--- /srv/reproducible-results/rbuild-debian/r-b-build.88ZtQBtD/b1/numpy_2.2.3+ds-5_i386.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.88ZtQBtD/b2/numpy_2.2.3+ds-5_i386.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - 02216633a218f000562e53ac1f56a5d3 5811628 doc optional python-numpy-doc_2.2.3+ds-5_all.deb
│ + c9278d367aee30b020b35857e43c2d80 5811776 doc optional python-numpy-doc_2.2.3+ds-5_all.deb
│   b49bca3955ba2733c9eab7427e208faf 29561492 debug optional python3-numpy-dbgsym_2.2.3+ds-5_i386.deb
│   7a879024cf54dda864e64f68093acac0 145792 python optional python3-numpy-dev_2.2.3+ds-5_i386.deb
│   bce6078295d4ee3b39c68dd546156b6a 5060120 python optional python3-numpy_2.2.3+ds-5_i386.deb
├── python-numpy-doc_2.2.3+ds-5_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2025-03-09 20:14:24.000000 debian-binary
│ │ --rw-r--r--   0        0        0    64876 2025-03-09 20:14:24.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5746560 2025-03-09 20:14:24.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0    64884 2025-03-09 20:14:24.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0  5746700 2025-03-09 20:14:24.000000 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 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46891 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45382 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    82403 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45982 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    89078 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    35540 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    44350 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    44353 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    52723 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    38070 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41915 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45998 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50957 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    27535 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    54450 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ │ @@ -2610,15 +2610,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    24374 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.matlib.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26288 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.other.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    37419 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials-package.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46847 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.chebyshev.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51499 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.classes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43104 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43639 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite_e.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    47585 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    47589 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43031 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.laguerre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42812 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.legendre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28772 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.poly1d.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41877 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polynomial.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26623 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polyutils.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26761 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.rec.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26422 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/reference/routines.set.html
