--- /srv/reproducible-results/rbuild-debian/r-b-build.Bhe7UtWe/b1/numpy_2.2.4+ds-1_i386.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.Bhe7UtWe/b2/numpy_2.2.4+ds-1_i386.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - ec57c3af03287470732dff9db408b88c 5814320 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│ + a9bda27846303a39e116f9b2c7cc5ddb 5813972 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│   d6fcb46411900e5db7d5fe338a86fc95 29558272 debug optional python3-numpy-dbgsym_2.2.4+ds-1_i386.deb
│   df1588b87ce74d5a57d75cf3abc9309d 145412 python optional python3-numpy-dev_2.2.4+ds-1_i386.deb
│   7b549317f7f472ce978ceb0b2d7b3271 5060276 python optional python3-numpy_2.2.4+ds-1_i386.deb
├── python-numpy-doc_2.2.4+ds-1_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2025-04-01 19:45:23.000000 debian-binary
│ │  -rw-r--r--   0        0        0    64888 2025-04-01 19:45:23.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5749240 2025-04-01 19:45:23.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0  5748892 2025-04-01 19:45:23.000000 data.tar.xz
│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./md5sums
│ │ │ │ ├── ./md5sums
│ │ │ │ │┄ Files differ
│ ├── data.tar.xz
│ │ ├── data.tar
│ │ │ ├── file list
│ │ │ │ @@ -2578,15 +2578,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42758 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    47423 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45546 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    82403 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45982 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    89078 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    35540 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    44352 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    44353 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    52723 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    38070 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41915 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45998 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50957 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    27535 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    54450 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ │ @@ -2610,15 +2610,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    24374 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.matlib.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26288 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.other.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    37419 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials-package.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46847 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.chebyshev.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51499 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.classes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43104 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43639 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite_e.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    47585 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    47589 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43031 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.laguerre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42812 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.legendre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28772 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.poly1d.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41877 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polynomial.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26623 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polyutils.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26761 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.rec.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26422 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.set.html
│ │ │ │ @@ -2755,15 +2755,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    31655 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32348 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32865 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.3-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32016 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.4-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    13407 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    90990 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12397 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2687933 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2687889 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   177614 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64100 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    18746 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.html
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ @@ -536,30 +536,30 @@
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [1]: </span><span class="kn">import</span> <span class="nn">numpy.random</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [2]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">7.3 ms +- 72.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">14.6 ms +- 36.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.15 ms +- 79.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">6.2 ms +- 22.2 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">6.17 ms +- 61.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">17.4 ms +- 223 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">3.46 ms +- 15.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">5.83 ms +- 11.3 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">27.1 ms +- 302 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">32.6 ms +- 522 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">12.1 ms +- 18.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">14.2 ms +- 12 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p><a class="reference internal" href="generated/numpy.random.Generator.integers.html#numpy.random.Generator.integers" title="numpy.random.Generator.integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">integers</span></code></a> is now the canonical way to generate integer
│ │ │ │  random numbers from a discrete uniform distribution. This replaces both
│ │ │ │  <a class="reference internal" href="generated/numpy.random.randint.html#numpy.random.randint" title="numpy.random.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a> and the deprecated <a class="reference internal" href="generated/numpy.random.random_integers.html#numpy.random.random_integers" title="numpy.random.random_integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random_integers</span></code></a>.</p></li>
│ │ │ │  <li><p>The <a class="reference internal" href="generated/numpy.random.rand.html#numpy.random.rand" title="numpy.random.rand"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rand</span></code></a> and <a class="reference internal" href="generated/numpy.random.randn.html#numpy.random.randn" title="numpy.random.randn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randn</span></code></a> methods are only available through the legacy
│ │ │ │ @@ -586,21 +586,21 @@
│ │ │ │  <li><p>Standard Exponentials (<a class="reference internal" href="generated/numpy.random.Generator.standard_exponential.html#numpy.random.Generator.standard_exponential" title="numpy.random.Generator.standard_exponential"><code class="xref py py-obj docutils literal notranslate"><span class="pre">standard_exponential</span></code></a>)</p></li>
│ │ │ │  </ul>
│ │ │ │  </li>
│ │ │ │  </ul>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [6]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [7]: </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[7]: </span><span class="go">array([0.23463919, 0.72393835, 0.14778879])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.62899335, 0.03774   , 0.21407664])</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([0.87651783, 0.8591692 , 0.7715133 ], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.32505184, 0.85750914, 0.6715027 ], 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([153,  30, 207], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([232, 105, 192], dtype=uint8)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul>
│ │ │ │  <li><p>Optional <code class="docutils literal notranslate"><span class="pre">out</span></code> argument that allows existing arrays to be filled for
│ │ │ │  select distributions</p>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Uniforms (<a class="reference internal" href="generated/numpy.random.Generator.random.html#numpy.random.Generator.random" title="numpy.random.Generator.random"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random</span></code></a>)</p></li>
│ │ │ │ @@ -613,18 +613,18 @@
│ │ │ │  </li>
│ │ │ │  </ul>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [10]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [11]: </span><span class="n">existing</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [12]: </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">out</span><span class="o">=</span><span class="n">existing</span><span class="p">[:</span><span class="mi">2</span><span class="p">])</span>
│ │ │ │ -<span class="gh">Out[12]: </span><span class="go">array([0.64358556, 0.04163277])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.35711538, 0.22780344])</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">[0.64358556 0.04163277 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.35711538 0.22780344 0.         0.        ]</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Optional <code class="docutils literal notranslate"><span class="pre">axis</span></code> argument for methods like <a class="reference internal" href="generated/numpy.random.Generator.choice.html#numpy.random.Generator.choice" title="numpy.random.Generator.choice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">choice</span></code></a>,
│ │ │ │  <a class="reference internal" href="generated/numpy.random.Generator.permutation.html#numpy.random.Generator.permutation" title="numpy.random.Generator.permutation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">permutation</span></code></a> and <a class="reference internal" href="generated/numpy.random.Generator.shuffle.html#numpy.random.Generator.shuffle" title="numpy.random.Generator.shuffle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">shuffle</span></code></a> that controls which
│ │ │ │  axis an operation is performed over for multi-dimensional arrays.</p></li>
│ │ │ │  </ul>
│ │ │ │ @@ -636,25 +636,25 @@
│ │ │ │  <span class="gh">Out[16]: </span>
│ │ │ │  <span class="go">array([[ 0,  1,  2,  3],</span>
│ │ │ │  <span class="go">       [ 4,  5,  6,  7],</span>
│ │ │ │  <span class="go">       [ 8,  9, 10, 11]])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [17]: </span><span class="n">rng</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
│ │ │ │  <span class="gh">Out[17]: </span>
│ │ │ │ -<span class="go">array([[ 2,  0,  2,  1,  0],</span>
│ │ │ │ -<span class="go">       [ 6,  4,  6,  5,  4],</span>
│ │ │ │ -<span class="go">       [10,  8, 10,  9,  8]])</span>
│ │ │ │ +<span class="go">array([[ 0,  2,  1,  1,  3],</span>
│ │ │ │ +<span class="go">       [ 4,  6,  5,  5,  7],</span>
│ │ │ │ +<span class="go">       [ 8, 10,  9,  9, 11]])</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,  2,  0,  3],</span>
│ │ │ │ -<span class="go">       [ 5,  6,  4,  7],</span>
│ │ │ │ -<span class="go">       [ 9, 10,  8, 11]])</span>
│ │ │ │ +<span class="go">array([[ 1,  2,  3,  0],</span>
│ │ │ │ +<span class="go">       [ 5,  6,  7,  4],</span>
│ │ │ │ +<span class="go">       [ 9, 10, 11,  8]])</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Added a method to sample from the complex normal distribution
│ │ │ │  (<em class="xref py py-obj">complex_normal</em>)</p></li>
│ │ │ │  </ul>
│ │ │ │  </section>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -102,26 +102,26 @@
│ │ │ │ │  In [1]: import numpy.random
│ │ │ │ │  
│ │ │ │ │  In [2]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [3]: %timeit -n 1 rng.standard_normal(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_normal(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -7.3 ms +- 72.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -14.6 ms +- 36.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.15 ms +- 79.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +6.2 ms +- 22.2 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)
│ │ │ │ │     ...:
│ │ │ │ │ -6.17 ms +- 61.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -17.4 ms +- 223 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +3.46 ms +- 15.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +5.83 ms +- 11.3 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)
│ │ │ │ │     ...:
│ │ │ │ │ -27.1 ms +- 302 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -32.6 ms +- 522 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +12.1 ms +- 18.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +14.2 ms +- 12 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │      * _i_n_t_e_g_e_r_s is now the canonical way to generate integer random numbers from
│ │ │ │ │        a discrete uniform distribution. This replaces both _r_a_n_d_i_n_t and the
│ │ │ │ │        deprecated _r_a_n_d_o_m___i_n_t_e_g_e_r_s.
