--- /srv/reproducible-results/rbuild-debian/r-b-build.0G5AIiCT/b1/numpy_2.2.4+ds-1_amd64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.0G5AIiCT/b2/numpy_2.2.4+ds-1_amd64.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - ef12668dab3481316de06aa275151d90 5813904 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│ + 865459aaffc9914fd19c99de7bd98ee7 5814148 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│   be6e12c72b6e1958a22920a6cf12ce11 30549304 debug optional python3-numpy-dbgsym_2.2.4+ds-1_amd64.deb
│   0da7207383b6ebbcbe9edbf5799379ed 138728 python optional python3-numpy-dev_2.2.4+ds-1_amd64.deb
│   58dbaabd1cc1903ea26cf45065bceb99 5095572 python optional python3-numpy_2.2.4+ds-1_amd64.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    64884 2025-04-01 19:45:23.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5748828 2025-04-01 19:45:23.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0  5749072 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)    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)    44349 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)  2687911 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2687893 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   177614 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64100 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    18746 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/user/basics.html
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ @@ -536,30 +536,30 @@
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [1]: </span><span class="kn">import</span> <span class="nn">numpy.random</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [2]: </span><span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_normal(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">1.14 ms +- 28.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">2.26 ms +- 148 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.16 ms +- 9.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.03 ms +- 15.8 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">545 us +- 16.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">1.61 ms +- 69.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">524 us +- 21 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.38 ms +- 12.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [5]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_gamma(3.0, 100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_gamma(3.0, 100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">2.2 ms +- 18.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">4.44 ms +- 29.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.14 ms +- 33.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.16 ms +- 24.4 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p><a class="reference internal" href="generated/numpy.random.Generator.integers.html#numpy.random.Generator.integers" title="numpy.random.Generator.integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">integers</span></code></a> is now the canonical way to generate integer
│ │ │ │  random numbers from a discrete uniform distribution. This replaces both
│ │ │ │  <a class="reference internal" href="generated/numpy.random.randint.html#numpy.random.randint" title="numpy.random.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a> and the deprecated <a class="reference internal" href="generated/numpy.random.random_integers.html#numpy.random.random_integers" title="numpy.random.random_integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random_integers</span></code></a>.</p></li>
│ │ │ │  <li><p>The <a class="reference internal" href="generated/numpy.random.rand.html#numpy.random.rand" title="numpy.random.rand"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rand</span></code></a> and <a class="reference internal" href="generated/numpy.random.randn.html#numpy.random.randn" title="numpy.random.randn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randn</span></code></a> methods are only available through the legacy
│ │ │ │ @@ -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([0.52982092, 0.42295032, 0.24147651])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.29293961, 0.65281904, 0.13724775])</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([0.9568871 , 0.1235407 , 0.99757785], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.96676505, 0.3154664 , 0.50938195], 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([ 71, 215,  84], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([33, 49, 40], 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([0.62682846, 0.76426864])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.5231906 , 0.65732983])</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">[0.62682846 0.76426864 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.5231906  0.65732983 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,  1,  0,  3,  2],</span>
│ │ │ │ -<span class="go">       [ 6,  5,  4,  7,  6],</span>
│ │ │ │ -<span class="go">       [10,  9,  8, 11, 10]])</span>
│ │ │ │ +<span class="go">array([[ 3,  2,  2,  2,  0],</span>
│ │ │ │ +<span class="go">       [ 7,  6,  6,  6,  4],</span>
│ │ │ │ +<span class="go">       [11, 10, 10, 10,  8]])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [18]: </span><span class="n">rng</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>        <span class="c1"># Shuffle in-place</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [19]: </span><span class="n">a</span>
│ │ │ │  <span class="gh">Out[19]: </span>
│ │ │ │ -<span class="go">array([[ 1,  2,  3,  0],</span>
│ │ │ │ -<span class="go">       [ 5,  6,  7,  4],</span>
│ │ │ │ -<span class="go">       [ 9, 10, 11,  8]])</span>
│ │ │ │ +<span class="go">array([[ 1,  3,  2,  0],</span>
│ │ │ │ +<span class="go">       [ 5,  7,  6,  4],</span>
│ │ │ │ +<span class="go">       [ 9, 11, 10,  8]])</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <ul class="simple">
│ │ │ │  <li><p>Added a method to sample from the complex normal distribution
│ │ │ │  (<em class="xref py py-obj">complex_normal</em>)</p></li>
│ │ │ │  </ul>
│ │ │ │  </section>
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -102,26 +102,26 @@
│ │ │ │ │  In [1]: import numpy.random
│ │ │ │ │  
│ │ │ │ │  In [2]: rng = np.random.default_rng()
│ │ │ │ │  
│ │ │ │ │  In [3]: %timeit -n 1 rng.standard_normal(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_normal(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -1.14 ms +- 28.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -2.26 ms +- 148 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.16 ms +- 9.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.03 ms +- 15.8 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)
│ │ │ │ │     ...:
│ │ │ │ │ -545 us +- 16.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -1.61 ms +- 69.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +524 us +- 21 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.38 ms +- 12.7 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │  In [5]: %timeit -n 1 rng.standard_gamma(3.0, 100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_gamma(3.0, 100000)
│ │ │ │ │     ...:
│ │ │ │ │ -2.2 ms +- 18.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -4.44 ms +- 29.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.14 ms +- 33.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.16 ms +- 24.4 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │      * _i_n_t_e_g_e_r_s is now the canonical way to generate integer random numbers from
│ │ │ │ │        a discrete uniform distribution. This replaces both _r_a_n_d_i_n_t and the
│ │ │ │ │        deprecated _r_a_n_d_o_m___i_n_t_e_g_e_r_s.
│ │ │ │ │      * The _r_a_n_d and _r_a_n_d_n methods are only available through the legacy
│ │ │ │ │        _R_a_n_d_o_m_S_t_a_t_e.
