--- /srv/reproducible-results/rbuild-debian/r-b-build.SpjQZP3d/b1/numpy_2.2.3+ds-2_arm64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.SpjQZP3d/b2/numpy_2.2.3+ds-2_arm64.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - e193ff5fabaa07fefc7fb417d9eef4d5 5812312 doc optional python-numpy-doc_2.2.3+ds-2_all.deb
│ + 7d545bd7a91f5efce0a96b6abf0685f3 5812220 doc optional python-numpy-doc_2.2.3+ds-2_all.deb
│   9d1c696a0890513e7fc13f7ad84abdf5 28802504 debug optional python3-numpy-dbgsym_2.2.3+ds-2_arm64.deb
│   3c16155db12db9a63d33f2906ae4b232 135436 python optional python3-numpy-dev_2.2.3+ds-2_arm64.deb
│   9777387a460890c5d50dbdd0fbba0d09 4133128 python optional python3-numpy_2.2.3+ds-2_arm64.deb
├── python-numpy-doc_2.2.3+ds-2_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2025-02-20 10:56:23.000000 debian-binary
│ │ --rw-r--r--   0        0        0    64816 2025-02-20 10:56:23.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5747304 2025-02-20 10:56:23.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0    64836 2025-02-20 10:56:23.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0  5747192 2025-02-20 10:56:23.000000 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 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46891 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45382 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    82403 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45982 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/index.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    89078 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/legacy.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    35540 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/multithreading.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    44350 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    44354 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/new-or-different.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    52723 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/parallel.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    38070 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/performance.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41915 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    45998 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50957 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    27535 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    54450 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html
│ │ │ │ @@ -2610,15 +2610,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    24374 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.matlib.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26288 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.other.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    37419 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials-package.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46847 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.chebyshev.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    51499 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.classes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43104 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43639 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.hermite_e.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)    47589 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)    47587 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    43031 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.laguerre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    42812 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.legendre.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    28772 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.poly1d.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    41877 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polynomial.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26623 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.polynomials.polyutils.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26761 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.rec.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    26422 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.set.html
│ │ │ │ @@ -2754,15 +2754,15 @@
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    46199 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.0-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    31563 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32256 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    32747 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.3-notes.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    13407 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release/template.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    90523 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/release.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    12397 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/search.html