│ │ │ │ @@ -2754,15 +2754,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46199 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release/2.2.0-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    31563 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32256 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32747 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release/2.2.3-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    13407 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    90523 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12397 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2686442 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2686433 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   177614 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64100 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-03-09 20:14:24.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    18746 2025-03-09 20:14:24.000000 ./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">7.29 ms +- 962 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">14.2 ms +- 147 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.47 ms +- 204 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">6.21 ms +- 31.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">5.8 ms +- 80.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">16.6 ms +- 73.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">3.78 ms +- 46.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">5.84 ms +- 19.3 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">29.5 ms +- 357 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">42.9 ms +- 18 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">12.4 ms +- 30 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">14.3 ms +- 25.1 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([0.63916943, 0.41190027, 0.77778762])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.44341898, 0.48485351, 0.14821712])</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([0.30106312, 0.18675065, 0.21117067], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.65999645, 0.6686265 , 0.3359151 ], 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([205, 106, 156], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([221,  44, 120], 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([0.78118065, 0.9207799 ])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.52837855, 0.59357937])</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">[0.78118065 0.9207799  0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.52837855 0.59357937 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([[ 0,  1,  2,  0,  3],</span>
│ │ │ │ -<span class="go">       [ 4,  5,  6,  4,  7],</span>
│ │ │ │ -<span class="go">       [ 8,  9, 10,  8, 11]])</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([[ 2,  1,  3,  0],</span>
│ │ │ │ -<span class="go">       [ 6,  5,  7,  4],</span>
│ │ │ │ -<span class="go">       [10,  9, 11,  8]])</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 {}
│ │ │ │ │ @@ -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)
│ │ │ │ │     ...:
│ │ │ │ │ -7.29 ms +- 962 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -14.2 ms +- 147 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.47 ms +- 204 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +6.21 ms +- 31.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │  In [4]: %timeit -n 1 rng.standard_exponential(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_exponential(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -5.8 ms +- 80.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -16.6 ms +- 73.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +3.78 ms +- 46.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +5.84 ms +- 19.3 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)
│ │ │ │ │     ...:
│ │ │ │ │ -29.5 ms +- 357 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -42.9 ms +- 18 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +12.4 ms +- 30 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +14.3 ms +- 25.1 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([0.63916943, 0.41190027, 0.77778762])
│ │ │ │ │ +Out[7]: array([0.44341898, 0.48485351, 0.14821712])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.30106312, 0.18675065, 0.21117067], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.65999645, 0.6686265 , 0.3359151 ], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([205, 106, 156], dtype=uint8)
│ │ │ │ │ +Out[9]: array([221,  44, 120], 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([0.78118065, 0.9207799 ])
│ │ │ │ │ +Out[12]: array([0.52837855, 0.59357937])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.78118065 0.9207799  0.         0.        ]
│ │ │ │ │ +[0.52837855 0.59357937 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([[ 0,  1,  2,  0,  3],
│ │ │ │ │ -       [ 4,  5,  6,  4,  7],
│ │ │ │ │ -       [ 8,  9, 10,  8, 11]])
│ │ │ │ │ +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([[ 2,  1,  3,  0],
│ │ │ │ │ -       [ 6,  5,  7,  4],
│ │ │ │ │ -       [10,  9, 11,  8]])