│ │ │ │ │      * _G_e_n_e_r_a_t_o_r_._r_a_n_d_o_m is now the canonical way to generate floating-point
│ │ │ │ │        random numbers, which replaces _R_a_n_d_o_m_S_t_a_t_e_._r_a_n_d_o_m___s_a_m_p_l_e, _s_a_m_p_l_e, and
│ │ │ │ │ @@ -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([0.52982092, 0.42295032, 0.24147651])
│ │ │ │ │ +Out[7]: array([0.29293961, 0.65281904, 0.13724775])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.9568871 , 0.1235407 , 0.99757785], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.96676505, 0.3154664 , 0.50938195], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([ 71, 215,  84], dtype=uint8)
│ │ │ │ │ +Out[9]: array([33, 49, 40], 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([0.62682846, 0.76426864])
│ │ │ │ │ +Out[12]: array([0.5231906 , 0.65732983])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.62682846 0.76426864 0.         0.        ]
│ │ │ │ │ +[0.5231906  0.65732983 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,  1,  0,  3,  2],
│ │ │ │ │ -       [ 6,  5,  4,  7,  6],
│ │ │ │ │ -       [10,  9,  8, 11, 10]])
│ │ │ │ │ +array([[ 3,  2,  2,  2,  0],
│ │ │ │ │ +       [ 7,  6,  6,  6,  4],
│ │ │ │ │ +       [11, 10, 10, 10,  8]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 1,  2,  3,  0],
│ │ │ │ │ -       [ 5,  6,  7,  4],
│ │ │ │ │ -       [ 9, 10, 11,  8]])
│ │ │ │ │ +array([[ 1,  3,  2,  0],
│ │ │ │ │ +       [ 5,  7,  6,  4],
│ │ │ │ │ +       [ 9, 11, 10,  8]])
│ │ │ │ │      * Added a method to sample from the complex normal distribution
│ │ │ │ │        (ccoommpplleexx__nnoorrmmaall)
│ │ │ │ │  _p_r_e_v_i_o_u_s
│ │ │ │ │  _M_u_l_t_i_t_h_r_e_a_d_e_d_ _g_e_n_e_r_a_t_i_o_n
│ │ │ │ │  _n_e_x_t
│ │ │ │ │  _P_e_r_f_o_r_m_a_n_c_e
│ │ │ │ │  © Copyright 2008-2025, NumPy Developers.
│ │ │ ├── ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ @@ -609,31 +609,31 @@
│ │ │ │  
│ │ │ │  <span class="gp">In [3]: </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span> <span class="o">+</span> <span class="n">rng</span><span class="o">.</span><span class="n">standard_normal</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <p>With the legacy polynomial module, a linear fit (i.e. polynomial of degree 1)
│ │ │ │  could be applied to these data with <a class="reference internal" href="generated/numpy.polyfit.html#numpy.polyfit" title="numpy.polyfit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">polyfit</span></code></a>:</p>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
│ │ │ │ -<span class="gh">Out[4]: </span><span class="go">array([1.00621178, 0.14101989])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 0.91501666, -0.00424889])</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([4.66897291, 4.52795303], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.11332609, 4.11757499], 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([0.14101989, 1.00621178], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.00424889,  0.91501666], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  </section>
│ │ │ │  </section>
│ │ │ │  <section id="documentation-for-the-polynomial-package">
│ │ │ │  <h2>Documentation for the <a class="reference internal" href="routines.polynomials-package.html#module-numpy.polynomial" title="numpy.polynomial"><code class="xref py py-obj docutils literal notranslate"><span class="pre">polynomial</span></code></a> package<a class="headerlink" href="#documentation-for-the-polynomial-package" title="Link to this heading">#</a></h2>
│ │ │ │  <p>In addition to standard power series polynomials, the polynomial package
│ │ │ │ ├── html2text {}
│ │ │ │ │ @@ -150,26 +150,26 @@
│ │ │ │ │  
│ │ │ │ │  In [2]: x = np.arange(10)
│ │ │ │ │  
│ │ │ │ │  In [3]: y = np.arange(10) + rng.standard_normal(10)
│ │ │ │ │  With the legacy polynomial module, a linear fit (i.e. polynomial of degree 1)
│ │ │ │ │  could be applied to these data with _p_o_l_y_f_i_t:
│ │ │ │ │  In [4]: np.polyfit(x, y, deg=1)
│ │ │ │ │ -Out[4]: array([1.00621178, 0.14101989])
│ │ │ │ │ +Out[4]: array([ 0.91501666, -0.00424889])
│ │ │ │ │  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([4.66897291, 4.52795303], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.11332609, 4.11757499], 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([0.14101989, 1.00621178], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.00424889,  0.91501666], 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 {}
│ │ │ │ │ @@ -32327,19 +32327,19 @@
│ │ │ │ │          "0010": 1519,
│ │ │ │ │          "0011": 138,
│ │ │ │ │          "001637457145670096": 2315,
│ │ │ │ │          "001j": [1596, 1653, 1710, 1767, 1824, 1879, 1893],
│ │ │ │ │          "002": [1335, 1602, 1659, 1716, 1773, 1830, 1886],
│ │ │ │ │          "0024": 477,
│ │ │ │ │          "003": [2327, 2372, 2419],
│ │ │ │ │ +        "00424889": 2488,
│ │ │ │ │          "005": 2188,
│ │ │ │ │          "0050000029": [357, 359],
│ │ │ │ │          "0050045159": [357, 359],
│ │ │ │ │          "00578369": 1754,
│ │ │ │ │ -        "00621178": 2488,
│ │ │ │ │          "00625": 1585,
