Source code for datasketch.lshensemble

-from collections import deque
+from collections import deque, Counter
 import numpy as np
 from datasketch.lsh import integrate, MinHashLSH
+from datasketch.lshensemble_partition import optimal_partitions
 
 
 def _false_positive_probability(threshold, b, r, xq):
@@ -99,7 +101,7 @@ 
Source code for datasketch.lshensemble
     '''
     _probability = lambda t : 1 - (1 - (t/(1 + xq - t))**float(r))**float(b)
     if xq >= threshold:
-        a, err = integrate(_probability, 0.0, threshold) 
+        a, err = integrate(_probability, 0.0, threshold)
         return a
     a, err = integrate(_probability, 0.0, xq)
     return a
@@ -143,11 +145,11 @@ 
Source code for datasketch.lshensemble
 
 
[docs]class MinHashLSHEnsemble(object):
     '''
-    The :ref:`minhash_lsh_ensemble` index. It supports 
+    The :ref:`minhash_lsh_ensemble` index. It supports
     :ref:`containment` queries.
-    The implementation is based on 
-    `E. Zhu et al. <http://www.vldb.org/pvldb/vol9/p1185-zhu.pdf>`_. 
-    
+    The implementation is based on
+    `E. Zhu et al. <http://www.vldb.org/pvldb/vol9/p1185-zhu.pdf>`_.
+
     Args:
         threshold (float): The Containment threshold between 0.0 and
             1.0. The initialized LSH Ensemble will be optimized for the threshold by
@@ -155,12 +157,12 @@ 
Source code for datasketch.lshensemble
         num_perm (int, optional): The number of permutation functions used
             by the MinHash to be indexed. For weighted MinHash, this
             is the sample size (`sample_size`).
-        num_part (int, optional): The number of partitions in LSH Ensemble. 
+        num_part (int, optional): The number of partitions in LSH Ensemble.
         m (int, optional): The memory usage factor: an LSH Ensemble uses approximately
-            `m` times more memory space than a MinHash LSH with the same number of 
-            sets indexed. The higher the `m` the better the accuracy. 
-        weights (tuple, optional): Used to adjust the relative importance of 
-            minizing false positive and false negative when optimizing 
+            `m` times more memory space than a MinHash LSH with the same number of
+            sets indexed. The higher the `m` the better the accuracy.
+        weights (tuple, optional): Used to adjust the relative importance of
+            minizing false positive and false negative when optimizing
             for the Containment threshold. Similar to the `weights` parameter
             in :class:`datasketch.MinHashLSH`.
 
@@ -172,17 +174,17 @@ 
Source code for datasketch.lshensemble
         due to parallelism.
 
     Note:
-        More information about the parameter `m` can be found in the 
+        More information about the parameter `m` can be found in the
         `Go implementation`_
         of LSH Ensemble, in which `m` is named `MaxK`.
-    
+
     .. _`Go implementation`: https://github.com/ekzhu/lshensemble
     .. _`the paper`: http://www.vldb.org/pvldb/vol9/p1185-zhu.pdf
     '''
 
 
[docs]    def __init__(self, threshold=0.9, num_perm=128, num_part=16, m=8, weights=(0.5,0.5)):
         if threshold > 1.0 or threshold < 0.0:
-            raise ValueError("threshold must be in [0.0, 1.0]") 
+            raise ValueError("threshold must be in [0.0, 1.0]")
         if num_perm < 2:
             raise ValueError("Too few permutation functions")
         if num_part < 2:
@@ -198,17 +200,19 @@ 
Source code for datasketch.lshensemble
         self.m = m
         rs = self._init_optimal_params(weights)
         # Initialize multiple LSH indexes for each partition
-        self.indexes = [dict((r, MinHashLSH(num_perm=self.h, params=(int(self.h/r), r))) for r in rs)
-                        for _ in range(0, num_part)] 
-        self.lowers = [None for _ in self.indexes]

