--- /srv/reproducible-results/rbuild-debian/r-b-build.7UtKB4TY/b1/numpy_2.2.4+ds-1_arm64.changes
+++ /srv/reproducible-results/rbuild-debian/r-b-build.7UtKB4TY/b2/numpy_2.2.4+ds-1_arm64.changes
├── Files
│ @@ -1,5 +1,5 @@
│  
│ - 5208c9c996c1bf14934e13c1a4714aac 5814136 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│ + abde7a449ceacf7bfa89ea5cf749aa98 5813872 doc optional python-numpy-doc_2.2.4+ds-1_all.deb
│   ed4ae6572e28f8b1dbd938419975210d 14383292 debug optional python3-numpy-dbgsym_2.2.4+ds-1_arm64.deb
│   3a5b3ecec4a4b617987f388521dd977f 136096 python optional python3-numpy-dev_2.2.4+ds-1_arm64.deb
│   eda4b103877c2256a35928417850a972 3604092 python optional python3-numpy_2.2.4+ds-1_arm64.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    64868 2025-04-01 19:45:23.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0  5749076 2025-04-01 19:45:23.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0    64872 2025-04-01 19:45:23.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0  5748808 2025-04-01 19:45:23.000000 data.tar.xz
│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./control
│ │ │ │ @@ -1,13 +1,13 @@
│ │ │ │  Package: python-numpy-doc
│ │ │ │  Source: numpy
│ │ │ │  Version: 1:2.2.4+ds-1
│ │ │ │  Architecture: all
│ │ │ │  Maintainer: Debian Python Team <team+python@tracker.debian.org>
│ │ │ │ -Installed-Size: 100719
│ │ │ │ +Installed-Size: 100718
│ │ │ │  Depends: libjs-sphinxdoc (>= 8.1)
│ │ │ │  Suggests: python-imageio-doc, python-pandas-doc, python-pytest-doc, python-scipy-doc, python-skimage-doc, python3-doc
│ │ │ │  Section: doc
│ │ │ │  Priority: optional
│ │ │ │  Multi-Arch: foreign
│ │ │ │  Homepage: http://www.numpy.org/
│ │ │ │  Description: Python library for numerical computations (Documentation)
│ │ │ ├── ./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
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│ │ │ │  -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)    45068 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)    44923 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)    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)    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)    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)  2687993 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/searchindex.js
│ │ │ │ +-rw-r--r--   0 root         (0) root         (0)  2687990 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
│ │ │ │ @@ -536,35 +536,34 @@
│ │ │ │  <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">The slowest run took 15.74 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ -<span class="go">3.07 ms +- 5.09 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">The slowest run took 12.21 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ -<span class="go">8.77 ms +- 9.45 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">The slowest run took 11.70 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ +<span class="go">2.29 ms +- 3.37 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">The slowest run took 4.29 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ +<span class="go">3.7 ms +- 2.84 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [4]: </span><span class="o">%</span><span class="k">timeit</span> -n 1 rng.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span><span class="o">%</span><span class="k">timeit</span> -n 1 numpy.random.standard_exponential(100000)
│ │ │ │  <span class="gp">   ...: </span>
│ │ │ │ -<span class="go">The slowest run took 9.19 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ -<span class="go">2.15 ms +- 2.82 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">The slowest run took 5.65 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ -<span class="go">4.06 ms +- 3.64 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">817 us +- 38.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">The slowest run took 6.15 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ +<span class="go">3.04 ms +- 3.13 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │  </pre></div>
│ │ │ │  </div>
│ │ │ │  <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="gp">In [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">The slowest run took 4.32 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ -<span class="go">5.92 ms +- 3.99 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ -<span class="go">9.08 ms +- 3.97 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">2.95 ms +- 1.41 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)</span>
│ │ │ │ +<span class="go">The slowest run took 4.57 times longer than the fastest. This could mean that an intermediate result is being cached.</span>
│ │ │ │ +<span class="go">9.72 ms +- 6.98 ms 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
│ │ │ │ @@ -591,21 +590,21 @@
│ │ │ │  <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([0.34194237, 0.91932205, 0.94178031])</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">array([0.94041448, 0.19110624, 0.94988671])</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([0.02471197, 0.9925222 , 0.48664033], dtype=float32)</span>
│ │ │ │ +<span class="gh">Out[8]: </span><span class="go">array([0.7870627 , 0.8089857 , 0.85572165], 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([ 11, 193, 173], dtype=uint8)</span>
│ │ │ │ +<span class="gh">Out[9]: </span><span class="go">array([131,  55, 201], 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>
│ │ │ │ @@ -618,18 +617,18 @@
│ │ │ │  </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([0.28363179, 0.47329423])</span>
│ │ │ │ +<span class="gh">Out[12]: </span><span class="go">array([0.5927328 , 0.86546345])</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">[0.28363179 0.47329423 0.         0.        ]</span>
│ │ │ │ +<span class="go">[0.5927328  0.86546345 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>
│ │ │ │ @@ -641,25 +640,25 @@
│ │ │ │  <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([[ 3,  1,  2,  1,  0],</span>
│ │ │ │ -<span class="go">       [ 7,  5,  6,  5,  4],</span>
│ │ │ │ -<span class="go">       [11,  9, 10,  9,  8]])</span>
│ │ │ │ +<span class="go">array([[ 2,  3,  3,  2,  2],</span>
│ │ │ │ +<span class="go">       [ 6,  7,  7,  6,  6],</span>
│ │ │ │ +<span class="go">       [10, 11, 11, 10, 10]])</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,  3,  2,  0],</span>
│ │ │ │ -<span class="go">       [ 5,  7,  6,  4],</span>
│ │ │ │ -<span class="go">       [ 9, 11, 10,  8]])</span>
│ │ │ │ +<span class="go">array([[ 0,  3,  2,  1],</span>
│ │ │ │ +<span class="go">       [ 4,  7,  6,  5],</span>
│ │ │ │ +<span class="go">       [ 8, 11, 10,  9]])</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 {}
│ │ │ │ │ @@ -102,36 +102,34 @@
│ │ │ │ │  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)
│ │ │ │ │     ...:
│ │ │ │ │ -The slowest run took 15.74 times longer than the fastest. This could mean that
│ │ │ │ │ +The slowest run took 11.70 times longer than the fastest. This could mean that
│ │ │ │ │  an intermediate result is being cached.
│ │ │ │ │ -3.07 ms +- 5.09 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -The slowest run took 12.21 times longer than the fastest. This could mean that
│ │ │ │ │ +2.29 ms +- 3.37 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +The slowest run took 4.29 times longer than the fastest. This could mean that
│ │ │ │ │  an intermediate result is being cached.
│ │ │ │ │ -8.77 ms +- 9.45 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +3.7 ms +- 2.84 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │  In [4]: %timeit -n 1 rng.standard_exponential(100000)
│ │ │ │ │     ...: %timeit -n 1 numpy.random.standard_exponential(100000)
│ │ │ │ │     ...:
│ │ │ │ │ -The slowest run took 9.19 times longer than the fastest. This could mean that
│ │ │ │ │ +817 us +- 38.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +The slowest run took 6.15 times longer than the fastest. This could mean that
│ │ │ │ │  an intermediate result is being cached.
│ │ │ │ │ -2.15 ms +- 2.82 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -The slowest run took 5.65 times longer than the fastest. This could mean that
│ │ │ │ │ -an intermediate result is being cached.
│ │ │ │ │ -4.06 ms +- 3.64 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +3.04 ms +- 3.13 ms 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)
│ │ │ │ │     ...:
│ │ │ │ │ -The slowest run took 4.32 times longer than the fastest. This could mean that
│ │ │ │ │ +2.95 ms +- 1.41 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +The slowest run took 4.57 times longer than the fastest. This could mean that
│ │ │ │ │  an intermediate result is being cached.
