--- /srv/reproducible-results/rbuild-debian/r-b-build.1V5VxBss/b1/numpy_2.1.2+ds-1_arm64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.1V5VxBss/b2/numpy_2.1.2+ds-1_arm64.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - 0f837f2302c4aea6f210a24a787bcd8b 4274468 doc optional python-numpy-doc_2.1.2+ds-1_all.deb
│ + 18fda3143c95a56fa613f7b7ca06ac3b 4274944 doc optional python-numpy-doc_2.1.2+ds-1_all.deb
│   c1f135f3f7a201e663a28582192e94a2 28525316 debug optional python3-numpy-dbgsym_2.1.2+ds-1_arm64.deb
│   cb4e6fb8a63e4b9f86631087f70b1941 132964 python optional python3-numpy-dev_2.1.2+ds-1_arm64.deb
│   9f45ba3addb2568fbd8f8cfc296aed44 4094272 python optional python3-numpy_2.1.2+ds-1_arm64.deb
├── python-numpy-doc_2.1.2+ds-1_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2024-10-08 16:55:28.000000 debian-binary
│ │  -rw-r--r--   0        0        0    64272 2024-10-08 16:55:28.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  4210004 2024-10-08 16:55:28.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0  4210480 2024-10-08 16:55:28.000000 data.tar.xz
│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./md5sums
│ │ │ │ ├── ./md5sums
│ │ │ │ │┄ Files differ
│ ├── data.tar.xz
│ │ ├── data.tar
│ │ │ ├── file list
│ │ │ │ @@ -2551,15 +2551,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41337 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45470 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43949 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    80660 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    44882 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    87879 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    34441 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    43253 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    43255 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51517 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    36886 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    40533 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    44848 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50276 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26416 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    53301 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ │ @@ -2722,15 +2722,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    30743 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release/2.0.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    60923 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release/2.1.0-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28892 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release/2.1.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    29558 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release/2.1.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12270 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    86302 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    11448 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2680947 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2680940 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   176281 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    49410 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32345 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    62981 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64717 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    17721 2024-10-08 16:55:28.000000 ./usr/share/doc/python-numpy/html/user/basics.html
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ @@ -521,30 +521,30 @@
│ │ │ │  <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">1.03 ms +- 54.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">2.51 ms +- 19.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.02 ms +- 41.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.51 ms +- 25.2 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">981 us +- 22.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">1.75 ms +- 8.44 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">987 us +- 9.32 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.75 ms +- 16.3 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">2.47 ms +- 25.4 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">4.47 ms +- 16 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.46 ms +- 15.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.46 ms +- 19.4 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
│ │ │ │ @@ -571,21 +571,21 @@
│ │ │ │  <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([0.95234883, 0.01611173, 0.84589499])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.54260604, 0.77878359, 0.77082726])</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([0.8747235 , 0.22989058, 0.28830016], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.7993823 , 0.6500705 , 0.02361113], 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([108, 250, 131], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([ 63, 195,  38], 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>
│ │ │ │ @@ -598,18 +598,18 @@
│ │ │ │  </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([0.88520721, 0.54551373])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.93281603, 0.01499371])</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">[0.88520721 0.54551373 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.93281603 0.01499371 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>
│ │ │ │ @@ -621,25 +621,25 @@
│ │ │ │  <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([[ 3,  0,  2,  0,  1],</span>
│ │ │ │ -<span class="go">       [ 7,  4,  6,  4,  5],</span>
│ │ │ │ -<span class="go">       [11,  8, 10,  8,  9]])</span>
│ │ │ │ +<span class="go">array([[ 2,  2,  3,  2,  0],</span>
│ │ │ │ +<span class="go">       [ 6,  6,  7,  6,  4],</span>
│ │ │ │ +<span class="go">       [10, 10, 11, 10,  8]])</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([[ 0,  1,  2,  3],</span>
│ │ │ │ -<span class="go">       [ 4,  5,  6,  7],</span>
│ │ │ │ -<span class="go">       [ 8,  9, 10, 11]])</span>
│ │ │ │ +<span class="go">array([[ 1,  0,  2,  3],</span>
│ │ │ │ +<span class="go">       [ 5,  4,  6,  7],</span>
│ │ │ │ +<span class="go">       [ 9,  8, 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 {}
│ │ │ │ │ @@ -101,26 +101,26 @@
│ │ │ │ │  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)
│ │ │ │ │     ...:
│ │ │ │ │ -1.03 ms +- 54.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -2.51 ms +- 19.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.02 ms +- 41.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.51 ms +- 25.2 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)
│ │ │ │ │     ...:
│ │ │ │ │ -981 us +- 22.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -1.75 ms +- 8.44 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +987 us +- 9.32 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.75 ms +- 16.3 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)
│ │ │ │ │     ...:
│ │ │ │ │ -2.47 ms +- 25.4 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -4.47 ms +- 16 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.46 ms +- 15.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.46 ms +- 19.4 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
│ │ │ │ │ @@ -139,38 +139,38 @@
│ │ │ │ │            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([0.95234883, 0.01611173, 0.84589499])
│ │ │ │ │ +Out[7]: array([0.54260604, 0.77878359, 0.77082726])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.8747235 , 0.22989058, 0.28830016], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.7993823 , 0.6500705 , 0.02361113], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([108, 250, 131], dtype=uint8)
│ │ │ │ │ +Out[9]: array([ 63, 195,  38], 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([0.88520721, 0.54551373])
│ │ │ │ │ +Out[12]: array([0.93281603, 0.01499371])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.88520721 0.54551373 0.         0.        ]
│ │ │ │ │ +[0.93281603 0.01499371 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))
│ │ │ │ │  
│ │ │ │ │ @@ -178,25 +178,25 @@
│ │ │ │ │  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([[ 3,  0,  2,  0,  1],
│ │ │ │ │ -       [ 7,  4,  6,  4,  5],
│ │ │ │ │ -       [11,  8, 10,  8,  9]])
│ │ │ │ │ +array([[ 2,  2,  3,  2,  0],
│ │ │ │ │ +       [ 6,  6,  7,  6,  4],
│ │ │ │ │ +       [10, 10, 11, 10,  8]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 0,  1,  2,  3],
│ │ │ │ │ -       [ 4,  5,  6,  7],
│ │ │ │ │ -       [ 8,  9, 10, 11]])
│ │ │ │ │ +array([[ 1,  0,  2,  3],
│ │ │ │ │ +       [ 5,  4,  6,  7],
│ │ │ │ │ +       [ 9,  8, 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 2008-2024, NumPy Developers.