│ │ │ │ │          "007000999997857": 1541,
│ │ │ │ │          "00867716": [2319, 2363, 2410],
│ │ │ │ │          "00950034": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "009a87ff44bf": 42,
│ │ │ │ │          "00j": [514, 642, 2167],
│ │ │ │ │          "01": [41, 42, 45, 54, 55, 62, 147, 162, 163, 164, 335, 361, 410, 514, 547, 557, 566, 669, 897, 1088, 1094, 1586, 1594, 1601, 1658, 1715, 1772, 1829, 1885, 2104, 2160, 2252, 2323, 2329, 2367, 2373, 2414, 2420, 2525, 2658],
│ │ │ │ │ @@ -32369,15 +32369,15 @@
│ │ │ │ │          "0253": 2652,
│ │ │ │ │          "02654825": 1891,
│ │ │ │ │          "02658058e": 2666,
│ │ │ │ │          "02755911": 2666,
│ │ │ │ │          "027559113243068367": 2666,
│ │ │ │ │          "02785049": 1867,
│ │ │ │ │          "02i": [513, 2644],
│ │ │ │ │ -        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2658],
│ │ │ │ │ +        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2461, 2658],
│ │ │ │ │          "03125": [1585, 2491],
│ │ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │ │          "0361": 2607,
│ │ │ │ │          "03703704": 1809,
│ │ │ │ │          "03943254e": 2104,
│ │ │ │ │          "03968254": [1113, 1543],
│ │ │ │ │          "0396842": 680,
│ │ │ │ │ @@ -32615,14 +32615,15 @@
│ │ │ │ │          "11218": 2542,
│ │ │ │ │          "11219": 2539,
│ │ │ │ │          "11251": 2539,
│ │ │ │ │          "11274": 2540,
│ │ │ │ │          "11294": 2540,
│ │ │ │ │          "113": [674, 2463, 2666],
│ │ │ │ │          "11308": 2542,
│ │ │ │ │ +        "11332609": 2488,
│ │ │ │ │          "1138": 2612,
│ │ │ │ │          "114": 2463,
│ │ │ │ │          "11407192": 1822,
│ │ │ │ │          "1142": [2353, 2400, 2450],
│ │ │ │ │          "1149": 2612,
│ │ │ │ │          "115": [1654, 2463],
│ │ │ │ │          "1151": 657,
│ │ │ │ │ @@ -32639,14 +32640,15 @@
│ │ │ │ │          "11682": 2543,
│ │ │ │ │          "11698": 2543,
│ │ │ │ │          "11700": 2543,
│ │ │ │ │          "11719": 2543,
│ │ │ │ │          "11720": 2543,
│ │ │ │ │          "11746": 2543,
│ │ │ │ │          "11757": 2543,
│ │ │ │ │ +        "11757499": 2488,
│ │ │ │ │          "11758": 2543,
│ │ │ │ │          "11759": 2543,
│ │ │ │ │          "11760": 2543,
│ │ │ │ │          "11761": 2543,
│ │ │ │ │          "11763": 2543,
│ │ │ │ │          "11769564": 2635,
│ │ │ │ │          "117696": 2635,
│ │ │ │ │ @@ -32716,15 +32718,14 @@
│ │ │ │ │          "123456789": [2091, 2393, 2644],
│ │ │ │ │          "12345678903141592653589793": 2299,
│ │ │ │ │          "123456789a12": 25,
│ │ │ │ │          "123456789a123456789b": 25,
│ │ │ │ │          "1234567e": 2172,
│ │ │ │ │          "12346": 2462,
│ │ │ │ │          "1235": 2091,
│ │ │ │ │ -        "1235407": 2461,
│ │ │ │ │          "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,
│ │ │ │ │          "12658": 2560,
│ │ │ │ │ @@ -32787,14 +32788,15 @@
│ │ │ │ │          "13610": 2560,
│ │ │ │ │          "13620": 2551,
│ │ │ │ │          "13641": 2551,
│ │ │ │ │          "13644": 2551,
│ │ │ │ │          "1366": 36,
│ │ │ │ │          "13698": 2560,
│ │ │ │ │          "13710533": [2319, 2363, 2410],
│ │ │ │ │ +        "13724775": 2461,
│ │ │ │ │          "13742": 2552,
│ │ │ │ │          "1377": 2612,
│ │ │ │ │          "13794": 2560,
│ │ │ │ │          "138": 2463,
│ │ │ │ │          "13808": [2553, 2558],
│ │ │ │ │          "13823": 2552,
│ │ │ │ │          "13829": 2560,
│ │ │ │ │ @@ -32825,15 +32827,14 @@
│ │ │ │ │          "14052": 2552,
│ │ │ │ │          "14056": 2552,
│ │ │ │ │          "14057": 2552,
│ │ │ │ │          "14058": 2552,
│ │ │ │ │          "14084": 2552,
│ │ │ │ │          "141": 669,
│ │ │ │ │          "14100": 2560,
│ │ │ │ │ -        "14101989": 2488,
│ │ │ │ │          "141120": 2642,
│ │ │ │ │          "14112001": 2666,
│ │ │ │ │          "14142": 2560,
│ │ │ │ │          "14156": 2555,
│ │ │ │ │          "14157": 2555,
│ │ │ │ │          "141571941375841": 2202,
│ │ │ │ │          "14158": 2555,
│ │ │ │ │ @@ -32945,15 +32946,15 @@
│ │ │ │ │          "14720": 2560,
│ │ │ │ │          "14730": 2560,
│ │ │ │ │          "14758": 2558,
│ │ │ │ │          "14771": 2560,
│ │ │ │ │          "14777": 2560,
│ │ │ │ │          "14781": 2558,
│ │ │ │ │          "14787": 2569,
│ │ │ │ │ -        "148": [2344, 2386, 2433, 2461, 2463],
│ │ │ │ │ +        "148": [2344, 2386, 2433, 2463],
│ │ │ │ │          "14812": 3,
│ │ │ │ │          "148293216": 2666,
│ │ │ │ │          "14841": 2560,
│ │ │ │ │          "14851": 2558,
│ │ │ │ │          "14852": 2558,
│ │ │ │ │          "14853": 2553,
│ │ │ │ │          "14854": 2553,
│ │ │ │ │ @@ -33667,15 +33668,15 @@
│ │ │ │ │          "20985": 2585,
│ │ │ │ │          "20986": 2585,
│ │ │ │ │          "20992": 2585,
│ │ │ │ │          "20993": 2588,
│ │ │ │ │          "20_ver": 0,
│ │ │ │ │          "20count": 141,
│ │ │ │ │          "20d03bcfd": 0,
│ │ │ │ │ -        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2635, 2637, 2641, 2642, 2649, 2654, 2657, 2665, 2666, 2668],
