--- /srv/reproducible-results/rbuild-debian/tmp.4ltGJH7E4d/b1/scipy_1.6.0-2_amd64.changes
+++ /srv/reproducible-results/rbuild-debian/tmp.4ltGJH7E4d/b2/scipy_1.6.0-2_amd64.changes
├── Files
│ @@ -1,4 +1,4 @@
│  
│ - ea4fbe92185be40f63b21c2c1be3c578 24077808 doc optional python-scipy-doc_1.6.0-2_all.deb
│ + 55d8d1630c9b4328f4ed5c224e321a24 24077836 doc optional python-scipy-doc_1.6.0-2_all.deb
│   112dbc623e1d3d74f5f90e0f8390aabc 80697908 debug optional python3-scipy-dbg_1.6.0-2_amd64.deb
│   717e8626226f00e925b7e42b1226c194 12308060 python optional python3-scipy_1.6.0-2_amd64.deb
├── python-scipy-doc_1.6.0-2_all.deb
│ ├── file list
│ │ @@ -1,3 +1,3 @@
│ │  -rw-r--r--   0        0        0        4 2021-01-16 12:26:56.000000 debian-binary
│ │ --rw-r--r--   0        0        0   113048 2021-01-16 12:26:56.000000 control.tar.xz
│ │ --rw-r--r--   0        0        0 23964568 2021-01-16 12:26:56.000000 data.tar.xz
│ │ +-rw-r--r--   0        0        0   113060 2021-01-16 12:26:56.000000 control.tar.xz
│ │ +-rw-r--r--   0        0        0 23964584 2021-01-16 12:26:56.000000 data.tar.xz
│ ├── control.tar.xz
│ │ ├── control.tar
│ │ │ ├── ./md5sums
│ │ │ │ ├── ./md5sums
│ │ │ │ │┄ Files differ
│ ├── data.tar.xz
│ │ ├── data.tar
│ │ │ ├── ./usr/share/doc/python-scipy-doc/html/generated/scipy.cluster.hierarchy.ClusterNode.pre_order.html
│ │ │ │ @@ -104,15 +104,15 @@
│ │ │ │          <div class="bodywrapper">
│ │ │ │            <div class="body" id="spc-section-body">
│ │ │ │              
│ │ │ │    <div class="section" id="scipy-cluster-hierarchy-clusternode-pre-order">
│ │ │ │  <h1>scipy.cluster.hierarchy.ClusterNode.pre_order<a class="headerlink" href="#scipy-cluster-hierarchy-clusternode-pre-order" title="Permalink to this headline">¶</a></h1>
│ │ │ │  <dl class="py method">
│ │ │ │  <dt id="scipy.cluster.hierarchy.ClusterNode.pre_order">
│ │ │ │ -<code class="sig-prename descclassname">ClusterNode.</code><code class="sig-name descname">pre_order</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">func=&lt;function ClusterNode.&lt;lambda&gt; at 0x7f0e23cf5e50&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/cluster/hierarchy.py#L1222-L1282"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.cluster.hierarchy.ClusterNode.pre_order" title="Permalink to this definition">¶</a></dt>
│ │ │ │ +<code class="sig-prename descclassname">ClusterNode.</code><code class="sig-name descname">pre_order</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">func=&lt;function ClusterNode.&lt;lambda&gt; at 0x7f611becce50&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/cluster/hierarchy.py#L1222-L1282"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.cluster.hierarchy.ClusterNode.pre_order" title="Permalink to this definition">¶</a></dt>
│ │ │ │  <dd><p>Perform pre-order traversal without recursive function calls.</p>
│ │ │ │  <p>When a leaf node is first encountered, <code class="docutils literal notranslate"><span class="pre">func</span></code> is called with
│ │ │ │  the leaf node as its argument, and its result is appended to
│ │ │ │  the list.</p>
│ │ │ │  <p>For example, the statement:</p>
│ │ │ │  <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">ids</span> <span class="o">=</span> <span class="n">root</span><span class="o">.</span><span class="n">pre_order</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">id</span><span class="p">)</span>
│ │ │ │  </pre></div>
│ │ │ ├── ./usr/share/doc/python-scipy-doc/html/generated/scipy.optimize.brute.html
│ │ │ │ @@ -102,15 +102,15 @@
│ │ │ │          <div class="bodywrapper">
│ │ │ │            <div class="body" id="spc-section-body">