│ │ │ │ │ -5.92 ms +- 3.99 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ -9.08 ms +- 3.97 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ │ +9.72 ms +- 6.98 ms 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
│ │ │ │ │ @@ -150,38 +148,38 @@
│ │ │ │ │            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([0.34194237, 0.91932205, 0.94178031])
│ │ │ │ │ +Out[7]: array([0.94041448, 0.19110624, 0.94988671])
│ │ │ │ │  
│ │ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ │ -Out[8]: array([0.02471197, 0.9925222 , 0.48664033], dtype=float32)
│ │ │ │ │ +Out[8]: array([0.7870627 , 0.8089857 , 0.85572165], dtype=float32)
│ │ │ │ │  
│ │ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ │ -Out[9]: array([ 11, 193, 173], dtype=uint8)
│ │ │ │ │ +Out[9]: array([131,  55, 201], 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([0.28363179, 0.47329423])
│ │ │ │ │ +Out[12]: array([0.5927328 , 0.86546345])
│ │ │ │ │  
│ │ │ │ │  In [13]: print(existing)
│ │ │ │ │ -[0.28363179 0.47329423 0.         0.        ]
│ │ │ │ │ +[0.5927328  0.86546345 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))
│ │ │ │ │  
│ │ │ │ │ @@ -189,25 +187,25 @@
│ │ │ │ │  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([[ 3,  1,  2,  1,  0],
│ │ │ │ │ -       [ 7,  5,  6,  5,  4],
│ │ │ │ │ -       [11,  9, 10,  9,  8]])
│ │ │ │ │ +array([[ 2,  3,  3,  2,  2],
│ │ │ │ │ +       [ 6,  7,  7,  6,  6],
│ │ │ │ │ +       [10, 11, 11, 10, 10]])
│ │ │ │ │  
│ │ │ │ │  In [18]: rng.shuffle(a, axis=1)        # Shuffle in-place
│ │ │ │ │  
│ │ │ │ │  In [19]: a
│ │ │ │ │  Out[19]:
│ │ │ │ │ -array([[ 1,  3,  2,  0],
│ │ │ │ │ -       [ 5,  7,  6,  4],
│ │ │ │ │ -       [ 9, 11, 10,  8]])
│ │ │ │ │ +array([[ 0,  3,  2,  1],
│ │ │ │ │ +       [ 4,  7,  6,  5],
│ │ │ │ │ +       [ 8, 11, 10,  9]])
│ │ │ │ │      * 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([ 1.07557467, -0.16889551])</span>
│ │ │ │ +<span class="gh">Out[4]: </span><span class="go">array([0.92122459, 0.40715967])</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([4.67119052, 4.84008604], domain=[0., 9.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[6]: </span><span class="go">Polynomial([4.55267033, 4.14551067], 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([-0.16889551,  1.07557467], domain=[-1.,  1.], window=[-1.,  1.], symbol=&#39;x&#39;)</span>
│ │ │ │ +<span class="gh">Out[7]: </span><span class="go">Polynomial([0.40715967, 0.92122459], 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([ 1.07557467, -0.16889551])
│ │ │ │ │ +Out[4]: array([0.92122459, 0.40715967])
│ │ │ │ │  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([4.67119052, 4.84008604], domain=[0., 9.], window=[-1.,
│ │ │ │ │ +Out[6]: Polynomial([4.55267033, 4.14551067], 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([-0.16889551,  1.07557467], domain=[-1.,  1.], window=[-1.,
│ │ │ │ │ +Out[7]: Polynomial([0.40715967, 0.92122459], 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 {}
│ │ │ │ │ @@ -32361,15 +32361,14 @@
│ │ │ │ │          "01t12": 55,
│ │ │ │ │          "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": 2644,
│ │ │ │ │          "02332573e": 54,
│ │ │ │ │ -        "02471197": 2461,
│ │ │ │ │          "0253": 2652,
│ │ │ │ │          "02654825": 1891,
│ │ │ │ │          "02658058e": 2666,
│ │ │ │ │          "02755911": 2666,
│ │ │ │ │          "027559113243068367": 2666,
│ │ │ │ │          "02785049": 1867,
│ │ │ │ │          "02i": [513, 2644],
│ │ │ │ │ @@ -32378,56 +32377,55 @@
│ │ │ │ │          "0326911": [2335, 2378, 2425],
│ │ │ │ │          "0361": 2607,
│ │ │ │ │          "03703704": 1809,
│ │ │ │ │          "03943254e": 2104,
│ │ │ │ │          "03968254": [1113, 1543],
│ │ │ │ │          "0396842": 680,
│ │ │ │ │          "03t13": 55,
│ │ │ │ │ -        "04": [54, 55, 164, 410, 547, 1586, 2463, 2594, 2659],
│ │ │ │ │ +        "04": [54, 55, 164, 410, 547, 1586, 2461, 2463, 2594, 2659],
│ │ │ │ │          "0400": 360,
│ │ │ │ │          "04097352": 2635,
│ │ │ │ │          "04166667": [1544, 1585],
│ │ │ │ │          "04211c6": 2521,
│ │ │ │ │          "04551152e": 2104,
│ │ │ │ │          "04719755": 1911,
│ │ │ │ │          "05": [55, 91, 163, 410, 548, 669, 896, 1095, 1871, 2083, 2173, 2353, 2400, 2450, 2648],
│ │ │ │ │          "0500": 360,
│ │ │ │ │          "05093587": 2635,
│ │ │ │ │          "05208333": 1585,
│ │ │ │ │          "05263157894736836": 2257,
│ │ │ │ │          "0549999999999997": 2083,
│ │ │ │ │          "055": 2083,
│ │ │ │ │          "0596779": 1153,
│ │ │ │ │ -        "06": [55, 566, 2083, 2461, 2508],
│ │ │ │ │ +        "06": [55, 566, 2083, 2508],
│ │ │ │ │          "0614962j": [439, 453],
│ │ │ │ │          "0625": [418, 624, 1645],
│ │ │ │ │          "06369197489564249": 2458,
│ │ │ │ │          "06381726": 349,
│ │ │ │ │          "0660": [302, 2131],
│ │ │ │ │          "06959433e": [420, 947],
│ │ │ │ │ -        "07": [55, 164, 547, 896, 897, 1335, 2170, 2461, 2508],
│ │ │ │ │ +        "07": [55, 164, 547, 896, 897, 1335, 2170, 2508],
│ │ │ │ │          "07106781e": 514,
│ │ │ │ │          "07407407": 1809,
│ │ │ │ │ -        "07557467": 2488,
│ │ │ │ │          "07779185": 2458,
│ │ │ │ │          "07937323": 524,
│ │ │ │ │          "07944154": [657, 2655],
│ │ │ │ │ -        "08": [55, 91, 147, 410, 523, 548, 896, 1095, 2322, 2366, 2413, 2461, 2525, 2659],
│ │ │ │ │ +        "08": [55, 91, 147, 410, 523, 548, 896, 1095, 2322, 2366, 2413, 2525, 2659],