│ │ │ │ │ +        "21": [21, 26, 28, 30, 31, 40, 47, 54, 55, 58, 74, 98, 162, 163, 270, 336, 357, 359, 377, 388, 396, 403, 476, 477, 628, 661, 669, 880, 905, 944, 1069, 1229, 1312, 1466, 1869, 1881, 1986, 2091, 2168, 2172, 2208, 2225, 2230, 2237, 2238, 2342, 2343, 2461, 2463, 2513, 2515, 2517, 2519, 2567, 2568, 2572, 2583, 2585, 2588, 2594, 2627, 2628, 2632, 2635, 2637, 2641, 2642, 2649, 2654, 2657, 2665, 2666, 2668],
│ │ │ │ │          "210": 363,
│ │ │ │ │          "21001": 2588,
│ │ │ │ │          "21029": 2588,
│ │ │ │ │          "210306068529402873165736369884012333109": [2275, 2280],
│ │ │ │ │          "21048": 2586,
│ │ │ │ │          "211": 2491,
│ │ │ │ │          "21106": 2586,
│ │ │ │ │ @@ -33720,15 +33721,15 @@
│ │ │ │ │          "21473": 2587,
│ │ │ │ │          "21474": 2587,
│ │ │ │ │          "2147483647": [144, 535, 1102, 2648],
│ │ │ │ │          "2147483648": [50, 535, 1098, 2594, 2648],
│ │ │ │ │          "21475": 2587,
│ │ │ │ │          "21483": 2594,
│ │ │ │ │          "21485": 2588,
│ │ │ │ │ -        "215": [680, 2461, 2491],
│ │ │ │ │ +        "215": [680, 2491],
│ │ │ │ │          "21506": 2594,
│ │ │ │ │          "21512": 2587,
│ │ │ │ │          "21525": 2587,
│ │ │ │ │          "21536": 2587,
│ │ │ │ │          "21541": 2587,
│ │ │ │ │          "21547": 2587,
│ │ │ │ │          "2155": [305, 2134],
│ │ │ │ │ @@ -33993,15 +33994,15 @@
│ │ │ │ │          "23936": 2622,
│ │ │ │ │          "2394691": 2312,
│ │ │ │ │          "23968": 2600,
│ │ │ │ │          "23994": 2598,
│ │ │ │ │          "23998": 2622,
│ │ │ │ │          "23e": 477,
│ │ │ │ │          "23e24": 477,
│ │ │ │ │ -        "24": [10, 38, 47, 54, 55, 56, 58, 59, 62, 67, 98, 107, 108, 355, 356, 358, 408, 409, 477, 528, 531, 541, 542, 567, 638, 661, 662, 664, 838, 905, 939, 964, 968, 969, 1010, 1133, 1144, 1546, 1577, 1607, 1664, 1721, 1778, 1835, 1864, 1883, 1902, 2100, 2114, 2168, 2175, 2200, 2208, 2223, 2225, 2226, 2230, 2237, 2247, 2342, 2463, 2513, 2519, 2543, 2555, 2622, 2623, 2635, 2641, 2645, 2649, 2652, 2657, 2659, 2666, 2668],
│ │ │ │ │ +        "24": [10, 38, 47, 54, 55, 56, 58, 59, 62, 67, 98, 107, 108, 355, 356, 358, 408, 409, 477, 528, 531, 541, 542, 567, 638, 661, 662, 664, 838, 905, 939, 964, 968, 969, 1010, 1133, 1144, 1546, 1577, 1607, 1664, 1721, 1778, 1835, 1864, 1883, 1902, 2100, 2114, 2168, 2175, 2200, 2208, 2223, 2225, 2226, 2230, 2237, 2247, 2342, 2461, 2463, 2513, 2519, 2543, 2555, 2622, 2623, 2635, 2641, 2645, 2649, 2652, 2657, 2659, 2666, 2668],
│ │ │ │ │          "240": [57, 363],
│ │ │ │ │          "24011": 2622,
│ │ │ │ │          "24018": 2622,
│ │ │ │ │          "2403": 2615,
│ │ │ │ │          "24036": 2600,
│ │ │ │ │          "24037": 2600,
│ │ │ │ │          "24038": 2600,
│ │ │ │ │ @@ -34018,15 +34019,14 @@
│ │ │ │ │          "24122": 2600,
│ │ │ │ │          "24126": 2622,
│ │ │ │ │          "24127": 2600,
│ │ │ │ │          "24128": 2600,
│ │ │ │ │          "24129": 2600,
│ │ │ │ │          "24134": 2600,
│ │ │ │ │          "24144": 2622,
│ │ │ │ │ -        "24147651": 2461,
│ │ │ │ │          "24148": 2601,
│ │ │ │ │          "24154": 2622,
│ │ │ │ │          "24174": 2601,
│ │ │ │ │          "24179": 2601,
│ │ │ │ │          "24182": 2601,
│ │ │ │ │          "24183": 2601,
│ │ │ │ │          "24184": 2601,
│ │ │ │ │ @@ -34332,15 +34332,15 @@
│ │ │ │ │          "25914": 2622,
│ │ │ │ │          "25943": 2622,
│ │ │ │ │          "25954": 2622,
│ │ │ │ │          "25d0": 32,
│ │ │ │ │          "25j": 2659,
│ │ │ │ │          "25t03": 55,
│ │ │ │ │          "25x": 138,
│ │ │ │ │ -        "26": [29, 30, 40, 50, 54, 55, 58, 63, 79, 146, 944, 2204, 2208, 2310, 2333, 2377, 2424, 2461, 2513, 2519, 2534, 2536, 2537, 2577, 2599, 2601, 2622, 2625, 2629, 2641, 2657, 2658, 2666],
│ │ │ │ │ +        "26": [29, 30, 40, 50, 54, 55, 58, 63, 79, 146, 944, 2204, 2208, 2310, 2333, 2377, 2424, 2513, 2519, 2534, 2536, 2537, 2577, 2599, 2601, 2622, 2625, 2629, 2641, 2657, 2658, 2666],
│ │ │ │ │          "260": [162, 1328, 2238, 2576, 2666],
│ │ │ │ │          "26064346e": 147,
│ │ │ │ │          "26081": 2625,
│ │ │ │ │          "26103": 2625,
│ │ │ │ │          "26137788e": 2104,
│ │ │ │ │          "26157": 2625,
│ │ │ │ │          "262": 2666,
│ │ │ │ │ @@ -34511,15 +34511,15 @@
│ │ │ │ │          "27t00": 360,
│ │ │ │ │          "27t01": 360,
│ │ │ │ │          "27t02": 360,
│ │ │ │ │          "27t04": 360,
│ │ │ │ │          "27t05": 360,
│ │ │ │ │          "27t06": 360,
│ │ │ │ │          "27t07": 360,
│ │ │ │ │ -        "28": [36, 54, 55, 146, 409, 661, 1695, 1704, 1707, 1862, 2168, 2208, 2225, 2461, 2463, 2513, 2538, 2539, 2540, 2543, 2629, 2641, 2649, 2657, 2659, 2666],
│ │ │ │ │ +        "28": [36, 54, 55, 146, 409, 661, 1695, 1704, 1707, 1862, 2168, 2208, 2225, 2463, 2513, 2538, 2539, 2540, 2543, 2629, 2641, 2649, 2657, 2659, 2666],
│ │ │ │ │          "28000000e": 1335,
│ │ │ │ │          "2800000e": 1335,
│ │ │ │ │          "28006": 2630,
│ │ │ │ │          "28007": 2630,
│ │ │ │ │          "2801": 2613,
│ │ │ │ │          "28021": 2630,
│ │ │ │ │          "28044": 2630,
│ │ │ │ │ @@ -34599,22 +34599,23 @@
│ │ │ │ │          "28657": 28,
│ │ │ │ │          "28790332": 2666,
│ │ │ │ │          "2883": [1643, 1655],