│ │ │ │ │      * The _r_a_n_d and _r_a_n_d_n methods are only available through the legacy
│ │ │ │ │        _R_a_n_d_o_m_S_t_a_t_e.
│ │ │ │ │      * _G_e_n_e_r_a_t_o_r_._r_a_n_d_o_m is now the canonical way to generate floating-point
│ │ │ │ │        random numbers, which replaces _R_a_n_d_o_m_S_t_a_t_e_._r_a_n_d_o_m___s_a_m_p_l_e, _s_a_m_p_l_e, and
│ │ │ │ │ @@ -140,38 +140,38 @@
│ │ │ │ │            o Uniforms (_r_a_n_d_o_m and _i_n_t_e_g_e_r_s)
│ │ │ │ │            o Normals (_s_t_a_n_d_a_r_d___n_o_r_m_a_l)
│ │ │ │ │            o Standard Gammas (_s_t_a_n_d_a_r_d___g_a_m_m_a)
│ │ │ │ │            o Standard Exponentials (_s_t_a_n_d_a_r_d___e_x_p_o_n_e_n_t_i_a_l)
│ │ │ │ │  In [6]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [7]: rng.random(3, dtype=np.float64)
│ │ │ │ │ -Out[7]: array([0.23463919, 0.72393835, 0.14778879])
│ │ │ │ │ +Out[7]: array([0.62899335, 0.03774   , 0.21407664])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.87651783, 0.8591692 , 0.7715133 ], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.32505184, 0.85750914, 0.6715027 ], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([153,  30, 207], dtype=uint8)
│ │ │ │ │ +Out[9]: array([232, 105, 192], 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([0.64358556, 0.04163277])
│ │ │ │ │ +Out[12]: array([0.35711538, 0.22780344])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.64358556 0.04163277 0.         0.        ]
│ │ │ │ │ +[0.35711538 0.22780344 0.         0.        ]
│ │ │ │ │      * Optional axis argument for methods like _c_h_o_i_c_e, _p_e_r_m_u_t_a_t_i_o_n and _s_h_u_f_f_l_e
│ │ │ │ │        that controls which axis an operation is performed over for multi-
│ │ │ │ │        dimensional arrays.
│ │ │ │ │  In [14]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [15]: a = np.arange(12).reshape((3, 4))
│ │ │ │ │  
│ │ │ │ │ @@ -179,25 +179,25 @@
│ │ │ │ │  Out[16]:
│ │ │ │ │  array([[ 0,  1,  2,  3],
│ │ │ │ │         [ 4,  5,  6,  7],
│ │ │ │ │         [ 8,  9, 10, 11]])
│ │ │ │ │  
│ │ │ │ │  In [17]: rng.choice(a, axis=1, size=5)
│ │ │ │ │  Out[17]:
│ │ │ │ │ -array([[ 2,  0,  2,  1,  0],
│ │ │ │ │ -       [ 6,  4,  6,  5,  4],
│ │ │ │ │ -       [10,  8, 10,  9,  8]])
│ │ │ │ │ +array([[ 0,  2,  1,  1,  3],
│ │ │ │ │ +       [ 4,  6,  5,  5,  7],
│ │ │ │ │ +       [ 8, 10,  9,  9, 11]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 1,  2,  0,  3],
│ │ │ │ │ -       [ 5,  6,  4,  7],
│ │ │ │ │ -       [ 9, 10,  8, 11]])
│ │ │ │ │ +array([[ 1,  2,  3,  0],
│ │ │ │ │ +       [ 5,  6,  7,  4],
│ │ │ │ │ +       [ 9, 10, 11,  8]])
│ │ │ │ │      * Added a method to sample from the complex normal distribution
│ │ │ │ │        (ccoommpplleexx__nnoorrmmaall)
│ │ │ │ │  _p_r_e_v_i_o_u_s
│ │ │ │ │  _M_u_l_t_i_t_h_r_e_a_d_e_d_ _g_e_n_e_r_a_t_i_o_n
│ │ │ │ │  _n_e_x_t
│ │ │ │ │  _P_e_r_f_o_r_m_a_n_c_e
│ │ │ │ │  © Copyright 2008-2025, NumPy Developers.
