│ │ │ │          "22982": 2599,
│ │ │ │          "22989": 2596,
│ │ │ │          "22997": 2599,
│ │ │ │          "22998": 2599,
│ │ │ │          "22e": 457,
│ │ │ │ -        "23": [1, 8, 10, 18, 32, 43, 47, 54, 55, 58, 62, 63, 75, 79, 98, 135, 139, 163, 270, 287, 329, 336, 483, 513, 628, 669, 880, 905, 917, 1029, 1069, 1104, 1229, 1241, 1312, 1324, 1466, 1478, 1545, 1707, 1748, 1777, 1903, 1913, 1986, 1998, 2154, 2208, 2235, 2237, 2256, 2321, 2340, 2342, 2365, 2383, 2412, 2430, 2461, 2513, 2519, 2542, 2552, 2595, 2622, 2627, 2635, 2637, 2641, 2645, 2648, 2657, 2666],
│ │ │ │ +        "23": [1, 8, 10, 18, 32, 43, 47, 54, 55, 58, 62, 63, 75, 79, 98, 135, 139, 163, 270, 287, 329, 336, 483, 513, 628, 669, 880, 905, 917, 1029, 1069, 1104, 1229, 1241, 1312, 1324, 1466, 1478, 1545, 1707, 1748, 1777, 1903, 1913, 1986, 1998, 2154, 2208, 2235, 2237, 2256, 2321, 2340, 2342, 2365, 2383, 2412, 2430, 2513, 2519, 2542, 2552, 2595, 2622, 2627, 2635, 2637, 2641, 2645, 2648, 2657, 2666],
│ │ │ │          "230": 409,
│ │ │ │          "230000071797338e": 477,
│ │ │ │          "23011": 2599,
│ │ │ │          "23019": 2599,
│ │ │ │          "23020": 2599,
│ │ │ │          "23030": 2596,
│ │ │ │          "23031": 2596,
│ │ │ │ @@ -33953,15 +33946,15 @@
│ │ │ │          "23345": 2597,
│ │ │ │          "23357": 2599,
│ │ │ │          "23358": 2599,
│ │ │ │          "23370": 2597,
│ │ │ │          "23371": 2599,
│ │ │ │          "23376": 2599,
│ │ │ │          "23385948e": 54,
│ │ │ │ -        "234": 55,
│ │ │ │ +        "234": [55, 2461],
│ │ │ │          "23403": 2599,
│ │ │ │          "2345672e": 2172,
│ │ │ │          "234567e": 2172,
│ │ │ │          "23480": 2599,
│ │ │ │          "23528": 2599,
│ │ │ │          "23543": 2597,
│ │ │ │          "23544": 2597,
│ │ │ │ @@ -33998,15 +33991,15 @@
│ │ │ │          "23936": 2622,
│ │ │ │          "2394691": 2312,
│ │ │ │          "23968": 2600,
│ │ │ │          "23994": 2598,
│ │ │ │          "23998": 2622,
│ │ │ │          "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, 2461, 2463, 2513, 2519, 2543, 2555, 2622, 2623, 2635, 2641, 2645, 2649, 2652, 2657, 2659, 2666, 2668],
│ │ │ │ +        "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,
│ │ │ │          "24018": 2622,
│ │ │ │          "2403": 2615,
│ │ │ │          "24036": 2600,
│ │ │ │          "24037": 2600,
│ │ │ │          "24038": 2600,
│ │ │ │ @@ -34014,14 +34007,15 @@
│ │ │ │          "24053": [2602, 2622],
│ │ │ │          "24074": 2600,
│ │ │ │          "240820": 2635,
│ │ │ │          "24082018": 2635,
│ │ │ │          "24085": 2622,
│ │ │ │          "24117": 2600,
│ │ │ │          "24118": 2600,
│ │ │ │ +        "24118272": 2461,
│ │ │ │          "24119": 2600,
│ │ │ │          "24120": 2600,
│ │ │ │          "24122": 2600,
│ │ │ │          "24126": 2622,
│ │ │ │          "24127": 2600,
│ │ │ │          "24128": 2600,