│ │ │ │ │          "0800": 2525,
│ │ │ │ │          "08187135": 54,
│ │ │ │ │          "08333333": [1645, 1871],
│ │ │ │ │          "08405657": 1867,
│ │ │ │ │          "0855": 2642,
│ │ │ │ │          "08553692": 38,
│ │ │ │ │          "085537": 2642,
│ │ │ │ │          "0856306": 1154,
│ │ │ │ │          "08618131": 1526,
│ │ │ │ │          "08703704": [1113, 1543],
│ │ │ │ │          "087300000000000003": [2346, 2392, 2441],
│ │ │ │ │ -        "09": [55, 2171, 2323, 2367, 2414, 2461],
│ │ │ │ │ +        "09": [55, 2171, 2323, 2367, 2414],
│ │ │ │ │          "090097550553843": 2642,
│ │ │ │ │          "09417735": [349, 2457, 2639],
│ │ │ │ │          "0943951": 1911,
│ │ │ │ │          "09640474436813": 675,
│ │ │ │ │          "09861229": [657, 2655],
│ │ │ │ │          "0999755859375": 62,
│ │ │ │ │          "099975586": 62,
│ │ │ │ │ @@ -32750,15 +32748,15 @@
│ │ │ │ │          "1300000": 2635,
│ │ │ │ │          "13020": 2549,
│ │ │ │ │          "13026": 2549,
│ │ │ │ │          "13028": 2549,
│ │ │ │ │          "13038": 2549,
│ │ │ │ │          "13041": 2549,
│ │ │ │ │          "13090": [186, 827, 999, 1172, 1259, 1414, 1933],
│ │ │ │ │ -        "131": [527, 2463],
│ │ │ │ │ +        "131": [527, 2461, 2463],
│ │ │ │ │          "1312": 485,
│ │ │ │ │          "13182611e": [420, 947],
│ │ │ │ │          "132": [527, 2330, 2374, 2421, 2463, 2637],
│ │ │ │ │          "1324274851176597e": 1867,
│ │ │ │ │          "133": [527, 2330, 2374, 2421],
│ │ │ │ │          "13392": 2551,
│ │ │ │ │          "13394": 2551,
│ │ │ │ │ @@ -32917,14 +32915,15 @@
│ │ │ │ │          "14510": 2560,
│ │ │ │ │          "14512": 2557,
│ │ │ │ │          "14513": 2557,
│ │ │ │ │          "14515": 2557,
│ │ │ │ │          "14518": 2560,
│ │ │ │ │          "14519": 2557,
│ │ │ │ │          "14527": 2560,
│ │ │ │ │ +        "14551067": 2488,
│ │ │ │ │          "14557": 2557,
│ │ │ │ │          "14563": 2557,
│ │ │ │ │          "14567": 2560,
│ │ │ │ │          "14578": 2557,
│ │ │ │ │          "14583": 2560,
│ │ │ │ │          "14593": 2559,
│ │ │ │ │          "14596": 2560,
│ │ │ │ │ @@ -33157,15 +33156,14 @@
│ │ │ │ │          "168": 2463,
│ │ │ │ │          "16815": 2572,
│ │ │ │ │          "16830": 2588,
│ │ │ │ │          "16832": 2567,
│ │ │ │ │          "16841": 2572,
│ │ │ │ │          "16872": 2567,
│ │ │ │ │          "16875": 2567,
│ │ │ │ │ -        "16889551": 2488,
│ │ │ │ │          "16904": 2567,
│ │ │ │ │          "16905": 2567,
│ │ │ │ │          "16906": 2567,
│ │ │ │ │          "16916": 2567,
│ │ │ │ │          "16922": 2567,
│ │ │ │ │          "16938": 2572,
│ │ │ │ │          "16959": 2568,
│ │ │ │ │ @@ -33200,15 +33198,15 @@
│ │ │ │ │          "17244": 2568,
│ │ │ │ │          "17245": 2568,
│ │ │ │ │          "17269252e": [421, 948],
│ │ │ │ │          "17272": 2568,
│ │ │ │ │          "17284": 2572,
│ │ │ │ │          "17296777": 2635,
│ │ │ │ │          "17298": 2569,
│ │ │ │ │ -        "173": [669, 2461, 2637],
│ │ │ │ │ +        "173": [669, 2637],
│ │ │ │ │          "17336": 2569,
│ │ │ │ │          "17344": 2572,
│ │ │ │ │          "17394": 2572,
│ │ │ │ │          "174": 2463,
│ │ │ │ │          "17446": 2569,
│ │ │ │ │          "17450": 2569,
│ │ │ │ │          "17456": 2572,
│ │ │ │ │ @@ -33371,26 +33369,27 @@
│ │ │ │ │          "19029263503854454": 2348,
│ │ │ │ │          "19031": 2576,
│ │ │ │ │          "19049": 2576,
│ │ │ │ │          "1905": 2612,
│ │ │ │ │          "19062": 2583,
│ │ │ │ │          "1908": [2353, 2400, 2450],
│ │ │ │ │          "19083": 2583,
│ │ │ │ │ +        "19110624": 2461,
│ │ │ │ │          "19135": 2583,
│ │ │ │ │          "19151": 2583,
│ │ │ │ │          "191614240": 95,
│ │ │ │ │          "1918": 2612,
│ │ │ │ │          "192": [69, 669, 1519, 2463],
│ │ │ │ │          "19211": 2583,
│ │ │ │ │          "192163377": 2098,
│ │ │ │ │          "19226": 2588,
│ │ │ │ │          "1923875335537315": [2352, 2389, 2399, 2436, 2449],
│ │ │ │ │          "19249760": [420, 947],
│ │ │ │ │          "19259": 2583,
│ │ │ │ │ -        "193": [2461, 2463, 2637],
│ │ │ │ │ +        "193": [2463, 2637],
│ │ │ │ │          "19311": 2577,
│ │ │ │ │          "1932": [2359, 2406, 2456],
│ │ │ │ │          "19324": 2577,
│ │ │ │ │          "19330": 2577,
│ │ │ │ │          "19342": 2577,
│ │ │ │ │          "19343": 2577,
│ │ │ │ │          "19347": 2577,
│ │ │ │ │ @@ -33542,15 +33541,15 @@
│ │ │ │ │          "20080": 2579,
│ │ │ │ │          "20080221202153": 2490,
│ │ │ │ │          "20081": 2579,
│ │ │ │ │          "20082": 2579,
│ │ │ │ │          "2009": 55,
│ │ │ │ │          "20090423014010": [2357, 2404, 2454],
│ │ │ │ │          "20090514091424": [2346, 2392, 2441],
│ │ │ │ │ -        "201": [2103, 2666],
│ │ │ │ │ +        "201": [2103, 2461, 2666],
│ │ │ │ │          "2010": [55, 67, 361, 2531],
│ │ │ │ │          "20100312": 67,
│ │ │ │ │          "20100814160313": 2609,
│ │ │ │ │          "20100817112505": 2609,
│ │ │ │ │          "20106": 2579,
│ │ │ │ │          "2011": [40, 55, 162, 163, 164, 547, 2303],
│ │ │ │ │          "2012": [55, 162, 163],
│ │ │ │ │ @@ -33667,15 +33666,15 @@
│ │ │ │ │          "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, 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],
│ │ │ │ │ +        "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],
│ │ │ │ │          "210": 363,
│ │ │ │ │          "21001": 2588,
│ │ │ │ │          "21029": 2588,
│ │ │ │ │          "210306068529402873165736369884012333109": [2275, 2280],