│ │ │ │ --rw-r--r--   0 root         (0) root         (0)  2686402 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2686436 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │  drwxr-xr-x   0 root         (0) root         (0)        0 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)   177614 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/absolute_beginners.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    50529 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/basics.broadcasting.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    33464 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/basics.copies.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    64100 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/basics.creation.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    65763 2025-02-20 10:56:23.000000 ./usr/share/doc/python-numpy/html/user/basics.dispatch.html
│ │ │ │  -rw-r--r--   0 root         (0) root         (0)    18746 2025-02-20 10:56:23.000000 ./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">1.02 ms +- 50.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">2.5 ms +- 23.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.03 ms +- 55.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.5 ms +- 18.1 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">1 ms +- 13 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">1.76 ms +- 16.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">989 us +- 56.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">1.78 ms +- 41.5 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">2.48 ms +- 47.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">4.47 ms +- 18.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.46 ms +- 20.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">4.48 ms +- 24.5 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([0.96793645, 0.5155824 , 0.79586284])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.45851992, 0.87310644, 0.99868124])</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([0.54442155, 0.16678327, 0.72702813], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.76738876, 0.00512075, 0.16780466], 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([151, 231,  41], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([191, 200, 118], 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([0.62945065, 0.90141997])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.6915577 , 0.24935843])</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">[0.62945065 0.90141997 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.6915577  0.24935843 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([[ 1,  3,  2,  3,  0],</span>
│ │ │ │ -<span class="go">       [ 5,  7,  6,  7,  4],</span>
│ │ │ │ -<span class="go">       [ 9, 11, 10, 11,  8]])</span>
│ │ │ │ +<span class="go">array([[ 0,  3,  3,  2,  3],</span>
│ │ │ │ +<span class="go">       [ 4,  7,  7,  6,  7],</span>
│ │ │ │ +<span class="go">       [ 8, 11, 11, 10, 11]])</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [18]: </span><span class="n">rng</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>        <span class="c1"># Shuffle in-place</span>
│ │ │ │  
│ │ │ │  <span class="gp">In [19]: </span><span class="n">a</span>
│ │ │ │  <span class="gh">Out[19]: </span>
│ │ │ │ -<span class="go">array([[ 0,  1,  3,  2],</span>
│ │ │ │ -<span class="go">       [ 4,  5,  7,  6],</span>
│ │ │ │ -<span class="go">       [ 8,  9, 11, 10]])</span>
│ │ │ │ +<span class="go">array([[ 3,  1,  0,  2],</span>
│ │ │ │ +<span class="go">       [ 7,  5,  4,  6],</span>
│ │ │ │ +<span class="go">       [11,  9,  8, 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)
│ │ │ │ │     ...:
│ │ │ │ │ -1.02 ms +- 50.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -2.5 ms +- 23.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.03 ms +- 55.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.5 ms +- 18.1 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)
│ │ │ │ │     ...:
│ │ │ │ │ -1 ms +- 13 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -1.76 ms +- 16.6 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +989 us +- 56.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +1.78 ms +- 41.5 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)
│ │ │ │ │     ...:
│ │ │ │ │ -2.48 ms +- 47.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -4.47 ms +- 18.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +2.46 ms +- 20.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +4.48 ms +- 24.5 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([0.96793645, 0.5155824 , 0.79586284])