│ │ │ │          "24129": 2600,
│ │ │ │ @@ -34251,14 +34245,15 @@
│ │ │ │          "25276297": 2655,
│ │ │ │          "25292": 2622,
│ │ │ │          "253": 2652,
│ │ │ │          "25323": 2606,
│ │ │ │          "25347": 2622,
│ │ │ │          "25377": 2605,
│ │ │ │          "25378": 2605,
│ │ │ │ +        "2537861": 2461,
│ │ │ │          "25379": 2605,
│ │ │ │          "25380": 2605,
│ │ │ │          "25388": 2622,
│ │ │ │          "254": [143, 570],
│ │ │ │          "25409": 2622,
│ │ │ │          "25419": 2605,
│ │ │ │          "25420": 2605,
│ │ │ │ @@ -34293,15 +34288,14 @@
│ │ │ │          "25536": 2622,
│ │ │ │          "25539": 2606,
│ │ │ │          "25553": 2622,
│ │ │ │          "25557246e": 438,
│ │ │ │          "25570": 2622,
│ │ │ │          "25584": 2606,
│ │ │ │          "25585": 2606,
│ │ │ │ -        "2559352": 2488,
│ │ │ │          "25599": 2606,
│ │ │ │          "256": [69, 186, 287, 333, 418, 438, 514, 624, 827, 999, 1172, 1241, 1259, 1324, 1414, 1478, 1933, 1998, 2158, 2290, 2303, 2304, 2461, 2462, 2613, 2637, 2650],
│ │ │ │          "2561": 2615,
│ │ │ │          "25618": 2606,
│ │ │ │          "25619": 2606,
│ │ │ │          "25620": 2606,
│ │ │ │          "25630": 2606,
│ │ │ │ @@ -34351,14 +34345,15 @@
│ │ │ │          "262": 2666,
│ │ │ │          "26268": 2625,
│ │ │ │          "26285": 2625,
│ │ │ │          "26292": 2625,
│ │ │ │          "26313": 2625,
│ │ │ │          "26388": 2625,
│ │ │ │          "26393": 2622,
│ │ │ │ +        "26405331": 2461,
│ │ │ │          "26452": 2625,
│ │ │ │          "26501": 2625,
│ │ │ │          "26579": 2625,
│ │ │ │          "26580": 2625,
│ │ │ │          "26590556": 2635,
│ │ │ │          "26598632": 1228,
│ │ │ │          "266": 2463,
│ │ │ │ @@ -34463,14 +34458,15 @@
│ │ │ │          "27480": 2627,
│ │ │ │          "27481": 2627,
│ │ │ │          "27482": 2629,
│ │ │ │          "27484": 2627,
│ │ │ │          "27501": 2627,
│ │ │ │          "27506": 2627,
│ │ │ │          "27512": 2628,
│ │ │ │ +        "27516724": 2461,
│ │ │ │          "27537": 2628,
│ │ │ │          "27538": 2628,
│ │ │ │          "27539": 2628,
│ │ │ │          "27543": 2628,
│ │ │ │          "27549": 2628,
│ │ │ │          "27561": 2628,
│ │ │ │          "27562": 2628,
│ │ │ │ @@ -34516,15 +34512,15 @@
│ │ │ │          "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,
│ │ │ │          "28007": 2630,
│ │ │ │          "2801": 2613,
│ │ │ │          "28021": 2630,
│ │ │ │          "28044": 2630,
│ │ │ │ @@ -34734,15 +34730,14 @@
│ │ │ │          "33333": [2173, 2175],
│ │ │ │          "33333333": [1335, 1544, 1702, 1750, 1771, 1812, 1816, 1818, 1819, 1863, 1865, 2491, 2645],
│ │ │ │          "333333333": 2171,
│ │ │ │          "3333333333333": 2171,
│ │ │ │          "33333334": 2171,
│ │ │ │          "3333333e": 1335,
│ │ │ │          "33339": 2173,
│ │ │ │ -        "33339157": 2488,
