--- /srv/reproducible-results/rbuild-debian/r-b-build.psKYtW8c/b1/numpy_2.1.3+ds-1_i386.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.psKYtW8c/b2/numpy_2.1.3+ds-1_i386.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - 9ee9905d6a282a9c3415e34baf4935fd 4276428 doc optional python-numpy-doc_2.1.3+ds-1_all.deb
│ + d5a4a59cceffce6513206502d04ada22 4276616 doc optional python-numpy-doc_2.1.3+ds-1_all.deb
│   f710c8fdcdba934b54c9aaec5003974e 58962248 debug optional python3-numpy-dbgsym_2.1.3+ds-1_i386.deb
│   5ec66059b8be660ee10b36fc5d949cf7 144460 python optional python3-numpy-dev_2.1.3+ds-1_i386.deb
│   2dff6df1cbee73a416dd3583fc5d3b1a 7497824 python optional python3-numpy_2.1.3+ds-1_i386.deb
├── python-numpy-doc_2.1.3+ds-1_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2024-11-22 23:37:09.000000 debian-binary
│ │ --rw-r--r--   0        0        0    64176 2024-11-22 23:37:09.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  4212060 2024-11-22 23:37:09.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0    64188 2024-11-22 23:37:09.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0  4212236 2024-11-22 23:37:09.000000 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 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46002 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    44113 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    80660 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    44882 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    87879 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    34441 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    43256 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    43250 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51517 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    36886 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    40533 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    44848 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50276 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26416 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    53301 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ │ @@ -2723,15 +2723,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    61015 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release/2.1.0-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28984 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release/2.1.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    29676 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release/2.1.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32180 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release/2.1.3-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12270 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    86999 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    11448 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2682752 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2682786 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   176281 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    49410 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32345 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    62981 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64717 2024-11-22 23:37:09.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    17721 2024-11-22 23:37:09.000000 ./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">4.44 ms +- 77.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">6.21 ms +- 17.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">6.82 ms +- 140 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">16.9 ms +- 4.1 ms 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">3.76 ms +- 16.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">5.86 ms +- 26.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">5.62 ms +- 147 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">16.2 ms +- 204 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">12.3 ms +- 15.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">14.2 ms +- 20.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">28.5 ms +- 178 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">33.4 ms +- 211 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([0.47787383, 0.78327068, 0.79074583])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.52142238, 0.27307693, 0.16662583])</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([0.8278483 , 0.06296438, 0.01827687], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.4137339 , 0.36163253, 0.53980225], 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([233, 177,  73], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([ 52, 142, 171], 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([0.69242368, 0.60935161])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.36011562, 0.70817669])</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">[0.69242368 0.60935161 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.36011562 0.70817669 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([[ 1,  1,  3,  0,  0],</span>
│ │ │ │ -<span class="go">       [ 5,  5,  7,  4,  4],</span>
│ │ │ │ -<span class="go">       [ 9,  9, 11,  8,  8]])</span>