│ │ │ │ │          "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, 2641, 2657, 2666],
│ │ │ │ │ +        "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, 2641, 2657, 2666],
│ │ │ │ │          "290": 2300,
│ │ │ │ │          "29001ed": 13,
│ │ │ │ │          "290301": 55,
│ │ │ │ │          "292": 55,
│ │ │ │ │          "29229249": 524,
│ │ │ │ │          "29239766": 54,
│ │ │ │ │          "2925464970228": 657,
│ │ │ │ │ +        "29293961": 2461,
│ │ │ │ │          "294241": 55,
│ │ │ │ │          "296": 669,
│ │ │ │ │          "2969": 2614,
│ │ │ │ │          "297": [438, 2477, 2666],
│ │ │ │ │          "29718677": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "2973": 2614,
│ │ │ │ │          "29737120e": 566,
│ │ │ │ │ @@ -34693,14 +34694,15 @@
│ │ │ │ │          "3134": 2614,
│ │ │ │ │          "3135": 2614,
│ │ │ │ │          "3136": 2614,
│ │ │ │ │          "314": [420, 947],
│ │ │ │ │          "3141": 562,
│ │ │ │ │          "3153": 2615,
│ │ │ │ │          "31534378e": 660,
│ │ │ │ │ +        "3154664": 2461,
│ │ │ │ │          "316": [680, 1923, 2659],
│ │ │ │ │          "3160": 2615,
│ │ │ │ │          "3168": 2615,
│ │ │ │ │          "3173": 2617,
│ │ │ │ │          "3175": 2617,
│ │ │ │ │          "317811": 28,
│ │ │ │ │          "317j": [411, 617],
│ │ │ │ │ @@ -34715,15 +34717,15 @@
│ │ │ │ │          "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,
│ │ │ │ │ -        "33": [54, 58, 144, 336, 838, 939, 941, 1010, 1907, 1922, 1999, 2173, 2175, 2176, 2208, 2303, 2513, 2621, 2637, 2641, 2657, 2666],
│ │ │ │ │ +        "33": [54, 58, 144, 336, 838, 939, 941, 1010, 1907, 1922, 1999, 2173, 2175, 2176, 2208, 2303, 2461, 2513, 2621, 2637, 2641, 2657, 2666],
│ │ │ │ │          "330": 363,
│ │ │ │ │          "3301": 2615,
│ │ │ │ │          "330m": 409,
│ │ │ │ │          "3312": 2615,
│ │ │ │ │          "3324": [13, 2615],
│ │ │ │ │          "333": [652, 950, 2173],
│ │ │ │ │          "33333": [2173, 2175],
│ │ │ │ │ @@ -34791,15 +34793,15 @@
│ │ │ │ │          "3743": 2615,
│ │ │ │ │          "375": [1634, 1663],
│ │ │ │ │          "37601032": [2387, 2434],
│ │ │ │ │          "377": 28,
│ │ │ │ │          "378": 652,
│ │ │ │ │          "379": 533,
│ │ │ │ │          "3793": 2615,
│ │ │ │ │ -        "38": [59, 542, 968, 969, 1545, 1752, 1761, 2107, 2204, 2208, 2313, 2333, 2361, 2377, 2408, 2424, 2510, 2572, 2657, 2666],
│ │ │ │ │ +        "38": [59, 542, 968, 969, 1545, 1752, 1761, 2107, 2204, 2208, 2313, 2333, 2361, 2377, 2408, 2424, 2461, 2510, 2572, 2657, 2666],
│ │ │ │ │          "380": [2238, 2576],
│ │ │ │ │          "38268343": 642,
│ │ │ │ │          "38268343j": 642,
│ │ │ │ │          "3832": 2615,
│ │ │ │ │          "38434191e": 660,
│ │ │ │ │          "38446749": 1867,
│ │ │ │ │          "385": [2270, 2300],
│ │ │ │ │ @@ -34836,15 +34838,15 @@
│ │ │ │ │          "3w": 62,
│ │ │ │ │          "3x": [1542, 2491],
│ │ │ │ │          "3x3": [63, 1148, 2665],
│ │ │ │ │          "3x4": 2665,
│ │ │ │ │          "3x4x5": 2665,
│ │ │ │ │          "3x8000": [2350, 2397, 2447],
│ │ │ │ │          "4": [4, 5, 9, 12, 14, 25, 29, 30, 32, 37, 38, 39, 40, 47, 50, 54, 55, 56, 57, 58, 59, 61, 63, 65, 66, 67, 68, 69, 76, 78, 89, 90, 95, 96, 97, 98, 99, 104, 105, 107, 108, 109, 110, 111, 113, 115, 118, 120, 121, 127, 129, 130, 132, 134, 135, 136, 138, 140, 141, 144, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 167, 171, 176, 177, 185, 194, 213, 214, 215, 234, 239, 262, 264, 270, 280, 284, 287, 290, 295, 302, 305, 336, 337, 338, 339, 340, 341, 342, 345, 348, 352, 353, 354, 355, 356, 357, 358, 359, 360, 364, 365, 366, 367, 368, 369, 370, 371, 372, 374, 375, 376, 385, 396, 401, 404, 408, 409, 410, 411, 412, 413, 415, 416, 417, 418, 419, 421, 422, 432, 435, 439, 440, 442, 443, 444, 445, 446, 447, 448, 450, 453, 454, 455, 456, 461, 464, 466, 467, 470, 472, 473, 474, 477, 478, 482, 483, 489, 513, 514, 520, 521, 522, 523, 524, 526, 527, 528, 529, 530, 531, 532, 533, 538, 540, 541, 542, 543, 544, 545, 549, 553, 554, 560, 565, 566, 567, 569, 572, 573, 574, 575, 582, 584, 608, 617, 618, 619, 621, 622, 623, 624, 625, 628, 638, 639, 640, 645, 647, 648, 649, 650, 651, 653, 657, 660, 661, 662, 663, 664, 666, 667, 668, 669, 673, 676, 680, 751, 823, 826, 830, 831, 834, 844, 847, 855, 859, 860, 863, 864, 865, 868, 873, 874, 877, 880, 881, 883, 884, 886, 887, 888, 891, 893, 897, 903, 904, 905, 906, 908, 911, 912, 913, 914, 916, 917, 919, 922, 924, 925, 926, 928, 929, 932, 936, 942, 943, 944, 945, 946, 948, 950, 952, 953, 957, 958, 959, 960, 961, 963, 964, 967, 968, 969, 976, 978, 988, 993, 997, 1002, 1003, 1006, 1011, 1020, 1023, 1027, 1029, 1038, 1042, 1044, 1045, 1048, 1049, 1050, 1052, 1054, 1061, 1063, 1066, 1069, 1070, 1072, 1074, 1076, 1077, 1078, 1081, 1083, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1094, 1096, 1097, 1100, 1103, 1104, 1105, 1106, 1107, 1110, 1113, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1133, 1135, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1148, 1153, 1154, 1155, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1166, 