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ @@ -592,31 +592,31 @@
│ │ │ │  
│ │ │ │  <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([ 0.98100691, -0.17549395])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 1.05471935, -0.57880148])</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([4.23903715, 4.4145311 ], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.16743561, 4.7462371 ], 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([-0.17549395,  0.98100691], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.57880148,  1.05471935], 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([ 0.98100691, -0.17549395])
│ │ │ │ │ +Out[4]: array([ 1.05471935, -0.57880148])
│ │ │ │ │  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([4.23903715, 4.4145311 ], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.16743561, 4.7462371 ], 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([-0.17549395,  0.98100691], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.57880148,  1.05471935], 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 {}
│ │ │ │ │ @@ -32285,39 +32285,40 @@
│ │ │ │ │          "010": [652, 1600, 1657, 1714, 1771, 1828, 1884],
│ │ │ │ │          "0100": 1517,
│ │ │ │ │          "01041667": 1583,
│ │ │ │ │          "011": [1600, 1657, 1714, 1771, 1828, 1884],
│ │ │ │ │          "012": [1600, 1657, 1714, 1771, 1828, 1884],
│ │ │ │ │          "0123456789": [312, 2130],
│ │ │ │ │          "01280782": [2332, 2375, 2422],
│ │ │ │ │ +        "01499371": 2458,
│ │ │ │ │          "016": [647, 652],
│ │ │ │ │ -        "01611173": 2458,
│ │ │ │ │          "01652764": 2626,
│ │ │ │ │          "01666667": 1542,
│ │ │ │ │          "016j": 2103,
│ │ │ │ │          "01831564": 1658,
│ │ │ │ │          "018318": [2350, 2397, 2447],
│ │ │ │ │          "01j": 523,
│ │ │ │ │          "01t00": [55, 62, 370, 2522],
│ │ │ │ │          "01t08": 2522,
│ │ │ │ │          "01t12": 55,
│ │ │ │ │ -        "02": [54, 55, 156, 171, 172, 419, 556, 575, 668, 1333, 1584, 1599, 1656, 1713, 1770, 1814, 1827, 1883, 2102],
│ │ │ │ │ +        "02": [54, 55, 156, 171, 172, 419, 556, 575, 668, 1333, 1584, 1599, 1656, 1713, 1770, 1814, 1827, 1883, 2102, 2458],
│ │ │ │ │          "020995": 57,
│ │ │ │ │          "02284196": 1695,
│ │ │ │ │          "02294967": 1638,
│ │ │ │ │          "023": 2635,
│ │ │ │ │          "02332573e": 54,
│ │ │ │ │ +        "02361113": 2458,
│ │ │ │ │          "0253": 2643,
│ │ │ │ │          "02654825": 1889,
│ │ │ │ │          "02658058e": 2657,
│ │ │ │ │          "02755911": 2657,
│ │ │ │ │          "027559113243068367": 2657,
│ │ │ │ │          "02785049": 1865,
│ │ │ │ │          "02i": [522, 2635],
│ │ │ │ │ -        "03": [55, 67, 172, 575, 668, 1333, 1584, 1814, 2458, 2649],
│ │ │ │ │ +        "03": [55, 67, 172, 575, 668, 1333, 1584, 1814, 2649],
│ │ │ │ │          "03125": [1583, 2488],
│ │ │ │ │          "0326911": [2332, 2375, 2422],
│ │ │ │ │          "0361": 2604,
│ │ │ │ │          "03703704": 1807,
│ │ │ │ │          "03943254e": 2102,
│ │ │ │ │          "03968254": [1112, 1541],
│ │ │ │ │          "0396842": 679,
│ │ │ │ │ @@ -32330,14 +32331,15 @@
│ │ │ │ │          "04551152e": 2102,
│ │ │ │ │          "04719755": 1909,
│ │ │ │ │          "05": [55, 100, 172, 419, 557, 668, 895, 1094, 1869, 2081, 2171, 2350, 2397, 2447],
│ │ │ │ │          "0500": 369,
│ │ │ │ │          "05093587": 2626,
│ │ │ │ │          "05208333": 1583,
│ │ │ │ │          "05263157894736836": 2254,
│ │ │ │ │ +        "05471935": 2485,
│ │ │ │ │          "0549999999999997": 2081,
│ │ │ │ │          "055": 2081,
│ │ │ │ │          "0596779": 1152,
│ │ │ │ │          "06": [55, 575, 2081, 2505],
│ │ │ │ │          "0614962j": [448, 462],
│ │ │ │ │          "0625": [87, 427, 1643],
│ │ │ │ │          "06369197489564249": 2455,
│ │ │ │ │ @@ -32503,15 +32505,15 @@
│ │ │ │ │          "1071": 2460,
│ │ │ │ │          "10725": 2534,
│ │ │ │ │          "10726": 2534,