│ │ │ │ +<span class="go">array([[ 3,  2,  1,  2,  0],</span>
│ │ │ │ +<span class="go">       [ 7,  6,  5,  6,  4],</span>
│ │ │ │ +<span class="go">       [11, 10,  9, 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([[ 1,  0,  2,  3],</span>
│ │ │ │ -<span class="go">       [ 5,  4,  6,  7],</span>
│ │ │ │ -<span class="go">       [ 9,  8, 10, 11]])</span>
│ │ │ │ +<span class="go">array([[ 1,  0,  3,  2],</span>
│ │ │ │ +<span class="go">       [ 5,  4,  7,  6],</span>
│ │ │ │ +<span class="go">       [ 9,  8, 11, 10]])</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)
│ │ │ │ │     ...:
│ │ │ │ │ -4.44 ms +- 77.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -6.21 ms +- 17.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +6.82 ms +- 140 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +16.9 ms +- 4.1 ms 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)
│ │ │ │ │     ...:
│ │ │ │ │ -3.76 ms +- 16.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -5.86 ms +- 26.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +5.62 ms +- 147 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +16.2 ms +- 204 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)
│ │ │ │ │     ...:
│ │ │ │ │ -12.3 ms +- 15.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -14.2 ms +- 20.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +28.5 ms +- 178 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +33.4 ms +- 211 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([0.47787383, 0.78327068, 0.79074583])
│ │ │ │ │ +Out[7]: array([0.52142238, 0.27307693, 0.16662583])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.8278483 , 0.06296438, 0.01827687], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.4137339 , 0.36163253, 0.53980225], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([233, 177,  73], dtype=uint8)
│ │ │ │ │ +Out[9]: array([ 52, 142, 171], 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([0.69242368, 0.60935161])
│ │ │ │ │ +Out[12]: array([0.36011562, 0.70817669])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.69242368 0.60935161 0.         0.        ]
│ │ │ │ │ +[0.36011562 0.70817669 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([[ 1,  1,  3,  0,  0],
│ │ │ │ │ -       [ 5,  5,  7,  4,  4],
│ │ │ │ │ -       [ 9,  9, 11,  8,  8]])
│ │ │ │ │ +array([[ 3,  2,  1,  2,  0],
│ │ │ │ │ +       [ 7,  6,  5,  6,  4],
│ │ │ │ │ +       [11, 10,  9, 10,  8]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 1,  0,  2,  3],
│ │ │ │ │ -       [ 5,  4,  6,  7],
│ │ │ │ │ -       [ 9,  8, 10, 11]])
│ │ │ │ │ +array([[ 1,  0,  3,  2],
│ │ │ │ │ +       [ 5,  4,  7,  6],
│ │ │ │ │ +       [ 9,  8, 11, 10]])
│ │ │ │ │      * 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([1.04049332, 0.25546594])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([0.94495158, 0.4044994 ])</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([4.9376859 , 4.68221996], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.65678152, 4.25228213], 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([0.25546594, 1.04049332], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([0.4044994 , 0.94495158], 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([1.04049332, 0.25546594])
│ │ │ │ │ +Out[4]: array([0.94495158, 0.4044994 ])
│ │ │ │ │  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([4.9376859 , 4.68221996], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.65678152, 4.25228213], 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([0.25546594, 1.04049332], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([0.4044994 , 0.94495158], 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 {}
│ │ │ │ │ @@ -32296,15 +32296,14 @@
│ │ │ │ │          "012": [1600, 1657, 1714, 1771, 1828, 1884],
│ │ │ │ │          "0123456789": [312, 2130],
│ │ │ │ │          "01280782": [2332, 2375, 2422],
│ │ │ │ │          "016": [647, 652],
│ │ │ │ │          "01652764": 2627,
│ │ │ │ │          "01666667": 1542,
│ │ │ │ │          "016j": 2103,
│ │ │ │ │ -        "01827687": 2458,
│ │ │ │ │          "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],
│ │ │ │ │ @@ -32327,15 +32326,14 @@
│ │ │ │ │          "03703704": 1807,
│ │ │ │ │          "03943254e": 2102,
│ │ │ │ │          "03968254": [1112, 1541],
│ │ │ │ │          "0396842": 679,
│ │ │ │ │          "03t13": 55,
│ │ │ │ │          "04": [54, 55, 173, 419, 556, 1584, 2460, 2591, 2651],
│ │ │ │ │          "0400": 369,
│ │ │ │ │ -        "04049332": 2485,
│ │ │ │ │          "04097352": 2627,
│ │ │ │ │          "04166667": [1542, 1583],
│ │ │ │ │          "04211c6": 2518,
│ │ │ │ │          "04551152e": 2102,
│ │ │ │ │          "04719755": 1909,
│ │ │ │ │          "05": [55, 100, 172, 419, 557, 668, 895, 1094, 1869, 2081, 2171, 2350, 2397, 2447],
│ │ │ │ │          "0500": 369,
│ │ │ │ │ @@ -32344,15 +32342,14 @@
│ │ │ │ │          "05263157894736836": 2254,
│ │ │ │ │          "0549999999999997": 2081,
│ │ │ │ │          "055": 2081,
│ │ │ │ │          "0596779": 1152,
│ │ │ │ │          "06": [55, 575, 2081, 2505],
│ │ │ │ │          "0614962j": [448, 462],
│ │ │ │ │          "0625": [87, 427, 1643],
│ │ │ │ │ -        "06296438": 2458,
│ │ │ │ │          "06369197489564249": 2455,
│ │ │ │ │          "06381726": 358,