│ │ │ │ │ +Out[7]: array([0.45851992, 0.87310644, 0.99868124])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.54442155, 0.16678327, 0.72702813], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.76738876, 0.00512075, 0.16780466], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([151, 231,  41], dtype=uint8)
│ │ │ │ │ +Out[9]: array([191, 200, 118], 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([0.62945065, 0.90141997])
│ │ │ │ │ +Out[12]: array([0.6915577 , 0.24935843])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.62945065 0.90141997 0.         0.        ]
│ │ │ │ │ +[0.6915577  0.24935843 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([[ 1,  3,  2,  3,  0],
│ │ │ │ │ -       [ 5,  7,  6,  7,  4],
│ │ │ │ │ -       [ 9, 11, 10, 11,  8]])
│ │ │ │ │ +array([[ 0,  3,  3,  2,  3],
│ │ │ │ │ +       [ 4,  7,  7,  6,  7],
│ │ │ │ │ +       [ 8, 11, 11, 10, 11]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 0,  1,  3,  2],
│ │ │ │ │ -       [ 4,  5,  7,  6],
│ │ │ │ │ -       [ 8,  9, 11, 10]])
│ │ │ │ │ +array([[ 3,  1,  0,  2],
│ │ │ │ │ +       [ 7,  5,  4,  6],
│ │ │ │ │ +       [11,  9,  8, 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([ 1.12072376, -0.69517923])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([ 1.11858991, -0.107156  ])</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([4.34807771, 5.04325694], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.9264986, 5.0336546], 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([-0.69517923,  1.12072376], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([-0.107156  ,  1.11858991], 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([ 1.12072376, -0.69517923])
│ │ │ │ │ +Out[4]: array([ 1.11858991, -0.107156  ])
│ │ │ │ │  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([4.34807771, 5.04325694], domain=[0., 9.], window=[-1.,
│ │ │ │ │ -1.], symbol='x')
│ │ │ │ │ +Out[6]: Polynomial([4.9264986, 5.0336546], 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([-0.69517923,  1.12072376], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([-0.107156  ,  1.11858991], 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 {}
│ │ │ │ │ @@ -32325,14 +32325,15 @@
│ │ │ │ │          "001j": [1596, 1653, 1710, 1767, 1824, 1879, 1893],
│ │ │ │ │          "002": [1335, 1602, 1659, 1716, 1773, 1830, 1886],
│ │ │ │ │          "0024": 477,
│ │ │ │ │          "003": [2327, 2372, 2419],
│ │ │ │ │          "005": 2188,
│ │ │ │ │          "0050000029": [357, 359],
│ │ │ │ │          "0050045159": [357, 359],
│ │ │ │ │ +        "00512075": 2461,
│ │ │ │ │          "00578369": 1754,
│ │ │ │ │          "00625": 1585,
│ │ │ │ │          "007000999997857": 1541,
│ │ │ │ │          "00867716": [2319, 2363, 2410],
│ │ │ │ │          "00950034": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "009a87ff44bf": 42,
│ │ │ │ │          "00j": [514, 642, 2167],
│ │ │ │ │ @@ -32350,42 +32351,42 @@
│ │ │ │ │          "016j": 2105,
│ │ │ │ │          "01831564": 1660,
│ │ │ │ │          "018318": [2353, 2400, 2450],
│ │ │ │ │          "01j": 514,
│ │ │ │ │          "01t00": [55, 62, 361, 2525],
│ │ │ │ │          "01t08": 2525,
│ │ │ │ │          "01t12": 55,
│ │ │ │ │ -        "02": [54, 55, 147, 162, 163, 410, 547, 566, 669, 1335, 1586, 1601, 1658, 1715, 1772, 1816, 1829, 1885, 2104, 2461],
│ │ │ │ │ +        "02": [54, 55, 147, 162, 163, 410, 547, 566, 669, 1335, 1586, 1601, 1658, 1715, 1772, 1816, 1829, 1885, 2104],
│ │ │ │ │          "020995": 57,
│ │ │ │ │          "02284196": 1697,
│ │ │ │ │          "02294967": 1640,
│ │ │ │ │          "023": 2643,
│ │ │ │ │          "02332573e": 54,
│ │ │ │ │          "0253": 2651,
│ │ │ │ │          "02654825": 1891,
│ │ │ │ │          "02658058e": 2665,
│ │ │ │ │          "02755911": 2665,
│ │ │ │ │          "027559113243068367": 2665,
│ │ │ │ │          "02785049": 1867,
│ │ │ │ │          "02i": [513, 2643],
│ │ │ │ │ -        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2657],
│ │ │ │ │ +        "03": [55, 67, 163, 566, 669, 1335, 1586, 1816, 2461, 2657],
│ │ │ │ │          "03125": [1585, 2491],
│ │ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │ │ +        "0336546": 2488,
│ │ │ │ │          "0361": 2607,
│ │ │ │ │          "03703704": 1809,
│ │ │ │ │          "03943254e": 2104,
│ │ │ │ │          "03968254": [1113, 1543],
│ │ │ │ │          "0396842": 680,
│ │ │ │ │          "03t13": 55,
│ │ │ │ │          "04": [54, 55, 164, 410, 547, 1586, 2463, 2594, 2658],
│ │ │ │ │          "0400": 360,
│ │ │ │ │          "04097352": 2634,
│ │ │ │ │          "04166667": [1544, 1585],
│ │ │ │ │          "04211c6": 2521,
│ │ │ │ │ -        "04325694": 2488,
│ │ │ │ │          "04551152e": 2104,
│ │ │ │ │          "04719755": 1911,
│ │ │ │ │          "05": [55, 91, 163, 410, 548, 669, 896, 1095, 1871, 2083, 2173, 2353, 2400, 2450, 2647],
│ │ │ │ │          "0500": 360,
│ │ │ │ │          "05093587": 2634,
│ │ │ │ │          "05208333": 1585,
│ │ │ │ │          "05263157894736836": 2257,
│ │ │ │ │ @@ -32552,14 +32553,15 @@
│ │ │ │ │          "10624": 2536,
│ │ │ │ │          "10629": 2536,
│ │ │ │ │          "10630": 2536,