│ │ │ │              
│ │ │ │    <div class="section" id="scipy-optimize-brute">
│ │ │ │  <h1>scipy.optimize.brute<a class="headerlink" href="#scipy-optimize-brute" title="Permalink to this headline">¶</a></h1>
│ │ │ │  <dl class="py function">
│ │ │ │  <dt id="scipy.optimize.brute">
│ │ │ │ -<code class="sig-prename descclassname">scipy.optimize.</code><code class="sig-name descname">brute</code><span class="sig-paren">(</span><em class="sig-param">func</em>, <em class="sig-param">ranges</em>, <em class="sig-param">args=()</em>, <em class="sig-param">Ns=20</em>, <em class="sig-param">full_output=0</em>, <em class="sig-param">finish=&lt;function fmin at 0x7f0e28f77790&gt;</em>, <em class="sig-param">disp=False</em>, <em class="sig-param">workers=1</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/optimize/optimize.py#L3066-L3320"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.optimize.brute" title="Permalink to this definition">¶</a></dt>
│ │ │ │ +<code class="sig-prename descclassname">scipy.optimize.</code><code class="sig-name descname">brute</code><span class="sig-paren">(</span><em class="sig-param">func</em>, <em class="sig-param">ranges</em>, <em class="sig-param">args=()</em>, <em class="sig-param">Ns=20</em>, <em class="sig-param">full_output=0</em>, <em class="sig-param">finish=&lt;function fmin at 0x7f61211e7790&gt;</em>, <em class="sig-param">disp=False</em>, <em class="sig-param">workers=1</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/optimize/optimize.py#L3066-L3320"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.optimize.brute" title="Permalink to this definition">¶</a></dt>
│ │ │ │  <dd><p>Minimize a function over a given range by brute force.</p>
│ │ │ │  <p>Uses the “brute force” method, i.e., computes the function’s value
│ │ │ │  at each point of a multidimensional grid of points, to find the global
│ │ │ │  minimum of the function.</p>
│ │ │ │  <p>The function is evaluated everywhere in the range with the datatype of the
│ │ │ │  first call to the function, as enforced by the <code class="docutils literal notranslate"><span class="pre">vectorize</span></code> NumPy
│ │ │ │  function. The value and type of the function evaluation returned when
│ │ │ ├── ./usr/share/doc/python-scipy-doc/html/generated/scipy.stats.median_abs_deviation.html
│ │ │ │ @@ -102,15 +102,15 @@
│ │ │ │          <div class="bodywrapper">
│ │ │ │            <div class="body" id="spc-section-body">
│ │ │ │              
│ │ │ │    <div class="section" id="scipy-stats-median-abs-deviation">
│ │ │ │  <h1>scipy.stats.median_abs_deviation<a class="headerlink" href="#scipy-stats-median-abs-deviation" title="Permalink to this headline">¶</a></h1>
│ │ │ │  <dl class="py function">
│ │ │ │  <dt id="scipy.stats.median_abs_deviation">
│ │ │ │ -<code class="sig-prename descclassname">scipy.stats.</code><code class="sig-name descname">median_abs_deviation</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">axis=0</em>, <em class="sig-param">center=&lt;function median at 0x7f0e2c84be50&gt;</em>, <em class="sig-param">scale=1.0</em>, <em class="sig-param">nan_policy='propagate'</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/stats/stats.py#L2951-L3101"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.stats.median_abs_deviation" title="Permalink to this definition">¶</a></dt>