│ │ │ │ │          "0660": [311, 2129],
│ │ │ │ │          "06959433e": [429, 946],
│ │ │ │ │          "07": [55, 173, 556, 895, 896, 1333, 2168, 2505],
│ │ │ │ │          "07106781e": 523,
│ │ │ │ │          "07407407": 1807,
│ │ │ │ │ @@ -32755,15 +32752,15 @@
│ │ │ │ │          "13905": 2549,
│ │ │ │ │          "13933": 2549,
│ │ │ │ │          "13984": 2549,
│ │ │ │ │          "13994": 2549,
│ │ │ │ │          "13d7934": 13,
│ │ │ │ │          "13j": 1913,
│ │ │ │ │          "14": [9, 47, 54, 55, 56, 57, 58, 59, 107, 116, 117, 123, 149, 150, 151, 279, 375, 376, 384, 445, 469, 485, 494, 495, 522, 539, 551, 553, 555, 575, 644, 649, 654, 668, 879, 892, 904, 962, 967, 968, 1068, 1082, 1142, 1149, 1228, 1245, 1310, 1464, 1563, 1575, 1584, 1693, 1702, 1709, 1756, 1762, 1865, 1871, 1984, 2084, 2087, 2089, 2113, 2203, 2204, 2206, 2207, 2208, 2220, 2222, 2223, 2235, 2238, 2243, 2330, 2335, 2339, 2374, 2378, 2382, 2421, 2425, 2429, 2454, 2458, 2460, 2487, 2510, 2516, 2528, 2539, 2540, 2541, 2542, 2543, 2544, 2550, 2551, 2556, 2557, 2558, 2563, 2569, 2573, 2580, 2581, 2582, 2583, 2585, 2588, 2593, 2596, 2597, 2619, 2624, 2627, 2630, 2633, 2637, 2645, 2649, 2651, 2658],
│ │ │ │ │ -        "140": [2236, 2573],
│ │ │ │ │ +        "140": [2236, 2458, 2573],
│ │ │ │ │          "14022471": [2384, 2431],
│ │ │ │ │          "14036": 2557,
│ │ │ │ │          "14039": 2557,
│ │ │ │ │          "14042": 2549,
│ │ │ │ │          "14043": 2549,
│ │ │ │ │          "14044": 2549,
│ │ │ │ │          "14045": 2549,
│ │ │ │ │ @@ -32797,15 +32794,15 @@
│ │ │ │ │          "14162": 2549,
│ │ │ │ │          "14166": 2552,
│ │ │ │ │          "14181": 2557,
│ │ │ │ │          "14194": 2552,
│ │ │ │ │          "14197": 2557,
│ │ │ │ │          "14198": 2552,
│ │ │ │ │          "14199": 2552,
│ │ │ │ │ -        "142": 654,
│ │ │ │ │ +        "142": [654, 2458],
│ │ │ │ │          "14200": 2552,
│ │ │ │ │          "14201": 2552,
│ │ │ │ │          "14211": 2550,
│ │ │ │ │          "14227": 2557,
│ │ │ │ │          "14228": 2552,
│ │ │ │ │          "14236": 2552,
│ │ │ │ │          "14237": 2552,
│ │ │ │ │ @@ -32882,14 +32879,15 @@
│ │ │ │ │          "14644661": 1754,
│ │ │ │ │          "14673309e": 2658,
│ │ │ │ │          "14682": 2557,
│ │ │ │ │          "14686": 2550,
│ │ │ │ │          "14687": 2554,
│ │ │ │ │          "14692469": 2627,
│ │ │ │ │          "146925": 2627,
│ │ │ │ │ +        "147": 2458,
│ │ │ │ │          "14717": 2557,
│ │ │ │ │          "14718": 2557,
│ │ │ │ │          "14720": 2557,
│ │ │ │ │          "14730": 2557,
│ │ │ │ │          "14758": 2555,
│ │ │ │ │          "14771": 2557,
│ │ │ │ │          "14777": 2557,
│ │ │ │ │ @@ -33073,14 +33071,15 @@
│ │ │ │ │          "16594": 2569,
│ │ │ │ │          "166": [674, 2460],
│ │ │ │ │          "16649": 2564,
│ │ │ │ │          "16650": 2569,
│ │ │ │ │          "16652": 2564,
│ │ │ │ │          "16654": 2564,
│ │ │ │ │          "16656": 2564,
│ │ │ │ │ +        "16662583": 2458,
│ │ │ │ │          "166659832": [849, 1029],
│ │ │ │ │          "16666667": [1524, 1542, 1757, 1869],
│ │ │ │ │          "166670640": [849, 1029],
│ │ │ │ │          "166691080": [849, 1029],
│ │ │ │ │          "16672": 2564,
│ │ │ │ │          "16675": 2569,
│ │ │ │ │          "16693": 2564,
│ │ │ │ │ @@ -33126,15 +33125,15 @@
│ │ │ │ │          "17000": 2565,
│ │ │ │ │          "17010": 2569,
│ │ │ │ │          "17015": 2565,
│ │ │ │ │          "17022005e": 54,
│ │ │ │ │          "17029": 2569,
│ │ │ │ │          "17067": 2569,
│ │ │ │ │          "17068": 2569,
│ │ │ │ │ -        "171": 2460,
│ │ │ │ │ +        "171": [2458, 2460],
│ │ │ │ │          "17116": 2569,
│ │ │ │ │          "17123": 2569,
│ │ │ │ │          "17125": 2565,
│ │ │ │ │          "17150989": 2627,
│ │ │ │ │          "171510": 2627,
│ │ │ │ │          "17157288": [641, 643],
│ │ │ │ │          "17195": 2569,
│ │ │ │ │ @@ -33175,26 +33174,26 @@
│ │ │ │ │          "176": 2460,
│ │ │ │ │          "17647": 2566,
│ │ │ │ │          "17652": 2566,
│ │ │ │ │          "17653": 2566,
│ │ │ │ │          "17660": 2566,
│ │ │ │ │          "17679": 2567,
│ │ │ │ │          "17680": 2567,
│ │ │ │ │ -        "177": [523, 575, 679, 2458, 2651],
│ │ │ │ │ +        "177": [523, 575, 679, 2651],
│ │ │ │ │          "17706": 2569,
│ │ │ │ │          "17709": 2585,
│ │ │ │ │          "17711": 28,
│ │ │ │ │          "17727": 2573,
│ │ │ │ │          "1774": [2326, 2370, 2417],
│ │ │ │ │          "17756": 2568,
│ │ │ │ │          "1776": 2609,
│ │ │ │ │          "17774": 2568,
│ │ │ │ │          "17775": 2568,
│ │ │ │ │          "17786": 2568,
│ │ │ │ │ -        "178": 575,
│ │ │ │ │ +        "178": [575, 2458],
│ │ │ │ │          "17843": [2573, 2580],
│ │ │ │ │          "17900": 2573,
│ │ │ │ │          "17917": 2568,
│ │ │ │ │          "17918": 2568,
│ │ │ │ │          "17919": 2568,
│ │ │ │ │          "17921": 2573,
│ │ │ │ │          "17924": 2568,
│ │ │ │ │ @@ -33459,15 +33458,15 @@
│ │ │ │ │          "1j": [47, 59, 82, 83, 88, 95, 103, 112, 113, 124, 135, 138, 225, 256, 352, 353, 359, 361, 422, 423, 428, 440, 453, 455, 458, 523, 547, 558, 569, 624, 640, 641, 643, 653, 658, 929, 1110, 1111, 1160, 1194, 1198, 1215, 1280, 1297, 1434, 1451, 1516, 1639, 1696, 1753, 1890, 1912, 1954, 1971, 2103, 2106, 2110, 2165, 2471, 2580, 2657, 2658],
│ │ │ │ │          "1l_0": 1820,