│ │ │ │ │          "1066": 370,
│ │ │ │ │          "10674": 2537,
│ │ │ │ │          "1067949133": [420, 947],
│ │ │ │ │          "1071": 2463,
│ │ │ │ │ +        "107156": 2488,
│ │ │ │ │          "10725": 2537,
│ │ │ │ │          "10726": 2537,
│ │ │ │ │          "10727": 2537,
│ │ │ │ │          "10729": 2537,
│ │ │ │ │          "1073741821": [420, 421, 947, 948, 1923],
│ │ │ │ │          "1078": 2622,
│ │ │ │ │          "108": [524, 2463],
│ │ │ │ │ @@ -32649,17 +32651,18 @@
│ │ │ │ │          "11776": 2543,
│ │ │ │ │          "11777": 2543,
│ │ │ │ │          "11779": 2543,
│ │ │ │ │          "11781": 2543,
│ │ │ │ │          "11785": 2543,
│ │ │ │ │          "11786": 2543,
│ │ │ │ │          "1179": 2463,
│ │ │ │ │ -        "118": 2463,
│ │ │ │ │ +        "118": [2461, 2463],
│ │ │ │ │          "1180339887498949": 2115,
│ │ │ │ │          "11803399": 1228,
│ │ │ │ │ +        "11858991": 2488,
│ │ │ │ │          "11885628817151628": 2458,
│ │ │ │ │          "119": 2616,
│ │ │ │ │          "11902": 2544,
│ │ │ │ │          "11981": 2544,
│ │ │ │ │          "11982": 2544,
│ │ │ │ │          "11985": 2541,
│ │ │ │ │          "11986": 2541,
│ │ │ │ │ @@ -32669,15 +32672,14 @@
│ │ │ │ │          "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],
│ │ │ │ │          "120131": [1644, 1656],
│ │ │ │ │          "12065": 2594,
│ │ │ │ │ -        "12072376": 2488,
│ │ │ │ │          "12080": 2545,
│ │ │ │ │          "12083": 2545,
│ │ │ │ │          "12084": 2545,
│ │ │ │ │          "12085": 2545,
│ │ │ │ │          "121": [431, 2463],
│ │ │ │ │          "121393": 28,
│ │ │ │ │          "12150": 2625,
│ │ │ │ │ @@ -32978,15 +32980,15 @@
│ │ │ │ │          "1500000": 2634,
│ │ │ │ │          "15006": 2588,
│ │ │ │ │          "15012": 2560,
│ │ │ │ │          "15028c96": 2667,
│ │ │ │ │          "15038": 2559,
│ │ │ │ │          "15067": 2559,
│ │ │ │ │          "15068": 2560,
│ │ │ │ │ -        "151": [2358, 2405, 2455, 2461, 2463],
│ │ │ │ │ +        "151": [2358, 2405, 2455, 2463],
│ │ │ │ │          "15113": 2560,
│ │ │ │ │          "15118": 2566,
│ │ │ │ │          "15119": 2566,
│ │ │ │ │          "15121": 2572,
│ │ │ │ │          "15158": 2561,
│ │ │ │ │          "15159": 2561,
│ │ │ │ │          "15161": 2561,
│ │ │ │ │ @@ -33127,15 +33129,14 @@
│ │ │ │ │          "16656": 2567,
│ │ │ │ │          "166659832": [850, 1030],
│ │ │ │ │          "16666667": [1526, 1544, 1759, 1871],
│ │ │ │ │          "166670640": [850, 1030],
│ │ │ │ │          "166691080": [850, 1030],
│ │ │ │ │          "16672": 2567,
│ │ │ │ │          "16675": 2572,
│ │ │ │ │ -        "16678327": 2461,
│ │ │ │ │          "16693": 2567,
│ │ │ │ │          "167": 2463,
│ │ │ │ │          "16703": 2567,
│ │ │ │ │          "16705": 2567,
│ │ │ │ │          "16710": 2572,
│ │ │ │ │          "16714": 2567,
│ │ │ │ │          "1672": 2612,
│ │ │ │ │ @@ -33144,14 +33145,15 @@
│ │ │ │ │          "1675": 2612,
│ │ │ │ │          "16768": 2567,
│ │ │ │ │          "16772": 2567,
│ │ │ │ │          "16776": 2567,
│ │ │ │ │          "16779": 2567,
│ │ │ │ │          "1678": 55,
│ │ │ │ │          "16780": 2567,
│ │ │ │ │ +        "16780466": 2461,
│ │ │ │ │          "16784": 2567,
│ │ │ │ │          "16795": 2567,
│ │ │ │ │          "168": 2463,
│ │ │ │ │          "16815": 2572,
│ │ │ │ │          "16830": 2588,
│ │ │ │ │          "16832": 2567,
│ │ │ │ │          "16841": 2572,
│ │ │ │ │ @@ -33366,14 +33368,15 @@
│ │ │ │ │          "19029263503854454": 2348,
│ │ │ │ │          "19031": 2576,
│ │ │ │ │          "19049": 2576,
│ │ │ │ │          "1905": 2612,
│ │ │ │ │          "19062": 2583,
│ │ │ │ │          "1908": [2353, 2400, 2450],
│ │ │ │ │          "19083": 2583,
│ │ │ │ │ +        "191": 2461,
│ │ │ │ │          "19135": 2583,
│ │ │ │ │          "19151": 2583,
│ │ │ │ │          "191614240": 95,
│ │ │ │ │          "1918": 2612,
│ │ │ │ │          "192": [69, 669, 1519, 2463],
│ │ │ │ │          "19211": 2583,
│ │ │ │ │          "192163377": 2098,
│ │ │ │ │ @@ -33511,16 +33514,16 @@
│ │ │ │ │          "1l_0": 1822,
│ │ │ │ │          "1rc1": 577,
│ │ │ │ │          "1st": [36, 74, 642, 2616, 2636, 2640],
│ │ │ │ │          "1th": [661, 2168],
│ │ │ │ │          "1type": 2554,
│ │ │ │ │          "1xn": 2664,
│ │ │ │ │          "2": [0, 1, 2, 4, 5, 9, 12, 13, 14, 19, 20, 24, 25, 26, 29, 30, 31, 32, 34, 36, 37, 38, 43, 47, 48, 52, 53, 54, 55, 56, 58, 59, 60, 61, 62, 65, 66, 68, 69, 70, 72, 73, 74, 75, 76, 79, 86, 88, 89, 90, 95, 96, 97, 98, 99, 101, 102, 103, 104, 106, 107, 108, 109, 110, 111, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 163, 167, 168, 169, 170, 171, 176, 177, 184, 185, 186, 194, 196, 204, 210, 213, 214, 215, 227, 229, 234, 238, 239, 251, 261, 262, 263, 264, 270, 278, 280, 284, 287, 290, 293, 301, 303, 315, 316, 328, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 389, 390, 394, 396, 398, 400, 401, 404, 408, 409, 410, 411, 412, 413, 415, 416, 417, 418, 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│ │ │ │ │ -        "20": [0, 22, 