│ │ │ │ │ +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 2008-2025, 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([0.95298507, 0.22234397])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 1.07488973, -0.58555718])</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([4.5107768 , 4.28843283], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.25144661, 4.83700379], 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([0.22234397, 0.95298507], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.58555718,  1.07488973], 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([0.95298507, 0.22234397])
│ │ │ │ │ +Out[4]: array([ 1.07488973, -0.58555718])
│ │ │ │ │  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([4.5107768 , 4.28843283], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.25144661, 4.83700379], 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([0.22234397, 0.95298507], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.58555718,  1.07488973], 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 {}
│ │ │ │ │ @@ -32397,14 +32397,15 @@
│ │ │ │ │          "06369197489564249": 2458,
│ │ │ │ │          "06381726": 349,
│ │ │ │ │          "0660": [302, 2131],
│ │ │ │ │          "06959433e": [420, 947],
│ │ │ │ │          "07": [55, 164, 547, 896, 897, 1335, 2170, 2508],
│ │ │ │ │          "07106781e": 514,
│ │ │ │ │          "07407407": 1809,
│ │ │ │ │ +        "07488973": 2488,
│ │ │ │ │          "07779185": 2458,
│ │ │ │ │          "07937323": 524,
│ │ │ │ │          "07944154": [657, 2654],
│ │ │ │ │          "08": [55, 91, 147, 410, 523, 548, 896, 1095, 2322, 2366, 2413, 2525, 2658],
│ │ │ │ │          "0800": 2525,
│ │ │ │ │          "08187135": 54,
│ │ │ │ │          "08333333": [1645, 1871],
│ │ │ │ │ @@ -32536,15 +32537,15 @@
│ │ │ │ │          "10558": 2536,
│ │ │ │ │          "10559": 2536,
│ │ │ │ │          "10560": 2536,
│ │ │ │ │          "10561": 2536,
│ │ │ │ │          "10562": 2536,
│ │ │ │ │          "10563": 2536,
│ │ │ │ │          "1057109529998157": 2665,
│ │ │ │ │ -        "106": [55, 524, 2461],
│ │ │ │ │ +        "106": [55, 524],
│ │ │ │ │          "10607": 2536,
│ │ │ │ │          "10608": 2536,
│ │ │ │ │          "10609": 2536,
│ │ │ │ │          "10610": 2536,
│ │ │ │ │          "10612": 2536,
│ │ │ │ │          "10615": 2599,
│ │ │ │ │          "10622": 2536,
│ │ │ │ │ @@ -32665,15 +32666,15 @@
│ │ │ │ │          "11987": 2541,
│ │ │ │ │          "11992": 2544,
│ │ │ │ │          "11995": 2541,
│ │ │ │ │          "11e": 457,
│ │ │ │ │          "11ee694744f2552d": 13,
│ │ │ │ │          "11x": 1527,
│ │ │ │ │          "12": [8, 25, 28, 29, 40, 47, 52, 54, 55, 58, 59, 61, 67, 78, 79, 98, 107, 108, 134, 136, 140, 141, 147, 153, 215, 270, 336, 354, 355, 363, 364, 366, 367, 371, 374, 375, 403, 409, 435, 439, 441, 453, 489, 520, 523, 524, 530, 538, 566, 568, 628, 661, 669, 680, 863, 880, 881, 905, 916, 941, 963, 1027, 1048, 1069, 1070, 1107, 1116, 1135, 1159, 1160, 1161, 1164, 1166, 1167, 1193, 1194, 1195, 1198, 1204, 1205, 1206, 1212, 1213, 1228, 1229, 1236, 1240, 1247, 1249, 1281, 1312, 1435, 1466, 1510, 1527, 1574, 1577, 1588, 1591, 1601, 1637, 1644, 1650, 1656, 1658, 1707, 1715, 1752, 1765, 1772, 1829, 1864, 1871, 1876, 1885, 1890, 1902, 1904, 1911, 1912, 1913, 1919, 1955, 1986, 2089, 2168, 2204, 2205, 2206, 2208, 2209, 2210, 2223, 2224, 2225, 2237, 2246, 2248, 2299, 2313, 2327, 2328, 2332, 2341, 2342, 2372, 2376, 2384, 2388, 2419, 2423, 2431, 2435, 2457, 2461, 2463, 2477, 2491, 2513, 2514, 2519, 2525, 2531, 2532, 2533, 2534, 2535, 2545, 2547, 2549, 2554, 2557, 2560, 2569, 2570, 2572, 2573, 2575, 2583, 2587, 2588, 2595, 2597, 2599, 2601, 2603, 2604, 2605, 2606, 2622, 2623, 2624, 2625, 2628, 2629, 2630, 2634, 2636, 2637, 2640, 2641, 2644, 2648, 2656, 2658, 2665, 2667],
│ │ │ │ │ -        "120": [32, 356, 358, 363, 568, 1212, 2225, 2606],
│ │ │ │ │ +        "120": [32, 356, 358, 363, 568, 1212, 2225, 2461, 2606],
│ │ │ │ │          "120131": [1644, 1656],
│ │ │ │ │          "12065": 2594,
│ │ │ │ │          "12080": 2545,
│ │ │ │ │          "12083": 2545,
│ │ │ │ │          "12084": 2545,
│ │ │ │ │          "12085": 2545,
│ │ │ │ │          "121": [431, 2463],
│ │ │ │ │ @@ -32928,26 +32929,26 @@
│ │ │ │ │          "14644661": 1756,
│ │ │ │ │          "14673309e": 2665,
│ │ │ │ │          "14682": 2560,
│ │ │ │ │          "14686": 2553,
│ │ │ │ │          "14687": 2557,
│ │ │ │ │          "14692469": 2634,
│ │ │ │ │          "146925": 2634,
│ │ │ │ │ -        "147": 2461,
│ │ │ │ │          "14717": 2560,
│ │ │ │ │          "14718": 2560,
│ │ │ │ │          "14720": 2560,
│ │ │ │ │          "14730": 2560,
│ │ │ │ │          "14758": 2558,
│ │ │ │ │          "14771": 2560,