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ @@ -609,31 +609,31 @@
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span> <span class="o">+</span> <span class="n">rng</span><span class="o">.</span><span class="n">standard_normal</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>With the legacy polynomial module, a linear fit (i.e. polynomial of degree 1)
│ │ │ │  could be applied to these data with <a class="reference internal" href="generated/numpy.polyfit.html#numpy.polyfit" title="numpy.polyfit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">polyfit</span></code></a>:</p>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[4]: </span><span class="go">array([0.98287535, 0.47084069])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 1.1262849 , -0.14201884])</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([4.89377979, 4.42293909], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.9262632 , 5.06828204], 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([0.47084069, 0.98287535], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.14201884,  1.1262849 ], 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([0.98287535, 0.47084069])
│ │ │ │ │ +Out[4]: array([ 1.1262849 , -0.14201884])
│ │ │ │ │  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([4.89377979, 4.42293909], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.9262632 , 5.06828204], 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([0.47084069, 0.98287535], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.14201884,  1.1262849 ], 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 {}
│ │ │ │ │ @@ -32373,22 +32373,22 @@
│ │ │ │ │          "02785049": 1867,
│ │ │ │ │          "02i": [513, 2644],
│ │ │ │ │          "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2658],
│ │ │ │ │          "03125": [1585, 2491],
│ │ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │ │          "0361": 2607,
│ │ │ │ │          "03703704": 1809,
│ │ │ │ │ +        "03774": 2461,
│ │ │ │ │          "03943254e": 2104,
│ │ │ │ │          "03968254": [1113, 1543],
│ │ │ │ │          "0396842": 680,
│ │ │ │ │          "03t13": 55,
│ │ │ │ │          "04": [54, 55, 164, 410, 547, 1586, 2463, 2594, 2659],
│ │ │ │ │          "0400": 360,
│ │ │ │ │          "04097352": 2635,
│ │ │ │ │ -        "04163277": 2461,
│ │ │ │ │          "04166667": [1544, 1585],
│ │ │ │ │          "04211c6": 2521,
│ │ │ │ │          "04551152e": 2104,
│ │ │ │ │          "04719755": 1911,
│ │ │ │ │          "05": [55, 91, 163, 410, 548, 669, 896, 1095, 1871, 2083, 2173, 2353, 2400, 2450, 2648],
│ │ │ │ │          "0500": 360,
│ │ │ │ │          "05093587": 2635,
│ │ │ │ │ @@ -32399,14 +32399,15 @@
│ │ │ │ │          "0596779": 1153,
│ │ │ │ │          "06": [55, 566, 2083, 2508],
│ │ │ │ │          "0614962j": [439, 453],
│ │ │ │ │          "0625": [418, 624, 1645],
│ │ │ │ │          "06369197489564249": 2458,
│ │ │ │ │          "06381726": 349,
│ │ │ │ │          "0660": [302, 2131],
│ │ │ │ │ +        "06828204": 2488,
│ │ │ │ │          "06959433e": [420, 947],
│ │ │ │ │          "07": [55, 164, 547, 896, 897, 1335, 2170, 2508],
│ │ │ │ │          "07106781e": 514,
│ │ │ │ │          "07407407": 1809,
│ │ │ │ │          "07779185": 2458,
│ │ │ │ │          "07937323": 524,
│ │ │ │ │          "07944154": [657, 2655],
│ │ │ │ │ @@ -32524,15 +32525,15 @@
│ │ │ │ │          "10403": 2536,
│ │ │ │ │          "10412": 2536,
│ │ │ │ │          "10424": 2536,
│ │ │ │ │          "10425": 2536,
│ │ │ │ │          "10431": 2536,
│ │ │ │ │          "10435": 2536,
│ │ │ │ │          "1049": 2098,
│ │ │ │ │ -        "105": 2463,
│ │ │ │ │ +        "105": [2461, 2463],
│ │ │ │ │          "10534": 2536,
│ │ │ │ │          "10536": 2536,
│ │ │ │ │          "10537": 2536,
│ │ │ │ │          "10539": 2536,
│ │ │ │ │          "10540": 2536,
│ │ │ │ │          "10541": 2536,
│ │ │ │ │          "10542": 2536,
│ │ │ │ │ @@ -32722,14 +32723,15 @@
│ │ │ │ │          "1235": 2091,
│ │ │ │ │          "123abc": [302, 305, 2131, 2134],
│ │ │ │ │          "124": [98, 905],
│ │ │ │ │          "125": [470, 660, 1114, 1142, 1645, 1651, 1899, 1900, 2239, 2339, 2382, 2429, 2460, 2491, 2659, 2666],
│ │ │ │ │          "12589991e": 645,
│ │ │ │ │          "126": [863, 1048, 1116, 1904],
│ │ │ │ │          "1261": 2612,
│ │ │ │ │ +        "1262849": 2488,
│ │ │ │ │          "12658": 2560,
│ │ │ │ │          "12697628": 2635,
│ │ │ │ │          "127": [62, 66, 514, 863, 1048, 1102, 1116, 1904, 2301, 2302, 2462, 2463, 2464, 2583, 2639],
│ │ │ │ │          "12736": [2548, 2549],
│ │ │ │ │          "12767": 2548,
│ │ │ │ │          "12768": 2548,
│ │ │ │ │          "12769": 2548,
│ │ │ │ │ @@ -32851,14 +32853,15 @@
│ │ │ │ │          "14194": 2555,
│ │ │ │ │          "14197": 2560,
│ │ │ │ │          "14198": 2555,
│ │ │ │ │          "14199": 2555,
│ │ │ │ │          "142": 655,
│ │ │ │ │          "14200": 2555,
│ │ │ │ │          "14201": 2555,
│ │ │ │ │ +        "14201884": 2488,
│ │ │ │ │          "14211": 2553,
│ │ │ │ │          "14227": 2560,
│ │ │ │ │          "14228": 2555,
│ │ │ │ │          "14236": 2555,