│ │ │ │ │          "1rc1": 586,
│ │ │ │ │          "1st": [36, 74, 641, 2613, 2629, 2633],
│ │ │ │ │          "1type": 2551,
│ │ │ │ │          "1xn": 2657,
│ │ │ │ │          "2": [0, 1, 2, 4, 5, 9, 12, 13, 14, 19, 20, 24, 25, 26, 29, 30, 31, 32, 34, 36, 37, 38, 43, 47, 48, 52, 53, 54, 55, 56, 58, 59, 60, 61, 62, 65, 66, 68, 69, 70, 72, 73, 74, 75, 76, 79, 80, 81, 82, 84, 85, 86, 87, 88, 95, 97, 98, 99, 104, 105, 106, 107, 108, 110, 111, 112, 113, 115, 116, 117, 118, 119, 120, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 172, 176, 177, 178, 179, 180, 185, 186, 193, 194, 195, 203, 205, 213, 219, 222, 223, 224, 236, 238, 243, 247, 248, 260, 270, 271, 272, 273, 279, 287, 289, 293, 296, 299, 302, 310, 312, 324, 325, 337, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 398, 399, 403, 405, 407, 409, 410, 413, 417, 418, 419, 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│ │ │ │ │ -        "20": [0, 21, 22, 24, 32, 38, 47, 54, 55, 57, 58, 59, 60, 74, 78, 99, 104, 107, 108, 122, 129, 130, 132, 133, 146, 150, 152, 169, 172, 279, 296, 345, 350, 351, 358, 363, 365, 367, 380, 429, 445, 447, 448, 450, 452, 453, 454, 455, 457, 458, 459, 460, 461, 462, 463, 464, 489, 490, 491, 492, 495, 496, 498, 522, 536, 543, 549, 557, 576, 577, 578, 579, 627, 652, 666, 668, 819, 847, 850, 854, 856, 859, 863, 865, 869, 879, 892, 895, 896, 899, 900, 904, 905, 911, 912, 916, 932, 936, 939, 940, 946, 950, 955, 957, 964, 966, 976, 984, 985, 989, 1018, 1023, 1024, 1025, 1030, 1037, 1039, 1043, 1048, 1050, 1055, 1068, 1082, 1087, 1088, 1093, 1096, 1099, 1100, 1105, 1108, 1113, 1116, 1117, 1122, 1123, 1130, 1142, 1144, 1145, 1228, 1240, 1245, 1310, 1322, 1464, 1476, 1480, 1514, 1806, 1865, 1869, 1904, 1984, 1996, 2071, 2087, 2113, 2163, 2170, 2172, 2201, 2202, 2206, 2221, 2222, 2235, 2236, 2238, 2246, 2253, 2254, 2267, 2297, 2313, 2316, 2318, 2320, 2325, 2330, 2334, 2335, 2339, 2345, 2358, 2362, 2374, 2377, 2378, 2380, 2385, 2387, 2405, 2409, 2421, 2424, 2425, 2427, 2432, 2435, 2458, 2459, 2460, 2467, 2510, 2514, 2516, 2530, 2532, 2539, 2557, 2568, 2573, 2574, 2580, 2581, 2591, 2596, 2599, 2600, 2605, 2619, 2624, 2627, 2629, 2633, 2634, 2637, 2649, 2650, 2658],
│ │ │ │ │ +        "20": [0, 21, 22, 24, 32, 38, 47, 54, 55, 57, 58, 59, 60, 74, 78, 99, 104, 107, 108, 122, 129, 130, 132, 133, 146, 150, 152, 169, 172, 279, 296, 345, 350, 351, 358, 363, 365, 367, 380, 429, 445, 447, 448, 450, 452, 453, 454, 455, 457, 458, 459, 460, 461, 462, 463, 464, 489, 490, 491, 492, 495, 496, 498, 522, 536, 543, 549, 557, 576, 577, 578, 579, 627, 652, 666, 668, 819, 847, 850, 854, 856, 859, 863, 865, 869, 879, 892, 895, 896, 899, 900, 904, 905, 911, 912, 916, 932, 936, 939, 940, 946, 950, 955, 957, 964, 966, 976, 984, 985, 989, 1018, 1023, 1024, 1025, 1030, 1037, 1039, 1043, 1048, 1050, 1055, 1068, 1082, 1087, 1088, 1093, 1096, 1099, 1100, 1105, 1108, 1113, 1116, 1117, 1122, 1123, 1130, 1142, 1144, 1145, 1228, 1240, 1245, 1310, 1322, 1464, 1476, 1480, 1514, 1806, 1865, 1869, 1904, 1984, 1996, 2071, 2087, 2113, 2163, 2170, 2172, 2201, 2202, 2206, 2221, 2222, 2235, 2236, 2238, 2246, 2253, 2254, 2267, 2297, 2313, 2316, 2318, 2320, 2325, 2330, 2334, 2335, 2339, 2345, 2358, 2362, 2374, 2377, 2378, 2380, 2385, 2387, 2405, 2409, 2421, 2424, 2425, 2427, 2432, 2435, 2459, 2460, 2467, 2510, 2514, 2516, 2530, 2532, 2539, 2557, 2568, 2573, 2574, 2580, 2581, 2591, 2596, 2599, 2600, 2605, 2619, 2624, 2627, 2629, 2633, 2634, 2637, 2649, 2650, 2658],
│ │ │ │ │          "200": [450, 455, 2334, 2336, 2343, 2351, 2354, 2377, 2379, 2389, 2398, 2401, 2424, 2426, 2438, 2448, 2451, 2637, 2640, 2658],
│ │ │ │ │          "2000": [523, 535, 2522, 2610],
│ │ │ │ │          "20000": [2313, 2356, 2358, 2403, 2405, 2453, 2580],
│ │ │ │ │          "2000000": 2627,
│ │ │ │ │          "20000000e": 896,
│ │ │ │ │          "2001": [55, 2319, 2323, 2326, 2327, 2328, 2332, 2336, 2337, 2363, 2368, 2370, 2371, 2372, 2375, 2379, 2380, 2410, 2415, 2417, 2418, 2419, 2422, 2426, 2427],
│ │ │ │ │          "2002": [55, 369, 2313, 2320, 2350, 2358, 2364, 2397, 2405, 2411, 2447],
│ │ │ │ │ @@ -33530,14 +33529,15 @@
│ │ │ │ │          "20300": 2577,
│ │ │ │ │          "20302": 2577,
│ │ │ │ │          "20314": 2580,
│ │ │ │ │          "20324493e": 54,
│ │ │ │ │          "2033": 2609,
│ │ │ │ │          "20357": 2578,
│ │ │ │ │          "20394": 2585,
│ │ │ │ │ +        "204": 2458,
│ │ │ │ │          "20414": 2585,
│ │ │ │ │          "2045": 2609,
│ │ │ │ │          "2046": 2609,
│ │ │ │ │          "20462": 2578,
│ │ │ │ │          "20463": 2578,
│ │ │ │ │          "20464": 2578,
│ │ │ │ │          "20465": 2578,
│ │ │ │ │ @@ -33610,21 +33610,21 @@
│ │ │ │ │          "20985": 2582,
│ │ │ │ │          "20986": 2582,
│ │ │ │ │          "20992": 2582,
│ │ │ │ │          "20993": 2585,
│ │ │ │ │          "20_ver": 0,
│ │ │ │ │          "20count": 150,
│ │ │ │ │          "20d03bcfd": 0,
│ │ │ │ │ -        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 107, 171, 172, 279, 345, 366, 368, 386, 397, 405, 412, 485, 486, 627, 668, 879, 904, 943, 1068, 1228, 1310, 1464, 1867, 1879, 1984, 2089, 2170, 2206, 2223, 2235, 2236, 2339, 2340, 2458, 2460, 2510, 2512, 2514, 2516, 2564, 2565, 2569, 2580, 2582, 2585, 2591, 2624, 2625, 2627, 2629, 2633, 2634, 2641, 2646, 2649, 2657, 2658, 2660],