│ │ │ │ │          "10727": 2534,
│ │ │ │ │          "10729": 2534,
│ │ │ │ │          "1073741821": [429, 430, 946, 947, 1921],
│ │ │ │ │          "1078": 2619,
│ │ │ │ │ -        "108": [533, 2458, 2460],
│ │ │ │ │ +        "108": [533, 2460],
│ │ │ │ │          "10862": 2535,
│ │ │ │ │          "10868": 2535,
│ │ │ │ │          "1088311": 2340,
│ │ │ │ │          "10898": 2539,
│ │ │ │ │          "109": [145, 532, 2460],
│ │ │ │ │          "10905": 2535,
│ │ │ │ │          "10941": 2325,
│ │ │ │ │ @@ -32689,15 +32691,15 @@
│ │ │ │ │          "1300000": 2626,
│ │ │ │ │          "13020": 2546,
│ │ │ │ │          "13026": 2546,
│ │ │ │ │          "13028": 2546,
│ │ │ │ │          "13038": 2546,
│ │ │ │ │          "13041": 2546,
│ │ │ │ │          "13090": [195, 826, 998, 1171, 1257, 1412, 1931],
│ │ │ │ │ -        "131": [536, 2458, 2460],
│ │ │ │ │ +        "131": [536, 2460],
│ │ │ │ │          "1312": 494,
│ │ │ │ │          "13182611e": [429, 946],
│ │ │ │ │          "132": [536, 2327, 2371, 2418, 2460, 2628],
│ │ │ │ │          "1324274851176597e": 1865,
│ │ │ │ │          "133": [536, 2327, 2371, 2418],
│ │ │ │ │          "13392": 2548,
│ │ │ │ │          "13394": 2548,
│ │ │ │ │ @@ -33079,14 +33081,15 @@
│ │ │ │ │          "16703": 2564,
│ │ │ │ │          "16705": 2564,
│ │ │ │ │          "16710": 2569,
│ │ │ │ │          "16714": 2564,
│ │ │ │ │          "1672": 2609,
│ │ │ │ │          "16724": 2564,
│ │ │ │ │          "16730": 2569,
│ │ │ │ │ +        "16743561": 2485,
│ │ │ │ │          "1675": 2609,
│ │ │ │ │          "16768": 2564,
│ │ │ │ │          "16772": 2564,
│ │ │ │ │          "16776": 2564,
│ │ │ │ │          "16779": 2564,
│ │ │ │ │          "1678": 55,
│ │ │ │ │          "16780": 2564,
│ │ │ │ │ @@ -33153,15 +33156,14 @@
│ │ │ │ │          "1749": 2608,
│ │ │ │ │          "17492": 2573,
│ │ │ │ │          "175": [2460, 2650],
│ │ │ │ │          "17522": 2566,
│ │ │ │ │          "17530": 2580,
│ │ │ │ │          "17535": 2569,
│ │ │ │ │          "17545176": 1152,
│ │ │ │ │ -        "17549395": 2485,
│ │ │ │ │          "17568": 2566,
│ │ │ │ │          "17577": [2569, 2651],
│ │ │ │ │          "17580": 2569,
│ │ │ │ │          "17582": 2580,
│ │ │ │ │          "17586": 2573,
│ │ │ │ │          "17596": 2569,
│ │ │ │ │          "176": 2460,
│ │ │ │ │ @@ -33354,15 +33356,15 @@
│ │ │ │ │          "19478": 2580,
│ │ │ │ │          "19479": 2580,
│ │ │ │ │          "1948": 2609,
│ │ │ │ │          "19495": 2574,
│ │ │ │ │          "19496": 2574,
│ │ │ │ │          "19497": 2575,
│ │ │ │ │          "19499": 2574,
│ │ │ │ │ -        "195": [2329, 2373, 2420],
│ │ │ │ │ +        "195": [2329, 2373, 2420, 2458],
│ │ │ │ │          "1950": 145,
│ │ │ │ │          "19500": 2574,
│ │ │ │ │          "19501": 2574,
│ │ │ │ │          "19502": 2574,
│ │ │ │ │          "19503": 2574,
│ │ │ │ │          "1951": [2355, 2402, 2452],
│ │ │ │ │          "19510": 2574,
│ │ │ │ │ @@ -33685,15 +33687,15 @@
│ │ │ │ │          "219": 2460,
│ │ │ │ │          "21925": 2591,
│ │ │ │ │          "21949": 2586,
│ │ │ │ │          "21951": 2586,
│ │ │ │ │          "21952": 2586,
│ │ │ │ │          "21976": 2591,
│ │ │ │ │          "21995": 2591,
│ │ │ │ │ -        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 107, 116, 117, 118, 172, 279, 345, 387, 434, 494, 627, 657, 668, 879, 904, 1044, 1068, 1112, 1210, 1228, 1292, 1310, 1334, 1335, 1338, 1339, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1356, 1446, 1464, 1512, 1519, 1520, 1541, 1589, 1903, 1906, 1911, 1966, 1984, 2089, 2206, 2234, 2235, 2330, 2339, 2458, 2510, 2514, 2516, 2531, 2585, 2626, 2628, 2632, 2648, 2657],
│ │ │ │ │ +        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 107, 116, 117, 118, 172, 279, 345, 387, 434, 494, 627, 657, 668, 879, 904, 1044, 1068, 1112, 1210, 1228, 1292, 1310, 1334, 1335, 1338, 1339, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1356, 1446, 1464, 1512, 1519, 1520, 1541, 1589, 1903, 1906, 1911, 1966, 1984, 2089, 2206, 2234, 2235, 2330, 2339, 2510, 2514, 2516, 2531, 2585, 2626, 2628, 2632, 2648, 2657],