│ │ │ │ │          "21048": 2586,
│ │ │ │ │          "211": 2491,
│ │ │ │ │          "21106": 2586,
│ │ │ │ │ @@ -34566,15 +34565,14 @@
│ │ │ │ │          "28305": 2632,
│ │ │ │ │          "283185307179586": 2238,
│ │ │ │ │          "28318531": [1891, 2238],
│ │ │ │ │          "28321": 2632,
│ │ │ │ │          "28324": 2632,
│ │ │ │ │          "28333": 2633,
│ │ │ │ │          "28348": 2633,
│ │ │ │ │ -        "28363179": 2461,
│ │ │ │ │          "28377": 2633,
│ │ │ │ │          "28379": 2633,
│ │ │ │ │          "28385": 2633,
│ │ │ │ │          "28420": 2633,
│ │ │ │ │          "28422": 2633,
│ │ │ │ │          "28423": 2633,
│ │ │ │ │          "28424": 2633,
│ │ │ │ │ @@ -34599,15 +34597,15 @@
│ │ │ │ │          "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, 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, 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],
│ │ │ │ │          "290": 2300,
│ │ │ │ │          "29001ed": 13,
│ │ │ │ │          "290301": 55,
│ │ │ │ │          "292": 55,
│ │ │ │ │          "29229249": 524,
│ │ │ │ │          "29239766": 54,
│ │ │ │ │          "2925464970228": 657,
│ │ │ │ │ @@ -34703,15 +34701,15 @@
│ │ │ │ │          "3173": 2617,
│ │ │ │ │          "3175": 2617,
│ │ │ │ │          "317811": 28,
│ │ │ │ │          "317j": [411, 617],
│ │ │ │ │          "318": 1526,
│ │ │ │ │          "3192": 2615,
│ │ │ │ │          "31962608": [196, 836, 1008, 1179, 1266, 1421, 1940],
│ │ │ │ │ -        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 137, 144, 215, 270, 336, 390, 434, 514, 584, 661, 880, 893, 1027, 1069, 1083, 1143, 1198, 1229, 1249, 1281, 1312, 1345, 1348, 1435, 1466, 1519, 1884, 1886, 1902, 1955, 1986, 2076, 2091, 2168, 2204, 2208, 2225, 2240, 2261, 2262, 2268, 2269, 2272, 2273, 2274, 2277, 2278, 2279, 2282, 2283, 2284, 2287, 2288, 2299, 2300, 2301, 2302, 2303, 2304, 2314, 2331, 2375, 2422, 2458, 2459, 2460, 2461, 2462, 2508, 2513, 2520, 2521, 2522, 2535, 2543, 2544, 2545, 2546, 2547, 2557, 2562, 2564, 2572, 2574, 2579, 2582, 2587, 2588, 2599, 2602, 2606, 2607, 2617, 2622, 2633, 2637, 2639, 2641, 2645, 2646, 2648, 2649, 2652, 2657, 2658, 2659, 2666],
│ │ │ │ │ +        "32": [1, 13, 21, 50, 54, 55, 56, 59, 61, 62, 63, 65, 69, 74, 137, 144, 215, 270, 336, 390, 434, 514, 584, 661, 880, 893, 1027, 1069, 1083, 1143, 1198, 1229, 1249, 1281, 1312, 1345, 1348, 1435, 1466, 1519, 1884, 1886, 1902, 1955, 1986, 2076, 2091, 2168, 2204, 2208, 2225, 2240, 2261, 2262, 2268, 2269, 2272, 2273, 2274, 2277, 2278, 2279, 2282, 2283, 2284, 2287, 2288, 2299, 2300, 2301, 2302, 2303, 2304, 2314, 2331, 2375, 2422, 2458, 2459, 2460, 2462, 2508, 2513, 2520, 2521, 2522, 2535, 2543, 2544, 2545, 2546, 2547, 2557, 2562, 2564, 2572, 2574, 2579, 2582, 2587, 2588, 2599, 2602, 2606, 2607, 2617, 2622, 2633, 2637, 2639, 2641, 2645, 2646, 2648, 2649, 2652, 2657, 2658, 2659, 2666],
│ │ │ │ │          "320": 1149,
│ │ │ │ │          "32000": 2094,
│ │ │ │ │          "32119158": 1867,
│ │ │ │ │          "323": [260, 421, 948, 1059, 1222, 1305, 1350, 1459, 1579, 1590, 1604, 1605, 1639, 1649, 1661, 1662, 1696, 1706, 1718, 1719, 1753, 1763, 1775, 1776, 1810, 1820, 1832, 1833, 1866, 1875, 1887, 1888, 1979, 2312],
│ │ │ │ │          "3263": 2617,
│ │ │ │ │          "32767": 535,
│ │ │ │ │          "32768": 535,
│ │ │ │ │ @@ -34740,15 +34738,14 @@
│ │ │ │ │          "3361": [99, 906],
│ │ │ │ │          "3364": 2615,
│ │ │ │ │          "3373": 2615,
│ │ │ │ │          "33872321e": 2104,
│ │ │ │ │          "34": [12, 28, 144, 441, 1880, 1919, 2208, 2463, 2491, 2566, 2583, 2641, 2657, 2666],
│ │ │ │ │          "340": [2238, 2576],
│ │ │ │ │          "34132519": [680, 2659],
│ │ │ │ │ -        "34194237": 2461,
│ │ │ │ │          "3421": 2615,
│ │ │ │ │          "343": 2666,
│ │ │ │ │          "34317802": 1153,
│ │ │ │ │          "34376245": 2635,
│ │ │ │ │          "3456": 13,
│ │ │ │ │          "3458": 2615,
│ │ │ │ │          "3471280": 1923,
│ │ │ │ │ @@ -34778,29 +34775,29 @@
│ │ │ │ │          "3628523": 2458,
│ │ │ │ │          "36363636": 136,
│ │ │ │ │          "3644j": [415, 621],
│ │ │ │ │          "365": [544, 1344, 1346, 1522, 1908],
│ │ │ │ │          "366": 55,
│ │ │ │ │          "36674": 2098,
│ │ │ │ │          "36787944": [1660, 1774],
│ │ │ │ │ -        "37": [59, 60, 136, 1913, 2083, 2204, 2236, 2463, 2641, 2657, 2666],
│ │ │ │ │ +        "37": [59, 60, 136, 1913, 2083, 2204, 2236, 2461, 2463, 2641, 2657, 2666],
│ │ │ │ │          "370": 652,
│ │ │ │ │          "3701": 2615,
│ │ │ │ │          "37079802": [349, 2639],
│ │ │ │ │          "3712": 2615,
│ │ │ │ │          "3728": 2615,
│ │ │ │ │          "3728973198": 2594,
│ │ │ │ │          "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],
│ │ │ │ │ @@ -34850,21 +34847,22 @@
│ │ │ │ │          "40077": [1644, 1656],
│ │ │ │ │          "400e": 2658,
│ │ │ │ │          "4018": [2615, 2617],
│ │ │ │ │          "4024": 2617,
│ │ │ │ │          "4027": 2617,
│ │ │ │ │          "40274501": 1154,
│ │ │ │ │          "4051": [2615, 2617],
│ │ │ │ │ +        "40715967": 2488,
│ │ │ │ │          "409": 2463,
│ │ │ │ │          "40918587e": 2104,
│ │ │ │ │          "40919914": 2666,
│ │ │ │ │          "4093": 2617,
│ │ │ │ │          "4094": [2615, 2617],
│ │ │ │ │          "4096": [72, 2092],
│ │ │ │ │ -        "41": [941, 1114, 1123, 1124, 1131, 1913, 2104, 2107, 2208, 2236, 2585, 2657, 2666],
│ │ │ │ │ +        "41": [941, 1114, 1123, 1124, 1131, 1913, 2104, 2107, 2208, 2236, 2461, 2585, 2657, 2666],
│ │ │ │ │          "4109": 2617,