│ │ │ │ │ +        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 107, 171, 172, 279, 345, 366, 368, 386, 397, 405, 412, 485, 486, 627, 668, 879, 904, 943, 1068, 1228, 1310, 1464, 1867, 1879, 1984, 2089, 2170, 2206, 2223, 2235, 2236, 2339, 2340, 2460, 2510, 2512, 2514, 2516, 2564, 2565, 2569, 2580, 2582, 2585, 2591, 2624, 2625, 2627, 2629, 2633, 2634, 2641, 2646, 2649, 2657, 2658, 2660],
│ │ │ │ │          "210": 372,
│ │ │ │ │          "21001": 2585,
│ │ │ │ │          "21029": 2585,
│ │ │ │ │          "210306068529402873165736369884012333109": [2272, 2277],
│ │ │ │ │          "21048": 2583,
│ │ │ │ │ -        "211": 2488,
│ │ │ │ │ +        "211": [2458, 2488],
│ │ │ │ │          "21106": 2583,
│ │ │ │ │          "21120": 2596,
│ │ │ │ │          "21130": 2585,
│ │ │ │ │          "21137": 2583,
│ │ │ │ │          "21138": 2583,
│ │ │ │ │          "21139": 2583,
│ │ │ │ │          "21140": 2583,
│ │ │ │ │ @@ -33875,15 +33875,15 @@
│ │ │ │ │          "23208": 2594,
│ │ │ │ │          "23221": 2594,
│ │ │ │ │          "23226": 2594,
│ │ │ │ │          "23229": 2596,
│ │ │ │ │          "23240": 2596,
│ │ │ │ │          "23275": 2596,
│ │ │ │ │          "23297648": 358,
│ │ │ │ │ -        "233": [28, 2458, 2460],
│ │ │ │ │ +        "233": [28, 2460],
│ │ │ │ │          "23302": 2596,
│ │ │ │ │          "23314": 2596,
│ │ │ │ │          "23322": 2596,
│ │ │ │ │          "23341": 2594,
│ │ │ │ │          "23342": 2594,
│ │ │ │ │          "23343": 2594,
│ │ │ │ │          "23344": 2594,
│ │ │ │ │ @@ -34176,14 +34176,15 @@
│ │ │ │ │          "25203": 2602,
│ │ │ │ │          "25204": 2602,
│ │ │ │ │          "25205": 2602,
│ │ │ │ │          "25217": 2602,
│ │ │ │ │          "25218": 2602,
│ │ │ │ │          "25219": 2602,
│ │ │ │ │          "25227": 2602,
│ │ │ │ │ +        "25228213": 2485,
│ │ │ │ │          "25233": 2619,
│ │ │ │ │          "25240": 2602,
│ │ │ │ │          "25249": 2602,
│ │ │ │ │          "25255": 2619,
│ │ │ │ │          "25271": 2619,
│ │ │ │ │          "25276297": 2647,
│ │ │ │ │          "25292": 2619,
│ │ │ │ │ @@ -34225,15 +34226,14 @@
│ │ │ │ │          "25495": 2619,
│ │ │ │ │          "255": [62, 149, 152, 153, 296, 379, 497, 579, 598, 942, 1240, 1322, 1476, 1996, 2301, 2596, 2610, 2619, 2658],
│ │ │ │ │          "25523": 2603,
│ │ │ │ │          "25528411": [2384, 2431],
│ │ │ │ │          "25531": 2619,
│ │ │ │ │          "25536": 2619,
│ │ │ │ │          "25539": 2603,
│ │ │ │ │ -        "25546594": 2485,
│ │ │ │ │          "25553": 2619,
│ │ │ │ │          "25557246e": 447,
│ │ │ │ │          "25570": 2619,
│ │ │ │ │          "25584": 2603,
│ │ │ │ │          "25585": 2603,
│ │ │ │ │          "25599": 2603,
│ │ │ │ │          "256": [69, 87, 195, 296, 342, 427, 447, 523, 826, 998, 1171, 1240, 1257, 1322, 1412, 1476, 1931, 1996, 2156, 2287, 2300, 2301, 2458, 2459, 2610, 2629, 2642],
│ │ │ │ │ @@ -34273,15 +34273,15 @@
│ │ │ │ │          "25914": 2619,
│ │ │ │ │          "25943": 2619,
│ │ │ │ │          "25954": 2619,
│ │ │ │ │          "25d0": 32,
│ │ │ │ │          "25j": 2651,
│ │ │ │ │          "25t03": 55,
│ │ │ │ │          "25x": 147,
│ │ │ │ │ -        "26": [21, 29, 30, 40, 50, 54, 55, 58, 63, 79, 155, 892, 943, 1082, 1142, 1345, 1347, 2113, 2202, 2206, 2238, 2307, 2330, 2374, 2421, 2458, 2510, 2516, 2531, 2533, 2534, 2574, 2596, 2598, 2619, 2622, 2633, 2649, 2650, 2658],
│ │ │ │ │ +        "26": [21, 29, 30, 40, 50, 54, 55, 58, 63, 79, 155, 892, 943, 1082, 1142, 1345, 1347, 2113, 2202, 2206, 2238, 2307, 2330, 2374, 2421, 2510, 2516, 2531, 2533, 2534, 2574, 2596, 2598, 2619, 2622, 2633, 2649, 2650, 2658],
│ │ │ │ │          "260": [171, 1326, 2236, 2573, 2658],
│ │ │ │ │          "26064346e": 156,
│ │ │ │ │          "26081": 2622,
│ │ │ │ │          "26103": 2622,
│ │ │ │ │          "26137788e": 2102,
│ │ │ │ │          "26157": 2622,
│ │ │ │ │          "262": 2658,
│ │ │ │ │ @@ -34376,14 +34376,15 @@
│ │ │ │ │          "27267": 2623,
│ │ │ │ │          "27276": 2623,
│ │ │ │ │          "27278": 2623,
│ │ │ │ │          "27279": 2621,
│ │ │ │ │          "27287": 2623,
│ │ │ │ │          "27303": 2623,
│ │ │ │ │          "27304": 2623,
│ │ │ │ │ +        "27307693": 2458,
│ │ │ │ │          "27333": 2624,
│ │ │ │ │          "27400": 2624,
│ │ │ │ │          "27406": 2624,
│ │ │ │ │          "27416": 2624,
│ │ │ │ │          "27433": 2624,
│ │ │ │ │          "27437": 2624,
│ │ │ │ │          "27439": 2624,
│ │ │ │ │ @@ -34427,15 +34428,15 @@
│ │ │ │ │          "27t00": 369,
│ │ │ │ │          "27t01": 369,
│ │ │ │ │          "27t02": 369,
│ │ │ │ │          "27t04": 369,
│ │ │ │ │          "27t05": 369,
│ │ │ │ │          "27t06": 369,
│ │ │ │ │          "27t07": 369,
│ │ │ │ │ -        "28": [36, 54, 55, 155, 418, 1693, 1702, 1705, 1860, 2206, 2223, 2460, 2510, 2535, 2536, 2537, 2540, 2633, 2641, 2649, 2651, 2658],
│ │ │ │ │ +        "28": [36, 54, 55, 155, 418, 1693, 1702, 1705, 1860, 2206, 2223, 2458, 2460, 2510, 2535, 2536, 2537, 2540, 2633, 2641, 2649, 2651, 2658],
│ │ │ │ │          "28000000e": 1333,
│ │ │ │ │          "2800000e": 1333,
│ │ │ │ │          "2801": 2610,
│ │ │ │ │          "281": 2460,
│ │ │ │ │          "2826": [296, 1240, 1322, 1476, 1996],
│ │ │ │ │          "28293632": 99,
│ │ │ │ │          "2829785": 1153,
│ │ │ │ │ @@ -34563,15 +34564,15 @@