+        self.indexes = [dict((r, MinHashLSH(num_perm=self.h,
+            params=(int(self.h/r), r))) for r in rs)
+            for _ in range(0, num_part)]
+        self.lowers = [None for _ in self.indexes]
+        self.uppers = [None for _ in self.indexes]

 
     def _init_optimal_params(self, weights):
         false_positive_weight, false_negative_weight = weights
         self.xqs = np.exp(np.linspace(-5, 5, 10))
-        self.params = np.array([_optimal_param(self.threshold, self.h, self.m, 
-                                               xq, 
+        self.params = np.array([_optimal_param(self.threshold, self.h, self.m,
+                                               xq,
                                                false_positive_weight,
-                                               false_negative_weight) 
+                                               false_negative_weight)
                                 for xq in self.xqs], dtype=np.int)
         # Find all unique r
         rs = set()
@@ -221,7 +225,7 @@ 
Source code for datasketch.lshensemble
         if i == len(self.params):
             i = i - 1
         return self.params[i]
-    
+
 
[docs]    def index(self, entries):
         '''
         Index all sets given their keys, MinHashes, and sizes.
@@ -232,7 +236,7 @@ 
Source code for datasketch.lshensemble
                 in the form of `(key, minhash, size)`, where `key` is the unique
                 identifier of a set, `minhash` is the MinHash of the set,
                 and `size` is the size or number of unique items in the set.
-        
+
         Note:
             `size` must be positive.
         '''
@@ -247,33 +251,36 @@ 
Source code for datasketch.lshensemble
             entries = list(queue)
         if len(entries) == 0:
             raise ValueError("entries is empty")
+        # Create optimal partitions.
+        sizes, counts = np.array(sorted(
+            Counter(e[2] for e in entries).most_common())).T
+        partitions = optimal_partitions(sizes, counts, len(self.indexes))
+        for i, (lower, upper) in enumerate(partitions):
+            self.lowers[i], self.uppers[i] = lower, upper
+        # Insert into partitions.
         entries.sort(key=lambda e : e[2])
-        if entries[0][2] < 0:
-            raise ValueError("Non-positive set size found in entries")
-        part_size = int(len(entries) / len(self.indexes)) + 1
-        for i, index in enumerate(self.indexes):
-            if part_size*i >= len(entries):
-                continue
-            self.lowers[i] = entries[part_size*i][2]
-            for r in index:
-                for key, minhash, size in entries[part_size*i:part_size*(i+1)]:
-                    index[r].insert(key, minhash)

+        curr_part = 0
+        for key, minhash, size in entries:
+            if size > self.uppers[curr_part]:
+                curr_part += 1
+            for r in self.indexes[curr_part]:
+                self.indexes[curr_part][r].insert(key, minhash)

 
 
[docs]    def query(self, minhash, size):
         '''
-        Giving the MinHash and size of the query set, retrieve 
+        Giving the MinHash and size of the query set, retrieve
         keys that references sets with containment with respect to
         the query set greater than the threshold.
-        
+
         Args:
-            minhash (datasketch.MinHash): The MinHash of the query set. 
+            minhash (datasketch.MinHash): The MinHash of the query set.
             size (int): The size (number of unique items) of the query set.
 
         Returns:
             `iterator` of keys.
         '''
         for i, index in enumerate(self.indexes):
-            u = self.lowers[i]
+            u = self.uppers[i]
             if u is None:
                 continue
             b, r = self._get_optimal_param(u, size)
@@ -285,7 +292,7 @@ 
Source code for datasketch.lshensemble
         Args:
             key (hashable): The unique identifier of a set.
 
-        Returns: 
+        Returns:
             bool: True only if the key exists in the index.
         '''
         return any(any(key in index[r] for r in index)
@@ -296,19 +303,19 @@ 
Source code for datasketch.lshensemble
         Returns:
             bool: Check if the index is empty.
         '''
-        return all(all(index[r].is_empty() for r in index) 
-                   for index in self.indexes) 

+        return all(all(index[r].is_empty() for r in index)
+                   for index in self.indexes)

 
 
 if __name__ == "__main__":
     import numpy as np
     xqs = np.exp(np.linspace(-5, 5, 10))
     threshold = 0.5
-    max_r = 8 
+    max_r = 8
     num_perm = 256
     false_negative_weight, false_positive_weight = 0.5, 0.5
     for xq in xqs:
-        b, r = _optimal_param(threshold, num_perm, max_r, xq, 
+        b, r = _optimal_param(threshold, num_perm, max_r, xq,
                 false_positive_weight, false_negative_weight)
         print("threshold: %.2f, xq: %.3f, b: %d, r: %d" % (threshold, xq, b, r))
 