│ │ │ │ │          "41211849": 2666,
│ │ │ │ │          "4123": [2615, 2617],
│ │ │ │ │          "4134": 2617,
│ │ │ │ │          "41357986e": 2175,
│ │ │ │ │          "4138": 2617,
│ │ │ │ │          "4141": 2615,
│ │ │ │ │ @@ -34939,15 +34937,15 @@
│ │ │ │ │          "4476": 2621,
│ │ │ │ │          "4483": 2617,
│ │ │ │ │          "4485": 2617,
│ │ │ │ │          "4486": 2617,
│ │ │ │ │          "449294e": 2170,
│ │ │ │ │          "44948974": 2659,
│ │ │ │ │          "44999999925494177": 2115,
│ │ │ │ │ -        "45": [12, 18, 38, 58, 94, 105, 130, 339, 666, 851, 866, 944, 1025, 1026, 1031, 1051, 1212, 1882, 1886, 2103, 2204, 2461, 2637, 2644, 2657, 2666],
│ │ │ │ │ +        "45": [12, 18, 38, 58, 94, 105, 130, 339, 666, 851, 866, 944, 1025, 1026, 1031, 1051, 1212, 1882, 1886, 2103, 2204, 2637, 2644, 2657, 2666],
│ │ │ │ │          "450": 55,
│ │ │ │ │          "45000005": 2115,
│ │ │ │ │          "45038594": [349, 2639],
│ │ │ │ │          "45053314": 2635,
│ │ │ │ │          "4511316": 2666,
│ │ │ │ │          "4520525295346629": 1228,
│ │ │ │ │          "4532": [409, 661, 2168],
│ │ │ │ │ @@ -34983,15 +34981,14 @@
│ │ │ │ │          "471": [136, 147, 2463],
│ │ │ │ │          "47108547995356098": [2345, 2391, 2439],
│ │ │ │ │          "47140452j": 2491,
│ │ │ │ │          "472": 55,
│ │ │ │ │          "4722": 2618,
│ │ │ │ │          "4723": 2621,
│ │ │ │ │          "4730": [409, 661, 2168],
│ │ │ │ │ -        "47329423": 2461,
│ │ │ │ │          "4733": 2618,
│ │ │ │ │          "47458546": 349,
│ │ │ │ │          "47536961": 349,
│ │ │ │ │          "47613949": [2335, 2378, 2425],
│ │ │ │ │          "4774": 2618,
│ │ │ │ │          "479": 2620,
│ │ │ │ │          "4796": [409, 661, 2168],
│ │ │ │ │ @@ -35002,15 +34999,14 @@
│ │ │ │ │          "4809319": 1153,
│ │ │ │ │          "4816": [99, 906],
│ │ │ │ │          "48219694e": [421, 948],
│ │ │ │ │          "4836": 2618,
│ │ │ │ │          "484": [2517, 2583, 2625],
│ │ │ │ │          "4853": 2618,
│ │ │ │ │          "4861946401452": 2334,
│ │ │ │ │ -        "48664033": 2461,
│ │ │ │ │          "4874": [409, 661, 2168],
│ │ │ │ │          "4882": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │          "4896": 2620,
│ │ │ │ │          "49": [71, 2208, 2323, 2367, 2414, 2567, 2568, 2641, 2657, 2666],
│ │ │ │ │          "4928": [409, 661, 2168],
│ │ │ │ │          "49293": 1644,
│ │ │ │ │          "49313049": [2387, 2434],
│ │ │ │ │ @@ -35124,20 +35120,21 @@
│ │ │ │ │          "5470": [2353, 2400, 2450],
│ │ │ │ │          "5481": 2621,
│ │ │ │ │          "5492": 2621,
│ │ │ │ │          "54930614": [106, 131],
│ │ │ │ │          "5493061443340549": [413, 619],
│ │ │ │ │          "54959369": 2666,
│ │ │ │ │          "54999924": 1247,
│ │ │ │ │ -        "55": [28, 59, 60, 73, 893, 1083, 1143, 1525, 1905, 2090, 2204, 2240, 2622, 2657],
│ │ │ │ │ +        "55": [28, 59, 60, 73, 893, 1083, 1143, 1525, 1905, 2090, 2204, 2240, 2461, 2622, 2657],
│ │ │ │ │          "55000000074505806": 1247,
│ │ │ │ │          "5510652": 2635,
│ │ │ │ │          "55111512e": 642,
│ │ │ │ │          "55131477": 1153,
│ │ │ │ │          "5524": 2621,
│ │ │ │ │ +        "55267033": 2488,
│ │ │ │ │          "55458479": 349,
│ │ │ │ │          "55490914e": 2666,
│ │ │ │ │          "5555555555555554": 1349,
│ │ │ │ │          "55627469": 349,
│ │ │ │ │          "55645993": 2635,
│ │ │ │ │          "5580": 2535,
│ │ │ │ │          "55914881e": 2104,
│ │ │ │ │ @@ -35148,15 +35145,15 @@
│ │ │ │ │          "5620499351813308": 86,
│ │ │ │ │          "5625": 2491,
│ │ │ │ │          "56294995342131": 2083,
│ │ │ │ │          "5640": [2353, 2400, 2450],
│ │ │ │ │          "567": 2644,
│ │ │ │ │          "56826729e": 2104,
│ │ │ │ │          "56917101": 2635,
│ │ │ │ │ -        "57": [58, 669, 2204, 2322, 2366, 2413, 2463, 2491, 2637, 2657],
│ │ │ │ │ +        "57": [58, 669, 2204, 2322, 2366, 2413, 2461, 2463, 2491, 2637, 2657],
│ │ │ │ │          "5707963267948966": [102, 125],
│ │ │ │ │          "57079633": [94, 105, 130, 1911, 2238, 2666],
│ │ │ │ │          "5708": [412, 618],
│ │ │ │ │          "57115742": 524,
│ │ │ │ │          "57136612e": 2173,
│ │ │ │ │          "57510612": 660,
│ │ │ │ │          "576": 2615,
│ │ │ │ │ @@ -35171,14 +35168,15 @@
│ │ │ │ │          "58289208": 2635,
│ │ │ │ │          "584388": 55,
│ │ │ │ │          "585": [378, 1358, 1514, 2583],
│ │ │ │ │          "58578644": 1756,
│ │ │ │ │          "58826587": 349,
│ │ │ │ │          "59": [55, 2208, 2602, 2657],
│ │ │ │ │          "5910": [287, 1241, 1324, 1478, 1998],
│ │ │ │ │ +        "5927328": 2461,
│ │ │ │ │          "595726": 2635,
│ │ │ │ │          "59572603": 2635,
│ │ │ │ │          "5969": [99, 906],
│ │ │ │ │          "598150": 2642,
│ │ │ │ │          "59815003": 38,
│ │ │ │ │          "5982": 2642,
│ │ │ │ │          "59903635e": 147,
│ │ │ │ │ @@ -35230,15 +35228,15 @@
│ │ │ │ │          "631198588": 55,
│ │ │ │ │          "63317787e": [2166, 2167],
│ │ │ │ │          "63526532": 2458,
│ │ │ │ │          "636363636364": [2353, 2400, 2450],
│ │ │ │ │          "63696169": 2635,
│ │ │ │ │          "6376": 2522,
│ │ │ │ │          "6390": [2353, 2400, 2450],
│ │ │ │ │ -        "64": [1, 5, 13, 21, 30, 50, 55, 56, 59, 61, 62, 63, 65, 66, 69, 74, 79, 315, 339, 409, 457, 470, 514, 584, 660, 669, 944, 1345, 1348, 1519, 1899, 1900, 2076, 2083, 2143, 2261, 2262, 2264, 2268, 2269, 2273, 2274, 2278, 2279, 2283, 2284, 2287, 2288, 2299, 2300, 2303, 2304, 2314, 2328, 2458, 2461, 2462, 2464, 2513, 2520, 2542, 2547, 2578, 2579, 2580, 2583, 2599, 2602, 2603, 2610, 2615, 2616, 2635, 2639, 2648, 2649, 2657, 2659, 2665, 2666],