│ │ │ │ │          "220": [2236, 2573],
│ │ │ │ │          "22004": 2591,
│ │ │ │ │          "22014": 2591,
│ │ │ │ │          "22030": 2587,
│ │ │ │ │          "22031": 2587,
│ │ │ │ │          "22032": 2587,
│ │ │ │ │          "22033": 2587,
│ │ │ │ │ @@ -33829,15 +33831,14 @@
│ │ │ │ │          "22969": 2593,
│ │ │ │ │          "22970": 2593,
│ │ │ │ │          "22971": 2593,
│ │ │ │ │          "22972": 2593,
│ │ │ │ │          "22976": 2593,
│ │ │ │ │          "22982": 2596,
│ │ │ │ │          "22989": 2593,
│ │ │ │ │ -        "22989058": 2458,
│ │ │ │ │          "22997": 2596,
│ │ │ │ │          "22998": 2596,
│ │ │ │ │          "22e": 466,
│ │ │ │ │          "23": [1, 8, 10, 18, 32, 43, 47, 54, 55, 58, 62, 63, 75, 79, 107, 144, 148, 172, 279, 296, 338, 345, 492, 522, 627, 668, 879, 904, 916, 1028, 1068, 1103, 1228, 1240, 1310, 1322, 1464, 1476, 1543, 1705, 1746, 1775, 1901, 1911, 1984, 1996, 2152, 2206, 2233, 2235, 2253, 2318, 2337, 2339, 2362, 2380, 2409, 2427, 2510, 2516, 2539, 2549, 2592, 2619, 2624, 2626, 2628, 2632, 2636, 2639, 2648, 2657],
│ │ │ │ │          "230": 418,
│ │ │ │ │          "230000071797338e": 486,
│ │ │ │ │          "23011": 2596,
│ │ │ │ │ @@ -33918,15 +33919,14 @@
│ │ │ │ │          "23809": 2619,
│ │ │ │ │          "23830": 2619,
│ │ │ │ │          "23847": 2619,
│ │ │ │ │          "2385": 2614,
│ │ │ │ │          "23861": 2619,
│ │ │ │ │          "23871": 2619,
│ │ │ │ │          "23890": 2595,
│ │ │ │ │ -        "23903715": 2485,
│ │ │ │ │          "23919": 2619,
│ │ │ │ │          "23921": 2619,
│ │ │ │ │          "23922": 2619,
│ │ │ │ │          "23936": 2619,
│ │ │ │ │          "2394691": 2309,
│ │ │ │ │          "23968": 2597,
│ │ │ │ │          "23994": 2595,
│ │ │ │ │ @@ -34112,15 +34112,15 @@
│ │ │ │ │          "24955": 2601,
│ │ │ │ │          "24962": 2601,
│ │ │ │ │          "24971": 2601,
│ │ │ │ │          "24972": 2601,
│ │ │ │ │          "24977": 2601,
│ │ │ │ │          "24978": 2619,
│ │ │ │ │          "25": [10, 50, 54, 55, 56, 58, 69, 87, 149, 370, 386, 418, 427, 449, 490, 498, 529, 535, 537, 553, 644, 659, 666, 668, 679, 869, 880, 892, 916, 1055, 1069, 1082, 1134, 1141, 1142, 1239, 1347, 1524, 1525, 1540, 1579, 1604, 1649, 1692, 1700, 1832, 1905, 2088, 2089, 2202, 2237, 2238, 2248, 2262, 2263, 2320, 2322, 2334, 2345, 2346, 2364, 2377, 2387, 2393, 2411, 2424, 2435, 2443, 2458, 2460, 2470, 2473, 2488, 2510, 2512, 2516, 2564, 2599, 2601, 2619, 2620, 2626, 2632, 2636, 2645, 2648, 2650, 2657],
│ │ │ │ │ -        "250": [370, 2458, 2460],
│ │ │ │ │ +        "250": [370, 2460],
│ │ │ │ │          "2500": 651,
│ │ │ │ │          "25000": 651,
│ │ │ │ │          "25003": 2601,
│ │ │ │ │          "25043": 2601,
│ │ │ │ │          "25049": 2601,
│ │ │ │ │          "25054": 2619,
│ │ │ │ │          "25071": 2601,
│ │ │ │ │ @@ -34413,15 +34413,14 @@
│ │ │ │ │          "28318531": [1889, 2236],
│ │ │ │ │          "285": [575, 636],
│ │ │ │ │          "286": 363,
│ │ │ │ │          "28613933": 1152,
│ │ │ │ │          "28657": 28,
│ │ │ │ │          "28790332": 2657,
│ │ │ │ │          "2883": [1641, 1653],
│ │ │ │ │ -        "28830016": 2458,
│ │ │ │ │          "28853036": 1865,
│ │ │ │ │          "28904982231052": 674,
│ │ │ │ │          "2892": 2612,
│ │ │ │ │          "28mathematical_const": 76,
│ │ │ │ │          "29": [10, 21, 45, 54, 55, 76, 153, 172, 1636, 1645, 2206, 2325, 2460, 2461, 2510, 2544, 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2560, 2561, 2562, 2563, 2564, 2565, 2584, 2599, 2619, 2632, 2648, 2657],
│ │ │ │ │          "290": 2297,
│ │ │ │ │          "29001ed": 13,
│ │ │ │ │ @@ -34522,15 +34521,15 @@
│ │ │ │ │          "3173": 2614,
│ │ │ │ │          "3175": 2614,
│ │ │ │ │          "317811": 28,
│ │ │ │ │          "317j": [80, 420],
│ │ │ │ │          "318": 1524,
│ │ │ │ │          "3192": 2612,