│ │ │ │ │          "14237": 2555,
│ │ │ │ │          "14248": 2560,
│ │ │ │ │          "14255": 2560,
│ │ │ │ │ @@ -32941,15 +32944,14 @@
│ │ │ │ │          "14717": 2560,
│ │ │ │ │          "14718": 2560,
│ │ │ │ │          "14720": 2560,
│ │ │ │ │          "14730": 2560,
│ │ │ │ │          "14758": 2558,
│ │ │ │ │          "14771": 2560,
│ │ │ │ │          "14777": 2560,
│ │ │ │ │ -        "14778879": 2461,
│ │ │ │ │          "14781": 2558,
│ │ │ │ │          "14787": 2569,
│ │ │ │ │          "148": [2344, 2386, 2433, 2463],
│ │ │ │ │          "14812": 3,
│ │ │ │ │          "148293216": 2666,
│ │ │ │ │          "14841": 2560,
│ │ │ │ │          "14851": 2558,
│ │ │ │ │ @@ -33016,15 +33018,15 @@
│ │ │ │ │          "15245": 2561,
│ │ │ │ │          "15246": 2561,
│ │ │ │ │          "15247": 2561,
│ │ │ │ │          "15250": 2561,
│ │ │ │ │          "15251": 2566,
│ │ │ │ │          "15255": 2566,
│ │ │ │ │          "15271": 2576,
│ │ │ │ │ -        "153": [2461, 2583],
│ │ │ │ │ +        "153": 2583,
│ │ │ │ │          "15302337": 523,
│ │ │ │ │          "1534": 485,
│ │ │ │ │          "15355": 2566,
│ │ │ │ │          "15385": 2566,
│ │ │ │ │          "154": [2463, 2666],
│ │ │ │ │          "15427": 2566,
│ │ │ │ │          "15463": 2566,
│ │ │ │ │ @@ -33374,15 +33376,15 @@
│ │ │ │ │          "19062": 2583,
│ │ │ │ │          "1908": [2353, 2400, 2450],
│ │ │ │ │          "19083": 2583,
│ │ │ │ │          "19135": 2583,
│ │ │ │ │          "19151": 2583,
│ │ │ │ │          "191614240": 95,
│ │ │ │ │          "1918": 2612,
│ │ │ │ │ -        "192": [69, 669, 1519, 2463],
│ │ │ │ │ +        "192": [69, 669, 1519, 2461, 2463],
│ │ │ │ │          "19211": 2583,
│ │ │ │ │          "192163377": 2098,
│ │ │ │ │          "19226": 2588,
│ │ │ │ │          "1923875335537315": [2352, 2389, 2399, 2436, 2449],
│ │ │ │ │          "19249760": [420, 947],
│ │ │ │ │          "19259": 2583,
│ │ │ │ │          "193": [2463, 2637],
│ │ │ │ │ @@ -33609,15 +33611,15 @@
│ │ │ │ │          "2052": 2615,
│ │ │ │ │          "20580": 2588,
│ │ │ │ │          "20589": 2588,
│ │ │ │ │          "206": 2463,
│ │ │ │ │          "20613": 2581,
│ │ │ │ │          "20618": 2581,
│ │ │ │ │          "2063": 2612,
│ │ │ │ │ -        "207": [2461, 2463],
│ │ │ │ │ +        "207": 2463,
│ │ │ │ │          "20702": 2584,
│ │ │ │ │          "20703": 2584,
│ │ │ │ │          "20704": 2584,
│ │ │ │ │          "20714": 2584,
│ │ │ │ │          "20722": 2588,
│ │ │ │ │          "20724": 2584,
│ │ │ │ │          "20725": 2584,
│ │ │ │ │ @@ -33703,14 +33705,15 @@
│ │ │ │ │          "21277": 2587,
│ │ │ │ │          "213": [12, 2491],
│ │ │ │ │          "21336384": 2659,
│ │ │ │ │          "2134086255804012e": 1923,
│ │ │ │ │          "21350": 2587,
│ │ │ │ │          "21354": 2588,
│ │ │ │ │          "21386": 2587,
│ │ │ │ │ +        "21407664": 2461,
│ │ │ │ │          "21437": 2594,
│ │ │ │ │          "21438": 2587,
│ │ │ │ │          "21444": 2587,
│ │ │ │ │          "21445": 2587,
│ │ │ │ │          "21446": 2587,
│ │ │ │ │          "21447": 2587,
│ │ │ │ │          "21448": 2587,
│ │ │ │ │ @@ -33749,15 +33752,15 @@
│ │ │ │ │          "219": 2463,
│ │ │ │ │          "21925": 2594,
│ │ │ │ │          "21949": 2589,
│ │ │ │ │          "21951": 2589,
│ │ │ │ │          "21952": 2589,
│ │ │ │ │          "21976": 2594,
│ │ │ │ │          "21995": 2594,
│ │ │ │ │ -        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 98, 107, 108, 109, 163, 270, 336, 378, 425, 485, 628, 658, 669, 880, 905, 1045, 1069, 1113, 1211, 1229, 1294, 1312, 1336, 1337, 1340, 1341, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1358, 1448, 1466, 1514, 1521, 1522, 1543, 1591, 1905, 1908, 1913, 1968, 1986, 2091, 2208, 2236, 2237, 2342, 2513, 2517, 2519, 2534, 2588, 2635, 2637, 2641, 2657, 2666],
│ │ │ │ │ +        "22": [21, 22, 29, 30, 40, 47, 52, 54, 55, 58, 59, 98, 107, 108, 109, 163, 270, 336, 378, 425, 485, 628, 658, 669, 880, 905, 1045, 1069, 1113, 1211, 1229, 1294, 1312, 1336, 1337, 1340, 1341, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1358, 1448, 1466, 1514, 1521, 1522, 1543, 1591, 1905, 1908, 1913, 1968, 1986, 2091, 2208, 2236, 2237, 2342, 2461, 2513, 2517, 2519, 2534, 2588, 2635, 2637, 2641, 2657, 2666],
│ │ │ │ │          "220": [2238, 2576],
│ │ │ │ │          "22004": 2594,
│ │ │ │ │          "22014": 2594,
│ │ │ │ │          "22030": 2590,
│ │ │ │ │          "22031": 2590,
│ │ │ │ │          "22032": 2590,
│ │ │ │ │          "22033": 2590,
│ │ │ │ │ @@ -33792,15 +33795,14 @@
│ │ │ │ │          "22221": 2591,
│ │ │ │ │          "22222": 2591,
│ │ │ │ │          "222222": 1335,
│ │ │ │ │          "22223": 2591,
│ │ │ │ │          "22224": 2591,
│ │ │ │ │          "22228": 2594,
│ │ │ │ │          "22230": 2591,
│ │ │ │ │ -        "223": 2461,
│ │ │ │ │          "22313": 2594,
│ │ │ │ │          "22314355": 2655,
│ │ │ │ │          "22315": 2599,
│ │ │ │ │          "22316": 2594,
│ │ │ │ │          "22357": 2594,
│ │ │ │ │          "22368": 2592,
│ │ │ │ │          "22370": 2592,
│ │ │ │ │ @@ -33860,14 +33862,15 @@
│ │ │ │ │          "22707": 2599,
│ │ │ │ │          "22723872": 349,
│ │ │ │ │          "22733602246716966": 2457,