24, 32, 38, 47, 54, 55, 57, 58, 59, 60, 74, 78, 90, 95, 98, 99, 113, 120, 121, 123, 124, 137, 141, 143, 160, 163, 270, 287, 336, 341, 342, 349, 354, 356, 358, 371, 420, 436, 438, 439, 441, 443, 444, 445, 446, 448, 449, 450, 451, 452, 453, 454, 455, 480, 481, 482, 483, 486, 487, 489, 513, 527, 534, 540, 548, 567, 568, 569, 570, 628, 653, 661, 667, 669, 820, 848, 851, 855, 857, 860, 864, 866, 870, 880, 893, 896, 897, 900, 901, 905, 906, 912, 913, 917, 933, 937, 940, 941, 947, 951, 956, 958, 965, 967, 977, 985, 986, 990, 1019, 1024, 1025, 1026, 1031, 1038, 1040, 1044, 1049, 1051, 1056, 1069, 1083, 1088, 1089, 1094, 1097, 1100, 1101, 1106, 1109, 1114, 1117, 1118, 1123, 1124, 1131, 1143, 1145, 1146, 1229, 1241, 1247, 1312, 1324, 1466, 1478, 1482, 1516, 1808, 1867, 1871, 1906, 1986, 1998, 2073, 2089, 2115, 2165, 2168, 2172, 2174, 2203, 2204, 2208, 2223, 2224, 2237, 2238, 2240, 2249, 2252, 2256, 2257, 2270, 2300, 2316, 2319, 2321, 2323, 2328, 2333, 2337, 2338, 2342, 2348, 2361, 2365, 2377, 2380, 2381, 2383, 2388, 2390, 2408, 2412, 2424, 2427, 2428, 2430, 2435, 2438, 2462, 2463, 2470, 2513, 2517, 2519, 2533, 2535, 2542, 2560, 2571, 2576, 2577, 2583, 2584, 2594, 2599, 2602, 2603, 2608, 2622, 2627, 2634, 2636, 2640, 2641, 2644, 2656, 2657, 2665],
│ │ │ │ │ -        "200": [441, 446, 2337, 2339, 2346, 2354, 2357, 2380, 2382, 2392, 2401, 2404, 2427, 2429, 2441, 2451, 2454, 2644, 2647, 2665],
│ │ │ │ │ +        "20": [0, 22, 24, 32, 38, 47, 54, 55, 57, 58, 59, 60, 74, 78, 90, 95, 98, 99, 113, 120, 121, 123, 124, 137, 141, 143, 160, 163, 270, 287, 336, 341, 342, 349, 354, 356, 358, 371, 420, 436, 438, 439, 441, 443, 444, 445, 446, 448, 449, 450, 451, 452, 453, 454, 455, 480, 481, 482, 483, 486, 487, 489, 513, 527, 534, 540, 548, 567, 568, 569, 570, 628, 653, 661, 667, 669, 820, 848, 851, 855, 857, 860, 864, 866, 870, 880, 893, 896, 897, 900, 901, 905, 906, 912, 913, 917, 933, 937, 940, 941, 947, 951, 956, 958, 965, 967, 977, 985, 986, 990, 1019, 1024, 1025, 1026, 1031, 1038, 1040, 1044, 1049, 1051, 1056, 1069, 1083, 1088, 1089, 1094, 1097, 1100, 1101, 1106, 1109, 1114, 1117, 1118, 1123, 1124, 1131, 1143, 1145, 1146, 1229, 1241, 1247, 1312, 1324, 1466, 1478, 1482, 1516, 1808, 1867, 1871, 1906, 1986, 1998, 2073, 2089, 2115, 2165, 2168, 2172, 2174, 2203, 2204, 2208, 2223, 2224, 2237, 2238, 2240, 2249, 2252, 2256, 2257, 2270, 2300, 2316, 2319, 2321, 2323, 2328, 2333, 2337, 2338, 2342, 2348, 2361, 2365, 2377, 2380, 2381, 2383, 2388, 2390, 2408, 2412, 2424, 2427, 2428, 2430, 2435, 2438, 2461, 2462, 2463, 2470, 2513, 2517, 2519, 2533, 2535, 2542, 2560, 2571, 2576, 2577, 2583, 2584, 2594, 2599, 2602, 2603, 2608, 2622, 2627, 2634, 2636, 2640, 2641, 2644, 2656, 2657, 2665],
│ │ │ │ │ +        "200": [441, 446, 2337, 2339, 2346, 2354, 2357, 2380, 2382, 2392, 2401, 2404, 2427, 2429, 2441, 2451, 2454, 2461, 2644, 2647, 2665],
│ │ │ │ │          "2000": [514, 526, 2525, 2613],
│ │ │ │ │          "20000": [2316, 2359, 2361, 2406, 2408, 2456, 2583],
│ │ │ │ │          "2000000": 2634,
│ │ │ │ │          "20000000e": 897,
│ │ │ │ │          "2001": [55, 2322, 2326, 2329, 2330, 2331, 2335, 2339, 2340, 2366, 2371, 2373, 2374, 2375, 2378, 2382, 2383, 2413, 2418, 2420, 2421, 2422, 2425, 2429, 2430],
│ │ │ │ │          "2002": [55, 360, 2316, 2323, 2353, 2361, 2367, 2400, 2408, 2414, 2450],
│ │ │ │ │          "20020": 2588,
│ │ │ │ │ @@ -33893,25 +33896,25 @@
│ │ │ │ │          "22972": 2596,
│ │ │ │ │          "22976": 2596,
│ │ │ │ │          "22982": 2599,
│ │ │ │ │          "22989": 2596,
│ │ │ │ │          "22997": 2599,
│ │ │ │ │          "22998": 2599,
│ │ │ │ │          "22e": 457,
│ │ │ │ │ -        "23": [1, 8, 10, 18, 32, 43, 47, 54, 55, 58, 62, 63, 75, 79, 98, 135, 139, 163, 270, 287, 329, 336, 483, 513, 628, 669, 880, 905, 917, 1029, 1069, 1104, 1229, 1241, 1312, 1324, 1466, 1478, 1545, 1707, 1748, 1777, 1903, 1913, 1986, 1998, 2154, 2208, 2235, 2237, 2256, 2321, 2340, 2342, 2365, 2383, 2412, 2430, 2461, 2513, 2519, 2542, 2552, 2595, 2622, 2627, 2634, 2636, 2640, 2644, 2647, 2656, 2665],
│ │ │ │ │ +        "23": [1, 8, 10, 18, 32, 43, 47, 54, 55, 58, 62, 63, 75, 79, 98, 135, 139, 163, 270, 287, 329, 336, 483, 513, 628, 669, 880, 905, 917, 1029, 1069, 1104, 1229, 1241, 1312, 1324, 1466, 1478, 1545, 1707, 1748, 1777, 1903, 1913, 1986, 1998, 2154, 2208, 2235, 2237, 2256, 2321, 2340, 2342, 2365, 2383, 2412, 2430, 2513, 2519, 2542, 2552, 2595, 2622, 2627, 2634, 2636, 2640, 2644, 2647, 2656, 2665],
│ │ │ │ │          "230": 409,
│ │ │ │ │          "230000071797338e": 477,
│ │ │ │ │          "23011": 2599,
│ │ │ │ │          "23019": 2599,
│ │ │ │ │          "23020": 2599,
│ │ │ │ │          "23030": 2596,
│ │ │ │ │          "23031": 2596,
│ │ │ │ │          "23041": 2599,
│ │ │ │ │          "23060": 2599,
│ │ │ │ │ -        "231": [1212, 2461],
│ │ │ │ │ +        "231": 1212,
│ │ │ │ │          "23105": 2599,
│ │ │ │ │          "2311": [333, 2158],
│ │ │ │ │          "23111996": 1867,
│ │ │ │ │          "23113": 2599,