│ │ │ │ │          "31962608": [205, 835, 1007, 1178, 1264, 1419, 1938],
│ │ │ │ │ -        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 146, 153, 224, 279, 345, 399, 443, 523, 593, 879, 892, 1026, 1068, 1082, 1142, 1197, 1228, 1247, 1279, 1310, 1343, 1346, 1433, 1464, 1517, 1882, 1884, 1900, 1953, 1984, 2074, 2089, 2202, 2206, 2223, 2238, 2258, 2259, 2265, 2266, 2269, 2270, 2271, 2274, 2275, 2276, 2279, 2280, 2281, 2284, 2285, 2296, 2297, 2298, 2299, 2300, 2301, 2311, 2328, 2372, 2419, 2455, 2456, 2457, 2459, 2505, 2510, 2517, 2518, 2519, 2532, 2540, 2541, 2542, 2543, 2544, 2554, 2559, 2561, 2569, 2571, 2576, 2579, 2584, 2585, 2596, 2599, 2603, 2604, 2614, 2619, 2628, 2630, 2632, 2636, 2637, 2639, 2640, 2643, 2648, 2649, 2650, 2657],
│ │ │ │ │ +        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 146, 153, 224, 279, 345, 399, 443, 523, 593, 879, 892, 1026, 1068, 1082, 1142, 1197, 1228, 1247, 1279, 1310, 1343, 1346, 1433, 1464, 1517, 1882, 1884, 1900, 1953, 1984, 2074, 2089, 2202, 2206, 2223, 2238, 2258, 2259, 2265, 2266, 2269, 2270, 2271, 2274, 2275, 2276, 2279, 2280, 2281, 2284, 2285, 2296, 2297, 2298, 2299, 2300, 2301, 2311, 2328, 2372, 2419, 2455, 2456, 2457, 2458, 2459, 2505, 2510, 2517, 2518, 2519, 2532, 2540, 2541, 2542, 2543, 2544, 2554, 2559, 2561, 2569, 2571, 2576, 2579, 2584, 2585, 2596, 2599, 2603, 2604, 2614, 2619, 2628, 2630, 2632, 2636, 2637, 2639, 2640, 2643, 2648, 2649, 2650, 2657],
│ │ │ │ │          "320": 1148,
│ │ │ │ │          "32000": 2092,
│ │ │ │ │          "32119158": 1865,
│ │ │ │ │          "323": [269, 430, 947, 1058, 1221, 1303, 1348, 1457, 1577, 1588, 1602, 1603, 1637, 1647, 1659, 1660, 1694, 1704, 1716, 1717, 1751, 1761, 1773, 1774, 1808, 1818, 1830, 1831, 1864, 1873, 1885, 1886, 1977, 2309],
│ │ │ │ │          "3263": 2614,
│ │ │ │ │          "32767": 544,
│ │ │ │ │          "32768": 544,
│ │ │ │ │ @@ -34610,15 +34609,15 @@
│ │ │ │ │          "3743": 2612,
│ │ │ │ │          "375": [1632, 1661],
│ │ │ │ │          "37601032": [2384, 2431],
│ │ │ │ │          "377": 28,
│ │ │ │ │          "378": 651,
│ │ │ │ │          "379": 542,
│ │ │ │ │          "3793": 2612,
│ │ │ │ │ -        "38": [59, 551, 967, 968, 1543, 1750, 1759, 2105, 2202, 2206, 2310, 2330, 2358, 2374, 2405, 2421, 2507, 2569, 2648, 2657],
│ │ │ │ │ +        "38": [59, 551, 967, 968, 1543, 1750, 1759, 2105, 2202, 2206, 2310, 2330, 2358, 2374, 2405, 2421, 2458, 2507, 2569, 2648, 2657],
│ │ │ │ │          "380": [2236, 2573],
│ │ │ │ │          "38268343": 641,
│ │ │ │ │          "38268343j": 641,
│ │ │ │ │          "3832": 2612,
│ │ │ │ │          "38434191e": 659,
│ │ │ │ │          "38446749": 1865,
│ │ │ │ │          "385": [2267, 2297],
│ │ │ │ │ @@ -34674,29 +34673,28 @@
│ │ │ │ │          "4051": [2612, 2614],
│ │ │ │ │          "409": 2460,
│ │ │ │ │          "40918587e": 2102,
│ │ │ │ │          "40919914": 2657,
│ │ │ │ │          "4093": 2614,
│ │ │ │ │          "4094": [2612, 2614],
│ │ │ │ │          "4096": [72, 2090],
│ │ │ │ │ -        "41": [940, 1113, 1122, 1123, 1130, 1911, 2102, 2105, 2206, 2234, 2582, 2648, 2657],
│ │ │ │ │ +        "41": [940, 1113, 1122, 1123, 1130, 1911, 2102, 2105, 2206, 2234, 2458, 2582, 2648, 2657],
│ │ │ │ │          "4109": 2614,
│ │ │ │ │          "41211849": 2657,
│ │ │ │ │          "4123": [2612, 2614],
│ │ │ │ │          "4134": 2614,
│ │ │ │ │          "41357986e": 2173,
│ │ │ │ │          "4138": 2614,
│ │ │ │ │          "4141": 2612,
│ │ │ │ │          "41421356": [652, 1754, 2657],
│ │ │ │ │          "4142135623730951": [59, 636],
│ │ │ │ │          "4142135623730951j": 59,
│ │ │ │ │          "41421356j": 1525,
│ │ │ │ │          "4144": 2614,
│ │ │ │ │          "4145": 2614,
│ │ │ │ │ -        "4145311": 2485,
│ │ │ │ │          "41495": 2582,
│ │ │ │ │          "4152": 2614,
│ │ │ │ │          "4156": 2614,
│ │ │ │ │          "4167": 1641,
│ │ │ │ │          "4170": 2614,
│ │ │ │ │          "4176": 2614,
│ │ │ │ │          "4181": [28, 2618],