@@ -323,8 +330,8 @@ 
Source code for datasketch.lshensemble
       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     

 
diff --git a/docs/_modules/datasketch/lshforest.html b/docs/_modules/datasketch/lshforest.html
index a6f765d4..17c50903 100644
--- a/docs/_modules/datasketch/lshforest.html
+++ b/docs/_modules/datasketch/lshforest.html
@@ -13,7 +13,8 @@
     
     
     
-    
+    
+    
     
     
    
@@ -243,8 +244,8 @@ 
Source code for datasketch.lshforest
       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     

 
diff --git a/docs/_modules/datasketch/minhash.html b/docs/_modules/datasketch/minhash.html
index 30734a41..68e8069d 100644
--- a/docs/_modules/datasketch/minhash.html
+++ b/docs/_modules/datasketch/minhash.html
@@ -13,7 +13,8 @@
     
     
     
-    
+    
+    
     
     
    
@@ -320,8 +321,8 @@ 
Source code for datasketch.minhash
       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     

 
diff --git a/docs/_modules/datasketch/weighted_minhash.html b/docs/_modules/datasketch/weighted_minhash.html
index 8745e732..eb029c42 100644
--- a/docs/_modules/datasketch/weighted_minhash.html
+++ b/docs/_modules/datasketch/weighted_minhash.html
@@ -13,7 +13,8 @@
     
     
     
-    
+    
+    
     
     
    
@@ -235,8 +236,8 @@ 
Source code for datasketch.weighted_minhash
       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     

 
diff --git a/docs/_modules/index.html b/docs/_modules/index.html
index 28ed37a1..408b0c64 100644
--- a/docs/_modules/index.html
+++ b/docs/_modules/index.html
@@ -13,7 +13,8 @@
     
     
     
-    
+    
+    
     
     
    
@@ -105,8 +106,8 @@ 
All modules for which code is available

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     

 
diff --git a/docs/_sources/lshensemble.rst.txt b/docs/_sources/lshensemble.rst.txt
index 0fd34772..3ad19b6e 100644
--- a/docs/_sources/lshensemble.rst.txt
+++ b/docs/_sources/lshensemble.rst.txt
@@ -82,8 +82,10 @@ Just like MinHash LSH, LSH Ensemble also works directly with :ref:`minhash` data
         for d in set3:
             m3.update(d.encode('utf8'))
 
-        # Create an LSH Ensemble index with a threshold 
-        lshensemble = MinHashLSHEnsemble(threshold=0.8, num_perm=128)
+        # Create an LSH Ensemble index with threshold and number of partition
+        # settings.
+        lshensemble = MinHashLSHEnsemble(threshold=0.8, num_perm=128, 
+            num_part=32)
 
         # Index takes an iterable of (key, minhash, size)
         lshensemble.index([("m2", m2, len(set2)), ("m3", m3, len(set3))])
@@ -97,13 +99,30 @@ Just like MinHash LSH, LSH Ensemble also works directly with :ref:`minhash` data
         for key in lshensemble.query(m1, len(set1)):
             print(key)
 
-The accuracy of LSH Ensemble increases as the number of permutation functions increases, 
-and the query performance decreases with more permutation functions, as the plot below shows.
+The precision of LSH Ensemble increases with the number of partitions, 
+so does the querying time, as the plot below shows.
 The experiment code can be found in the `benchmark` directory
 of the source code repository.
-
-.. figure:: /_static/lshensemble_benchmark.png
-   :alt: MinHashLSHEnsemble Benchmark
-
 There are other optional parameters that can be used to tune the index to achieve better accuracy or performance.
 See the documentation of :class:`datasketch.MinHashLSHEnsemble` for details.
+
+.. image:: /_static/lshensemble_benchmark_1k/lshensemble_num_perm_256_precision.png
+   :scale: 75 %
+   :align: center
+   :alt: MinHashLSHEnsemble Benchmark Precision
+
+.. image:: /_static/lshensemble_benchmark_1k/lshensemble_num_perm_256_recall.png
+   :scale: 75 %
+   :align: center
+   :alt: MinHashLSHEnsemble Benchmark Recall
+
+.. image:: /_static/lshensemble_benchmark_1k/lshensemble_num_perm_256_fscore.png
+   :scale: 75 %
+   :align: center
+   :alt: MinHashLSHEnsemble Benchmark F-Score
+
+.. image:: /_static/lshensemble_benchmark_1k/lshensemble_num_perm_256_query_time.png
+   :scale: 75 %
+   :align: center
+   :alt: MinHashLSHEnsemble Benchmark Query Time
+
diff --git a/docs/_static/alabaster.css b/docs/_static/alabaster.css
index 4c500fb9..e7fba1a2 100644
--- a/docs/_static/alabaster.css
+++ b/docs/_static/alabaster.css
@@ -166,19 +166,6 @@ div.sphinxsidebar hr {
     width: 50%;
 }
 