│ │ │ │ │ +        "64": [1, 5, 13, 21, 30, 50, 55, 56, 59, 61, 62, 63, 65, 66, 69, 74, 79, 315, 339, 409, 457, 470, 514, 584, 660, 669, 944, 1345, 1348, 1519, 1899, 1900, 2076, 2083, 2143, 2261, 2262, 2264, 2268, 2269, 2273, 2274, 2278, 2279, 2283, 2284, 2287, 2288, 2299, 2300, 2303, 2304, 2314, 2328, 2458, 2462, 2464, 2513, 2520, 2542, 2547, 2578, 2579, 2580, 2583, 2599, 2602, 2603, 2610, 2615, 2616, 2635, 2639, 2648, 2649, 2657, 2659, 2665, 2666],
│ │ │ │ │          "64023025": 2098,
│ │ │ │ │          "6416010000000001": 1114,
│ │ │ │ │          "64386512": 349,
│ │ │ │ │          "64402274e": 660,
│ │ │ │ │          "6446": [2550, 2554],
│ │ │ │ │          "646": [2517, 2576],
│ │ │ │ │          "6460": 2522,
│ │ │ │ │ @@ -35255,15 +35253,15 @@
│ │ │ │ │          "6488": 2522,
│ │ │ │ │          "6491": 2522,
│ │ │ │ │          "6495": 2522,
│ │ │ │ │          "6497": 2522,
│ │ │ │ │          "6498": 2522,
│ │ │ │ │          "6499": 2522,
│ │ │ │ │          "64bit": [50, 61, 62, 2364, 2377, 2379, 2388, 2411, 2424, 2426, 2435, 2517, 2572, 2594],
│ │ │ │ │ -        "65": [2461, 2657],
│ │ │ │ │ +        "65": 2657,
│ │ │ │ │          "650": 2618,
│ │ │ │ │          "6500": 2522,
│ │ │ │ │          "6501": 2522,
│ │ │ │ │          "65028784": 2666,
│ │ │ │ │          "65143654": 1154,
│ │ │ │ │          "6515": [2353, 2400, 2450],
│ │ │ │ │          "65200189e": 566,
│ │ │ │ │ @@ -35331,15 +35329,14 @@
│ │ │ │ │          "6689502": 2576,
│ │ │ │ │          "669": 669,
│ │ │ │ │          "6695": 2522,
│ │ │ │ │          "6697": 2522,
│ │ │ │ │          "6698": 2522,
│ │ │ │ │          "67": [409, 670, 671, 672, 1901, 2542, 2644, 2657, 2666],
│ │ │ │ │          "67046769e": 147,
│ │ │ │ │ -        "67119052": 2488,
│ │ │ │ │          "6717": 2522,
│ │ │ │ │          "6718": 2522,
│ │ │ │ │          "6719": 2522,
│ │ │ │ │          "6721": 2522,
│ │ │ │ │          "6726": 2522,
│ │ │ │ │          "6735": 2522,
│ │ │ │ │          "6747": 2522,
│ │ │ │ │ @@ -35389,15 +35386,15 @@
│ │ │ │ │          "699": 520,
│ │ │ │ │          "6ad92e5": 13,
│ │ │ │ │          "6e17": 55,
│ │ │ │ │          "6j": [538, 851, 866, 1025, 1026, 1031, 1051, 1891, 1909, 1914, 2241],
│ │ │ │ │          "6th": [513, 669],
│ │ │ │ │          "6x": [1527, 2599],
│ │ │ │ │          "7": [12, 31, 32, 38, 42, 47, 54, 55, 56, 58, 59, 60, 61, 63, 66, 68, 74, 75, 89, 91, 96, 97, 98, 99, 117, 118, 132, 135, 137, 139, 140, 141, 147, 149, 150, 160, 170, 171, 213, 227, 234, 261, 270, 337, 348, 353, 355, 357, 359, 364, 365, 366, 367, 369, 370, 372, 375, 408, 435, 467, 471, 472, 478, 514, 520, 527, 530, 542, 543, 544, 548, 565, 566, 567, 577, 608, 628, 640, 648, 651, 653, 659, 661, 664, 666, 669, 830, 853, 857, 860, 863, 864, 865, 880, 881, 883, 886, 887, 888, 893, 896, 897, 903, 904, 906, 912, 913, 914, 917, 919, 920, 921, 924, 926, 927, 928, 941, 943, 946, 950, 952, 953, 957, 963, 968, 969, 1002, 1033, 1040, 1044, 1048, 1049, 1050, 1060, 1069, 1070, 1072, 1076, 1077, 1078, 1083, 1101, 1106, 1107, 1116, 1119, 1127, 1135, 1143, 1148, 1149, 1157, 1159, 1160, 1161, 1164, 1166, 1167, 1191, 1193, 1194, 1195, 1200, 1203, 1204, 1205, 1206, 1212, 1213, 1223, 1228, 1229, 1230, 1236, 1240, 1242, 1248, 1249, 1278, 1283, 1286, 1306, 1312, 1331, 1334, 1342, 1344, 1346, 1433, 1437, 1440, 1460, 1466, 1510, 1512, 1520, 1521, 1522, 1554, 1615, 1638, 1644, 1647, 1656, 1672, 1695, 1704, 1705, 1729, 1758, 1770, 1786, 1805, 1816, 1843, 1870, 1880, 1882, 1904, 1908, 1912, 1913, 1914, 1916, 1953, 1957, 1960, 1980, 1986, 2071, 2076, 2078, 2079, 2081, 2082, 2085, 2087, 2091, 2096, 2098, 2104, 2107, 2110, 2115, 2116, 2162, 2163, 2164, 2168, 2171, 2172, 2204, 2205, 2206, 2208, 2209, 2210, 2211, 2212, 2222, 2224, 2225, 2235, 2236, 2237, 2238, 2240, 2241, 2246, 2248, 2257, 2315, 2320, 2323, 2328, 2333, 2339, 2341, 2342, 2347, 2352, 2367, 2377, 2382, 2384, 2388, 2389, 2395, 2399, 2414, 2424, 2429, 2431, 2435, 2436, 2445, 2449, 2457, 2458, 2460, 2461, 2463, 2488, 2491, 2513, 2518, 2519, 2520, 2521, 2522, 2525, 2526, 2527, 2528, 2529, 2530, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2538, 2539, 2540, 2541, 2542, 2543, 2544, 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2560, 2561, 2562, 2563, 2564, 2565, 2566, 2572, 2574, 2575, 2576, 2577, 2578, 2579, 2580, 2581, 2589, 2591, 2592, 2593, 2594, 2600, 2610, 2612, 2616, 2619, 2622, 2626, 2635, 2637, 2638, 2639, 2641, 2642, 2644, 2645, 2647, 2649, 2656, 2657, 2658, 2660, 2666],
│ │ │ │ │ -        "70": [59, 457, 567, 2241, 2248, 2657],
│ │ │ │ │ +        "70": [59, 457, 567, 2241, 2248, 2461, 2657],
│ │ │ │ │          "700": 567,
│ │ │ │ │          "70000000": 2635,
│ │ │ │ │          "701": 2463,
│ │ │ │ │          "703": 2625,
│ │ │ │ │          "7054": 2535,
│ │ │ │ │          "706": 520,
│ │ │ │ │          "70710678": [216, 247, 641, 1199, 1216, 1282, 1299, 1436, 1453, 1636, 1642, 1956, 1973, 2103],
│ │ │ │ │ @@ -35411,15 +35408,15 @@
│ │ │ │ │          "718281": 431,
│ │ │ │ │          "71828182845904523536028747135266249775724709369995": 76,
│ │ │ │ │          "71828183": [38, 2666],
│ │ │ │ │          "718282": 2642,
│ │ │ │ │          "7183": 2642,
│ │ │ │ │          "7185": [99, 906],
│ │ │ │ │          "71946897": 1153,
│ │ │ │ │ -        "72": [13, 355, 544, 669, 1764, 2463, 2572, 2657, 2659],
│ │ │ │ │ +        "72": [13, 355, 544, 669, 1764, 2461, 2463, 2572, 2657, 2659],