│ │ │ │ │          "14777": 2560,
│ │ │ │ │          "14781": 2558,
│ │ │ │ │          "14787": 2569,
│ │ │ │ │          "148": [2344, 2386, 2433, 2463],
│ │ │ │ │          "14812": 3,
│ │ │ │ │ +        "14821712": 2461,
│ │ │ │ │          "148293216": 2665,
│ │ │ │ │          "14841": 2560,
│ │ │ │ │          "14851": 2558,
│ │ │ │ │          "14852": 2558,
│ │ │ │ │          "14853": 2553,
│ │ │ │ │          "14854": 2553,
│ │ │ │ │          "14855": 2558,
│ │ │ │ │ @@ -33020,15 +33021,14 @@
│ │ │ │ │          "15355": 2566,
│ │ │ │ │          "15385": 2566,
│ │ │ │ │          "154": [2463, 2665],
│ │ │ │ │          "15427": 2566,
│ │ │ │ │          "15463": 2566,
│ │ │ │ │          "155": [2463, 2636],
│ │ │ │ │          "15534": 2566,
│ │ │ │ │ -        "156": 2461,
│ │ │ │ │          "15648": 2566,
│ │ │ │ │          "15666": 2572,
│ │ │ │ │          "15675": 2562,
│ │ │ │ │          "15676": 2562,
│ │ │ │ │          "15677": 2562,
│ │ │ │ │          "15679": 2562,
│ │ │ │ │          "15685": 2566,
│ │ │ │ │ @@ -33316,15 +33316,14 @@
│ │ │ │ │          "18638": 2574,
│ │ │ │ │          "18657": 2576,
│ │ │ │ │          "18658": 2576,
│ │ │ │ │          "18661": 2574,
│ │ │ │ │          "18666": 2576,
│ │ │ │ │          "1867": 1643,
│ │ │ │ │          "18671": 2574,
│ │ │ │ │ -        "18675065": 2461,
│ │ │ │ │          "18695": 2576,
│ │ │ │ │          "18697": 2576,
│ │ │ │ │          "187": [2332, 2376, 2423],
│ │ │ │ │          "1870": 2611,
│ │ │ │ │          "18718": 2576,
│ │ │ │ │          "18737": 2576,
│ │ │ │ │          "1874": 2611,
│ │ │ │ │ @@ -33582,14 +33581,15 @@
│ │ │ │ │          "20300": 2580,
│ │ │ │ │          "20302": 2580,
│ │ │ │ │          "20314": 2583,
│ │ │ │ │          "20324493e": 54,
│ │ │ │ │          "2033": 2612,
│ │ │ │ │          "20357": 2581,
│ │ │ │ │          "20394": 2588,
│ │ │ │ │ +        "204": 2461,
│ │ │ │ │          "20414": 2588,
│ │ │ │ │          "2045": 2612,
│ │ │ │ │          "2046": 2612,
│ │ │ │ │          "20462": 2581,
│ │ │ │ │          "20463": 2581,
│ │ │ │ │          "20464": 2581,
│ │ │ │ │          "20465": 2581,
│ │ │ │ │ @@ -33597,15 +33597,14 @@
│ │ │ │ │          "20467": 2581,
│ │ │ │ │          "20477401j": [439, 453],
│ │ │ │ │          "2048": 2612,
│ │ │ │ │          "204840": 2634,
│ │ │ │ │          "20484034": 2634,
│ │ │ │ │          "20495": 2581,
│ │ │ │ │          "20497": 2581,
│ │ │ │ │ -        "205": 2461,
│ │ │ │ │          "20500": 2588,
│ │ │ │ │          "2052": 2615,
│ │ │ │ │          "20580": 2588,
│ │ │ │ │          "20589": 2588,
│ │ │ │ │          "206": 2463,
│ │ │ │ │          "20613": 2581,
│ │ │ │ │          "20618": 2581,
│ │ │ │ │ @@ -33663,23 +33662,22 @@
│ │ │ │ │          "20985": 2585,
│ │ │ │ │          "20986": 2585,
│ │ │ │ │          "20992": 2585,
│ │ │ │ │          "20993": 2588,
│ │ │ │ │          "20_ver": 0,
│ │ │ │ │          "20count": 141,
│ │ │ │ │          "20d03bcfd": 0,
│ │ │ │ │ -        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2634, 2636, 2640, 2641, 2648, 2653, 2656, 2664, 2665, 2667],
│ │ │ │ │ +        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2461, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2634, 2636, 2640, 2641, 2648, 2653, 2656, 2664, 2665, 2667],
│ │ │ │ │          "210": 363,
│ │ │ │ │          "21001": 2588,
│ │ │ │ │          "21029": 2588,
│ │ │ │ │          "210306068529402873165736369884012333109": [2275, 2280],
│ │ │ │ │          "21048": 2586,
│ │ │ │ │          "211": 2491,
│ │ │ │ │          "21106": 2586,
│ │ │ │ │ -        "21117067": 2461,
│ │ │ │ │          "21120": 2599,
│ │ │ │ │          "21130": 2588,
│ │ │ │ │          "21137": 2586,
│ │ │ │ │          "21138": 2586,
│ │ │ │ │          "21139": 2586,
│ │ │ │ │          "21140": 2586,
│ │ │ │ │          "21141": 2586,
│ │ │ │ │ @@ -33766,14 +33764,15 @@
│ │ │ │ │          "22038": 2590,
│ │ │ │ │          "22039": 2590,
│ │ │ │ │          "2204460492503131e": 1915,
│ │ │ │ │          "22046": 2594,
│ │ │ │ │          "22055": 2594,
│ │ │ │ │          "22057": 2590,
│ │ │ │ │          "22078": 2590,
│ │ │ │ │ +        "221": 2461,
│ │ │ │ │          "22106": 2590,
│ │ │ │ │          "22107": 2590,
│ │ │ │ │          "22115": 2590,
│ │ │ │ │          "22135945e": 1149,
│ │ │ │ │          "22136": 2591,
│ │ │ │ │          "22137": 2599,
│ │ │ │ │          "22139": 2594,
│ │ │ │ │ @@ -33790,15 +33789,14 @@
│ │ │ │ │          "22221": 2591,
│ │ │ │ │          "22222": 2591,
│ │ │ │ │          "222222": 1335,
│ │ │ │ │          "22223": 2591,
│ │ │ │ │          "22224": 2591,
│ │ │ │ │          "22228": 2594,