-div.sphinxsidebar .badge {
-    border-bottom: none;
-}
-
-div.sphinxsidebar .badge:hover {
-    border-bottom: none;
-}
-
-/* To address an issue with donation coming after search */
-div.sphinxsidebar h3.donation {
-    margin-top: 10px;
-}
-
 /* -- body styles ----------------------------------------------------------- */
 
 a {
@@ -327,7 +314,7 @@ p.admonition-title:after {
 }
 
 pre, tt, code {
-    font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
+    font-family: 'Consolas', 'Menlo', 'Deja Vu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
     font-size: 0.9em;
 }
 
diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js
index b81190bb..63285938 100644
--- a/docs/_static/documentation_options.js
+++ b/docs/_static/documentation_options.js
@@ -7,290 +7,4 @@ var DOCUMENTATION_OPTIONS = {
     HAS_SOURCE: true,
     SOURCELINK_SUFFIX: '.txt',
     NAVIGATION_WITH_KEYS: false,
-    SEARCH_LANGUAGE_STOP_WORDS: ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"]
-};
-
-
-
-/* Non-minified version JS is _stemmer.js if file is provided */ 
-/**
- * Porter Stemmer
- */
-var Stemmer = function() {
-
-  var step2list = {
-    ational: 'ate',
-    tional: 'tion',
-    enci: 'ence',
-    anci: 'ance',
-    izer: 'ize',
-    bli: 'ble',
-    alli: 'al',
-    entli: 'ent',
-    eli: 'e',
-    ousli: 'ous',
-    ization: 'ize',
-    ation: 'ate',
-    ator: 'ate',
-    alism: 'al',
-    iveness: 'ive',
-    fulness: 'ful',
-    ousness: 'ous',
-    aliti: 'al',
-    iviti: 'ive',
-    biliti: 'ble',
-    logi: 'log'
-  };
-
-  var step3list = {
-    icate: 'ic',
-    ative: '',
-    alize: 'al',
-    iciti: 'ic',
-    ical: 'ic',
-    ful: '',
-    ness: ''
-  };
-
-  var c = "[^aeiou]";          // consonant
-  var v = "[aeiouy]";          // vowel
-  var C = c + "[^aeiouy]*";    // consonant sequence
-  var V = v + "[aeiou]*";      // vowel sequence
-
-  var mgr0 = "^(" + C + ")?" + V + C;                      // [C]VC... is m>0
-  var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$";    // [C]VC[V] is m=1
-  var mgr1 = "^(" + C + ")?" + V + C + V + C;              // [C]VCVC... is m>1
-  var s_v   = "^(" + C + ")?" + v;                         // vowel in stem
-
-  this.stemWord = function (w) {
-    var stem;
-    var suffix;
-    var firstch;
-    var origword = w;
-
-    if (w.length < 3)
-      return w;
-
-    var re;
-    var re2;
-    var re3;
-    var re4;
-
-    firstch = w.substr(0,1);
-    if (firstch == "y")
-      w = firstch.toUpperCase() + w.substr(1);
-
-    // Step 1a
-    re = /^(.+?)(ss|i)es$/;
-    re2 = /^(.+?)([^s])s$/;
-
-    if (re.test(w))
-      w = w.replace(re,"$1$2");
-    else if (re2.test(w))
-      w = w.replace(re2,"$1$2");
-
-    // Step 1b
-    re = /^(.+?)eed$/;
-    re2 = /^(.+?)(ed|ing)$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      re = new RegExp(mgr0);
-      if (re.test(fp[1])) {
-        re = /.$/;
-        w = w.replace(re,"");
-      }
-    }
-    else if (re2.test(w)) {
-      var fp = re2.exec(w);
-      stem = fp[1];
-      re2 = new RegExp(s_v);
-      if (re2.test(stem)) {
-        w = stem;
-        re2 = /(at|bl|iz)$/;
-        re3 = new RegExp("([^aeiouylsz])\\1$");
-        re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
-        if (re2.test(w))
-          w = w + "e";
-        else if (re3.test(w)) {
-          re = /.$/;
-          w = w.replace(re,"");
-        }
-        else if (re4.test(w))
-          w = w + "e";
-      }
-    }
-
-    // Step 1c
-    re = /^(.+?)y$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      stem = fp[1];
-      re = new RegExp(s_v);
-      if (re.test(stem))
-        w = stem + "i";
-    }
-
-    // Step 2
-    re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      stem = fp[1];
-      suffix = fp[2];
-      re = new RegExp(mgr0);
-      if (re.test(stem))
-        w = stem + step2list[suffix];
-    }
-
-    // Step 3
-    re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      stem = fp[1];
-      suffix = fp[2];
-      re = new RegExp(mgr0);
-      if (re.test(stem))
-        w = stem + step3list[suffix];
-    }
-
-    // Step 4
-    re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
-    re2 = /^(.+?)(s|t)(ion)$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      stem = fp[1];
-      re = new RegExp(mgr1);
-      if (re.test(stem))
-        w = stem;
-    }
-    else if (re2.test(w)) {
-      var fp = re2.exec(w);
-      stem = fp[1] + fp[2];
-      re2 = new RegExp(mgr1);
-      if (re2.test(stem))
-        w = stem;
-    }
-
-    // Step 5
-    re = /^(.+?)e$/;
-    if (re.test(w)) {
-      var fp = re.exec(w);
-      stem = fp[1];
-      re = new RegExp(mgr1);
-      re2 = new RegExp(meq1);
-      re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
-      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
-        w = stem;
-    }
-    re = /ll$/;
-    re2 = new RegExp(mgr1);
-    if (re.test(w) && re2.test(w)) {
-      re = /.$/;
-      w = w.replace(re,"");
-    }
-
-    // and turn initial Y back to y
-    if (firstch == "y")
-      w = firstch.toLowerCase() + w.substr(1);
-    return w;
-  }
-}
-
-
-
-
-
-var splitChars = (function() {
-    var result = {};
-    var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
-         1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
-         2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
-         2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
-         3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
-         3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
-         4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
-         8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
-         11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
-         43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
-    var i, j, start, end;
-    for (i = 0; i < singles.length; i++) {
-        result[singles[i]] = true;
-    }
-    var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
-         [722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
-         [1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
-         [1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
-         [1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
-         [2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