1167, 1171, 1178, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1203, 1204, 1205, 1206, 1208, 1211, 1212, 1213, 1224, 1226, 1227, 1228, 1229, 1230, 1236, 1239, 1240, 1241, 1242, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1258, 1265, 1278, 1279, 1281, 1286, 1291, 1294, 1307, 1309, 1312, 1319, 1322, 1324, 1326, 1327, 1328, 1329, 1331, 1333, 1334, 1336, 1337, 1339, 1341, 1342, 1344, 1346, 1347, 1349, 1351, 1413, 1420, 1433, 1434, 1435, 1440, 1445, 1448, 1461, 1463, 1466, 1473, 1476, 1478, 1479, 1480, 1483, 1510, 1512, 1513, 1515, 1517, 1520, 1521, 1522, 1523, 1526, 1527, 1540, 1541, 1542, 1543, 1544, 1545, 1554, 1557, 1574, 1575, 1577, 1578, 1579, 1586, 1588, 1590, 1591, 1596, 1604, 1605, 1606, 1615, 1618, 1635, 1639, 1643, 1644, 1649, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1661, 1662, 1663, 1672, 1675, 1692, 1694, 1696, 1706, 1709, 1710, 1711, 1718, 1719, 1720, 1729, 1732, 1749, 1750, 1751, 1753, 1757, 1758, 1759, 1763, 1765, 1766, 1767, 1768, 1769, 1770, 1775, 1776, 1777, 1786, 1789, 1805, 1806, 1808, 1809, 1810, 1812, 1816, 1818, 1820, 1822, 1824, 1832, 1833, 1834, 1843, 1846, 1862, 1864, 1865, 1866, 1867, 1869, 1870, 1875, 1876, 1879, 1880, 1881, 1882, 1883, 1884, 1886, 1887, 1888, 1889, 1890, 1893, 1896, 1897, 1899, 1900, 1902, 1904, 1905, 1908, 1909, 1911, 1912, 1913, 1914, 1915, 1916, 1919, 1922, 1923, 1924, 1932, 1939, 1953, 1954, 1955, 1960, 1965, 1968, 1981, 1983, 1986, 1993, 1996, 1998, 2071, 2072, 2074, 2075, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2087, 2088, 2089, 2090, 2091, 2093, 2095, 2096, 2097, 2098, 2101, 2104, 2106, 2107, 2110, 2111, 2114, 2115, 2116, 2119, 2123, 2124, 2126, 2127, 2131, 2134, 2139, 2145, 2161, 2163, 2164, 2168, 2175, 2176, 2178, 2184, 2195, 2199, 2201, 2202, 2204, 2205, 2206, 2208, 2209, 2210, 2211, 2217, 2223, 2224, 2225, 2229, 2230, 2236, 2237, 2238, 2239, 2240, 2241, 2243, 2244, 2246, 2247, 2248, 2250, 2251, 2256, 2257, 2290, 2303, 2304, 2308, 2312, 2316, 2319, 2320, 2322, 2324, 2327, 2328, 2329, 2332, 2333, 2334, 2339, 2340, 2341, 2342, 2343, 2347, 2352, 2356, 2359, 2361, 2363, 2364, 2366, 2368, 2373, 2376, 2377, 2382, 2383, 2384, 2388, 2389, 2390, 2395, 2399, 2403, 2406, 2408, 2410, 2411, 2413, 2415, 2420, 2423, 2424, 2429, 2430, 2431, 2435, 2436, 2438, 2445, 2449, 2453, 2456, 2457, 2460, 2461, 2462, 2463, 2470, 2488, 2489, 2490, 2491, 2510, 2513, 2519, 2529, 2530, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2538, 2540, 2541, 2542, 2543, 2544, 2545, 2547, 2548, 2549, 2550, 2552, 2559, 2566, 2572, 2579, 2581, 2588, 2591, 2593, 2599, 2602, 2607, 2609, 2610, 2613, 2614, 2615, 2616, 2617, 2619, 2620, 2622, 2624, 2625, 2628, 2635, 2637, 2638, 2640, 2641, 2642, 2644, 2645, 2646, 2647, 2649, 2650, 2652, 2653, 2655, 2657, 2658, 2659, 2665, 2666],
│ │ │ │ │ -        "40": [32, 99, 143, 270, 409, 444, 446, 454, 568, 569, 570, 880, 906, 1069, 1117, 1229, 1312, 1466, 1906, 1986, 2089, 2165, 2204, 2208, 2323, 2367, 2414, 2635, 2639, 2641, 2657, 2666],
│ │ │ │ │ +        "40": [32, 99, 143, 270, 409, 444, 446, 454, 568, 569, 570, 880, 906, 1069, 1117, 1229, 1312, 1466, 1906, 1986, 2089, 2165, 2204, 2208, 2323, 2367, 2414, 2461, 2635, 2639, 2641, 2657, 2666],
│ │ │ │ │          "400": [55, 444],
│ │ │ │ │          "4000000000000p": 669,
│ │ │ │ │          "4001": [99, 906],
│ │ │ │ │          "40067661": 2635,
│ │ │ │ │          "4007": 2620,
│ │ │ │ │          "40077": [1644, 1656],
│ │ │ │ │          "400e": 2658,
│ │ │ │ │ @@ -34886,15 +34888,14 @@
│ │ │ │ │          "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,
│ │ │ │ │ -        "42295032": 2461,
│ │ │ │ │          "423": 55,
│ │ │ │ │          "42310646": 1153,
│ │ │ │ │          "42332645": 2666,
│ │ │ │ │          "42457905e": 1586,
│ │ │ │ │          "425": [523, 524],
│ │ │ │ │          "4253": 2617,
│ │ │ │ │          "4254": 2617,
│ │ │ │ │ @@ -34915,15 +34916,15 @@
│ │ │ │ │          "4354": 2617,
│ │ │ │ │          "4359": 2617,
│ │ │ │ │          "4368": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4375": 2491,
│ │ │ │ │          "43857224": 1153,
│ │ │ │ │          "43887844": [349, 2457, 2639],
│ │ │ │ │          "43999999999998": 1114,
│ │ │ │ │ -        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2461, 2463, 2624, 2657, 2658, 2659, 2666],
│ │ │ │ │ +        "44": [16, 1525, 1758, 1905, 1907, 1922, 2208, 2463, 2624, 2657, 2658, 2659, 2666],
│ │ │ │ │          "440": [10, 2520],
│ │ │ │ │          "4400": [409, 661, 2168],
│ │ │ │ │          "44069024": 349,
│ │ │ │ │          "4408": 2617,
│ │ │ │ │          "44089210e": 1527,
│ │ │ │ │          "4408921e": [1765, 2175],
│ │ │ │ │          "4409e": 2091,
│ │ │ │ │ @@ -35004,15 +35005,15 @@
│ │ │ │ │          "4836": 2618,
│ │ │ │ │          "484": [2517, 2583, 2625],
│ │ │ │ │          "4853": 2618,
│ │ │ │ │          "4861946401452": 2334,
│ │ │ │ │          "4874": [409, 661, 2168],
│ │ │ │ │          "4882": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4896": 2620,
│ │ │ │ │ -        "49": [71, 2208, 2323, 2367, 2414, 2567, 2568, 2641, 2657, 2666],