│ │ │ │ │          "22230": 2591,
│ │ │ │ │ -        "22234397": 2488,
│ │ │ │ │          "22313": 2594,
│ │ │ │ │          "22314355": 2654,
│ │ │ │ │          "22315": 2599,
│ │ │ │ │          "22316": 2594,
│ │ │ │ │          "22357": 2594,
│ │ │ │ │          "22368": 2592,
│ │ │ │ │          "22370": 2592,
│ │ │ │ │ @@ -34173,15 +34171,15 @@
│ │ │ │ │          "2495": 2615,
│ │ │ │ │          "24955": 2604,
│ │ │ │ │          "24962": 2604,
│ │ │ │ │          "24971": 2604,
│ │ │ │ │          "24972": 2604,
│ │ │ │ │          "24977": 2604,
│ │ │ │ │          "24978": 2622,
│ │ │ │ │ -        "25": [10, 50, 54, 55, 56, 58, 69, 140, 361, 377, 409, 418, 440, 481, 489, 520, 526, 528, 544, 624, 645, 660, 667, 669, 680, 870, 881, 893, 917, 1056, 1070, 1083, 1135, 1142, 1143, 1240, 1349, 1526, 1527, 1542, 1581, 1606, 1651, 1694, 1702, 1834, 1907, 2089, 2090, 2091, 2204, 2239, 2240, 2251, 2265, 2266, 2323, 2325, 2337, 2348, 2349, 2367, 2380, 2390, 2396, 2414, 2427, 2438, 2446, 2463, 2473, 2476, 2491, 2513, 2515, 2519, 2567, 2602, 2604, 2622, 2623, 2634, 2640, 2644, 2653, 2656, 2658, 2665],
│ │ │ │ │ +        "25": [10, 50, 54, 55, 56, 58, 69, 140, 361, 377, 409, 418, 440, 481, 489, 520, 526, 528, 544, 624, 645, 660, 667, 669, 680, 870, 881, 893, 917, 1056, 1070, 1083, 1135, 1142, 1143, 1240, 1349, 1526, 1527, 1542, 1581, 1606, 1651, 1694, 1702, 1834, 1907, 2089, 2090, 2091, 2204, 2239, 2240, 2251, 2265, 2266, 2323, 2325, 2337, 2348, 2349, 2367, 2380, 2390, 2396, 2414, 2427, 2438, 2446, 2461, 2463, 2473, 2476, 2491, 2513, 2515, 2519, 2567, 2602, 2604, 2622, 2623, 2634, 2640, 2644, 2653, 2656, 2658, 2665],
│ │ │ │ │          "250": [361, 2463],
│ │ │ │ │          "2500": 652,
│ │ │ │ │          "25000": 652,
│ │ │ │ │          "25003": 2604,
│ │ │ │ │          "25043": 2604,
│ │ │ │ │          "25049": 2604,
│ │ │ │ │          "25054": 2622,
│ │ │ │ │ @@ -34207,14 +34205,15 @@
│ │ │ │ │          "25118": 2604,
│ │ │ │ │          "25119": 2604,
│ │ │ │ │          "25120": 2604,
│ │ │ │ │          "25121": 2604,
│ │ │ │ │          "25122": 2622,
│ │ │ │ │          "25130": 2605,
│ │ │ │ │          "25138": 2622,
│ │ │ │ │ +        "25144661": 2488,
│ │ │ │ │          "25145": 2622,
│ │ │ │ │          "25149": 2622,
│ │ │ │ │          "25155": 2622,
│ │ │ │ │          "25156": 2622,
│ │ │ │ │          "25158": 2622,
│ │ │ │ │          "25161": 2622,
│ │ │ │ │          "25168": 2622,
│ │ │ │ │ @@ -34568,20 +34567,19 @@
│ │ │ │ │          "28324": 2632,
│ │ │ │ │          "285": [566, 637],
│ │ │ │ │          "286": 354,
│ │ │ │ │          "28613933": 1153,
│ │ │ │ │          "28657": 28,
│ │ │ │ │          "28790332": 2665,
│ │ │ │ │          "2883": [1643, 1655],
│ │ │ │ │ -        "28843283": 2488,
│ │ │ │ │          "28853036": 1867,
│ │ │ │ │          "28904982231052": 675,
│ │ │ │ │          "2892": 2615,
│ │ │ │ │          "28mathematical_const": 76,
│ │ │ │ │ -        "29": [10, 21, 45, 54, 55, 76, 144, 163, 1638, 1647, 2208, 2328, 2461, 2463, 2464, 2513, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2560, 2561, 2562, 2563, 2564, 2565, 2566, 2567, 2568, 2587, 2602, 2622, 2640, 2656, 2665],
│ │ │ │ │ +        "29": [10, 21, 45, 54, 55, 76, 144, 163, 1638, 1647, 2208, 2328, 2463, 2464, 2513, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2560, 2561, 2562, 2563, 2564, 2565, 2566, 2567, 2568, 2587, 2602, 2622, 2640, 2656, 2665],
│ │ │ │ │          "290": 2300,
│ │ │ │ │          "29001ed": 13,
│ │ │ │ │          "290301": 55,
│ │ │ │ │          "292": 55,
│ │ │ │ │          "29229249": 524,
│ │ │ │ │          "29239766": 54,
│ │ │ │ │          "2925464970228": 657,
│ │ │ │ │ @@ -34624,39 +34622,38 @@
│ │ │ │ │          "2nd": [513, 641, 642, 655, 658, 669, 1526, 2335, 2378, 2425, 2636, 2640, 2665],
│ │ │ │ │          "2to3": 2616,
│ │ │ │ │          "2x": [1527, 1542, 2357, 2404, 2454, 2488, 2491, 2616, 2619],
│ │ │ │ │          "2x2": 47,
│ │ │ │ │          "2x3": [47, 72, 2664],
│ │ │ │ │          "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, 2463, 2513, 2531, 2587, 2608, 2636, 2640, 2644, 2656, 2665],
│ │ │ │ │ +        "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, 2636, 2640, 2644, 2656, 2665],
│ │ │ │ │          "300": [66, 363, 2238, 2576, 2644],
│ │ │ │ │          "3000": 2594,
│ │ │ │ │          "30000": 533,
│ │ │ │ │          "3000488281": 476,
│ │ │ │ │          "3003003": 1999,
│ │ │ │ │          "3006": 2614,
│ │ │ │ │          "3007": 2614,
│ │ │ │ │          "301": [438, 1923, 2477],
│ │ │ │ │ -        "30106312": 2461,
│ │ │ │ │          "30220482": [2345, 2391, 2439],
│ │ │ │ │          "30278462": 1154,