│ │ │ │ │          "720": [55, 356, 358, 1897, 2225, 2238, 2576],
│ │ │ │ │          "72075441": 680,
│ │ │ │ │          "721fc64": 13,
│ │ │ │ │          "72375": 1644,
│ │ │ │ │          "72538256": [103, 126],
│ │ │ │ │          "72686684e": 566,
│ │ │ │ │          "72717132": 2659,
│ │ │ │ │ @@ -35430,15 +35427,15 @@
│ │ │ │ │          "72949656": 2635,
│ │ │ │ │          "73": [2463, 2657],
│ │ │ │ │          "7320508075688772j": 59,
│ │ │ │ │          "73472348e": 1816,
│ │ │ │ │          "73496154e": 1867,
│ │ │ │ │          "73603959e": 2666,
│ │ │ │ │          "73799541": 1153,
│ │ │ │ │ -        "74": [2461, 2463, 2513, 2514, 2657],
│ │ │ │ │ +        "74": [2463, 2513, 2514, 2657],
│ │ │ │ │          "74000000": 2635,
│ │ │ │ │          "7416573867739413": 653,
│ │ │ │ │          "74165739": 653,
│ │ │ │ │          "74499359e": [420, 947],
│ │ │ │ │          "745966692414834": [648, 653],
│ │ │ │ │          "75": [58, 135, 440, 478, 516, 520, 528, 544, 645, 667, 870, 1056, 1542, 1606, 1634, 1663, 1834, 2091, 2257, 2491, 2657, 2659, 2666],
│ │ │ │ │          "7500": 652,
│ │ │ │ │ @@ -35480,15 +35477,15 @@
│ │ │ │ │          "7670": 2526,
│ │ │ │ │          "7671": 2526,
│ │ │ │ │          "7676": 2526,
│ │ │ │ │          "7680": 2526,
│ │ │ │ │          "769893": 2635,
│ │ │ │ │          "76989341": 2635,
│ │ │ │ │          "76991118": 1891,
│ │ │ │ │ -        "77": [29, 36, 37, 38, 39, 2461, 2463, 2635, 2654, 2657],
│ │ │ │ │ +        "77": [29, 36, 37, 38, 39, 2463, 2635, 2654, 2657],
│ │ │ │ │          "770": [287, 1241, 1324, 1478, 1998, 2650],
│ │ │ │ │          "77086955": 1526,
│ │ │ │ │          "7724": 2526,
│ │ │ │ │          "7725": [2353, 2400, 2450],
│ │ │ │ │          "7731": 2526,
│ │ │ │ │          "7736": 2527,
│ │ │ │ │          "7737": 2526,
│ │ │ │ │ @@ -35516,14 +35513,15 @@
│ │ │ │ │          "78497f4": 2521,
│ │ │ │ │          "7851": 2527,
│ │ │ │ │          "78539816": [94, 104, 105, 129, 130, 2238],
│ │ │ │ │          "78539816339744828": [104, 129],
│ │ │ │ │          "7854j": [413, 619],
│ │ │ │ │          "78571429e": 1816,
│ │ │ │ │          "78606431": [349, 2457, 2639],
│ │ │ │ │ +        "7870627": 2461,
│ │ │ │ │          "789": 2644,
│ │ │ │ │          "7896": 2527,
│ │ │ │ │          "79": [13, 87, 100, 104, 129, 2657],
│ │ │ │ │          "79033856e": 1149,
│ │ │ │ │          "7904": 2527,
│ │ │ │ │          "7917": 2527,
│ │ │ │ │          "7919": 2527,
│ │ │ │ │ @@ -35555,24 +35553,26 @@
│ │ │ │ │          "8010": 2527,
│ │ │ │ │          "8020": 2527,
│ │ │ │ │          "8024": 2527,
│ │ │ │ │          "8031": 2527,
│ │ │ │ │          "804": 2508,
│ │ │ │ │          "8044": 2527,
│ │ │ │ │          "8058837395885292": 666,
│ │ │ │ │ +        "8089857": 2461,
│ │ │ │ │          "80b3a34": 2614,
│ │ │ │ │          "81": [1650, 1884, 2635, 2641, 2645, 2657, 2666],
│ │ │ │ │          "81299683": 2635,
│ │ │ │ │          "812997": 2635,
│ │ │ │ │          "813": [270, 880, 1069, 1229, 1312, 1466, 1986],
│ │ │ │ │          "81327024": 2635,
│ │ │ │ │          "81349206": [1113, 1543],
│ │ │ │ │ +        "817": 2461,
│ │ │ │ │          "81814867": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "8192": [72, 517, 2092, 2619],
│ │ │ │ │ -        "82": [1650, 2323, 2367, 2414, 2461, 2463, 2657, 2666],
│ │ │ │ │ +        "82": [1650, 2323, 2367, 2414, 2463, 2657, 2666],
│ │ │ │ │          "8207540608310198": [2353, 2400, 2450],
│ │ │ │ │          "82276161": 349,
│ │ │ │ │          "8230": [2353, 2400, 2450],
│ │ │ │ │          "82485143": 2635,
│ │ │ │ │          "82502011": 349,
│ │ │ │ │          "8255": 2566,
│ │ │ │ │          "826716f": 2521,
│ │ │ │ │ @@ -35585,45 +35585,46 @@
│ │ │ │ │          "83314899": 1154,
│ │ │ │ │          "83333333": 1702,
│ │ │ │ │          "833333333333333": [893, 1083, 1143, 2240],
│ │ │ │ │          "8341": 2528,
│ │ │ │ │          "8346": 2528,
│ │ │ │ │          "83571711": 349,
│ │ │ │ │          "83697020e": [470, 1899, 1900],
│ │ │ │ │ -        "84": [2657, 2659],
│ │ │ │ │ +        "84": [2461, 2657, 2659],
│ │ │ │ │          "840": 1212,
│ │ │ │ │ -        "84008604": 2488,
│ │ │ │ │          "84057254": [2339, 2352, 2382, 2389, 2399, 2429, 2436, 2449],
│ │ │ │ │          "84090247": 2458,
│ │ │ │ │          "84123594": 523,
│ │ │ │ │          "84147098": 2666,
│ │ │ │ │          "8414709848078965": 2640,
│ │ │ │ │          "84147098j": 2666,
│ │ │ │ │          "841471": 2642,
│ │ │ │ │          "842523": 2515,
│ │ │ │ │          "84680802e": 2104,
│ │ │ │ │          "8480354764257312": 653,
│ │ │ │ │          "85": [409, 2657],
│ │ │ │ │          "85099543": 1822,
│ │ │ │ │          "85355339": 1756,
│ │ │ │ │          "85569": 2098,
│ │ │ │ │ +        "85572165": 2461,
│ │ │ │ │          "85602287": [2335, 2378, 2425],
│ │ │ │ │          "857": 410,
│ │ │ │ │          "8570331885190563e": [648, 653],
│ │ │ │ │          "85715698e": 2171,
│ │ │ │ │          "8577": 2539,
│ │ │ │ │          "85859792": [349, 2457, 2639],
│ │ │ │ │          "8595784": 2635,
│ │ │ │ │          "86": [59, 88, 101, 103, 106, 126, 131, 542, 968, 969, 2323, 2367, 2414, 2491, 2657],
│ │ │ │ │          "8601": [55, 62, 67, 2613],
│ │ │ │ │          "86260211e": 54,
│ │ │ │ │          "8630830": 13,
│ │ │ │ │          "86399": 55,
│ │ │ │ │          "86400": 55,
│ │ │ │ │          "86401": 55,
│ │ │ │ │ +        "86546345": 2461,
│ │ │ │ │          "8660254": 2103,
│ │ │ │ │          "86820401": [2345, 2391, 2439],