│ │ │ │          "33340274885464394": 2202,
│ │ │ │          "3340": [287, 1241, 1324, 1478, 1998],
│ │ │ │          "3348": 2617,
│ │ │ │          "33486982e": 438,
│ │ │ │          "3361": [99, 906],
│ │ │ │          "3364": 2615,
│ │ │ │          "3373": 2615,
│ │ │ │ @@ -34797,32 +34792,33 @@
│ │ │ │          "3743": 2615,
│ │ │ │          "375": [1634, 1663],
│ │ │ │          "37601032": [2387, 2434],
│ │ │ │          "377": 28,
│ │ │ │          "378": 652,
│ │ │ │          "379": 533,
│ │ │ │          "3793": 2615,
│ │ │ │ -        "38": [59, 542, 968, 969, 1545, 1752, 1761, 2107, 2204, 2208, 2313, 2333, 2361, 2377, 2408, 2424, 2510, 2572, 2657, 2666],
│ │ │ │ +        "38": [59, 542, 968, 969, 1545, 1752, 1761, 2107, 2204, 2208, 2313, 2333, 2361, 2377, 2408, 2424, 2461, 2510, 2572, 2657, 2666],
│ │ │ │          "380": [2238, 2576],
│ │ │ │          "38268343": 642,
│ │ │ │          "38268343j": 642,
│ │ │ │          "3832": 2615,
│ │ │ │          "38434191e": 660,
│ │ │ │          "38446749": 1867,
│ │ │ │          "385": [2270, 2300],
│ │ │ │          "3854": [287, 1241, 1324, 1478, 1998],
│ │ │ │ +        "38657608": 2488,
│ │ │ │          "38672696": [2352, 2399, 2449],
│ │ │ │          "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,
│ │ │ │          "39211752": 1153,
│ │ │ │          "39337286e": 1149,
│ │ │ │          "3971": 2615,
│ │ │ │ @@ -34861,15 +34857,15 @@
│ │ │ │          "4051": [2615, 2617],
│ │ │ │          "409": 2463,
│ │ │ │          "40918587e": 2104,
│ │ │ │          "40919914": 2666,
│ │ │ │          "4093": 2617,
│ │ │ │          "4094": [2615, 2617],
│ │ │ │          "4096": [72, 2092],
│ │ │ │ -        "41": [941, 1114, 1123, 1124, 1131, 1913, 2104, 2107, 2208, 2236, 2461, 2585, 2657, 2666],
│ │ │ │ +        "41": [941, 1114, 1123, 1124, 1131, 1913, 2104, 2107, 2208, 2236, 2585, 2657, 2666],
│ │ │ │          "4109": 2617,
│ │ │ │          "41211849": 2666,
│ │ │ │          "4123": [2615, 2617],
│ │ │ │          "4134": 2617,
│ │ │ │          "41357986e": 2175,
│ │ │ │          "4138": 2617,
│ │ │ │          "4141": 2615,
│ │ │ │ @@ -34904,14 +34900,15 @@
│ │ │ │          "4253": 2617,
│ │ │ │          "4254": 2617,
│ │ │ │          "4261": 2617,
│ │ │ │          "4262": 2617,
│ │ │ │          "4266": 2617,
│ │ │ │          "42667924": 1154,
│ │ │ │          "4267": 2617,
│ │ │ │ +        "427": 2461,
│ │ │ │          "4270": 2617,
│ │ │ │          "4276": 2617,
│ │ │ │          "429": 136,
│ │ │ │          "4294967293": 2639,
│ │ │ │          "4294967296": [196, 836, 1008, 1179, 1266, 1421, 1940],
│ │ │ │          "43": [2208, 2583, 2635, 2641, 2657, 2666],
│ │ │ │          "430148": 2635,
│ │ │ │ @@ -34981,15 +34978,15 @@
│ │ │ │          "46755891e": 54,
│ │ │ │          "468": [136, 147],
│ │ │ │          "4685006": [2352, 2399, 2449],
│ │ │ │          "4686": 12,
│ │ │ │          "46957616e": [470, 1899, 1900],