│ │ │ │ │          "3039": 2614,
│ │ │ │ │          "304": 22,
│ │ │ │ │          "30464": 2094,
│ │ │ │ │          "30498948e": 2665,
│ │ │ │ │          "305": [421, 948],
│ │ │ │ │          "3057": 2615,
│ │ │ │ │          "307": [1149, 2665],
│ │ │ │ │          "308": 1335,
│ │ │ │ │          "3083169284": [850, 1030],
│ │ │ │ │          "308j": 1335,
│ │ │ │ │          "309": [420, 421, 947, 948, 1149, 2460],
│ │ │ │ │          "30z": 360,
│ │ │ │ │ -        "31": [54, 55, 146, 336, 514, 669, 1088, 1094, 1638, 1711, 1867, 1913, 2204, 2236, 2327, 2331, 2375, 2422, 2513, 2520, 2636, 2640, 2656, 2665],
│ │ │ │ │ +        "31": [54, 55, 146, 336, 514, 669, 1088, 1094, 1638, 1711, 1867, 1913, 2204, 2236, 2327, 2331, 2375, 2422, 2461, 2513, 2520, 2636, 2640, 2656, 2665],
│ │ │ │ │          "31018314": 2458,
│ │ │ │ │          "3105": 2614,
│ │ │ │ │          "3108": 2614,
│ │ │ │ │          "3117": 2614,
│ │ │ │ │          "3118": [57, 2547],
│ │ │ │ │          "31183145": 2665,
│ │ │ │ │          "312088": 1867,
│ │ │ │ │ @@ -34708,14 +34705,15 @@
│ │ │ │ │          "33333334": 2171,
│ │ │ │ │          "3333333e": 1335,
│ │ │ │ │          "33339": 2173,
│ │ │ │ │          "33340274885464394": 2202,
│ │ │ │ │          "3340": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "3348": 2617,
│ │ │ │ │          "33486982e": 438,
│ │ │ │ │ +        "3359151": 2461,
│ │ │ │ │          "3361": [99, 906],
│ │ │ │ │          "3364": 2615,
│ │ │ │ │          "3373": 2615,
│ │ │ │ │          "33872321e": 2104,
│ │ │ │ │          "34": [12, 28, 144, 441, 1880, 1919, 2208, 2463, 2491, 2566, 2583, 2640, 2656, 2665],
│ │ │ │ │          "340": [2238, 2576],
│ │ │ │ │          "34132519": [680, 2658],
│ │ │ │ │ @@ -34739,15 +34737,14 @@
│ │ │ │ │          "35": [409, 489, 669, 870, 1056, 2204, 2325, 2369, 2416, 2572, 2634, 2640, 2656, 2665],
│ │ │ │ │          "350": [544, 635],
│ │ │ │ │          "3504": 2617,
│ │ │ │ │          "3534857623790153": 666,
│ │ │ │ │          "35355339": 1636,
│ │ │ │ │          "3541": 2615,
│ │ │ │ │          "35489284e": 2104,
│ │ │ │ │ -        "357": 2461,
│ │ │ │ │          "36": [58, 137, 355, 1752, 1761, 2204, 2225, 2323, 2367, 2414, 2463, 2491, 2536, 2648, 2656, 2658, 2665],
│ │ │ │ │          "360": [544, 2103, 2238, 2576],
│ │ │ │ │          "36045180e": 147,
│ │ │ │ │          "3608": 2615,
│ │ │ │ │          "361": [1344, 1346, 1522, 1908],
│ │ │ │ │          "362": 12,
│ │ │ │ │          "3628523": 2458,
│ │ │ │ │ @@ -34833,15 +34830,14 @@
│ │ │ │ │          "40918587e": 2104,
│ │ │ │ │          "40919914": 2665,
│ │ │ │ │          "4093": 2617,
│ │ │ │ │          "4094": [2615, 2617],
│ │ │ │ │          "4096": [72, 2092],
│ │ │ │ │          "41": [941, 1114, 1123, 1124, 1131, 1913, 2104, 2107, 2208, 2236, 2585, 2656, 2665],
│ │ │ │ │          "4109": 2617,
│ │ │ │ │ -        "41190027": 2461,
│ │ │ │ │          "41211849": 2665,
│ │ │ │ │          "4123": [2615, 2617],
│ │ │ │ │          "4134": 2617,
│ │ │ │ │          "41357986e": 2175,
│ │ │ │ │          "4138": 2617,
│ │ │ │ │          "4141": 2615,
│ │ │ │ │          "41421356": [653, 1756, 2665],
│ │ │ │ │ @@ -34856,15 +34852,15 @@
│ │ │ │ │          "4167": 1643,
│ │ │ │ │          "4170": 2617,
│ │ │ │ │          "4176": 2617,
│ │ │ │ │          "4181": [28, 2621],
│ │ │ │ │          "4187": 2617,
│ │ │ │ │          "4191": 2617,
│ │ │ │ │          "4197": 2617,
│ │ │ │ │ -        "42": [31, 58, 63, 147, 349, 669, 896, 897, 974, 1029, 2090, 2208, 2256, 2332, 2376, 2423, 2457, 2461, 2566, 2605, 2622, 2634, 2638, 2656, 2663, 2664, 2665],
│ │ │ │ │ +        "42": [31, 58, 63, 147, 349, 669, 896, 897, 974, 1029, 2090, 2208, 2256, 2332, 2376, 2423, 2457, 2566, 2605, 2622, 2634, 2638, 2656, 2663, 2664, 2665],
│ │ │ │ │          "420": [2238, 2576],
│ │ │ │ │          "42016704": 2665,
│ │ │ │ │          "4206": 2617,
│ │ │ │ │          "4220": 2617,
│ │ │ │ │          "4223": 2617,
│ │ │ │ │          "4225": 2617,
│ │ │ │ │          "423": 55,
│ │ │ │ │ @@ -34891,25 +34887,26 @@
│ │ │ │ │          "4354": 2617,
│ │ │ │ │          "4359": 2617,
│ │ │ │ │          "4368": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4375": 2491,
│ │ │ │ │          "43857224": 1153,
│ │ │ │ │          "43887844": [349, 2457, 2638],
│ │ │ │ │          "43999999999998": 1114,
│ │ │ │ │ -        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2463, 2624, 2656, 2657, 2658, 2665],
│ │ │ │ │ +        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2461, 2463, 2624, 2656, 2657, 2658, 2665],
│ │ │ │ │          "440": [10, 2520],
│ │ │ │ │          "4400": [409, 661, 2168],