│ │ │ │ +<code class="sig-prename descclassname">scipy.stats.</code><code class="sig-name descname">median_abs_deviation</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">axis=0</em>, <em class="sig-param">center=&lt;function median at 0x7f6124a5be50&gt;</em>, <em class="sig-param">scale=1.0</em>, <em class="sig-param">nan_policy='propagate'</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/stats/stats.py#L2951-L3101"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.stats.median_abs_deviation" title="Permalink to this definition">¶</a></dt>
│ │ │ │  <dd><p>Compute the median absolute deviation of the data along the given axis.</p>
│ │ │ │  <p>The median absolute deviation (MAD, <a class="reference internal" href="#r63fe0ba43769-1" id="id1">[1]</a>) computes the median over the
│ │ │ │  absolute deviations from the median. It is a measure of dispersion
│ │ │ │  similar to the standard deviation but more robust to outliers <a class="reference internal" href="#r63fe0ba43769-2" id="id2">[2]</a>.</p>
│ │ │ │  <p>The MAD of an empty array is <code class="docutils literal notranslate"><span class="pre">np.nan</span></code>.</p>
│ │ │ │  <div class="versionadded">
│ │ │ │  <p><span class="versionmodified added">New in version 1.5.0.</span></p>
│ │ │ ├── ./usr/share/doc/python-scipy-doc/html/generated/scipy.stats.multiscale_graphcorr.html
│ │ │ │ @@ -102,15 +102,15 @@
│ │ │ │          <div class="bodywrapper">
│ │ │ │            <div class="body" id="spc-section-body">
│ │ │ │              
│ │ │ │    <div class="section" id="scipy-stats-multiscale-graphcorr">
│ │ │ │  <h1>scipy.stats.multiscale_graphcorr<a class="headerlink" href="#scipy-stats-multiscale-graphcorr" title="Permalink to this headline">¶</a></h1>
│ │ │ │  <dl class="py function">
│ │ │ │  <dt id="scipy.stats.multiscale_graphcorr">
│ │ │ │ -<code class="sig-prename descclassname">scipy.stats.</code><code class="sig-name descname">multiscale_graphcorr</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">y</em>, <em class="sig-param">compute_distance=&lt;function _euclidean_dist at 0x7f0e28747280&gt;</em>, <em class="sig-param">reps=1000</em>, <em class="sig-param">workers=1</em>, <em class="sig-param">is_twosamp=False</em>, <em class="sig-param">random_state=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/stats/stats.py#L4865-L5144"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.stats.multiscale_graphcorr" title="Permalink to this definition">¶</a></dt>
│ │ │ │ +<code class="sig-prename descclassname">scipy.stats.</code><code class="sig-name descname">multiscale_graphcorr</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">y</em>, <em class="sig-param">compute_distance=&lt;function _euclidean_dist at 0x7f6120954280&gt;</em>, <em class="sig-param">reps=1000</em>, <em class="sig-param">workers=1</em>, <em class="sig-param">is_twosamp=False</em>, <em class="sig-param">random_state=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/v1.6.0/scipy/stats/stats.py#L4865-L5144"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.stats.multiscale_graphcorr" title="Permalink to this definition">¶</a></dt>
│ │ │ │  <dd><p>Computes the Multiscale Graph Correlation (MGC) test statistic.</p>
│ │ │ │  <p>Specifically, for each point, MGC finds the <span class="math notranslate nohighlight">\(k\)</span>-nearest neighbors for
│ │ │ │  one property (e.g. cloud density), and the <span class="math notranslate nohighlight">\(l\)</span>-nearest neighbors for
│ │ │ │  the other property (e.g. grass wetness) <a class="reference internal" href="#r882c1b4c2283-1" id="id1">[1]</a>. This pair <span class="math notranslate nohighlight">\((k, l)\)</span> is
│ │ │ │  called the “scale”. A priori, however, it is not know which scales will be
│ │ │ │  most informative. So, MGC computes all distance pairs, and then efficiently
│ │ │ │  computes the distance correlations for all scales. The local correlations