-         [2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
-         [2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
-         [2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
-         [2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
-         [2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
-         [2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
-         [3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
-         [3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
-         [3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
-         [3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
-         [3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
-         [3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
-         [4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
-         [4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
-         [4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
-         [4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
-         [5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
-         [6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
-         [6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
-         [6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
-         [6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
-         [7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
-         [7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
-         [8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
-         [8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
-         [8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
-         [10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
-         [11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
-         [12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
-         [12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
-         [12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
-         [19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
-         [42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
-         [42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
-         [43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
-         [43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
-         [43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
-         [43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
-         [44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
-         [57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
-         [64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
-         [65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
-         [65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
-    for (i = 0; i < ranges.length; i++) {
-        start = ranges[i][0];
-        end = ranges[i][1];
-        for (j = start; j <= end; j++) {
-            result[j] = true;
-        }
-    }
-    return result;
-})();
-
-function splitQuery(query) {
-    var result = [];
-    var start = -1;
-    for (var i = 0; i < query.length; i++) {
-        if (splitChars[query.charCodeAt(i)]) {
-            if (start !== -1) {
-                result.push(query.slice(start, i));
-                start = -1;
-            }
-        } else if (start === -1) {
-            start = i;
-        }
-    }
-    if (start !== -1) {
-        result.push(query.slice(start));
-    }
-    return result;
-}
-
-
+};
\ No newline at end of file
diff --git a/docs/_static/language_data.js b/docs/_static/language_data.js
new file mode 100644
index 00000000..908a6278
--- /dev/null
+++ b/docs/_static/language_data.js
@@ -0,0 +1,297 @@
+/*
+ * language_data.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * This script contains the language-specific data used by searchtools.js,
+ * namely the list of stopwords, stemmer, scorer and splitter.
+ *
+ * :copyright: Copyright 2007-2018 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
+
+
+/* Non-minified version JS is _stemmer.js if file is provided */ 
+/**
+ * Porter Stemmer
+ */
+var Stemmer = function() {
+
+  var step2list = {
+    ational: 'ate',
+    tional: 'tion',
+    enci: 'ence',
+    anci: 'ance',
+    izer: 'ize',
+    bli: 'ble',
+    alli: 'al',
+    entli: 'ent',
+    eli: 'e',
+    ousli: 'ous',
+    ization: 'ize',
+    ation: 'ate',
+    ator: 'ate',
+    alism: 'al',
+    iveness: 'ive',
+    fulness: 'ful',
+    ousness: 'ous',
+    aliti: 'al',
+    iviti: 'ive',
+    biliti: 'ble',
+    logi: 'log'
+  };
+
+  var step3list = {
+    icate: 'ic',
+    ative: '',
+    alize: 'al',
+    iciti: 'ic',
+    ical: 'ic',
+    ful: '',
+    ness: ''
+  };
+
+  var c = "[^aeiou]";          // consonant
+  var v = "[aeiouy]";          // vowel
+  var C = c + "[^aeiouy]*";    // consonant sequence
+  var V = v + "[aeiou]*";      // vowel sequence
+
+  var mgr0 = "^(" + C + ")?" + V + C;                      // [C]VC... is m>0
+  var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$";    // [C]VC[V] is m=1
+  var mgr1 = "^(" + C + ")?" + V + C + V + C;              // [C]VCVC... is m>1
+  var s_v   = "^(" + C + ")?" + v;                         // vowel in stem
+
+  this.stemWord = function (w) {
+    var stem;
+    var suffix;
+    var firstch;
+    var origword = w;
+
+    if (w.length < 3)
+      return w;
+
+    var re;
+    var re2;
+    var re3;
+    var re4;
+
+    firstch = w.substr(0,1);
+    if (firstch == "y")
+      w = firstch.toUpperCase() + w.substr(1);
+
+    // Step 1a
+    re = /^(.+?)(ss|i)es$/;
+    re2 = /^(.+?)([^s])s$/;
+
+    if (re.test(w))
+      w = w.replace(re,"$1$2");
+    else if (re2.test(w))
+      w = w.replace(re2,"$1$2");
+
+    // Step 1b
+    re = /^(.+?)eed$/;
+    re2 = /^(.+?)(ed|ing)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      re = new RegExp(mgr0);
+      if (re.test(fp[1])) {
+        re = /.$/;
+        w = w.replace(re,"");
+      }
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1];
+      re2 = new RegExp(s_v);
+      if (re2.test(stem)) {
+        w = stem;
+        re2 = /(at|bl|iz)$/;
+        re3 = new RegExp("([^aeiouylsz])\\1$");
+        re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+        if (re2.test(w))