│ │ │ │ │          "3263": 2614,
│ │ │ │ │          "32767": 544,
│ │ │ │ │          "32768": 544,
│ │ │ │ │          "32_767": 62,
│ │ │ │ │          "32_768": 62,
│ │ │ │ │          "32bit": [50, 61, 62, 2361, 2374, 2376, 2385, 2408, 2421, 2423, 2432, 2514, 2569, 2586],
│ │ │ │ │          "32x": 2580,
│ │ │ │ │ -        "33": [54, 58, 153, 345, 837, 938, 940, 1009, 1905, 1920, 1997, 2171, 2173, 2174, 2206, 2300, 2510, 2618, 2629, 2633, 2649, 2658],
│ │ │ │ │ +        "33": [54, 58, 153, 345, 837, 938, 940, 1009, 1905, 1920, 1997, 2171, 2173, 2174, 2206, 2300, 2458, 2510, 2618, 2629, 2633, 2649, 2658],
│ │ │ │ │          "330": 372,
│ │ │ │ │          "3301": 2612,
│ │ │ │ │          "330m": 418,
│ │ │ │ │          "3312": 2612,
│ │ │ │ │          "3324": [13, 2612],
│ │ │ │ │          "333": [651, 949, 2171],
│ │ │ │ │          "33333": [2171, 2173],
│ │ │ │ │ @@ -34614,17 +34615,19 @@
│ │ │ │ │          "3504": 2614,
│ │ │ │ │          "3534857623790153": 665,
│ │ │ │ │          "35355339": 1634,
│ │ │ │ │          "3541": 2612,
│ │ │ │ │          "35489284e": 2102,
│ │ │ │ │          "36": [58, 146, 364, 1750, 1759, 2202, 2223, 2320, 2364, 2411, 2460, 2488, 2533, 2641, 2649, 2651, 2658],
│ │ │ │ │          "360": [553, 2101, 2236, 2573],
│ │ │ │ │ +        "36011562": 2458,
│ │ │ │ │          "36045180e": 156,
│ │ │ │ │          "3608": 2612,
│ │ │ │ │          "361": [1342, 1344, 1520, 1906],
│ │ │ │ │ +        "36163253": 2458,
│ │ │ │ │          "362": 12,
│ │ │ │ │          "3628523": 2455,
│ │ │ │ │          "36363636": 145,
│ │ │ │ │          "3644j": [84, 424],
│ │ │ │ │          "365": [553, 1342, 1344, 1520, 1906],
│ │ │ │ │          "366": 55,
│ │ │ │ │          "36674": 2096,
│ │ │ │ │ @@ -34696,27 +34699,29 @@
│ │ │ │ │          "4007": 2617,
│ │ │ │ │          "40077": [1642, 1654],
│ │ │ │ │          "400e": 2650,
│ │ │ │ │          "4018": [2612, 2614],
│ │ │ │ │          "4024": 2614,
│ │ │ │ │          "4027": 2614,
│ │ │ │ │          "40274501": 1153,
│ │ │ │ │ +        "4044994": 2485,
│ │ │ │ │          "4051": [2612, 2614],
│ │ │ │ │          "409": 2460,
│ │ │ │ │          "40918587e": 2102,
│ │ │ │ │          "40919914": 2658,
│ │ │ │ │          "4093": 2614,
│ │ │ │ │          "4094": [2612, 2614],
│ │ │ │ │          "4096": [72, 2090],
│ │ │ │ │          "41": [940, 1113, 1122, 1123, 1130, 1911, 2102, 2105, 2206, 2234, 2582, 2649, 2658],
│ │ │ │ │          "4109": 2614,
│ │ │ │ │          "41211849": 2658,
│ │ │ │ │          "4123": [2612, 2614],
│ │ │ │ │          "4134": 2614,
│ │ │ │ │          "41357986e": 2173,
│ │ │ │ │ +        "4137339": 2458,
│ │ │ │ │          "4138": 2614,
│ │ │ │ │          "4141": 2612,
│ │ │ │ │          "41421356": [652, 1754, 2658],
│ │ │ │ │          "4142135623730951": [59, 636],
│ │ │ │ │          "4142135623730951j": 59,
│ │ │ │ │          "41421356j": 1525,
│ │ │ │ │          "4144": 2614,
│ │ │ │ │ @@ -34762,15 +34767,15 @@
│ │ │ │ │          "4354": 2614,
│ │ │ │ │          "4359": 2614,
│ │ │ │ │          "4368": [296, 1240, 1322, 1476, 1996],
│ │ │ │ │          "4375": 2488,
│ │ │ │ │          "43857224": 1152,
│ │ │ │ │          "43887844": [358, 2454, 2631],
│ │ │ │ │          "43999999999998": 1113,
│ │ │ │ │ -        "44": [16, 1523, 1756, 1903, 1905, 1920, 2206, 2458, 2460, 2621, 2649, 2650, 2651, 2658],
│ │ │ │ │ +        "44": [16, 1523, 1756, 1903, 1905, 1920, 2206, 2460, 2621, 2649, 2650, 2651, 2658],
│ │ │ │ │          "440": [10, 2517],
│ │ │ │ │          "4400": [418, 660, 2166],
│ │ │ │ │          "44069024": 358,
│ │ │ │ │          "4408": 2614,
│ │ │ │ │          "44089210e": 1525,
│ │ │ │ │          "4408921e": [1763, 2173],
│ │ │ │ │          "4409e": 2089,
│ │ │ │ │ @@ -34835,15 +34840,14 @@
│ │ │ │ │          "4723": 2618,
│ │ │ │ │          "4730": [418, 660, 2166],
│ │ │ │ │          "4733": 2615,
│ │ │ │ │          "47458546": 358,
│ │ │ │ │          "47536961": 358,
│ │ │ │ │          "47613949": [2332, 2375, 2422],
│ │ │ │ │          "4774": 2615,
│ │ │ │ │ -        "47787383": 2458,
│ │ │ │ │          "479": 2617,
│ │ │ │ │          "4796": [418, 660, 2166],
│ │ │ │ │          "48": [58, 279, 364, 879, 1068, 1141, 1228, 1310, 1464, 1865, 1984, 2206, 2237, 2320, 2364, 2411, 2649, 2651],
│ │ │ │ │          "480": [247, 857, 1040, 1206, 1288, 1442, 1962],
│ │ │ │ │          "4800": 57,
│ │ │ │ │          "48000000": 2627,
│ │ │ │ │          "4809319": 1152,
│ │ │ │ │ @@ -34923,16 +34927,17 @@
│ │ │ │ │          "51658839e": 1584,
│ │ │ │ │          "517": 10,
│ │ │ │ │          "5170": 2617,
│ │ │ │ │          "5184": 2617,
│ │ │ │ │          "51851852": 1807,
│ │ │ │ │          "519928": 2627,
│ │ │ │ │          "51992837": 2627,
│ │ │ │ │ -        "52": [10, 50, 62, 466, 1636, 1645, 1648, 2202, 2206, 2551, 2627, 2633, 2640, 2649, 2651, 2652, 2658],
│ │ │ │ │ +        "52": [10, 50, 62, 466, 1636, 1645, 1648, 2202, 2206, 2458, 2551, 2627, 2633, 2640, 2649, 2651, 2652, 2658],
│ │ │ │ │          "5203": 2617,
│ │ │ │ │ +        "52142238": 2458,
│ │ │ │ │          "5225": 2617,
│ │ │ │ │          "5231": 2617,
│ │ │ │ │          "52338984": [2342, 2388, 2436],
│ │ │ │ │          "52359878": 1909,
│ │ │ │ │          "52380952e": 1814,
│ │ │ │ │          "5240": 2617,
│ │ │ │ │          "5251": 2617,