│ │ │ │ │          "2312": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "23136": 2599,
│ │ │ │ │          "23147": 2596,
│ │ │ │ │ @@ -33988,15 +33991,15 @@
│ │ │ │ │          "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, 2634, 2640, 2644, 2648, 2651, 2656, 2658, 2665, 2667],
│ │ │ │ │ +        "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, 2634, 2640, 2644, 2648, 2651, 2656, 2658, 2665, 2667],
│ │ │ │ │          "240": [57, 363],
│ │ │ │ │          "24011": 2622,
│ │ │ │ │          "24018": 2622,
│ │ │ │ │          "2403": 2615,
│ │ │ │ │          "24036": 2600,
│ │ │ │ │          "24037": 2600,
│ │ │ │ │          "24038": 2600,
│ │ │ │ │ @@ -34160,14 +34163,15 @@
│ │ │ │ │          "24902": 2603,
│ │ │ │ │          "24906": 2603,
│ │ │ │ │          "24911": 2603,
│ │ │ │ │          "24912": 2603,
│ │ │ │ │          "24922": 2622,
│ │ │ │ │          "24929": 2604,
│ │ │ │ │          "24931": 2622,
│ │ │ │ │ +        "24935843": 2461,
│ │ │ │ │          "24940": 2622,
│ │ │ │ │          "24945": 2622,
│ │ │ │ │          "24946": 2622,
│ │ │ │ │          "2495": 2615,
│ │ │ │ │          "24955": 2604,
│ │ │ │ │          "24962": 2604,
│ │ │ │ │          "24971": 2604,
│ │ │ │ │ @@ -34722,15 +34726,14 @@
│ │ │ │ │          "3458": 2615,
│ │ │ │ │          "3471280": 1923,
│ │ │ │ │          "3472": 2615,
│ │ │ │ │          "34732142857143039": [1113, 1543],
│ │ │ │ │          "347845": 2634,
│ │ │ │ │          "34784527": 2634,
│ │ │ │ │          "3480": 2615,
│ │ │ │ │ -        "34807771": 2488,
│ │ │ │ │          "3484692283495345": [648, 653],
│ │ │ │ │          "34889999999999999": [2325, 2369, 2416],
│ │ │ │ │          "34890909": 523,
│ │ │ │ │          "34960421": 680,
│ │ │ │ │          "3497": 2615,
│ │ │ │ │          "35": [409, 489, 669, 870, 1056, 2204, 2325, 2369, 2416, 2572, 2634, 2640, 2656, 2665],
│ │ │ │ │          "350": [544, 635],
│ │ │ │ │ @@ -34922,16 +34925,17 @@
│ │ │ │ │          "4520525295346629": 1228,
│ │ │ │ │          "4532": [409, 661, 2168],
│ │ │ │ │          "4545724517479104": 2460,
│ │ │ │ │          "45560727e": 54,
│ │ │ │ │          "456": 1921,
│ │ │ │ │          "4567": 2643,
│ │ │ │ │          "45674898e": 566,
│ │ │ │ │ +        "45851992": 2461,
│ │ │ │ │          "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,
│ │ │ │ │ @@ -34944,15 +34948,15 @@
│ │ │ │ │          "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, 2461, 2656, 2665],
│ │ │ │ │ +        "47": [52, 2208, 2323, 2367, 2414, 2656, 2665],
│ │ │ │ │          "4702687338396767": 2348,
│ │ │ │ │          "471": [136, 147, 2463],
│ │ │ │ │          "47108547995356098": [2345, 2391, 2439],
│ │ │ │ │          "47140452j": 2491,
│ │ │ │ │          "472": 55,
│ │ │ │ │          "4722": 2618,
│ │ │ │ │          "4723": 2621,
│ │ │ │ │ @@ -35002,15 +35006,15 @@
│ │ │ │ │          "4th": [2322, 2339, 2366, 2382, 2413, 2429, 2640],
│ │ │ │ │          "4x": 2616,
│ │ │ │ │          "4x1": 2636,
│ │ │ │ │          "4x3": [2636, 2640],
│ │ │ │ │          "4x4": [2205, 2209],
│ │ │ │ │          "4x64": 2303,
│ │ │ │ │          "5": [10, 12, 14, 25, 26, 30, 31, 32, 36, 37, 38, 39, 47, 54, 55, 57, 58, 59, 60, 61, 62, 63, 70, 75, 76, 89, 90, 95, 96, 97, 98, 99, 106, 107, 111, 118, 127, 131, 132, 135, 136, 137, 138, 139, 140, 141, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 167, 170, 171, 176, 184, 194, 213, 234, 238, 261, 263, 270, 287, 329, 336, 337, 340, 341, 342, 345, 348, 350, 353, 354, 355, 356, 357, 358, 359, 364, 365, 366, 367, 369, 370, 371, 372, 373, 374, 375, 408, 409, 410, 413, 421, 435, 438, 439, 440, 442, 450, 453, 454, 456, 461, 462, 464, 467, 468, 469, 470, 471, 472, 473, 474, 475, 478, 480, 483, 489, 513, 514, 520, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 538, 539, 540, 542, 543, 544, 549, 553, 560, 562, 565, 566, 567, 569, 570, 573, 574, 575, 608, 619, 628, 636, 638, 640, 642, 644, 645, 651, 652, 653, 654, 658, 659, 660, 661, 664, 665, 666, 667, 668, 669, 676, 677, 678, 679, 680, 814, 822, 825, 830, 831, 834, 844, 855, 856, 858, 860, 863, 864, 865, 870, 875, 877, 880, 881, 883, 886, 887, 888, 893, 896, 903, 904, 906, 907, 911, 912, 913, 914, 917, 919, 924, 926, 929, 932, 937, 943, 944, 948, 950, 952, 953, 956, 957, 963, 964, 966, 967, 968, 969, 976, 992, 996, 1002, 1003, 1006, 1020, 1029, 1038, 1039, 1041, 1044, 1048, 1049, 1050, 1052, 1056, 1060, 1064, 1066, 1069, 1070, 1072, 1076, 1077, 1078, 1083, 1089, 1097, 1099, 1100, 1103, 1105, 1106, 1109, 1110, 1111, 1112, 1113, 1114, 1116, 1119, 1122, 1125, 1127, 1128, 1129, 1133, 1135, 1140, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1154, 1155, 1157, 1159, 1160, 1161, 1162, 1164, 1166, 1167, 1170, 1178, 1191, 1193, 1194, 1195, 1196, 1203, 1204, 1205, 1206, 1207, 1212, 1213, 1223, 1225, 1228, 1229, 1236, 1240, 1241, 1242, 1244, 1245, 1246, 1247, 1248, 1249, 1257, 1265, 1278, 1286, 1290, 1306, 1308, 1312, 1324, 1325, 1326, 1327, 1329, 1331, 1332, 1333, 1341, 1342, 1344, 1346, 1347, 1412, 1420, 1433, 1440, 1444, 1460, 1462, 1466, 1478, 1480, 1483, 1510, 1512, 