+          w = w + "e";
+        else if (re3.test(w)) {
+          re = /.$/;
+          w = w.replace(re,"");
+        }
+        else if (re4.test(w))
+          w = w + "e";
+      }
+    }
+
+    // Step 1c
+    re = /^(.+?)y$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(s_v);
+      if (re.test(stem))
+        w = stem + "i";
+    }
+
+    // Step 2
+    re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step2list[suffix];
+    }
+
+    // Step 3
+    re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step3list[suffix];
+    }
+
+    // Step 4
+    re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
+    re2 = /^(.+?)(s|t)(ion)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      if (re.test(stem))
+        w = stem;
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1] + fp[2];
+      re2 = new RegExp(mgr1);
+      if (re2.test(stem))
+        w = stem;
+    }
+
+    // Step 5
+    re = /^(.+?)e$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      re2 = new RegExp(meq1);
+      re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
+        w = stem;
+    }
+    re = /ll$/;
+    re2 = new RegExp(mgr1);
+    if (re.test(w) && re2.test(w)) {
+      re = /.$/;
+      w = w.replace(re,"");
+    }
+
+    // and turn initial Y back to y
+    if (firstch == "y")
+      w = firstch.toLowerCase() + w.substr(1);
+    return w;
+  }
+}
+
+
+
+
+
+var splitChars = (function() {
+    var result = {};
+    var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
+         1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
+         2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
+         2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
+         3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
+         3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
+         4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
+         8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
+         11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
+         43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
+    var i, j, start, end;
+    for (i = 0; i < singles.length; i++) {
+        result[singles[i]] = true;
+    }
+    var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
+         [722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
+         [1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
+         [1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
+         [1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
+         [2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
+         [2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
+         [2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
+         [2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
+         [2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
+         [2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
+         [2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
+         [3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
+         [3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
+         [3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
+         [3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
+         [3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
+         [3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
+         [4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
+         [4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
+         [4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
+         [4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
+         [5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
+         [6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
+         [6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
+         [6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
+         [6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
+         [7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
+         [7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
+         [8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
+         [8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
+         [8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
+         [10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
+         [11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
+         [12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
+         [12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
+         [12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
+         [19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
+         [42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
+         [42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
+         [43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
+         [43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
+         [43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
+         [43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
+         [44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
+         [57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
+         [64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
+         [65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
+         [65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
+    for (i = 0; i < ranges.length; i++) {
+        start = ranges[i][0];
+        end = ranges[i][1];
+        for (j = start; j <= end; j++) {
+            result[j] = true;
+        }
+    }
+    return result;
+})();
+
+function splitQuery(query) {
+    var result = [];
+    var start = -1;
+    for (var i = 0; i < query.length; i++) {
+        if (splitChars[query.charCodeAt(i)]) {
+            if (start !== -1) {
+                result.push(query.slice(start, i));
+                start = -1;
+            }
+        } else if (start === -1) {
+            start = i;
+        }
+    }
+    if (start !== -1) {
+        result.push(query.slice(start));
+    }
+    return result;
+}
+
+
diff --git a/docs/_static/lshensemble_benchmark.png b/docs/_static/lshensemble_benchmark.png
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-    
+    
+    
     