│ │ │ │          "47": [52, 2208, 2323, 2367, 2414, 2657, 2666],
│ │ │ │          "4702687338396767": 2348,
│ │ │ │ -        "47061387": 2461,
│ │ │ │ +        "47053287": 2488,
│ │ │ │          "471": [136, 147, 2463],
│ │ │ │          "47108547995356098": [2345, 2391, 2439],
│ │ │ │          "47140452j": 2491,
│ │ │ │          "472": 55,
│ │ │ │          "4722": 2618,
│ │ │ │          "4723": 2621,
│ │ │ │          "4730": [409, 661, 2168],
│ │ │ │ @@ -35141,15 +35138,15 @@
│ │ │ │          "55458479": 349,
│ │ │ │          "55490914e": 2666,
│ │ │ │          "5555555555555554": 1349,
│ │ │ │          "55627469": 349,
│ │ │ │          "55645993": 2635,
│ │ │ │          "5580": 2535,
│ │ │ │          "55914881e": 2104,
│ │ │ │ -        "56": [52, 55, 61, 544, 1764, 2204, 2461, 2463, 2657, 2659],
│ │ │ │ +        "56": [52, 55, 61, 544, 1764, 2204, 2463, 2657, 2659],
│ │ │ │          "5612": 2621,
│ │ │ │          "5614": 2522,
│ │ │ │          "562": [680, 2659],
│ │ │ │          "5620499351813308": 86,
│ │ │ │          "5625": 2491,
│ │ │ │          "56294995342131": 2083,
│ │ │ │          "5640": [2353, 2400, 2450],
│ │ │ │ @@ -35166,15 +35163,15 @@
│ │ │ │          "576": 2615,
│ │ │ │          "57721": [2326, 2371, 2418],
│ │ │ │          "5772156649015328606065120900824024310421": 76,
│ │ │ │          "5773": 2522,
│ │ │ │          "57860025": 1154,
│ │ │ │          "579365079365115": [1113, 1543],
│ │ │ │          "57x": 2594,
│ │ │ │ -        "58": [669, 1748, 1777, 2204, 2208, 2332, 2376, 2423, 2464, 2572, 2635, 2657],
│ │ │ │ +        "58": [669, 1748, 1777, 2204, 2208, 2332, 2376, 2423, 2461, 2464, 2572, 2635, 2657],
│ │ │ │          "582892": 2635,
│ │ │ │          "58289208": 2635,
│ │ │ │          "584388": 55,
│ │ │ │          "585": [378, 1358, 1514, 2583],
│ │ │ │          "58578644": 1756,
│ │ │ │          "58826587": 349,
│ │ │ │          "59": [55, 2208, 2602, 2657],
│ │ │ │ @@ -35208,14 +35205,15 @@
│ │ │ │          "6094": 2522,
│ │ │ │          "60x": 2599,
│ │ │ │          "61": [13, 2657],
│ │ │ │          "610": 28,
│ │ │ │          "61119": 2098,
│ │ │ │          "614064523559687": 2115,
│ │ │ │          "6143849206349179": [1113, 1543],
│ │ │ │ +        "6148415": 2461,
│ │ │ │          "6176": [99, 906],
│ │ │ │          "61799388": 1911,
│ │ │ │          "618": 669,
│ │ │ │          "6180": [2353, 2400, 2450],
│ │ │ │          "61988120985": [2323, 2367, 2414],
│ │ │ │          "61c54bbd": 42,
│ │ │ │          "62": [542, 968, 969, 2323, 2333, 2367, 2377, 2414, 2424, 2657],
│ │ │ │ @@ -35223,15 +35221,14 @@
│ │ │ │          "6227766": 514,
│ │ │ │          "623": [2394, 2444],
│ │ │ │          "62318272": [2319, 2363, 2410],
│ │ │ │          "62341325": 514,
│ │ │ │          "62374854": 2666,
│ │ │ │          "624": [2300, 2370, 2394, 2417, 2444, 2462],
│ │ │ │          "625": [99, 478, 645, 906, 2390, 2438],