│ │ │ │ │          "44069024": 349,
│ │ │ │ │          "4408": 2617,
│ │ │ │ │          "44089210e": 1527,
│ │ │ │ │          "4408921e": [1765, 2175],
│ │ │ │ │          "4409e": 2091,
│ │ │ │ │          "442": 2615,
│ │ │ │ │          "4428": 2617,
│ │ │ │ │          "4434142": 349,
│ │ │ │ │ +        "44341898": 2461,
│ │ │ │ │          "443469": 680,
│ │ │ │ │          "444": 485,
│ │ │ │ │          "4465": 2620,
│ │ │ │ │          "4466": 2617,
│ │ │ │ │          "4472136": 642,
│ │ │ │ │          "4472136j": 642,
│ │ │ │ │          "4476": 2621,
│ │ │ │ │ @@ -34929,15 +34926,15 @@
│ │ │ │ │          "4532": [409, 661, 2168],
│ │ │ │ │          "4545724517479104": 2460,
│ │ │ │ │          "45560727e": 54,
│ │ │ │ │          "456": 1921,
│ │ │ │ │          "4567": 2643,
│ │ │ │ │          "45674898e": 566,
│ │ │ │ │          "45a3d84": 2521,
│ │ │ │ │ -        "46": [409, 523, 905, 1707, 2204, 2208, 2640, 2656],
│ │ │ │ │ +        "46": [409, 523, 905, 1707, 2204, 2208, 2461, 2640, 2656],
│ │ │ │ │          "460": [2238, 2576],
│ │ │ │ │          "46009194e": 566,
│ │ │ │ │          "4602": 2618,
│ │ │ │ │          "4610935": 457,
│ │ │ │ │          "4613": 2618,
│ │ │ │ │          "4628": 2618,
│ │ │ │ │          "46351241j": 2081,
│ │ │ │ │ @@ -34950,15 +34947,15 @@
│ │ │ │ │          "46666491": 349,
│ │ │ │ │          "46716228e": 1586,
│ │ │ │ │          "46755891e": 54,
│ │ │ │ │          "468": [136, 147],
│ │ │ │ │          "4685006": [2352, 2399, 2449],
│ │ │ │ │          "4686": 12,
│ │ │ │ │          "46957616e": [470, 1899, 1900],
│ │ │ │ │ -        "47": [52, 2208, 2323, 2367, 2414, 2656, 2665],
│ │ │ │ │ +        "47": [52, 2208, 2323, 2367, 2414, 2461, 2656, 2665],
│ │ │ │ │          "4702687338396767": 2348,
│ │ │ │ │          "471": [136, 147, 2463],
│ │ │ │ │          "47108547995356098": [2345, 2391, 2439],
│ │ │ │ │          "47140452j": 2491,
│ │ │ │ │          "472": 55,
│ │ │ │ │          "4722": 2618,
│ │ │ │ │          "4723": 2621,
│ │ │ │ │ @@ -34975,14 +34972,15 @@
│ │ │ │ │          "4800": 57,
│ │ │ │ │          "48000000": 2634,
│ │ │ │ │          "4809319": 1153,
│ │ │ │ │          "4816": [99, 906],
│ │ │ │ │          "48219694e": [421, 948],
│ │ │ │ │          "4836": 2618,
│ │ │ │ │          "484": [2517, 2583, 2625],
│ │ │ │ │ +        "48485351": 2461,
│ │ │ │ │          "4853": 2618,
│ │ │ │ │          "4861946401452": 2334,
│ │ │ │ │          "4874": [409, 661, 2168],
│ │ │ │ │          "4882": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4896": 2620,
│ │ │ │ │          "49": [71, 2208, 2323, 2367, 2414, 2567, 2568, 2640, 2656, 2665],
│ │ │ │ │          "4928": [409, 661, 2168],
│ │ │ │ │ @@ -35031,15 +35029,14 @@
│ │ │ │ │          "5067": 2620,
│ │ │ │ │          "5082": 2620,
│ │ │ │ │          "5095": 2620,
│ │ │ │ │          "51": [58, 520, 1654, 1752, 1761, 1867, 1870, 2083, 2204, 2331, 2339, 2356, 2375, 2382, 2403, 2422, 2429, 2453, 2622, 2656, 2665],
│ │ │ │ │          "510": [143, 570],
│ │ │ │ │          "5100": 2620,
│ │ │ │ │          "5104": 2620,
│ │ │ │ │ -        "5107768": 2488,
│ │ │ │ │          "51182162": 2665,
│ │ │ │ │          "512": [69, 893, 1083, 1143, 1247, 2115, 2240, 2542, 2547, 2665],
│ │ │ │ │          "51327412": 1891,
│ │ │ │ │          "5136": 2620,
│ │ │ │ │          "5138": 2620,
│ │ │ │ │          "514229": 28,
│ │ │ │ │          "5147": 2620,
│ │ │ │ │ @@ -35064,14 +35061,15 @@
│ │ │ │ │          "52359878": 1911,
│ │ │ │ │          "52380952e": 1816,
│ │ │ │ │          "5240": 2620,
│ │ │ │ │          "5251": 2620,
│ │ │ │ │          "526": 2463,
│ │ │ │ │          "5260": [2353, 2400, 2450],
│ │ │ │ │          "5271": 42,
│ │ │ │ │ +        "52837855": 2461,
│ │ │ │ │          "53": [162, 457, 1638, 2208, 2551, 2554, 2656, 2665],
│ │ │ │ │          "5306": [409, 661, 2168],
│ │ │ │ │          "5313": 2621,
│ │ │ │ │          "5316": 2621,
│ │ │ │ │          "5324j": [416, 417, 622, 623],
│ │ │ │ │          "5354": 2621,
│ │ │ │ │          "5359": 2621,
│ │ │ │ │ @@ -35142,18 +35140,20 @@
│ │ │ │ │          "579365079365115": [1113, 1543],
│ │ │ │ │          "57x": 2594,
│ │ │ │ │          "58": [669, 1748, 1777, 2204, 2208, 2332, 2376, 2423, 2464, 2572, 2634, 2656],
│ │ │ │ │          "582892": 2634,
│ │ │ │ │          "58289208": 2634,
│ │ │ │ │          "584388": 55,
│ │ │ │ │          "585": [378, 1358, 1514, 2583],
│ │ │ │ │ +        "58555718": 2488,
│ │ │ │ │          "58578644": 1756,
│ │ │ │ │          "58826587": 349,
│ │ │ │ │          "59": [55, 2208, 2602, 2656],
│ │ │ │ │          "5910": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │ +        "59357937": 2461,