│ │ │ │ │          "22740995": 1149,
│ │ │ │ │          "22769": 2599,
│ │ │ │ │          "22776": 2599,
│ │ │ │ │          "22776602": [680, 2659],
│ │ │ │ │ +        "22780344": 2461,
│ │ │ │ │          "22786": 2599,
│ │ │ │ │          "228": 2463,
│ │ │ │ │          "22820": 2595,
│ │ │ │ │          "22830": 2595,
│ │ │ │ │          "22831": 2595,
│ │ │ │ │          "22832": 2595,
│ │ │ │ │          "22834": 2595,
│ │ │ │ │ @@ -33923,14 +33926,15 @@
│ │ │ │ │          "23148": 2596,
│ │ │ │ │          "23149": 2596,
│ │ │ │ │          "23150": 2596,
│ │ │ │ │          "23161": 2596,
│ │ │ │ │          "2317": 2620,
│ │ │ │ │          "23194": 2597,
│ │ │ │ │          "23195": 2599,
│ │ │ │ │ +        "232": 2461,
│ │ │ │ │          "23204345": [2345, 2391, 2439],
│ │ │ │ │          "23206": 2597,
│ │ │ │ │          "23207": 2597,
│ │ │ │ │          "23208": 2597,
│ │ │ │ │          "23221": 2597,
│ │ │ │ │          "23226": 2597,
│ │ │ │ │          "23229": 2599,
│ │ │ │ │ @@ -33952,15 +33956,14 @@
│ │ │ │ │          "23371": 2599,
│ │ │ │ │          "23376": 2599,
│ │ │ │ │          "23385948e": 54,
│ │ │ │ │          "234": 55,
│ │ │ │ │          "23403": 2599,
│ │ │ │ │          "2345672e": 2172,
│ │ │ │ │          "234567e": 2172,
│ │ │ │ │ -        "23463919": 2461,
│ │ │ │ │          "23480": 2599,
│ │ │ │ │          "23528": 2599,
│ │ │ │ │          "23543": 2597,
│ │ │ │ │          "23544": 2597,
│ │ │ │ │          "23598776": 1911,
│ │ │ │ │          "23601": 2599,
│ │ │ │ │          "23606798": 653,
│ │ │ │ │ @@ -34396,15 +34399,15 @@
│ │ │ │ │          "26963": 2623,
│ │ │ │ │          "26971": 2623,
│ │ │ │ │          "26978671": 2635,
│ │ │ │ │          "26981": 2625,
│ │ │ │ │          "2699": 1643,
│ │ │ │ │          "26995": 2623,
│ │ │ │ │          "26aa21a": 13,
│ │ │ │ │ -        "27": [54, 55, 58, 169, 470, 539, 554, 660, 680, 1142, 1884, 1899, 1900, 2208, 2239, 2316, 2361, 2408, 2461, 2463, 2491, 2513, 2533, 2534, 2624, 2639, 2641, 2645, 2657, 2659, 2666],
│ │ │ │ │ +        "27": [54, 55, 58, 169, 470, 539, 554, 660, 680, 1142, 1884, 1899, 1900, 2208, 2239, 2316, 2361, 2408, 2463, 2491, 2513, 2533, 2534, 2624, 2639, 2641, 2645, 2657, 2659, 2666],
│ │ │ │ │          "270": 363,
│ │ │ │ │          "27000": 2624,
│ │ │ │ │          "2700000": 2635,
│ │ │ │ │          "27000000": 2635,
│ │ │ │ │          "27001": 2624,
│ │ │ │ │          "27008": 2625,
│ │ │ │ │          "27021": 2624,
│ │ │ │ │ @@ -34650,24 +34653,23 @@
│ │ │ │ │          "2nd": [513, 641, 642, 655, 658, 669, 1526, 2335, 2378, 2425, 2637, 2641, 2666],
│ │ │ │ │          "2to3": 2616,
│ │ │ │ │          "2x": [1527, 1542, 2357, 2404, 2454, 2488, 2491, 2616, 2619],
│ │ │ │ │          "2x2": 47,
│ │ │ │ │          "2x3": [47, 72, 2665],
│ │ │ │ │          "2x3x5": 336,
│ │ │ │ │          "3": [1, 2, 5, 10, 11, 12, 14, 20, 24, 26, 29, 30, 31, 32, 34, 36, 37, 38, 42, 47, 50, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 66, 70, 72, 74, 76, 78, 79, 87, 89, 94, 96, 97, 98, 99, 100, 105, 107, 108, 109, 110, 111, 113, 114, 115, 116, 117, 118, 119, 120, 121, 123, 124, 127, 128, 130, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 143, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 167, 169, 171, 176, 177, 185, 186, 194, 196, 204, 210, 213, 214, 227, 229, 234, 238, 239, 251, 260, 261, 262, 263, 264, 270, 278, 280, 284, 287, 290, 312, 316, 318, 322, 323, 333, 335, 336, 337, 338, 340, 341, 342, 345, 346, 347, 348, 349, 350, 351, 353, 354, 355, 356, 357, 358, 359, 362, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 396, 398, 401, 404, 408, 409, 410, 416, 417, 420, 421, 422, 423, 432, 435, 436, 440, 441, 442, 443, 447, 448, 450, 451, 454, 456, 460, 461, 463, 464, 465, 466, 467, 468, 469, 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│ │ │ │ │ -        "30": [28, 41, 42, 54, 55, 57, 58, 63, 263, 336, 355, 360, 363, 409, 454, 484, 533, 864, 875, 977, 1049, 1064, 1113, 1117, 1118, 1225, 1308, 1462, 1543, 1638, 1906, 1911, 1982, 2089, 2103, 2115, 2165, 2204, 2216, 2224, 2241, 2316, 2319, 2322, 2323, 2325, 2326, 2329, 2339, 2340, 2344, 2371, 2373, 2382, 2383, 2386, 2394, 2418, 2420, 2429, 2430, 2433, 2444, 2461, 2463, 2513, 2531, 2587, 2608, 2637, 2641, 2645, 2657, 2666],
│ │ │ │ │ +        "30": [28, 41, 42, 54, 55, 57, 58, 63, 263, 336, 355, 360, 363, 409, 454, 484, 533, 864, 875, 977, 1049, 1064, 1113, 1117, 1118, 1225, 1308, 1462, 1543, 1638, 1906, 1911, 1982, 2089, 2103, 2115, 2165, 2204, 2216, 2224, 2241, 2316, 2319, 2322, 2323, 2325, 2326, 2329, 2339, 2340, 2344, 2371, 2373, 2382, 2383, 2386, 2394, 2418, 2420, 2429, 2430, 2433, 2444, 2463, 2513, 2531, 2587, 2608, 2637, 2641, 2645, 2657, 2666],
│ │ │ │ │          "300": [66, 363, 2238, 2576, 2645],
│ │ │ │ │          "3000": 2594,
│ │ │ │ │          "30000": 533,
│ │ │ │ │          "3000488281": 476,
│ │ │ │ │          "3003003": 1999,
│ │ │ │ │          "3006": 2614,
│ │ │ │ │          "3007": 2614,
│ │ │ │ │          "301": [438, 1923, 2477],
│ │ │ │ │ -        "302": 2461,
│ │ │ │ │          "30220482": [2345, 2391, 2439],
│ │ │ │ │          "30278462": 1154,
│ │ │ │ │          "3039": 2614,