│ │ │ ├── ./usr/share/doc/python-scipy-doc/html/searchindex.js
│ │ │ │ ├── js-beautify {}
│ │ │ │ │ @@ -4340,18 +4340,18 @@
│ │ │ │ │          "0b3": 3009,
│ │ │ │ │          "0f1": 2701,
│ │ │ │ │          "0f22701": 40,
│ │ │ │ │          "0rc1": [32, 3376, 3383, 3386],
│ │ │ │ │          "0rc2": [3372, 3376],
│ │ │ │ │          "0th": [385, 386, 510, 515, 1785, 1786],
│ │ │ │ │          "0x00": 562,
│ │ │ │ │ -        "0x7f0e23cf5e50": 61,
│ │ │ │ │ -        "0x7f0e28747280": 3127,
│ │ │ │ │ -        "0x7f0e28f77790": 1545,
│ │ │ │ │ -        "0x7f0e2c84be50": 3045,
│ │ │ │ │ +        "0x7f611becce50": 61,
│ │ │ │ │ +        "0x7f6120954280": 3127,
│ │ │ │ │ +        "0x7f61211e7790": 1545,
│ │ │ │ │ +        "0x7f6124a5be50": 3045,
│ │ │ │ │          "0x7fe753763180": 545,
│ │ │ │ │          "0x_3": 3427,
│ │ │ │ │          "0x_4": 3427,
│ │ │ │ │          "100": [10, 16, 41, 101, 143, 280, 287, 288, 356, 464, 497, 498, 510, 512, 513, 515, 563, 716, 1405, 1446, 1537, 1538, 1541, 1542, 1557, 1560, 1561, 1563, 1565, 1566, 1572, 1575, 1578, 1579, 1582, 1586, 1588, 1624, 1626, 1627, 1628, 1631, 1632, 1638, 1639, 1640, 1641, 1647, 1651, 1653, 1654, 1659, 1667, 1676, 1691, 1694, 1697, 1699, 1701, 1702, 1705, 1727, 1739, 1741, 1743, 1748, 1750, 1751, 1754, 1755, 1756, 1759, 1767, 1785, 1796, 1812, 2366, 2439, 2446, 2475, 2508, 2533, 2561, 2658, 2673, 2678, 2679, 2701, 2704, 2749, 2754, 2815, 2834, 2862, 2900, 2903, 2905, 2906, 2908, 2910, 2912, 2919, 2923, 2925, 2926, 2927, 2928, 2929, 2938, 2940, 2943, 2946, 2951, 2952, 2953, 2954, 2955, 2957, 2960, 2962, 2963, 2965, 2966, 2983, 2984, 2985, 2986, 2987, 2988, 2989, 2990, 2992, 2994, 2996, 2997, 2998, 2999, 3000, 3001, 3004, 3005, 3006, 3007, 3008, 3009, 3012, 3013, 3014, 3015, 3018, 3020, 3023, 3024, 3025, 3026, 3028, 3029, 3031, 3032, 3033, 3035, 3036, 3037, 3038, 3040, 3041, 3044, 3045, 3046, 3048, 3052, 3127, 3132, 3134, 3135, 3136, 3138, 3140, 3143, 3144, 3146, 3151, 3152, 3153, 3156, 3161, 3162, 3163, 3165, 3174, 3192, 3198, 3215, 3223, 3242, 3244, 3245, 3247, 3250, 3251, 3252, 3254, 3260, 3261, 3265, 3266, 3270, 3273, 3275, 3278, 3279, 3280, 3282, 3283, 3286, 3287, 3316, 3323, 3327, 3328, 3345, 3348, 3383, 3385, 3390, 3394, 3396, 3406, 3417, 3419, 3422, 3423, 3427, 3428, 3429, 3430, 3431, 3480, 3516],
│ │ │ │ │          "1000": [100, 287, 371, 401, 485, 501, 742, 1049, 1537, 1539, 1549, 1550, 1555, 1556, 1631, 1638, 1639, 1651, 1662, 1676, 1679, 1688, 1689, 1691, 1692, 1694, 1699, 1701, 1703, 1711, 1715, 1745, 1746, 1777, 1802, 1815, 2362, 2365, 2621, 2658, 2659, 2679, 2701, 2747, 2749, 2750, 2759, 2900, 2903, 2905, 2906, 2909, 2910, 2911, 2912, 2916, 2918, 2920, 2923, 2925, 2926, 2927, 2928, 2929, 2938, 2940, 2941, 2943, 2945, 2946, 2951, 2952, 2953, 2954, 2955, 2957, 2960, 2962, 2963, 2965, 2966, 2983, 2984, 2985, 2986, 2987, 2988, 2989, 2990, 2991, 2992, 2994, 2995, 2996, 2997, 2998, 2999, 3000, 3001, 3004, 3005, 3006, 3007, 3012, 3013, 3014, 3015, 3020, 3024, 3025, 3026, 3027, 3028, 3029, 3031, 3032, 3033, 3035, 3036, 3037, 3038, 3039, 3040, 3041, 3044, 3048, 3052, 3127, 3132, 3133, 3134, 3135, 3136, 3138, 3139, 3140, 3143, 3144, 3147, 3149, 3151, 3152, 3153, 3157, 3161, 3162, 3163, 3164, 3165, 3171, 3196, 3220, 3241, 3244, 3248, 3250, 3254, 3260, 3261, 3265, 3266, 3273, 3275, 3278, 3279, 3280, 3282, 3283, 3287, 3289, 3292, 3293, 3306, 3316, 3321, 3326, 3329, 3342, 3361, 3372, 3396, 3400, 3406, 3417, 3423, 3427, 3430, 3431],
│ │ │ │ │          "10000": [280, 282, 1572, 1663, 1669, 1687, 1729, 1802, 2645, 2913, 3019, 3154, 3155, 3431],
│ │ │ │ │          "100000": [10, 1565, 1715, 1743, 2908, 3011, 3215],