│ │ │ │ │ @@ -34734,15 +34732,15 @@
│ │ │ │ │          "4354": 2614,
│ │ │ │ │          "4359": 2614,
│ │ │ │ │          "4368": [296, 1240, 1322, 1476, 1996],
│ │ │ │ │          "4375": 2488,
│ │ │ │ │          "43857224": 1152,
│ │ │ │ │          "43887844": [358, 2454, 2630],
│ │ │ │ │          "43999999999998": 1113,
│ │ │ │ │ -        "44": [16, 1523, 1756, 1903, 1905, 1920, 2206, 2458, 2460, 2621, 2648, 2649, 2650, 2657],
│ │ │ │ │ +        "44": [16, 1523, 1756, 1903, 1905, 1920, 2206, 2460, 2621, 2648, 2649, 2650, 2657],
│ │ │ │ │          "440": [10, 2517],
│ │ │ │ │          "4400": [418, 660, 2166],
│ │ │ │ │          "44069024": 358,
│ │ │ │ │          "4408": 2614,
│ │ │ │ │          "44089210e": 1525,
│ │ │ │ │          "4408921e": [1763, 2173],
│ │ │ │ │          "4409e": 2089,
│ │ │ │ │ @@ -34772,15 +34770,15 @@
│ │ │ │ │          "4532": [418, 660, 2166],
│ │ │ │ │          "4545724517479104": 2457,
│ │ │ │ │          "45560727e": 54,
│ │ │ │ │          "456": 1919,
│ │ │ │ │          "4567": 2635,
│ │ │ │ │          "45674898e": 575,
│ │ │ │ │          "45a3d84": 2518,
│ │ │ │ │ -        "46": [418, 532, 904, 1705, 2202, 2206, 2632, 2648],
│ │ │ │ │ +        "46": [418, 532, 904, 1705, 2202, 2206, 2458, 2632, 2648],
│ │ │ │ │          "460": [2236, 2573],
│ │ │ │ │          "46009194e": 575,
│ │ │ │ │          "4602": 2615,
│ │ │ │ │          "4610935": 466,
│ │ │ │ │          "4613": 2615,
│ │ │ │ │          "4628": 2615,
│ │ │ │ │          "46351241j": 2079,
│ │ │ │ │ @@ -34793,15 +34791,15 @@
│ │ │ │ │          "46666491": 358,
│ │ │ │ │          "46716228e": 1584,
│ │ │ │ │          "46755891e": 54,
│ │ │ │ │          "468": [145, 156],
│ │ │ │ │          "4685006": [2349, 2396, 2446],
│ │ │ │ │          "4686": 12,
│ │ │ │ │          "46957616e": [479, 1897, 1898],
│ │ │ │ │ -        "47": [52, 2206, 2320, 2364, 2411, 2458, 2648, 2657],
│ │ │ │ │ +        "47": [52, 2206, 2320, 2364, 2411, 2648, 2657],
│ │ │ │ │          "4702687338396767": 2345,
│ │ │ │ │          "471": [145, 156, 2460],
│ │ │ │ │          "47108547995356098": [2342, 2388, 2436],
│ │ │ │ │          "47140452j": 2488,
│ │ │ │ │          "472": 55,
│ │ │ │ │          "4722": 2615,
│ │ │ │ │          "4723": 2618,
│ │ │ │ │ @@ -34922,26 +34920,26 @@
│ │ │ │ │          "536870910": 1900,
│ │ │ │ │          "5374": 2618,
│ │ │ │ │          "53814331": 2657,
│ │ │ │ │          "5388": 2618,
│ │ │ │ │          "5390": 2618,
│ │ │ │ │          "5393": 2618,
│ │ │ │ │          "5396": [296, 1240, 1322, 1476, 1996],
│ │ │ │ │ -        "54": [38, 59, 532, 1636, 1709, 1762, 2206, 2458, 2633, 2648],
│ │ │ │ │ +        "54": [38, 59, 532, 1636, 1709, 1762, 2206, 2633, 2648],
│ │ │ │ │          "540": [2236, 2573],
│ │ │ │ │          "54030231": 2657,
│ │ │ │ │          "54030231j": 2657,
│ │ │ │ │          "541": 2460,
│ │ │ │ │          "54117": 1642,
│ │ │ │ │          "5424": 2618,
│ │ │ │ │ +        "54260604": 2458,
│ │ │ │ │          "54323428": [2342, 2388, 2436],
│ │ │ │ │          "54362499": 2626,
│ │ │ │ │          "54402111": 2657,
│ │ │ │ │          "54545455": 145,
│ │ │ │ │ -        "54551373": 2458,
│ │ │ │ │          "54627315": 2626,
│ │ │ │ │          "5470": [2350, 2397, 2447],
│ │ │ │ │          "5481": 2618,
│ │ │ │ │          "5492": 2618,
│ │ │ │ │          "54930614": [115, 140],
│ │ │ │ │          "5493061443340549": [82, 422],
│ │ │ │ │          "54959369": 2657,
│ │ │ │ │ @@ -34978,14 +34976,15 @@
│ │ │ │ │          "57136612e": 2171,
│ │ │ │ │          "57510612": 659,
│ │ │ │ │          "576": 2612,
│ │ │ │ │          "57721": [2323, 2368, 2415],
│ │ │ │ │          "5772156649015328606065120900824024310421": 76,
│ │ │ │ │          "5773": 2519,
│ │ │ │ │          "57860025": 1153,
│ │ │ │ │ +        "57880148": 2485,
│ │ │ │ │          "579365079365115": [1112, 1541],
│ │ │ │ │          "57x": 2591,
│ │ │ │ │          "58": [668, 1746, 1775, 2202, 2206, 2329, 2373, 2420, 2461, 2569, 2626, 2648],