│ │ │ │ │          "304": 22,
│ │ │ │ │          "30464": 2094,
│ │ │ │ │          "30498948e": 2666,
│ │ │ │ │          "305": [421, 948],
│ │ │ │ │ @@ -34704,19 +34706,20 @@
│ │ │ │ │          "3173": 2617,
│ │ │ │ │          "3175": 2617,
│ │ │ │ │          "317811": 28,
│ │ │ │ │          "317j": [411, 617],
│ │ │ │ │          "318": 1526,
│ │ │ │ │          "3192": 2615,
│ │ │ │ │          "31962608": [196, 836, 1008, 1179, 1266, 1421, 1940],
│ │ │ │ │ -        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 137, 144, 215, 270, 336, 390, 434, 514, 584, 661, 880, 893, 1027, 1069, 1083, 1143, 1198, 1229, 1249, 1281, 1312, 1345, 1348, 1435, 1466, 1519, 1884, 1886, 1902, 1955, 1986, 2076, 2091, 2168, 2204, 2208, 2225, 2240, 2261, 2262, 2268, 2269, 2272, 2273, 2274, 2277, 2278, 2279, 2282, 2283, 2284, 2287, 2288, 2299, 2300, 2301, 2302, 2303, 2304, 2314, 2331, 2375, 2422, 2458, 2459, 2460, 2461, 2462, 2508, 2513, 2520, 2521, 2522, 2535, 2543, 2544, 2545, 2546, 2547, 2557, 2562, 2564, 2572, 2574, 2579, 2582, 2587, 2588, 2599, 2602, 2606, 2607, 2617, 2622, 2633, 2637, 2639, 2641, 2645, 2646, 2648, 2649, 2652, 2657, 2658, 2659, 2666],
│ │ │ │ │ +        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 137, 144, 215, 270, 336, 390, 434, 514, 584, 661, 880, 893, 1027, 1069, 1083, 1143, 1198, 1229, 1249, 1281, 1312, 1345, 1348, 1435, 1466, 1519, 1884, 1886, 1902, 1955, 1986, 2076, 2091, 2168, 2204, 2208, 2225, 2240, 2261, 2262, 2268, 2269, 2272, 2273, 2274, 2277, 2278, 2279, 2282, 2283, 2284, 2287, 2288, 2299, 2300, 2301, 2302, 2303, 2304, 2314, 2331, 2375, 2422, 2458, 2459, 2460, 2462, 2508, 2513, 2520, 2521, 2522, 2535, 2543, 2544, 2545, 2546, 2547, 2557, 2562, 2564, 2572, 2574, 2579, 2582, 2587, 2588, 2599, 2602, 2606, 2607, 2617, 2622, 2633, 2637, 2639, 2641, 2645, 2646, 2648, 2649, 2652, 2657, 2658, 2659, 2666],
│ │ │ │ │          "320": 1149,
│ │ │ │ │          "32000": 2094,
│ │ │ │ │          "32119158": 1867,
│ │ │ │ │          "323": [260, 421, 948, 1059, 1222, 1305, 1350, 1459, 1579, 1590, 1604, 1605, 1639, 1649, 1661, 1662, 1696, 1706, 1718, 1719, 1753, 1763, 1775, 1776, 1810, 1820, 1832, 1833, 1866, 1875, 1887, 1888, 1979, 2312],
│ │ │ │ │ +        "32505184": 2461,
│ │ │ │ │          "3263": 2617,
│ │ │ │ │          "32767": 535,
│ │ │ │ │          "32768": 535,
│ │ │ │ │          "32_767": 62,
│ │ │ │ │          "32_768": 62,
│ │ │ │ │          "32bit": [50, 61, 62, 2364, 2377, 2379, 2388, 2411, 2424, 2426, 2435, 2517, 2572, 2589],
│ │ │ │ │          "32x": 2583,
│ │ │ │ │ @@ -34765,15 +34768,16 @@
│ │ │ │ │          "35": [409, 489, 669, 870, 1056, 2204, 2325, 2369, 2416, 2572, 2635, 2641, 2657, 2666],
│ │ │ │ │          "350": [544, 635],
│ │ │ │ │          "3504": 2617,
│ │ │ │ │          "3534857623790153": 666,
│ │ │ │ │          "35355339": 1636,
│ │ │ │ │          "3541": 2615,
│ │ │ │ │          "35489284e": 2104,
│ │ │ │ │ -        "36": [58, 137, 355, 1752, 1761, 2204, 2225, 2323, 2367, 2414, 2461, 2463, 2491, 2536, 2649, 2657, 2659, 2666],
│ │ │ │ │ +        "35711538": 2461,
│ │ │ │ │ +        "36": [58, 137, 355, 1752, 1761, 2204, 2225, 2323, 2367, 2414, 2463, 2491, 2536, 2649, 2657, 2659, 2666],
│ │ │ │ │          "360": [544, 2103, 2238, 2576],
│ │ │ │ │          "36045180e": 147,
│ │ │ │ │          "3608": 2615,
│ │ │ │ │          "361": [1344, 1346, 1522, 1908],
│ │ │ │ │          "362": 12,
│ │ │ │ │          "3628523": 2458,
│ │ │ │ │          "36363636": 136,
│ │ │ │ │ @@ -34887,15 +34891,14 @@
│ │ │ │ │          "42": [31, 58, 63, 147, 349, 669, 896, 897, 974, 1029, 2090, 2208, 2256, 2332, 2376, 2423, 2457, 2566, 2605, 2622, 2635, 2639, 2657, 2664, 2665, 2666],
│ │ │ │ │          "420": [2238, 2576],
│ │ │ │ │          "42016704": 2666,
│ │ │ │ │          "4206": 2617,
│ │ │ │ │          "4220": 2617,
│ │ │ │ │          "4223": 2617,
│ │ │ │ │          "4225": 2617,
│ │ │ │ │ -        "42293909": 2488,
│ │ │ │ │          "423": 55,
│ │ │ │ │          "42310646": 1153,
│ │ │ │ │          "42332645": 2666,
│ │ │ │ │          "42457905e": 1586,
│ │ │ │ │          "425": [523, 524],
│ │ │ │ │          "4253": 2617,
│ │ │ │ │          "4254": 2617,
│ │ │ │ │ @@ -34954,15 +34957,15 @@
│ │ │ │ │          "4532": [409, 661, 2168],
│ │ │ │ │          "4545724517479104": 2460,
│ │ │ │ │          "45560727e": 54,
│ │ │ │ │          "456": 1921,
│ │ │ │ │          "4567": 2644,
│ │ │ │ │          "45674898e": 566,
│ │ │ │ │          "45a3d84": 2521,
│ │ │ │ │ -        "46": [409, 523, 905, 1707, 2204, 2208, 2641, 2657],
│ │ │ │ │ +        "46": [409, 523, 905, 1707, 2204, 2208, 2461, 2641, 2657],
│ │ │ │ │          "460": [2238, 2576],
│ │ │ │ │          "46009194e": 566,
│ │ │ │ │          "4602": 2618,
│ │ │ │ │          "4610935": 457,
│ │ │ │ │          "4613": 2618,
│ │ │ │ │          "4628": 2618,
│ │ │ │ │          "46351241j": 2081,
│ │ │ │ │ @@ -34977,15 +34980,14 @@
│ │ │ │ │          "46755891e": 54,
│ │ │ │ │          "468": [136, 147],
│ │ │ │ │          "4685006": [2352, 2399, 2449],
│ │ │ │ │          "4686": 12,
│ │ │ │ │          "46957616e": [470, 1899, 1900],
│ │ │ │ │          "47": [52, 2208, 2323, 2367, 2414, 2657, 2666],