1515, 1516, 1517, 1518, 1520, 1521, 1522, 1523, 1524, 1527, 1540, 1542, 1543, 1544, 1545, 1557, 1581, 1585, 1586, 1588, 1589, 1591, 1592, 1594, 1596, 1618, 1634, 1637, 1643, 1644, 1645, 1646, 1648, 1653, 1655, 1656, 1661, 1663, 1675, 1702, 1703, 1710, 1732, 1758, 1759, 1760, 1767, 1768, 1770, 1771, 1789, 1805, 1824, 1846, 1869, 1870, 1879, 1881, 1882, 1884, 1886, 1889, 1890, 1891, 1893, 1897, 1899, 1900, 1902, 1904, 1905, 1907, 1908, 1909, 1911, 1912, 1913, 1914, 1915, 1916, 1920, 1922, 1931, 1939, 1953, 1960, 1964, 1980, 1982, 1986, 1998, 1999, 2071, 2074, 2077, 2078, 2079, 2080, 2082, 2083, 2085, 2086, 2087, 2089, 2090, 2091, 2093, 2096, 2097, 2098, 2101, 2103, 2104, 2106, 2108, 2110, 2114, 2115, 2116, 2154, 2162, 2163, 2164, 2168, 2170, 2171, 2173, 2175, 2176, 2178, 2199, 2201, 2202, 2203, 2204, 2205, 2206, 2208, 2209, 2210, 2211, 2212, 2216, 2217, 2223, 2224, 2225, 2236, 2237, 2238, 2239, 2240, 2241, 2242, 2246, 2247, 2248, 2249, 2250, 2256, 2257, 2306, 2314, 2315, 2316, 2319, 2320, 2321, 2322, 2323, 2328, 2331, 2332, 2333, 2334, 2335, 2336, 2339, 2341, 2342, 2343, 2344, 2345, 2347, 2352, 2353, 2358, 2359, 2361, 2363, 2364, 2365, 2366, 2375, 2376, 2377, 2378, 2379, 2382, 2384, 2385, 2386, 2388, 2389, 2390, 2391, 2395, 2399, 2400, 2402, 2405, 2406, 2408, 2410, 2411, 2412, 2413, 2422, 2423, 2424, 2425, 2426, 2429, 2431, 2432, 2433, 2435, 2436, 2438, 2439, 2445, 2449, 2450, 2452, 2455, 2456, 2457, 2458, 2460, 2461, 2463, 2470, 2488, 2491, 2510, 2513, 2518, 2519, 2521, 2522, 2525, 2526, 2527, 2528, 2529, 2531, 2536, 2537, 2541, 2542, 2547, 2549, 2551, 2553, 2554, 2555, 2556, 2557, 2558, 2560, 2561, 2562, 2563, 2564, 2566, 2572, 2576, 2582, 2599, 2600, 2602, 2606, 2607, 2608, 2610, 2613, 2614, 2615, 2616, 2620, 2622, 2625, 2628, 2629, 2630, 2634, 2636, 2637, 2639, 2640, 2641, 2643, 2644, 2645, 2646, 2647, 2648, 2652, 2653, 2654, 2656, 2658, 2663, 2664, 2665],
│ │ │ │ │ -        "50": [50, 59, 60, 61, 63, 439, 453, 454, 514, 544, 567, 652, 667, 674, 675, 680, 1244, 1327, 1344, 1346, 1522, 1906, 1908, 2165, 2171, 2202, 2204, 2226, 2248, 2315, 2324, 2330, 2338, 2340, 2344, 2351, 2356, 2368, 2374, 2381, 2386, 2398, 2403, 2405, 2415, 2421, 2428, 2433, 2448, 2453, 2455, 2461, 2462, 2491, 2599, 2622, 2625, 2640, 2656, 2659, 2665],
│ │ │ │ │ +        "50": [50, 59, 60, 61, 63, 439, 453, 454, 514, 544, 567, 652, 667, 674, 675, 680, 1244, 1327, 1344, 1346, 1522, 1906, 1908, 2165, 2171, 2202, 2204, 2226, 2248, 2315, 2324, 2330, 2338, 2340, 2344, 2351, 2356, 2368, 2374, 2381, 2386, 2398, 2403, 2405, 2415, 2421, 2428, 2433, 2448, 2453, 2455, 2462, 2491, 2599, 2622, 2625, 2640, 2656, 2659, 2665],
│ │ │ │ │          "500": [63, 66, 409, 567, 657, 2238, 2343, 2385, 2432, 2531, 2576, 2607],
│ │ │ │ │          "5000": [652, 2335, 2378, 2425],
│ │ │ │ │          "50000": [652, 2594],
│ │ │ │ │          "5000000000000057e": 674,
│ │ │ │ │          "501": 14,
│ │ │ │ │          "5018": [409, 661, 2168],
│ │ │ │ │          "5027": 2620,
│ │ │ │ │ @@ -35035,15 +35039,14 @@
│ │ │ │ │          "5136": 2620,
│ │ │ │ │          "5138": 2620,
│ │ │ │ │          "514229": 28,
│ │ │ │ │          "5147": 2620,
│ │ │ │ │          "5148": 2620,
│ │ │ │ │          "51506735": 1822,
│ │ │ │ │          "5155": 2621,
│ │ │ │ │ -        "5155824": 2461,
│ │ │ │ │          "5162": [409, 661, 2168],
│ │ │ │ │          "5163": 2620,
│ │ │ │ │          "51640373": 2458,
│ │ │ │ │          "51658839e": 1586,
│ │ │ │ │          "517": 10,
│ │ │ │ │          "5170": 2620,
│ │ │ │ │          "5184": 2620,
│ │ │ │ │ @@ -35084,38 +35087,37 @@
│ │ │ │ │          "54030231j": 2665,
│ │ │ │ │          "541": 2463,
│ │ │ │ │          "54117": 1644,
│ │ │ │ │          "5424": 2621,
│ │ │ │ │          "54323428": [2345, 2391, 2439],
│ │ │ │ │          "54362499": 2634,
│ │ │ │ │          "54402111": 2665,
│ │ │ │ │ -        "54442155": 2461,
│ │ │ │ │          "54545455": 136,
│ │ │ │ │          "54627315": 2634,
│ │ │ │ │          "5470": [2353, 2400, 2450],
│ │ │ │ │          "5481": 2621,
│ │ │ │ │          "5492": 2621,
│ │ │ │ │          "54930614": [106, 131],
│ │ │ │ │          "5493061443340549": [413, 619],
│ │ │ │ │          "54959369": 2665,
│ │ │ │ │          "54999924": 1247,
│ │ │ │ │ -        "55": [28, 59, 60, 73, 893, 1083, 1143, 1525, 1905, 2090, 2204, 2240, 2622, 2656],
│ │ │ │ │ +        "55": [28, 59, 60, 73, 893, 1083, 1143, 1525, 1905, 2090, 2204, 2240, 2461, 2622, 2656],
│ │ │ │ │          "55000000074505806": 1247,
│ │ │ │ │          "5510652": 2634,
│ │ │ │ │          "55111512e": 642,
│ │ │ │ │          "55131477": 1153,
│ │ │ │ │          "5524": 2621,
│ │ │ │ │          "55458479": 349,
│ │ │ │ │          "55490914e": 2665,
│ │ │ │ │          "5555555555555554": 1349,
│ │ │ │ │          "55627469": 349,
│ │ │ │ │          "55645993": 2634,
│ │ │ │ │          "5580": 2535,
│ │ │ │ │          "55914881e": 2104,
│ │ │ │ │ -        "56": [52, 55, 61, 544, 1764, 2204, 2463, 2656, 2658],
│ │ │ │ │ +        "56": [52, 55, 61, 544, 1764, 2204, 2461, 2463, 2656, 2658],