│ │ │ │ │ +        "49": [71, 2208, 2323, 2367, 2414, 2461, 2567, 2568, 2641, 2657, 2666],
│ │ │ │ │          "4928": [409, 661, 2168],
│ │ │ │ │          "49293": 1644,
│ │ │ │ │          "49313049": [2387, 2434],
│ │ │ │ │          "49401501": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "496041986": [420, 947],
│ │ │ │ │          "49778714": 2238,
│ │ │ │ │          "49876311": [2352, 2399, 2449],
│ │ │ │ │ @@ -35050,14 +35051,15 @@
│ │ │ │ │          "50491112870": 55,
│ │ │ │ │          "50491123200": 55,
│ │ │ │ │          "50491123200000000": 55,
│ │ │ │ │          "50629471": 1154,
│ │ │ │ │          "5063": 2620,
│ │ │ │ │          "5067": 2620,
│ │ │ │ │          "5082": 2620,
│ │ │ │ │ +        "50938195": 2461,
│ │ │ │ │          "5095": 2620,
│ │ │ │ │          "51": [58, 520, 1654, 1752, 1761, 1867, 1870, 2083, 2204, 2331, 2339, 2356, 2375, 2382, 2403, 2422, 2429, 2453, 2622, 2657, 2666],
│ │ │ │ │          "510": [143, 570],
│ │ │ │ │          "5100": 2620,
│ │ │ │ │          "5104": 2620,
│ │ │ │ │          "51182162": 2666,
│ │ │ │ │          "512": [69, 893, 1083, 1143, 1247, 2115, 2240, 2542, 2547, 2666],
│ │ │ │ │ @@ -35079,24 +35081,24 @@
│ │ │ │ │          "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,
│ │ │ │ │          "5225": 2620,
│ │ │ │ │          "5231": 2620,
│ │ │ │ │ +        "5231906": 2461,
│ │ │ │ │          "52338984": [2345, 2391, 2439],
│ │ │ │ │          "52359878": 1911,
│ │ │ │ │          "52380952e": 1816,
│ │ │ │ │ +        "524": 2461,
│ │ │ │ │          "5240": 2620,
│ │ │ │ │          "5251": 2620,
│ │ │ │ │          "526": 2463,
│ │ │ │ │          "5260": [2353, 2400, 2450],
│ │ │ │ │          "5271": 42,
│ │ │ │ │ -        "52795303": 2488,
│ │ │ │ │ -        "52982092": 2461,
│ │ │ │ │          "53": [162, 457, 1638, 2208, 2551, 2554, 2657, 2666],
│ │ │ │ │          "5306": [409, 661, 2168],
│ │ │ │ │          "5313": 2621,
│ │ │ │ │          "5316": 2621,
│ │ │ │ │          "5324j": [416, 417, 622, 623],
│ │ │ │ │          "5354": 2621,
│ │ │ │ │          "5359": 2621,
│ │ │ │ │ @@ -35115,15 +35117,14 @@
│ │ │ │ │          "54030231j": 2666,
│ │ │ │ │          "541": 2463,
│ │ │ │ │          "54117": 1644,
│ │ │ │ │          "5424": 2621,
│ │ │ │ │          "54323428": [2345, 2391, 2439],
│ │ │ │ │          "54362499": 2635,
│ │ │ │ │          "54402111": 2666,
│ │ │ │ │ -        "545": 2461,
│ │ │ │ │          "54545455": 136,
│ │ │ │ │          "54627315": 2635,
│ │ │ │ │          "5470": [2353, 2400, 2450],
│ │ │ │ │          "5481": 2621,
│ │ │ │ │          "5492": 2621,
│ │ │ │ │          "54930614": [106, 131],
│ │ │ │ │          "5493061443340549": [413, 619],
│ │ │ │ │ @@ -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,
│ │ │ │ │ @@ -35220,15 +35221,14 @@
│ │ │ │ │          "6227766": 514,
│ │ │ │ │          "623": [2394, 2444],
│ │ │ │ │          "62318272": [2319, 2363, 2410],
│ │ │ │ │          "62341325": 514,
│ │ │ │ │          "62374854": 2666,
│ │ │ │ │          "624": [2300, 2370, 2394, 2417, 2444, 2462],
│ │ │ │ │          "625": [99, 478, 645, 906, 2390, 2438],
│ │ │ │ │ -        "62682846": 2461,
│ │ │ │ │          "6273591314603949": [2335, 2378, 2425],
│ │ │ │ │          "62949953e": 645,
│ │ │ │ │          "63": [58, 514, 669, 1748, 1777, 2336, 2463, 2520, 2566, 2594, 2642, 2657],
│ │ │ │ │          "631198583": 55,
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2166, 2167],
│ │ │ │ │          "63526532": 2458,
│ │ │ │ │ @@ -35267,14 +35267,15 @@
│ │ │ │ │          "6501": 2522,
│ │ │ │ │          "65028784": 2666,
│ │ │ │ │          "65143654": 1154,
│ │ │ │ │          "6515": [2353, 2400, 2450],
│ │ │ │ │          "65200189e": 566,
│ │ │ │ │          "6526": 2522,
│ │ │ │ │          "6527": 2522,
│ │ │ │ │ +        "65281904": 2461,
│ │ │ │ │          "6530": 2522,
│ │ │ │ │          "6532": 2522,
│ │ │ │ │          "6536": 2522,
│ │ │ │ │          "6537": 2522,
│ │ │ │ │          "6538": 2522,
│ │ │ │ │          "6546": 2522,
│ │ │ │ │          "65465": [2335, 2378, 2425],
│ │ │ │ │ @@ -35288,14 +35289,15 @@
│ │ │ │ │          "6563": 2522,
│ │ │ │ │          "6566128774142013e": 653,
│ │ │ │ │          "6567": 2522,
│ │ │ │ │          "65685425": 2659,
│ │ │ │ │          "6569": 2522,
│ │ │ │ │          "6569866": 2666,
│ │ │ │ │          "6572": 2522,
│ │ │ │ │ +        "65732983": 2461,
│ │ │ │ │          "6574": 2522,
│ │ │ │ │          "65745445": [88, 101],
│ │ │ │ │          "6575": 2522,
│ │ │ │ │          "6576": [99, 906, 2522],
│ │ │ │ │          "6577": 2522,
│ │ │ │ │          "6579": 2522,
│ │ │ │ │          "6586976": 1149,
│ │ │ │ │ @@ -35327,15 +35329,14 @@
│ │ │ │ │          "66669964e": 2171,
│ │ │ │ │          "6667": 2522,
│ │ │ │ │          "6668": 2522,
│ │ │ │ │          "6675": 2522,
│ │ │ │ │          "6678": 2522,
│ │ │ │ │          "6686": 2522,
│ │ │ │ │          "6689502": 2576,
│ │ │ │ │ -        "66897291": 2488,
│ │ │ │ │          "669": 669,
│ │ │ │ │          "6695": 2522,
│ │ │ │ │          "6697": 2522,
│ │ │ │ │          "6698": 2522,
│ │ │ │ │          "67": [409, 670, 671, 672, 1901, 2542, 2644, 2657, 2666],