│ │ │ │ │          "582892": 2626,
│ │ │ │ │          "58289208": 2626,
│ │ │ │ │          "584388": 55,
│ │ │ │ │          "585": [387, 1356, 1512, 2580],
│ │ │ │ │ @@ -35039,15 +35038,15 @@
│ │ │ │ │          "62318272": [2316, 2360, 2407],
│ │ │ │ │          "62341325": 523,
│ │ │ │ │          "62374854": 2657,
│ │ │ │ │          "624": [2297, 2367, 2391, 2414, 2441, 2459],
│ │ │ │ │          "625": [108, 487, 644, 905, 2387, 2435],
│ │ │ │ │          "6273591314603949": [2332, 2375, 2422],
│ │ │ │ │          "62949953e": 644,
│ │ │ │ │ -        "63": [58, 523, 668, 1746, 1775, 2333, 2460, 2517, 2563, 2591, 2633, 2648],
│ │ │ │ │ +        "63": [58, 523, 668, 1746, 1775, 2333, 2458, 2460, 2517, 2563, 2591, 2633, 2648],
│ │ │ │ │          "631198583": 55,
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2164, 2165],
│ │ │ │ │          "63526532": 2455,
│ │ │ │ │          "636363636364": [2350, 2397, 2447],
│ │ │ │ │          "63696169": 2626,
│ │ │ │ │          "6376": 2519,
│ │ │ │ │ @@ -35076,14 +35075,15 @@
│ │ │ │ │          "6497": 2519,
│ │ │ │ │          "6498": 2519,
│ │ │ │ │          "6499": 2519,
│ │ │ │ │          "64bit": [50, 61, 62, 2361, 2374, 2376, 2385, 2408, 2421, 2423, 2432, 2514, 2569, 2591],
│ │ │ │ │          "65": 2648,
│ │ │ │ │          "650": 2615,
│ │ │ │ │          "6500": 2519,
│ │ │ │ │ +        "6500705": 2458,
│ │ │ │ │          "6501": 2519,
│ │ │ │ │          "65028784": 2657,
│ │ │ │ │          "65143654": 1153,
│ │ │ │ │          "6515": [2350, 2397, 2447],
│ │ │ │ │          "65200189e": 575,
│ │ │ │ │          "6526": 2519,
│ │ │ │ │          "6527": 2519,
│ │ │ │ │ @@ -35253,14 +35253,15 @@
│ │ │ │ │          "73799541": 1152,
│ │ │ │ │          "74": [2460, 2510, 2511, 2648],
│ │ │ │ │          "74000000": 2626,
│ │ │ │ │          "7416573867739413": 652,
│ │ │ │ │          "74165739": 652,
│ │ │ │ │          "74499359e": [429, 946],
│ │ │ │ │          "745966692414834": [647, 652],
│ │ │ │ │ +        "7462371": 2485,
│ │ │ │ │          "75": [58, 144, 449, 487, 525, 529, 537, 553, 644, 666, 869, 1055, 1540, 1604, 1632, 1661, 1832, 2089, 2254, 2458, 2488, 2648, 2650, 2657],
│ │ │ │ │          "7500": 651,
│ │ │ │ │          "75000": 651,
│ │ │ │ │          "75008178": 358,
│ │ │ │ │          "75025": 28,
│ │ │ │ │          "7506": 2523,
│ │ │ │ │          "75078643": 358,
│ │ │ │ │ @@ -35299,14 +35300,15 @@
│ │ │ │ │          "7676": 2523,
│ │ │ │ │          "7680": 2523,
│ │ │ │ │          "769893": 2626,
│ │ │ │ │          "76989341": 2626,
│ │ │ │ │          "76991118": 1889,
│ │ │ │ │          "77": [29, 36, 37, 38, 39, 2460, 2626, 2645, 2648],
│ │ │ │ │          "770": [296, 1240, 1322, 1476, 1996, 2641],
│ │ │ │ │ +        "77082726": 2458,
│ │ │ │ │          "77086955": 1524,
│ │ │ │ │          "7724": 2523,
│ │ │ │ │          "7725": [2350, 2397, 2447],
│ │ │ │ │          "7731": 2523,
│ │ │ │ │          "7736": 2524,
│ │ │ │ │          "7737": 2523,
│ │ │ │ │          "7738": 2524,
│ │ │ │ │ @@ -35314,14 +35316,15 @@
│ │ │ │ │          "77447664948076": 674,
│ │ │ │ │          "77555756e": 1875,
│ │ │ │ │          "77598074": 358,
│ │ │ │ │          "77714685": 358,
│ │ │ │ │          "7774613834041182": 2312,
│ │ │ │ │          "7776": [108, 905],
│ │ │ │ │          "7778": 2524,
│ │ │ │ │ +        "77878359": 2458,
│ │ │ │ │          "7793": 2524,
│ │ │ │ │          "78": [2089, 2635, 2648],
│ │ │ │ │          "78096262": [2349, 2396, 2446],
│ │ │ │ │          "7816": 2524,
│ │ │ │ │          "7821": 2524,
│ │ │ │ │          "7824": 2524,
│ │ │ │ │          "7835": 2524,
│ │ │ │ │ @@ -35352,14 +35355,15 @@
│ │ │ │ │          "7954": 2524,
│ │ │ │ │          "7955": 2524,
│ │ │ │ │          "79579319e": 1865,
│ │ │ │ │          "79694221e": 1584,
│ │ │ │ │          "7972": 2524,
│ │ │ │ │          "7976931348623157e": 1333,
│ │ │ │ │          "79769313e": 1333,
│ │ │ │ │ +        "7993823": 2458,