│ │ │ │ │          "595726": 2634,
│ │ │ │ │          "59572603": 2634,
│ │ │ │ │          "5969": [99, 906],
│ │ │ │ │          "598150": 2641,
│ │ │ │ │          "59815003": 38,
│ │ │ │ │          "5982": 2641,
│ │ │ │ │          "59903635e": 147,
│ │ │ │ │ @@ -35205,15 +35205,14 @@
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2166, 2167],
│ │ │ │ │          "63526532": 2458,
│ │ │ │ │          "636363636364": [2353, 2400, 2450],
│ │ │ │ │          "63696169": 2634,
│ │ │ │ │          "6376": 2522,
│ │ │ │ │          "6390": [2353, 2400, 2450],
│ │ │ │ │ -        "63916943": 2461,
│ │ │ │ │          "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, 2634, 2638, 2647, 2648, 2656, 2658, 2664, 2665],
│ │ │ │ │          "64023025": 2098,
│ │ │ │ │          "6416010000000001": 1114,
│ │ │ │ │          "64386512": 349,
│ │ │ │ │          "64402274e": 660,
│ │ │ │ │          "6446": [2550, 2554],
│ │ │ │ │          "646": [2517, 2576],
│ │ │ │ │ @@ -35273,14 +35272,15 @@
│ │ │ │ │          "6577": 2522,
│ │ │ │ │          "6579": 2522,
│ │ │ │ │          "6586976": 1149,
│ │ │ │ │          "6590": 2522,
│ │ │ │ │          "6596": 2522,
│ │ │ │ │          "6596288841243357": 2458,
│ │ │ │ │          "659885634118668e": 645,
│ │ │ │ │ +        "65999645": 2461,
│ │ │ │ │          "65_535": 62,
│ │ │ │ │          "65x": 2594,
│ │ │ │ │          "66": [13, 58, 1922, 2547, 2656, 2665],
│ │ │ │ │          "6600475": 1149,
│ │ │ │ │          "6602": 2522,
│ │ │ │ │          "6606": 2522,
│ │ │ │ │          "6611": 2522,
│ │ │ │ │ @@ -35300,14 +35300,15 @@
│ │ │ │ │          "66666667e": 1816,
│ │ │ │ │          "66669964e": 2171,
│ │ │ │ │          "6667": 2522,
│ │ │ │ │          "6668": 2522,
│ │ │ │ │          "6675": 2522,
│ │ │ │ │          "6678": 2522,
│ │ │ │ │          "6686": 2522,
│ │ │ │ │ +        "6686265": 2461,
│ │ │ │ │          "6689502": 2576,
│ │ │ │ │          "669": 669,
│ │ │ │ │          "6695": 2522,
│ │ │ │ │          "6697": 2522,
│ │ │ │ │          "6698": 2522,
│ │ │ │ │          "67": [409, 670, 671, 672, 1901, 2542, 2643, 2656, 2665],
│ │ │ │ │          "67046769e": 147,
│ │ │ │ │ @@ -35399,15 +35400,15 @@
│ │ │ │ │          "72686684e": 566,
│ │ │ │ │          "72717132": 2658,
│ │ │ │ │          "72727273": 136,
│ │ │ │ │          "72847407": 1154,
│ │ │ │ │          "729": 2665,
│ │ │ │ │          "72904971": 1153,
│ │ │ │ │          "72949656": 2634,
│ │ │ │ │ -        "73": [2461, 2463, 2656],
│ │ │ │ │ +        "73": [2463, 2656],
│ │ │ │ │          "7320508075688772j": 59,
│ │ │ │ │          "73472348e": 1816,
│ │ │ │ │          "73496154e": 1867,
│ │ │ │ │          "73603959e": 2665,
│ │ │ │ │          "73799541": 1153,
│ │ │ │ │          "74": [2463, 2513, 2514, 2656],
│ │ │ │ │          "74000000": 2634,
│ │ │ │ │ @@ -35472,20 +35473,18 @@
│ │ │ │ │          "77447664948076": 675,
│ │ │ │ │          "7755575615628914e": 2647,
│ │ │ │ │          "77555756e": 1877,
│ │ │ │ │          "77598074": 349,
│ │ │ │ │          "77714685": 349,
│ │ │ │ │          "7774613834041182": 2315,
│ │ │ │ │          "7776": [99, 906],
│ │ │ │ │ -        "77778762": 2461,
│ │ │ │ │          "7778": 2527,
│ │ │ │ │          "7793": 2527,
│ │ │ │ │ -        "78": [2091, 2643, 2656],
│ │ │ │ │ +        "78": [2091, 2461, 2643, 2656],
│ │ │ │ │          "78096262": [2352, 2399, 2449],
│ │ │ │ │ -        "78118065": 2461,
│ │ │ │ │          "7816": 2527,
│ │ │ │ │          "7821": 2527,
│ │ │ │ │          "7824": 2527,
│ │ │ │ │          "7835": 2527,
│ │ │ │ │          "784": 2463,
│ │ │ │ │          "7847": 2527,
│ │ │ │ │          "784728999999999": 1114,
│ │ │ │ │ @@ -35519,15 +35518,15 @@
│ │ │ │ │          "79769313e": 1335,
│ │ │ │ │          "79ff": [102, 125],
│ │ │ │ │          "7e": 669,
│ │ │ │ │          "7e13": 55,
│ │ │ │ │          "7e17": 55,
│ │ │ │ │          "7x": [2566, 2599],
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│ │ │ │ │ +        "80": [69, 396, 409, 446, 977, 2248, 2346, 2357, 2383, 2392, 2404, 2430, 2441, 2454, 2588, 2622, 2647, 2648, 2656],
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│ │ │ │ │          "8020": 2527,
│ │ │ │ │ @@ -35562,15 +35561,16 @@
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│ │ │ │ │ +        "83700379": 2488,
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│ │ │ │ │ @@ -35641,15 +35641,14 @@
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│ │ │ │ │ @@ -35690,25 +35689,23 @@
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│ │ │ │ │ -        "95298507": 2488,
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