│ │ │ │ │          "5612": 2621,
│ │ │ │ │          "5614": 2522,
│ │ │ │ │          "562": [680, 2658],
│ │ │ │ │          "5620499351813308": 86,
│ │ │ │ │          "5625": 2491,
│ │ │ │ │          "56294995342131": 2083,
│ │ │ │ │          "5640": [2353, 2400, 2450],
│ │ │ │ │ @@ -35190,15 +35192,14 @@
│ │ │ │ │          "623": [2394, 2444],
│ │ │ │ │          "62318272": [2319, 2363, 2410],
│ │ │ │ │          "62341325": 514,
│ │ │ │ │          "62374854": 2665,
│ │ │ │ │          "624": [2300, 2370, 2394, 2417, 2444, 2462],
│ │ │ │ │          "625": [99, 478, 645, 906, 2390, 2438],
│ │ │ │ │          "6273591314603949": [2335, 2378, 2425],
│ │ │ │ │ -        "62945065": 2461,
│ │ │ │ │          "62949953e": 645,
│ │ │ │ │          "63": [58, 514, 669, 1748, 1777, 2336, 2463, 2520, 2566, 2594, 2641, 2656],
│ │ │ │ │          "631198583": 55,
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2166, 2167],
│ │ │ │ │          "63526532": 2458,
│ │ │ │ │          "636363636364": [2353, 2400, 2450],
│ │ │ │ │ @@ -35336,27 +35337,27 @@
│ │ │ │ │          "6843": 2524,
│ │ │ │ │          "68456316": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "68482974": 1153,
│ │ │ │ │          "6884": 2524,
│ │ │ │ │          "68862757": 660,
│ │ │ │ │          "6888893": [2352, 2399, 2449],
│ │ │ │ │          "69": [58, 431, 2656, 2665],
│ │ │ │ │ +        "6915577": 2461,
│ │ │ │ │          "6916": 2524,
│ │ │ │ │          "6922": 2524,
│ │ │ │ │          "6924": 2524,
│ │ │ │ │          "69312169": [1113, 1543],
│ │ │ │ │          "69314718": [76, 657, 2654],
│ │ │ │ │          "69314718055994529": 657,
│ │ │ │ │          "6931471805599453": 2257,
│ │ │ │ │          "6937": 2524,
│ │ │ │ │          "6942": 2524,
│ │ │ │ │          "6943": 2524,
│ │ │ │ │          "6949": 2524,
│ │ │ │ │          "6950": 2524,
│ │ │ │ │ -        "69517923": 2488,
│ │ │ │ │          "6952": 2524,
│ │ │ │ │          "69583040e": [420, 947],
│ │ │ │ │          "69646919": 1153,
│ │ │ │ │          "69736803": [349, 2457, 2638],
│ │ │ │ │          "699": 520,
│ │ │ │ │          "6ad92e5": 13,
│ │ │ │ │          "6e17": 55,
│ │ │ │ │ @@ -35389,15 +35390,14 @@
│ │ │ │ │          "72": [13, 355, 544, 669, 1764, 2463, 2572, 2656, 2658],
│ │ │ │ │          "720": [55, 356, 358, 1897, 2225, 2238, 2576],
│ │ │ │ │          "72075441": 680,
│ │ │ │ │          "721fc64": 13,
│ │ │ │ │          "72375": 1644,
│ │ │ │ │          "72538256": [103, 126],
│ │ │ │ │          "72686684e": 566,
│ │ │ │ │ -        "72702813": 2461,
│ │ │ │ │          "72717132": 2658,
│ │ │ │ │          "72727273": 136,
│ │ │ │ │          "72847407": 1154,
│ │ │ │ │          "729": 2665,
│ │ │ │ │          "72904971": 1153,
│ │ │ │ │          "72949656": 2634,
│ │ │ │ │          "73": [2463, 2656],
│ │ │ │ │ @@ -35433,28 +35433,29 @@
│ │ │ │ │          "7568025": 2665,
│ │ │ │ │          "75682846": 2658,
│ │ │ │ │          "7578": 2526,
│ │ │ │ │          "7590": 2526,
│ │ │ │ │          "75958653": 1911,
│ │ │ │ │          "7597": 2526,
│ │ │ │ │          "75j": 2658,
│ │ │ │ │ -        "76": [541, 1897, 2461, 2463, 2656, 2658],
│ │ │ │ │ +        "76": [541, 1897, 2463, 2656, 2658],
│ │ │ │ │          "7608": 2526,
│ │ │ │ │          "7611397": [349, 2457, 2638],
│ │ │ │ │          "76190476e": 1816,
│ │ │ │ │          "76322758": 1154,
│ │ │ │ │          "7638": 2526,
│ │ │ │ │          "76425276e": 1149,
│ │ │ │ │          "76492172": 349,
│ │ │ │ │          "7654": 2526,
│ │ │ │ │          "7656": 2526,
│ │ │ │ │          "7660": 2526,
│ │ │ │ │          "7665": 2526,
│ │ │ │ │          "7670": 2526,
│ │ │ │ │          "7671": 2526,
│ │ │ │ │ +        "76738876": 2461,
│ │ │ │ │          "7676": 2526,
│ │ │ │ │          "7680": 2526,
│ │ │ │ │          "769893": 2634,
│ │ │ │ │          "76989341": 2634,
│ │ │ │ │          "76991118": 1891,
│ │ │ │ │          "77": [29, 36, 37, 38, 39, 2463, 2634, 2653, 2656],
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│ │ │ │ │ @@ -35471,15 +35472,15 @@
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│ │ │ │ │ -        "78": [2091, 2643, 2656],
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│ │ │ │ │ @@ -35504,15 +35505,14 @@
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│ │ │ │ │ @@ -35592,14 +35592,15 @@
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│ │ │ │ │ @@ -35628,15 +35629,14 @@
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│ │ │ │ │ @@ -35650,14 +35650,15 @@
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│ │ │ │ │ @@ -35699,15 +35700,14 @@
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│ │ │ │ │ @@ -35742,14 +35742,15 @@
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│ │ │ │ │ @@ -35766,14 +35767,15 @@
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│ │ │ │ │ +        "99868124": 2461,
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│ │ │ │ │          "999": [543, 844, 864, 887, 1020, 1049, 1077, 1125, 2535, 2643],
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