│ │ │ │ │          "4702687338396767": 2348,
│ │ │ │ │ -        "47084069": 2488,
│ │ │ │ │          "471": [136, 147, 2463],
│ │ │ │ │          "47108547995356098": [2345, 2391, 2439],
│ │ │ │ │          "47140452j": 2491,
│ │ │ │ │          "472": 55,
│ │ │ │ │          "4722": 2618,
│ │ │ │ │          "4723": 2621,
│ │ │ │ │          "4730": [409, 661, 2168],
│ │ │ │ │ @@ -35079,15 +35081,14 @@
│ │ │ │ │          "5170": 2620,
│ │ │ │ │          "5184": 2620,
│ │ │ │ │          "51851852": 1809,
│ │ │ │ │          "519928": 2635,
│ │ │ │ │          "51992837": 2635,
│ │ │ │ │          "52": [10, 50, 62, 457, 1638, 1647, 1650, 2204, 2208, 2554, 2635, 2641, 2648, 2657, 2659, 2660, 2666],
│ │ │ │ │          "5203": 2620,
│ │ │ │ │ -        "522": 2461,
│ │ │ │ │          "5225": 2620,
│ │ │ │ │          "5231": 2620,
│ │ │ │ │          "52338984": [2345, 2391, 2439],
│ │ │ │ │          "52359878": 1911,
│ │ │ │ │          "52380952e": 1816,
│ │ │ │ │          "5240": 2620,
│ │ │ │ │          "5251": 2620,
│ │ │ │ │ @@ -35200,15 +35201,15 @@
│ │ │ │ │          "60546483": 523,
│ │ │ │ │          "60663578": 2635,
│ │ │ │ │          "607": [2339, 2382, 2429],
│ │ │ │ │          "60860684e": 1594,
│ │ │ │ │          "609": 2583,
│ │ │ │ │          "6094": 2522,
│ │ │ │ │          "60x": 2599,
│ │ │ │ │ -        "61": [13, 2461, 2657],
│ │ │ │ │ +        "61": [13, 2657],
│ │ │ │ │          "610": 28,
│ │ │ │ │          "61119": 2098,
│ │ │ │ │          "614064523559687": 2115,
│ │ │ │ │          "6143849206349179": [1113, 1543],
│ │ │ │ │          "6176": [99, 906],
│ │ │ │ │          "61799388": 1911,
│ │ │ │ │          "618": 669,
│ │ │ │ │ @@ -35221,28 +35222,28 @@
│ │ │ │ │          "623": [2394, 2444],
│ │ │ │ │          "62318272": [2319, 2363, 2410],
│ │ │ │ │          "62341325": 514,
│ │ │ │ │          "62374854": 2666,
│ │ │ │ │          "624": [2300, 2370, 2394, 2417, 2444, 2462],
│ │ │ │ │          "625": [99, 478, 645, 906, 2390, 2438],
│ │ │ │ │          "6273591314603949": [2335, 2378, 2425],
│ │ │ │ │ +        "62899335": 2461,
│ │ │ │ │          "62949953e": 645,
│ │ │ │ │          "63": [58, 514, 669, 1748, 1777, 2336, 2463, 2520, 2566, 2594, 2642, 2657],
│ │ │ │ │          "631198583": 55,
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2166, 2167],
│ │ │ │ │          "63526532": 2458,
│ │ │ │ │          "636363636364": [2353, 2400, 2450],
│ │ │ │ │          "63696169": 2635,
│ │ │ │ │          "6376": 2522,
│ │ │ │ │          "6390": [2353, 2400, 2450],
│ │ │ │ │          "64": [1, 5, 13, 21, 30, 50, 55, 56, 59, 61, 62, 63, 65, 66, 69, 74, 79, 315, 339, 409, 457, 470, 514, 584, 660, 669, 944, 1345, 1348, 1519, 1899, 1900, 2076, 2083, 2143, 2261, 2262, 2264, 2268, 2269, 2273, 2274, 2278, 2279, 2283, 2284, 2287, 2288, 2299, 2300, 2303, 2304, 2314, 2328, 2458, 2462, 2464, 2513, 2520, 2542, 2547, 2578, 2579, 2580, 2583, 2599, 2602, 2603, 2610, 2615, 2616, 2635, 2639, 2648, 2649, 2657, 2659, 2665, 2666],
│ │ │ │ │          "64023025": 2098,
│ │ │ │ │          "6416010000000001": 1114,
│ │ │ │ │ -        "64358556": 2461,
│ │ │ │ │          "64386512": 349,
│ │ │ │ │          "64402274e": 660,
│ │ │ │ │          "6446": [2550, 2554],
│ │ │ │ │          "646": [2517, 2576],
│ │ │ │ │          "6460": 2522,
│ │ │ │ │          "6462": 2522,
│ │ │ │ │          "6467": 2522,
│ │ │ │ │ @@ -35333,14 +35334,15 @@
│ │ │ │ │          "6689502": 2576,
│ │ │ │ │          "669": 669,
│ │ │ │ │          "6695": 2522,
│ │ │ │ │          "6697": 2522,
│ │ │ │ │          "6698": 2522,
│ │ │ │ │          "67": [409, 670, 671, 672, 1901, 2542, 2644, 2657, 2666],
│ │ │ │ │          "67046769e": 147,
│ │ │ │ │ +        "6715027": 2461,
│ │ │ │ │          "6717": 2522,
│ │ │ │ │          "6718": 2522,
│ │ │ │ │          "6719": 2522,
│ │ │ │ │          "6721": 2522,
│ │ │ │ │          "6726": 2522,
│ │ │ │ │          "6735": 2522,
│ │ │ │ │          "6747": 2522,
│ │ │ │ │ @@ -35412,20 +35414,19 @@
│ │ │ │ │          "718281": 431,
│ │ │ │ │          "71828182845904523536028747135266249775724709369995": 76,
│ │ │ │ │          "71828183": [38, 2666],
│ │ │ │ │          "718282": 2642,
│ │ │ │ │          "7183": 2642,
│ │ │ │ │          "7185": [99, 906],
│ │ │ │ │          "71946897": 1153,
│ │ │ │ │ -        "72": [13, 355, 544, 669, 1764, 2461, 2463, 2572, 2657, 2659],
│ │ │ │ │ +        "72": [13, 355, 544, 669, 1764, 2463, 2572, 2657, 2659],
│ │ │ │ │          "720": [55, 356, 358, 1897, 2225, 2238, 2576],
│ │ │ │ │          "72075441": 680,
│ │ │ │ │          "721fc64": 13,
│ │ │ │ │          "72375": 1644,
│ │ │ │ │ -        "72393835": 2461,
│ │ │ │ │          "72538256": [103, 126],
│ │ │ │ │          "72686684e": 566,
│ │ │ │ │          "72717132": 2659,
│ │ │ │ │          "72727273": 136,
│ │ │ │ │          "72847407": 1154,
│ │ │ │ │          "729": 2666,
│ │ │ │ │          "72904971": 1153,
│ │ │ │ │ @@ -35485,15 +35486,14 @@
│ │ │ │ │          "7680": 2526,
│ │ │ │ │          "769893": 2635,
│ │ │ │ │          "76989341": 2635,
│ │ │ │ │          "76991118": 1891,
│ │ │ │ │          "77": [29, 36, 37, 38, 39, 2463, 2635, 2654, 2657],