│ │ │ │ │          "67046769e": 147,
│ │ │ │ │          "6717": 2522,
│ │ │ │ │ @@ -35367,15 +35368,15 @@
│ │ │ │ │          "6840": 2524,
│ │ │ │ │          "6843": 2524,
│ │ │ │ │          "68456316": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "68482974": 1153,
│ │ │ │ │          "6884": 2524,
│ │ │ │ │          "68862757": 660,
│ │ │ │ │          "6888893": [2352, 2399, 2449],
│ │ │ │ │ -        "69": [58, 431, 2461, 2657, 2666],
│ │ │ │ │ +        "69": [58, 431, 2657, 2666],
│ │ │ │ │          "6916": 2524,
│ │ │ │ │          "6922": 2524,
│ │ │ │ │          "6924": 2524,
│ │ │ │ │          "69312169": [1113, 1543],
│ │ │ │ │          "69314718": [76, 657, 2655],
│ │ │ │ │          "69314718055994529": 657,
│ │ │ │ │          "6931471805599453": 2257,
│ │ │ │ │ @@ -35402,15 +35403,15 @@
│ │ │ │ │          "703": 2625,
│ │ │ │ │          "7054": 2535,
│ │ │ │ │          "706": 520,
│ │ │ │ │          "70710678": [216, 247, 641, 1199, 1216, 1282, 1299, 1436, 1453, 1636, 1642, 1956, 1973, 2103],
│ │ │ │ │          "70710678118654746": 637,
│ │ │ │ │          "70710678j": 641,
│ │ │ │ │          "7083": 2529,
│ │ │ │ │ -        "71": [354, 650, 2460, 2461, 2657],
│ │ │ │ │ +        "71": [354, 650, 2460, 2657],
│ │ │ │ │          "71080601": 2659,
│ │ │ │ │          "71238898": 1911,
│ │ │ │ │          "71387850e": 1586,
│ │ │ │ │          "718281": 431,
│ │ │ │ │          "71828182845904523536028747135266249775724709369995": 76,
│ │ │ │ │          "71828183": [38, 2666],
│ │ │ │ │          "718282": 2642,
│ │ │ │ │ @@ -35470,15 +35471,14 @@
│ │ │ │ │          "76": [541, 1897, 2463, 2657, 2659],
│ │ │ │ │          "7608": 2526,
│ │ │ │ │          "7611397": [349, 2457, 2639],
│ │ │ │ │          "76190476e": 1816,
│ │ │ │ │          "76322758": 1154,
│ │ │ │ │          "7638": 2526,
│ │ │ │ │          "76425276e": 1149,
│ │ │ │ │ -        "76426864": 2461,
│ │ │ │ │          "76492172": 349,
│ │ │ │ │          "7654": 2526,
│ │ │ │ │          "7656": 2526,
│ │ │ │ │          "7660": 2526,
│ │ │ │ │          "7665": 2526,
│ │ │ │ │          "7670": 2526,
│ │ │ │ │          "7671": 2526,
│ │ │ │ │ @@ -35588,15 +35588,15 @@
│ │ │ │ │          "83314899": 1154,
│ │ │ │ │          "83333333": 1702,
│ │ │ │ │          "833333333333333": [893, 1083, 1143, 2240],
│ │ │ │ │          "8341": 2528,
│ │ │ │ │          "8346": 2528,
│ │ │ │ │          "83571711": 349,
│ │ │ │ │          "83697020e": [470, 1899, 1900],
│ │ │ │ │ -        "84": [2461, 2657, 2659],
│ │ │ │ │ +        "84": [2657, 2659],
│ │ │ │ │          "840": 1212,
│ │ │ │ │          "84057254": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "84090247": 2458,
│ │ │ │ │          "84123594": 523,
│ │ │ │ │          "84147098": 2666,
│ │ │ │ │          "8414709848078965": 2640,
│ │ │ │ │          "84147098j": 2666,
│ │ │ │ │ @@ -35665,14 +35665,15 @@
│ │ │ │ │          "90384387e": 2104,
│ │ │ │ │          "90476190e": 1816,
│ │ │ │ │          "90909091": 136,
│ │ │ │ │          "909297": 2642,
│ │ │ │ │          "90929743": 2666,
│ │ │ │ │          "91": 2657,
│ │ │ │ │          "91275558": 2635,
│ │ │ │ │ +        "91501666": 2488,
│ │ │ │ │          "916666666666666": 1240,
│ │ │ │ │          "92": [98, 2657, 2659],
│ │ │ │ │          "921fb54442d18p": 2520,
│ │ │ │ │          "9223372036854775807": 2648,
│ │ │ │ │          "9223372036854775808": 2648,
│ │ │ │ │          "92346708": 349,
│ │ │ │ │          "92362781e": 2104,
│ │ │ │ │ @@ -35720,22 +35721,22 @@
│ │ │ │ │          "950684": 2635,
│ │ │ │ │          "95068423": 2635,
│ │ │ │ │          "9555": [2533, 2534],
│ │ │ │ │          "9556": [2533, 2534],
│ │ │ │ │          "9557": [2533, 2534],
│ │ │ │ │          "9558": [2533, 2534],
│ │ │ │ │          "9559": [2533, 2534],
│ │ │ │ │ -        "9568871": 2461,
│ │ │ │ │          "9580": [2533, 2534],
│ │ │ │ │          "95892427": 2666,
│ │ │ │ │          "96": [69, 1577, 1867, 2303, 2463, 2566, 2648, 2657, 2659, 2668],
│ │ │ │ │          "96139749": 2666,
│ │ │ │ │          "96202397": [2335, 2378, 2425],
│ │ │ │ │          "96360618": [2387, 2434],
│ │ │ │ │          "9665554": 349,
│ │ │ │ │ +        "96676505": 2461,
│ │ │ │ │          "96767474e": 54,
│ │ │ │ │          "96875": 2491,
│ │ │ │ │          "96979195": 2635,
│ │ │ │ │          "969792": 2635,
│ │ │ │ │          "96e7": 42,
│ │ │ │ │          "97": [2463, 2635, 2657, 2666],
│ │ │ │ │          "9700": 2666,
│ │ │ │ │ @@ -35792,15 +35793,14 @@
│ │ │ │ │          "9917": 2343,
│ │ │ │ │          "99256089": 349,
│ │ │ │ │          "99322285": [88, 101],
│ │ │ │ │          "99394529": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "99417356": 1754,
│ │ │ │ │          "99507202": 349,
│ │ │ │ │          "99734545": 1154,
│ │ │ │ │ -        "99757785": 2461,
│ │ │ │ │          "998": 2535,
│ │ │ │ │          "99822295": [103, 126],
│ │ │ │ │          "99827656": 1754,
│ │ │ │ │          "99885316e": 566,
│ │ │ │ │          "999": [543, 844, 864, 887, 1020, 1049, 1077, 1125, 2535, 2644],
│ │ │ │ │          "9990000e": 1335,
│ │ │ │ │          "99923895": 349,