     
     
@@ -909,7 +910,7 @@ 
MinHash LSH¶

 

 

-class datasketch.experimental.aio.lsh.AsyncMinHashLSH(threshold: float = 0.9, num_perm: int = 128, weights: Tuple[float, float] = (0.5, 0.5), params: Tuple[int, int] = None, storage_config: Dict[KT, VT] = None)[source]¶

+class datasketch.experimental.aio.lsh.AsyncMinHashLSH(threshold: float = 0.9, num_perm: int = 128, weights: Tuple[float, float] = (0.5, 0.5), params: Tuple[int, int] = None, storage_config: Dict = None)[source]¶
 
Asynchronous MinHashLSH index.

 @@ -943,7 +944,7 @@ 
Asynchronous MinHash LSH
 

-__init__(threshold: float = 0.9, num_perm: int = 128, weights: Tuple[float, float] = (0.5, 0.5), params: Tuple[int, int] = None, storage_config: Dict[KT, VT] = None)[source]¶

+__init__(threshold: float = 0.9, num_perm: int = 128, weights: Tuple[float, float] = (0.5, 0.5), params: Tuple[int, int] = None, storage_config: Dict = None)[source]¶
 
Initialize self.  See help(type(self)) for accurate signature.

 

 
@@ -1587,8 +1588,8 @@ 
HyperLogLog++Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
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+    
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@@ -453,8 +454,8 @@ 
W

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     
 
diff --git a/docs/hyperloglog.html b/docs/hyperloglog.html
index e5d8bb67..283a6457 100644
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+++ b/docs/hyperloglog.html
@@ -13,7 +13,8 @@
     
     
     
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+    
+    
     
     
     
@@ -161,8 +162,8 @@ 
Quick search

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
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-    
+    
+    
     
     
     
@@ -177,8 +178,8 @@ 
InstallSphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
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+    
+    
     
     
     
@@ -364,8 +365,8 @@ 
Connecting to Existing MinHash LSHSphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
       |
       
     
     
-    
+    
+    
     
     
     
@@ -159,8 +160,10 @@ 
LSH for Containmentfor d in set3:
     m3.update(d.encode('utf8'))
 