│ │ │ │ │          "79ff": [111, 134],
│ │ │ │ │          "7e": 668,
│ │ │ │ │          "7e13": 55,
│ │ │ │ │          "7e17": 55,
│ │ │ │ │          "7x": [2563, 2596],
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│ │ │ │ │          "80": [69, 405, 418, 455, 976, 2245, 2343, 2354, 2380, 2389, 2401, 2427, 2438, 2451, 2585, 2619, 2639, 2640, 2648],
│ │ │ │ │ @@ -35411,15 +35415,14 @@
│ │ │ │ │          "84090247": 2455,
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│ │ │ │ │          "84147098": 2657,
│ │ │ │ │          "8414709848078965": 2631,
│ │ │ │ │          "84147098j": 2657,
│ │ │ │ │          "841471": 2633,
│ │ │ │ │          "842523": 2512,
│ │ │ │ │ -        "84589499": 2458,
│ │ │ │ │          "84680802e": 2102,
│ │ │ │ │          "8480354764257312": 652,
│ │ │ │ │          "85": [418, 2648],
│ │ │ │ │          "85099543": 1820,
│ │ │ │ │          "85355339": 1754,
│ │ │ │ │          "85569": 2096,
│ │ │ │ │          "85602287": [2332, 2375, 2422],
│ │ │ │ │ @@ -35436,25 +35439,23 @@
│ │ │ │ │          "86399": 55,
│ │ │ │ │          "86400": 55,
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│ │ │ │ │          "8660254": 2101,
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│ │ │ │ │          "87": [2613, 2648],
│ │ │ │ │ -        "8747235": 2458,
│ │ │ │ │          "875": [487, 2488],
│ │ │ │ │          "8755": [195, 826, 998, 1171, 1257, 1412, 1931],
│ │ │ │ │          "87649168120691": 673,
│ │ │ │ │          "8770": [2350, 2397, 2447],
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│ │ │ │ │          "88079259": 542,
│ │ │ │ │          "881943016134134": 665,
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│ │ │ │ │          "888": [2511, 2649],
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│ │ │ │ │          "88889": 2649,
│ │ │ │ │          "888e": 2649,
│ │ │ │ │          "88975": 1642,
│ │ │ │ │          "89": [28, 2089, 2635, 2648],
│ │ │ │ │ @@ -35505,14 +35506,15 @@
│ │ │ │ │          "92771843": 1153,
│ │ │ │ │          "9299": 2529,
│ │ │ │ │          "93": 2648,
│ │ │ │ │          "9304e": 2089,
│ │ │ │ │          "931": 2584,
│ │ │ │ │          "9317": 2529,
│ │ │ │ │          "9319": 2529,
│ │ │ │ │ +        "93281603": 2458,
│ │ │ │ │          "9339": 2529,
│ │ │ │ │          "9340": 2529,
│ │ │ │ │          "934284": 358,
│ │ │ │ │          "93657855": 358,
│ │ │ │ │          "9371": 2529,
│ │ │ │ │          "9372": 2529,
│ │ │ │ │          "9373": 2529,
│ │ │ │ │ @@ -35531,15 +35533,14 @@
│ │ │ │ │          "9475673279178444": 2345,
│ │ │ │ │          "94864945": 2657,
│ │ │ │ │          "94909878": [2384, 2431],
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│ │ │ │ │          "9504637": 2657,
│ │ │ │ │          "950684": 2626,
│ │ │ │ │          "95068423": 2626,
│ │ │ │ │ -        "95234883": 2458,
│ │ │ │ │          "9555": [2530, 2531],
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│ │ │ │ │          "9557": [2530, 2531],
│ │ │ │ │          "9558": [2530, 2531],
│ │ │ │ │          "9559": [2530, 2531],
│ │ │ │ │          "9580": [2530, 2531],
│ │ │ │ │          "95892427": 2657,
│ │ │ │ │ @@ -35583,18 +35584,17 @@
│ │ │ │ │          "9799": 2657,
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│ │ │ │ │          "9800": 2657,
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│ │ │ │ │          "9802": 2657,
│ │ │ │ │          "98024613": 679,
│ │ │ │ │          "9807642": 1152,
│ │ │ │ │ -        "981": [2458, 2589],
│ │ │ │ │ -        "98100691": 2485,
│ │ │ │ │ +        "981": 2589,
│ │ │ │ │          "98136677": 532,
│ │ │ │ │ -        "987": 28,
│ │ │ │ │ +        "987": [28, 2458],
│ │ │ │ │          "987654321": 2390,
│ │ │ │ │          "98935825": 2657,
│ │ │ │ │          "9897": 2657,
│ │ │ │ │          "9898": 2657,
│ │ │ │ │          "9899": [114, 139, 2657],
│ │ │ │ │          "99": [12, 311, 417, 553, 671, 1095, 1904, 2129, 2457, 2626, 2648, 2649, 2657],
│ │ │ │ │          "9900": 2657,