│ │ │ │ │ @@ -34951,14 +34956,15 @@
│ │ │ │ │          "536870910": 1900,
│ │ │ │ │          "5374": 2618,
│ │ │ │ │          "53814331": 2658,
│ │ │ │ │          "5388": 2618,
│ │ │ │ │          "5390": 2618,
│ │ │ │ │          "5393": 2618,
│ │ │ │ │          "5396": [296, 1240, 1322, 1476, 1996],
│ │ │ │ │ +        "53980225": 2458,
│ │ │ │ │          "54": [38, 59, 532, 1636, 1709, 1762, 2206, 2634, 2649],
│ │ │ │ │          "540": [2236, 2573],
│ │ │ │ │          "54030231": 2658,
│ │ │ │ │          "54030231j": 2658,
│ │ │ │ │          "541": 2460,
│ │ │ │ │          "54117": 1642,
│ │ │ │ │          "5424": 2618,
│ │ │ │ │ @@ -35043,29 +35049,28 @@
│ │ │ │ │          "6019": 2519,
│ │ │ │ │          "60393245": 659,
│ │ │ │ │          "60546483": 532,
│ │ │ │ │          "60663578": 2627,
│ │ │ │ │          "607": [2336, 2379, 2426],
│ │ │ │ │          "60860684e": 1592,
│ │ │ │ │          "609": 2580,
│ │ │ │ │ -        "60935161": 2458,
│ │ │ │ │          "6094": 2519,
│ │ │ │ │          "60x": 2596,
│ │ │ │ │          "61": [13, 2649],
│ │ │ │ │          "610": 28,
│ │ │ │ │          "61119": 2096,
│ │ │ │ │          "614064523559687": 2113,
│ │ │ │ │          "6143849206349179": [1112, 1541],
│ │ │ │ │          "6176": [108, 905],
│ │ │ │ │          "61799388": 1909,
│ │ │ │ │          "618": 668,
│ │ │ │ │          "6180": [2350, 2397, 2447],
│ │ │ │ │          "61988120985": [2320, 2364, 2411],
│ │ │ │ │          "61c54bbd": 42,
│ │ │ │ │ -        "62": [551, 967, 968, 2320, 2330, 2364, 2374, 2411, 2421, 2649],
│ │ │ │ │ +        "62": [551, 967, 968, 2320, 2330, 2364, 2374, 2411, 2421, 2458, 2649],
│ │ │ │ │          "6208": 2519,
│ │ │ │ │          "6227766": 523,
│ │ │ │ │          "623": [2391, 2441],
│ │ │ │ │          "62318272": [2316, 2360, 2407],
│ │ │ │ │          "62341325": 523,
│ │ │ │ │          "62374854": 2658,
│ │ │ │ │          "624": [2297, 2367, 2391, 2414, 2441, 2459],
│ │ │ │ │ @@ -35129,14 +35134,15 @@
│ │ │ │ │          "65535": [593, 2616, 2619],
│ │ │ │ │          "6556": 2519,
│ │ │ │ │          "6558": 2519,
│ │ │ │ │          "6562": 2519,
│ │ │ │ │          "6563": 2519,
│ │ │ │ │          "6566128774142013e": 652,
│ │ │ │ │          "6567": 2519,
│ │ │ │ │ +        "65678152": 2485,
│ │ │ │ │          "65685425": 2651,
│ │ │ │ │          "6569": 2519,
│ │ │ │ │          "6569866": 2658,
│ │ │ │ │          "6572": 2519,
│ │ │ │ │          "6574": 2519,
│ │ │ │ │          "65745445": [97, 110],
│ │ │ │ │          "6575": 2519,
│ │ │ │ │ @@ -35203,28 +35209,26 @@
│ │ │ │ │          "6805": [2350, 2397, 2447],
│ │ │ │ │          "6807": 2519,
│ │ │ │ │          "68080986": 358,
│ │ │ │ │          "6813": 2519,
│ │ │ │ │          "6817": 2519,
│ │ │ │ │          "6819": 2519,
│ │ │ │ │          "68206631e": 2102,
│ │ │ │ │ -        "68221996": 2485,
│ │ │ │ │          "684": [2460, 2569],
│ │ │ │ │          "6840": 2521,
│ │ │ │ │          "6843": 2521,
│ │ │ │ │          "68456316": [2336, 2349, 2379, 2386, 2396, 2426, 2433, 2446],
│ │ │ │ │          "68482974": 1152,
│ │ │ │ │          "6884": 2521,
│ │ │ │ │          "68862757": 659,
│ │ │ │ │          "6888893": [2349, 2396, 2446],
│ │ │ │ │          "69": [58, 440, 2649, 2658],
│ │ │ │ │          "6916": 2521,
│ │ │ │ │          "6922": 2521,
│ │ │ │ │          "6924": 2521,
│ │ │ │ │ -        "69242368": 2458,
│ │ │ │ │          "69312169": [1112, 1541],
│ │ │ │ │          "69314718": [76, 656, 2647],
│ │ │ │ │          "69314718055994529": 656,
│ │ │ │ │          "6931471805599453": 2254,
│ │ │ │ │          "6937": 2521,
│ │ │ │ │          "6942": 2521,
│ │ │ │ │          "6943": 2521,
│ │ │ │ │ @@ -35247,14 +35251,15 @@
│ │ │ │ │          "701": 2460,
│ │ │ │ │          "703": 2622,
│ │ │ │ │          "7054": 2532,
│ │ │ │ │          "706": 529,
│ │ │ │ │          "70710678": [225, 256, 640, 1198, 1215, 1280, 1297, 1434, 1451, 1634, 1640, 1954, 1971, 2101],
│ │ │ │ │          "70710678118654746": 636,
│ │ │ │ │          "70710678j": 640,
│ │ │ │ │ +        "70817669": 2458,
│ │ │ │ │          "7083": 2526,
│ │ │ │ │          "71": [363, 649, 2457, 2649],
│ │ │ │ │          "71080601": 2651,
│ │ │ │ │          "71238898": 1909,
│ │ │ │ │          "71387850e": 1584,
│ │ │ │ │          "718281": 440,
│ │ │ │ │          "71828182845904523536028747135266249775724709369995": 76,
│ │ │ │ │ @@ -35272,15 +35277,15 @@
│ │ │ │ │          "72686684e": 575,
│ │ │ │ │          "72717132": 2651,
│ │ │ │ │          "72727273": 145,
│ │ │ │ │          "72847407": 1153,
│ │ │ │ │          "729": 2658,
│ │ │ │ │          "72904971": 1152,
│ │ │ │ │          "72949656": 2627,
│ │ │ │ │ -        "73": [2458, 2460, 2649],
│ │ │ │ │ +        "73": [2460, 2649],
│ │ │ │ │          "7320508075688772j": 59,
│ │ │ │ │          "73472348e": 1814,
│ │ │ │ │          "73496154e": 1865,
│ │ │ │ │          "73603959e": 2658,
│ │ │ │ │          "73799541": 1152,
│ │ │ │ │          "74": [2460, 2510, 2511, 2649],
│ │ │ │ │          "74000000": 2627,
│ │ │ │ │ @@ -35309,15 +35314,15 @@
│ │ │ │ │          "7568025": 2658,
│ │ │ │ │          "75682846": 2651,
│ │ │ │ │          "7578": 2523,
│ │ │ │ │          "7590": 2523,
│ │ │ │ │          "75958653": 1909,
│ │ │ │ │          "7597": 2523,
│ │ │ │ │          "75j": 2651,
│ │ │ │ │ -        "76": [550, 1895, 2458, 2460, 2649, 2651],