│ │ │ │ │          "86864911e": 1586,
│ │ │ │ │          "87": [2616, 2657],
│ │ │ │ │          "875": [478, 2491],
│ │ │ │ │          "8755": [186, 827, 999, 1172, 1259, 1414, 1933],
│ │ │ │ │          "87649168120691": 674,
│ │ │ │ │ @@ -35664,16 +35665,16 @@
│ │ │ │ │          "90476190e": 1816,
│ │ │ │ │          "90909091": 136,
│ │ │ │ │          "909297": 2642,
│ │ │ │ │          "90929743": 2666,
│ │ │ │ │          "91": 2657,
│ │ │ │ │          "91275558": 2635,
│ │ │ │ │          "916666666666666": 1240,
│ │ │ │ │ -        "91932205": 2461,
│ │ │ │ │ -        "92": [98, 2461, 2657, 2659],
│ │ │ │ │ +        "92": [98, 2657, 2659],
│ │ │ │ │ +        "92122459": 2488,
│ │ │ │ │          "921fb54442d18p": 2520,
│ │ │ │ │          "9223372036854775807": 2648,
│ │ │ │ │          "9223372036854775808": 2648,
│ │ │ │ │          "92346708": 349,
│ │ │ │ │          "92362781e": 2104,
│ │ │ │ │          "92387953": 642,
│ │ │ │ │          "92387953j": 642,
│ │ │ │ │ @@ -35704,22 +35705,23 @@
│ │ │ │ │          "9377": 2532,
│ │ │ │ │          "93773029": 349,
│ │ │ │ │          "9378": 2532,
│ │ │ │ │          "9379": 2532,
│ │ │ │ │          "9390": [2533, 2534],
│ │ │ │ │          "94": [409, 669, 2635, 2657],
│ │ │ │ │          "940": 2587,
│ │ │ │ │ +        "94041448": 2461,
│ │ │ │ │          "941257": 2635,
│ │ │ │ │          "94125714": 2635,
│ │ │ │ │ -        "94178031": 2461,
│ │ │ │ │          "94708397920832": 2642,
│ │ │ │ │          "9475673279178444": 2348,
│ │ │ │ │          "94864945": 2666,
│ │ │ │ │          "94909878": [2387, 2434],
│ │ │ │ │ -        "95": [37, 39, 646, 2353, 2400, 2450, 2635, 2654, 2657],
│ │ │ │ │ +        "94988671": 2461,
│ │ │ │ │ +        "95": [37, 39, 646, 2353, 2400, 2450, 2461, 2635, 2654, 2657],
│ │ │ │ │          "9504637": 2666,
│ │ │ │ │          "950684": 2635,
│ │ │ │ │          "95068423": 2635,
│ │ │ │ │          "9555": [2533, 2534],
│ │ │ │ │          "9556": [2533, 2534],
│ │ │ │ │          "9557": [2533, 2534],
│ │ │ │ │          "9558": [2533, 2534],
│ │ │ │ │ @@ -35732,15 +35734,15 @@
│ │ │ │ │          "96360618": [2387, 2434],
│ │ │ │ │          "9665554": 349,
│ │ │ │ │          "96767474e": 54,
│ │ │ │ │          "96875": 2491,
│ │ │ │ │          "96979195": 2635,
│ │ │ │ │          "969792": 2635,
│ │ │ │ │          "96e7": 42,
│ │ │ │ │ -        "97": [2461, 2463, 2635, 2657, 2666],
│ │ │ │ │ +        "97": [2463, 2635, 2657, 2666],
│ │ │ │ │          "9700": 2666,
│ │ │ │ │          "9701": 2666,
│ │ │ │ │          "9702": 2666,
│ │ │ │ │          "97074098": 349,
│ │ │ │ │          "973": [941, 1114, 1123, 1124, 1131],
│ │ │ │ │          "9732": [2533, 2534],
│ │ │ │ │          "9736": [2533, 2534],
│ │ │ │ │ @@ -35760,40 +35762,39 @@
│ │ │ │ │          "97719": 1644,
│ │ │ │ │          "9772": 2534,
│ │ │ │ │          "9794": 2534,
│ │ │ │ │          "9797": 2666,
│ │ │ │ │          "97974649": 524,
│ │ │ │ │          "9798": 2666,
│ │ │ │ │          "9799": 2666,
│ │ │ │ │ -        "98": [481, 647, 1157, 2635, 2657, 2666],
│ │ │ │ │ +        "98": [481, 647, 1157, 2461, 2635, 2657, 2666],
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│ │ │ │ │          "9898": 2666,
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│ │ │ │ │ -        "99": [12, 302, 408, 544, 672, 1096, 1906, 2131, 2460, 2461, 2635, 2657, 2658, 2666],
│ │ │ │ │ +        "99": [12, 302, 408, 544, 672, 1096, 1906, 2131, 2460, 2635, 2657, 2658, 2666],
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│ │ │ │ │          "99004057": 349,
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│ │ │ │ │          "99149989": [2345, 2391, 2439],
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│ │ │ │ │ -        "9925222": 2461,
│ │ │ │ │          "99256089": 349,
│ │ │ │ │          "99322285": [88, 101],
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│ │ │ │ │          "99507202": 349,
│ │ │ │ │          "99734545": 1154,
│ │ │ │ │          "998": 2535,
│ │ │ │ │ @@ -45984,15 +45985,15 @@
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│ │ │ │ │          "typic": [1, 4, 5, 6, 8, 9, 10, 11, 12, 13, 19, 20, 21, 22, 36, 39, 42, 54, 55, 58, 59, 61, 63, 65, 70, 72, 74, 78, 91, 114, 159, 161, 354, 409, 422, 427, 443, 457, 521, 522, 548, 571, 572, 579, 582, 583, 627, 655, 814, 850, 1030, 1513, 1526, 1577, 1578, 1580, 1585, 1588, 1640, 1645, 1697, 1702, 1754, 1759, 1811, 1816, 1867, 2089, 2094, 2123, 2126, 2127, 2138, 2139, 2145, 2219, 2223, 2226, 2251, 2258, 2290, 2334, 2462, 2473, 2507, 2513, 2514, 2515, 2517, 2518, 2542, 2599, 2616, 2635, 2637, 2644, 2645, 2647, 2648, 2652, 2653, 2654, 2668, 2669],
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│ │ │ │ │          "tzinfo": [67, 360],
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│ │ │ │ │          "t\u2081": 1895,
│ │ │ │ │          "t\u2082": 1895,
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│ │ │ │ │ +        "u": [10, 11, 12, 13, 14, 16, 18, 24, 30, 40, 50, 55, 56, 57, 62, 67, 69, 74, 78, 150, 163, 270, 302, 305, 360, 397, 560, 636, 642, 644, 659, 669, 880, 1069, 1148, 1229, 1312, 1345, 1348, 1466, 1542, 1585, 1645, 1702, 1759, 1816, 1871, 1986, 2086, 2131, 2134, 2213, 2230, 2270, 2358, 2405, 2455, 2461, 2464, 2499, 2507, 2508, 2510, 2513, 2535, 2542, 2554, 2556, 2572, 2599, 2622, 2625, 2629, 2642, 2647, 2648, 2649, 2656, 2665, 2669],
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│ │ │ │ │          "u13": [2469, 2503],
│ │ │ │ │          "u16": [56, 389],