│ │ │ │ -        "626": 2461,
│ │ │ │          "6273591314603949": [2335, 2378, 2425],
│ │ │ │          "62949953e": 645,
│ │ │ │          "63": [58, 514, 669, 1748, 1777, 2336, 2463, 2520, 2566, 2594, 2642, 2657],
│ │ │ │          "631198583": 55,
│ │ │ │          "631198588": 55,
│ │ │ │          "63317787e": [2166, 2167],
│ │ │ │          "63526532": 2458,
│ │ │ │ @@ -35343,14 +35340,15 @@
│ │ │ │          "6717": 2522,
│ │ │ │          "6718": 2522,
│ │ │ │          "6719": 2522,
│ │ │ │          "6721": 2522,
│ │ │ │          "6726": 2522,
│ │ │ │          "6735": 2522,
│ │ │ │          "6747": 2522,
│ │ │ │ +        "675": 2461,
│ │ │ │          "6753": [2353, 2400, 2450],
│ │ │ │          "6756": 2522,
│ │ │ │          "6757": 2522,
│ │ │ │          "6765": 28,
│ │ │ │          "6771": 2522,
│ │ │ │          "6775": 2522,
│ │ │ │          "6780": 2522,
│ │ │ │ @@ -35438,15 +35436,14 @@
│ │ │ │          "73496154e": 1867,
│ │ │ │          "73603959e": 2666,
│ │ │ │          "73799541": 1153,
│ │ │ │          "74": [2463, 2513, 2514, 2657],
│ │ │ │          "74000000": 2635,
│ │ │ │          "7416573867739413": 653,
│ │ │ │          "74165739": 653,
│ │ │ │ -        "74432687": 2488,
│ │ │ │          "74499359e": [420, 947],
│ │ │ │          "745966692414834": [648, 653],
│ │ │ │          "75": [58, 135, 440, 478, 516, 520, 528, 544, 645, 667, 870, 1056, 1542, 1606, 1634, 1663, 1834, 2091, 2257, 2461, 2491, 2657, 2659, 2666],
│ │ │ │          "7500": 652,
│ │ │ │          "75000": 652,
│ │ │ │          "75008178": 349,
│ │ │ │          "75025": 28,
│ │ │ │ @@ -35466,15 +35463,15 @@
│ │ │ │          "7568025": 2666,
│ │ │ │          "75682846": 2659,
│ │ │ │          "7578": 2526,
│ │ │ │          "7590": 2526,
│ │ │ │          "75958653": 1911,
│ │ │ │          "7597": 2526,
│ │ │ │          "75j": 2659,
│ │ │ │ -        "76": [541, 1897, 2461, 2463, 2657, 2659],
│ │ │ │ +        "76": [541, 1897, 2463, 2657, 2659],
│ │ │ │          "7608": 2526,
│ │ │ │          "7611397": [349, 2457, 2639],
│ │ │ │          "76190476e": 1816,
│ │ │ │          "76322758": 1154,
│ │ │ │          "7638": 2526,
│ │ │ │          "76425276e": 1149,
│ │ │ │          "76492172": 349,
│ │ │ │ @@ -35482,14 +35479,15 @@
│ │ │ │          "7656": 2526,
│ │ │ │          "7660": 2526,
│ │ │ │          "7665": 2526,
│ │ │ │          "7670": 2526,
│ │ │ │          "7671": 2526,
│ │ │ │          "7676": 2526,
│ │ │ │          "7680": 2526,
│ │ │ │ +        "76927745": 2461,
│ │ │ │          "769893": 2635,
│ │ │ │          "76989341": 2635,
│ │ │ │          "76991118": 1891,
│ │ │ │          "77": [29, 36, 37, 38, 39, 2463, 2635, 2654, 2657],
│ │ │ │          "770": [287, 1241, 1324, 1478, 1998, 2650],
│ │ │ │          "77086955": 1526,
│ │ │ │          "7724": 2526,
│ │ │ │ @@ -35561,15 +35559,15 @@
│ │ │ │          "8020": 2527,