│ │ │ │ │ +        "76": [550, 1895, 2460, 2649, 2651],
│ │ │ │ │          "7608": 2523,
│ │ │ │ │          "7611397": [358, 2454, 2631],
│ │ │ │ │          "76190476e": 1814,
│ │ │ │ │          "76322758": 1153,
│ │ │ │ │          "7638": 2523,
│ │ │ │ │          "76425276e": 1148,
│ │ │ │ │          "76492172": 358,
│ │ │ │ │ @@ -35328,15 +35333,15 @@
│ │ │ │ │          "7670": 2523,
│ │ │ │ │          "7671": 2523,
│ │ │ │ │          "7676": 2523,
│ │ │ │ │          "7680": 2523,
│ │ │ │ │          "769893": 2627,
│ │ │ │ │          "76989341": 2627,
│ │ │ │ │          "76991118": 1889,
│ │ │ │ │ -        "77": [29, 36, 37, 38, 39, 2458, 2460, 2627, 2646, 2649],
│ │ │ │ │ +        "77": [29, 36, 37, 38, 39, 2460, 2627, 2646, 2649],
│ │ │ │ │          "770": [296, 1240, 1322, 1476, 1996, 2642],
│ │ │ │ │          "77086955": 1524,
│ │ │ │ │          "7724": 2523,
│ │ │ │ │          "7725": [2350, 2397, 2447],
│ │ │ │ │          "7731": 2523,
│ │ │ │ │          "7736": 2524,
│ │ │ │ │          "7737": 2523,
│ │ │ │ │ @@ -35351,15 +35356,14 @@
│ │ │ │ │          "7778": 2524,
│ │ │ │ │          "7793": 2524,
│ │ │ │ │          "78": [2089, 2636, 2649],
│ │ │ │ │          "78096262": [2349, 2396, 2446],
│ │ │ │ │          "7816": 2524,
│ │ │ │ │          "7821": 2524,
│ │ │ │ │          "7824": 2524,
│ │ │ │ │ -        "78327068": 2458,
│ │ │ │ │          "7835": 2524,
│ │ │ │ │          "784": 2460,
│ │ │ │ │          "7847": 2524,
│ │ │ │ │          "784728999999999": 1113,
│ │ │ │ │          "7849": 2524,
│ │ │ │ │          "78497f4": 2518,
│ │ │ │ │          "7851": 2524,
│ │ │ │ │ @@ -35369,15 +35373,14 @@
│ │ │ │ │          "78571429e": 1814,
│ │ │ │ │          "78606431": [358, 2454, 2631],
│ │ │ │ │          "789": 2636,
│ │ │ │ │          "7896": 2524,
│ │ │ │ │          "79": [13, 96, 109, 113, 138, 2649],
│ │ │ │ │          "79033856e": 1148,
│ │ │ │ │          "7904": 2524,
│ │ │ │ │ -        "79074583": 2458,
│ │ │ │ │          "7917": 2524,
│ │ │ │ │          "7919": 2524,
│ │ │ │ │          "7920": [1211, 2524],
│ │ │ │ │          "7932": 2524,
│ │ │ │ │          "7939": 2524,
│ │ │ │ │          "79479508": [2342, 2388, 2436],
│ │ │ │ │          "795": 649,
│ │ │ │ │ @@ -35413,26 +35416,25 @@
│ │ │ │ │          "81299683": 2627,
│ │ │ │ │          "812997": 2627,
│ │ │ │ │          "813": [279, 879, 1068, 1228, 1310, 1464, 1984],
│ │ │ │ │          "81327024": 2627,
│ │ │ │ │          "81349206": [1112, 1541],
│ │ │ │ │          "81814867": [2336, 2349, 2379, 2386, 2396, 2426, 2433, 2446],
│ │ │ │ │          "8192": [72, 526, 2090, 2616],
│ │ │ │ │ -        "82": [1648, 2320, 2364, 2411, 2460, 2649, 2658],
│ │ │ │ │ +        "82": [1648, 2320, 2364, 2411, 2458, 2460, 2649, 2658],
│ │ │ │ │          "8207540608310198": [2350, 2397, 2447],
│ │ │ │ │          "82276161": 358,
│ │ │ │ │          "8230": [2350, 2397, 2447],
│ │ │ │ │          "82485143": 2627,
│ │ │ │ │          "82502011": 358,
│ │ │ │ │          "8255": 2563,
│ │ │ │ │          "826716f": 2518,
│ │ │ │ │          "82743037": 533,
│ │ │ │ │          "82770259": 2658,
│ │ │ │ │          "8277025938204418": 2658,
│ │ │ │ │ -        "8278483": 2458,
│ │ │ │ │          "827941": [523, 679, 2651],
│ │ │ │ │          "82842712": [641, 643],
│ │ │ │ │          "83": [2103, 2165, 2350, 2397, 2447, 2551, 2649],
│ │ │ │ │          "83314899": 1153,
│ │ │ │ │          "83333333": 1700,
│ │ │ │ │          "833333333333333": [892, 1082, 1142, 2238],
│ │ │ │ │          "8341": 2525,
│ │ │ │ │ @@ -35458,15 +35460,15 @@
│ │ │ │ │          "85602287": [2332, 2375, 2422],
│ │ │ │ │          "857": 419,
│ │ │ │ │          "8570331885190563e": [647, 652],
│ │ │ │ │          "85715698e": 2169,
│ │ │ │ │          "8577": 2536,
│ │ │ │ │          "85859792": [358, 2454, 2631],
│ │ │ │ │          "8595784": 2627,
│ │ │ │ │ -        "86": [59, 97, 110, 112, 115, 135, 140, 551, 967, 968, 2320, 2364, 2411, 2458, 2488, 2649],
│ │ │ │ │ +        "86": [59, 97, 110, 112, 115, 135, 140, 551, 967, 968, 2320, 2364, 2411, 2488, 2649],
│ │ │ │ │          "8601": [55, 62, 67, 2610],
│ │ │ │ │          "86260211e": 54,
│ │ │ │ │          "8630830": 13,
│ │ │ │ │          "86399": 55,
│ │ │ │ │          "86400": 55,
│ │ │ │ │          "86401": 55,
│ │ │ │ │          "8660254": 2101,
│ │ │ │ │ @@ -35545,24 +35547,24 @@
│ │ │ │ │          "934284": 358,
│ │ │ │ │          "93657855": 358,
│ │ │ │ │          "9371": 2529,
│ │ │ │ │          "9372": 2529,
│ │ │ │ │          "9373": 2529,
│ │ │ │ │          "9374": 2529,
│ │ │ │ │          "9376": 2529,
│ │ │ │ │ -        "9376859": 2485,
│ │ │ │ │          "9377": 2529,
│ │ │ │ │          "93773029": 358,
│ │ │ │ │          "9378": 2529,
│ │ │ │ │          "9379": 2529,
│ │ │ │ │          "9390": [2530, 2531],
│ │ │ │ │          "94": [418, 668, 2627, 2649],
│ │ │ │ │          "940": 2584,
│ │ │ │ │          "941257": 2627,
│ │ │ │ │          "94125714": 2627,
│ │ │ │ │ +        "94495158": 2485,
│ │ │ │ │          "94708397920832": 2634,
│ │ │ │ │          "9475673279178444": 2345,
│ │ │ │ │          "94864945": 2658,
│ │ │ │ │          "94909878": [2384, 2431],
│ │ │ │ │          "95": [37, 39, 645, 2350, 2397, 2447, 2627, 2646, 2649],
│ │ │ │ │          "9504637": 2658,
│ │ │ │ │          "950684": 2627,