│ │ │ │ │          "770": [287, 1241, 1324, 1478, 1998, 2650],
│ │ │ │ │          "77086955": 1526,
│ │ │ │ │ -        "7715133": 2461,
│ │ │ │ │          "7724": 2526,
│ │ │ │ │          "7725": [2353, 2400, 2450],
│ │ │ │ │          "7731": 2526,
│ │ │ │ │          "7736": 2527,
│ │ │ │ │          "7737": 2526,
│ │ │ │ │          "7738": 2527,
│ │ │ │ │          "77395605": [349, 2457, 2639],
│ │ │ │ │ @@ -35521,15 +35521,15 @@
│ │ │ │ │          "78539816": [94, 104, 105, 129, 130, 2238],
│ │ │ │ │          "78539816339744828": [104, 129],
│ │ │ │ │          "7854j": [413, 619],
│ │ │ │ │          "78571429e": 1816,
│ │ │ │ │          "78606431": [349, 2457, 2639],
│ │ │ │ │          "789": 2644,
│ │ │ │ │          "7896": 2527,
│ │ │ │ │ -        "79": [13, 87, 100, 104, 129, 2657],
│ │ │ │ │ +        "79": [13, 87, 100, 104, 129, 2461, 2657],
│ │ │ │ │          "79033856e": 1149,
│ │ │ │ │          "7904": 2527,
│ │ │ │ │          "7917": 2527,
│ │ │ │ │          "7919": 2527,
│ │ │ │ │          "7920": [1212, 2527],
│ │ │ │ │          "7932": 2527,
│ │ │ │ │          "7939": 2527,
│ │ │ │ │ @@ -35580,15 +35580,15 @@
│ │ │ │ │          "8255": 2566,
│ │ │ │ │          "826716f": 2521,
│ │ │ │ │          "82743037": 524,
│ │ │ │ │          "82770259": 2666,
│ │ │ │ │          "8277025938204418": 2666,
│ │ │ │ │          "827941": [514, 680, 2659],
│ │ │ │ │          "82842712": [642, 644],
│ │ │ │ │ -        "83": [2105, 2167, 2353, 2400, 2450, 2554, 2657],
│ │ │ │ │ +        "83": [2105, 2167, 2353, 2400, 2450, 2461, 2554, 2657],
│ │ │ │ │          "83314899": 1154,
│ │ │ │ │          "83333333": 1702,
│ │ │ │ │          "833333333333333": [893, 1083, 1143, 2240],
│ │ │ │ │          "8341": 2528,
│ │ │ │ │          "8346": 2528,
│ │ │ │ │          "83571711": 349,
│ │ │ │ │          "83697020e": [470, 1899, 1900],
│ │ │ │ │ @@ -35608,17 +35608,17 @@
│ │ │ │ │          "85099543": 1822,
│ │ │ │ │          "85355339": 1756,
│ │ │ │ │          "85569": 2098,
│ │ │ │ │          "85602287": [2335, 2378, 2425],
│ │ │ │ │          "857": 410,
│ │ │ │ │          "8570331885190563e": [648, 653],
│ │ │ │ │          "85715698e": 2171,
│ │ │ │ │ +        "85750914": 2461,
│ │ │ │ │          "8577": 2539,
│ │ │ │ │          "85859792": [349, 2457, 2639],
│ │ │ │ │ -        "8591692": 2461,
│ │ │ │ │          "8595784": 2635,
│ │ │ │ │          "86": [59, 88, 101, 103, 106, 126, 131, 542, 968, 969, 2323, 2367, 2414, 2491, 2657],
│ │ │ │ │          "8601": [55, 62, 67, 2613],
│ │ │ │ │          "86260211e": 54,
│ │ │ │ │          "8630830": 13,
│ │ │ │ │          "86399": 55,
│ │ │ │ │          "86400": 55,
│ │ │ │ │ @@ -35626,15 +35626,14 @@
│ │ │ │ │          "8660254": 2103,
│ │ │ │ │          "86820401": [2345, 2391, 2439],
│ │ │ │ │          "86864911e": 1586,
│ │ │ │ │          "87": [2616, 2657],
│ │ │ │ │          "875": [478, 2491],
│ │ │ │ │          "8755": [186, 827, 999, 1172, 1259, 1414, 1933],
│ │ │ │ │          "87649168120691": 674,
│ │ │ │ │ -        "87651783": 2461,
│ │ │ │ │          "8770": [2353, 2400, 2450],
│ │ │ │ │          "88": [408, 2462, 2463, 2657, 2659, 2668],
│ │ │ │ │          "8801": [99, 906],
│ │ │ │ │          "88031624": 2666,
│ │ │ │ │          "88079259": 533,
│ │ │ │ │          "881943016134134": 666,
│ │ │ │ │          "88622693": 1642,
│ │ │ │ │ @@ -35645,15 +35644,14 @@
│ │ │ │ │          "88975": 1644,
│ │ │ │ │          "89": [28, 2091, 2644, 2657],
│ │ │ │ │          "890": 2644,
│ │ │ │ │          "8900451": 1154,
│ │ │ │ │          "89086505": [2352, 2399, 2449],
│ │ │ │ │          "89206682e": 2104,
│ │ │ │ │          "8922078": 2458,
│ │ │ │ │ -        "89377979": 2488,
│ │ │ │ │          "89442719": 642,
│ │ │ │ │          "89442719j": 642,
│ │ │ │ │          "89721355": 349,
│ │ │ │ │          "89804309e": 2104,
│ │ │ │ │          "89920014": [2319, 2363, 2410],
│ │ │ │ │          "8999999999999999": 2107,
│ │ │ │ │          "8b2": 2554,
│ │ │ │ │ @@ -35681,14 +35679,15 @@
│ │ │ │ │          "92362781e": 2104,
│ │ │ │ │          "92387953": 642,
│ │ │ │ │          "92387953j": 642,
│ │ │ │ │          "9240": 2532,
│ │ │ │ │          "9255": 2532,
│ │ │ │ │          "9261": 2532,
│ │ │ │ │          "9262": 2532,
│ │ │ │ │ +        "9262632": 2488,
│ │ │ │ │          "9263": 2532,
│ │ │ │ │          "9267": 2532,
│ │ │ │ │          "92676499": [349, 2639],
│ │ │ │ │          "927": [539, 554],
│ │ │ │ │          "92771843": 1154,
│ │ │ │ │          "9299": 2532,
│ │ │ │ │          "93": 2657,
│ │ │ │ │ @@ -35771,15 +35770,14 @@
│ │ │ │ │          "9800": 2666,
│ │ │ │ │          "9801": 2666,
│ │ │ │ │          "9802": 2666,
│ │ │ │ │          "98024613": 680,
│ │ │ │ │          "9807642": 1153,
│ │ │ │ │          "981": 2592,
│ │ │ │ │          "98136677": 523,
│ │ │ │ │ -        "98287535": 2488,
│ │ │ │ │          "987": 28,
│ │ │ │ │          "987654321": 2393,
│ │ │ │ │          "98935825": 2666,
│ │ │ │ │          "9897": 2666,
│ │ │ │ │          "9898": 2666,
│ │ │ │ │          "9899": [105, 130, 2666],
│ │ │ │ │          "99": [12, 302, 408, 544, 672, 1096, 1906, 2131, 2460, 2635, 2657, 2658, 2666],