│ │ │ │          "8024": 2527,
│ │ │ │          "8031": 2527,
│ │ │ │          "804": 2508,
│ │ │ │          "8044": 2527,
│ │ │ │          "8058837395885292": 666,
│ │ │ │          "80b3a34": 2614,
│ │ │ │ -        "81": [1650, 1884, 2461, 2635, 2641, 2645, 2657, 2666],
│ │ │ │ +        "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],
│ │ │ │          "81814867": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │          "8192": [72, 517, 2092, 2619],
│ │ │ │ @@ -35615,15 +35613,15 @@
│ │ │ │          "8570331885190563e": [648, 653],
│ │ │ │          "85715698e": 2171,
│ │ │ │          "8577": 2539,
│ │ │ │          "85859792": [349, 2457, 2639],
│ │ │ │          "8595784": 2635,
│ │ │ │          "86": [59, 88, 101, 103, 106, 126, 131, 542, 968, 969, 2323, 2367, 2414, 2491, 2657],
│ │ │ │          "8601": [55, 62, 67, 2613],
│ │ │ │ -        "86256701": 2461,
│ │ │ │ +        "86169933": 2461,
│ │ │ │          "86260211e": 54,
│ │ │ │          "8630830": 13,
│ │ │ │          "86399": 55,
│ │ │ │          "86400": 55,
│ │ │ │          "86401": 55,
│ │ │ │          "8660254": 2103,
│ │ │ │          "86820401": [2345, 2391, 2439],
│ │ │ │ @@ -35668,14 +35666,15 @@
│ │ │ │          "90384387e": 2104,
│ │ │ │          "90476190e": 1816,
│ │ │ │          "90909091": 136,
│ │ │ │          "909297": 2642,
│ │ │ │          "90929743": 2666,
│ │ │ │          "91": 2657,
│ │ │ │          "91275558": 2635,
│ │ │ │ +        "91604321": 2488,
│ │ │ │          "916666666666666": 1240,
│ │ │ │          "92": [98, 2657, 2659],
│ │ │ │          "921fb54442d18p": 2520,
│ │ │ │          "9223372036854775807": 2648,
│ │ │ │          "9223372036854775808": 2648,
│ │ │ │          "92346708": 349,
│ │ │ │          "92362781e": 2104,
│ │ │ │ @@ -35735,27 +35734,28 @@
│ │ │ │          "96360618": [2387, 2434],
│ │ │ │          "9665554": 349,
│ │ │ │          "96767474e": 54,
│ │ │ │          "96875": 2491,
│ │ │ │          "96979195": 2635,
│ │ │ │          "969792": 2635,
│ │ │ │          "96e7": 42,
│ │ │ │ -        "97": [2463, 2635, 2657, 2666],
│ │ │ │ +        "97": [2461, 2463, 2635, 2657, 2666],
│ │ │ │          "9700": 2666,
│ │ │ │          "9701": 2666,
│ │ │ │          "9702": 2666,
│ │ │ │          "97074098": 349,
│ │ │ │          "973": [941, 1114, 1123, 1124, 1131],
│ │ │ │          "9732": [2533, 2534],
│ │ │ │          "9736": [2533, 2534],
│ │ │ │          "9742": [2533, 2534],
│ │ │ │          "9744": [2533, 2534],
│ │ │ │          "9745": [2533, 2534],
│ │ │ │          "9746": [2533, 2534],
│ │ │ │          "9747": [2533, 2534],
│ │ │ │ +        "97479468": 2488,
│ │ │ │          "97517215": 349,
│ │ │ │          "97562235": [349, 2457, 2639],
│ │ │ │          "9757": [2533, 2534],
│ │ │ │          "9764": [2533, 2534],
│ │ │ │          "9765": [2533, 2534],
│ │ │ │          "9766": [2533, 2534],
│ │ │ │          "9767": [2533, 2534],