-# Create an LSH Ensemble index with a threshold
-lshensemble = MinHashLSHEnsemble(threshold=0.8, num_perm=128)
+# Create an LSH Ensemble index with threshold and number of partition
+# settings.
+lshensemble = MinHashLSHEnsemble(threshold=0.8, num_perm=128,
+    num_part=32)
 
 # Index takes an iterable of (key, minhash, size)
 lshensemble.index([("m2", m2, len(set2)), ("m3", m3, len(set3))])
@@ -175,15 +178,16 @@ 
LSH for Containmentprint(key)
 
 
-
The accuracy of LSH Ensemble increases as the number of permutation functions increases,
-and the query performance decreases with more permutation functions, as the plot below shows.
+
The precision of LSH Ensemble increases with the number of partitions,
+so does the querying time, as the plot below shows.
 The experiment code can be found in the benchmark directory
-of the source code repository.

-

-MinHashLSHEnsemble Benchmark
-

-
There are other optional parameters that can be used to tune the index to achieve better accuracy or performance.
+of the source code repository.
+There are other optional parameters that can be used to tune the index to achieve better accuracy or performance.
 See the documentation of datasketch.MinHashLSHEnsemble for details.

+MinHashLSHEnsemble Benchmark Precision
+MinHashLSHEnsemble Benchmark Recall
+MinHashLSHEnsemble Benchmark F-Score
+MinHashLSHEnsemble Benchmark Query Time
 
 
 
@@ -198,8 +202,8 @@ 
LSH for ContainmentSphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
       |
       
     
     
-    
+    
+    
     
     
     
@@ -181,8 +182,8 @@ 
Quick search

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
       |
       
     
     
-    
+    
+    
     
     
     
@@ -166,8 +167,8 @@ 
Quick search

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
       |
       
     
     
-    
+    
+    
     
     
     
@@ -115,8 +116,8 @@ 
Search

       ©2018, Eric Zhu.
       
       |
-      Powered by Sphinx 1.8.1
-      & Alabaster 0.7.12
+      Powered by Sphinx 1.8.3
+      & Alabaster 0.7.11
       
     
 
diff --git a/docs/searchindex.js b/docs/searchindex.js
index 12ea704a..bd265a4d 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["documentation","hyperloglog","index","lsh","lshensemble","lshforest","minhash","weightedminhash"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.cpp":1,"sphinx.domains.javascript":1,"sphinx.domains.math":1,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,"sphinx.ext.viewcode":1,sphinx:55},filenames:["documentation.rst","hyperloglog.rst","index.rst","lsh.rst","lshensemble.rst","lshforest.rst","minhash.rst","weightedminhash.rst"],objects:{"datasketch.HyperLogLog":{__eq__:[0,1,1,""],__init__:[0,1,1,""],__len__:[0,1,1,""],clear:[0,1,1,""],copy:[0,1,1,""],count:[0,1,1,""],digest:[0,1,1,""],is_empty:[0,1,1,""],merge:[0,1,1,""],update:[0,1,1,""]},"datasketch.HyperLogLogPlusPlus":{__weakref__:[0,2,1,""],count:[0,1,1,""]},"datasketch.LeanMinHash":{__hash__:[0,1,1,""],__init__:[0,1,1,""],bytesize:[0,1,1,""],copy:[0,1,1,""],deserialize:[0,3,1,""],serialize:[0,1,1,""],union:[0,3,1,""],update:[0,1,1,""]},"datasketch.MinHash":{__eq__:[0,1,1,""],__init__:[0,1,1,""],__len__:[0,1,1,""],__weakref__:[0,2,1,""],clear:[0,1,1,""],copy:[0,1,1,""],count:[0,1,1,""],digest:[0,1,1,""],is_empty:[0,1,1,""],jaccard:[0,1,1,""],merge:[0,1,1,""],union:[0,3,1,""],update:[0,1,1,""]},"datasketch.MinHashLSH":{__contains__:[0,1,1,""],__init__:[0,1,1,""],__weakref__:[0,2,1,""],get_counts:[0,1,1,""],get_subset_counts:[0,1,1,""],insert:[0,1,1,""],insertion_session:[0,1,1,""],is_empty:[0,1,1,""],query:[0,1,1,""],remove:[0,1,1,""]},"datasketch.MinHashLSHEnsemble":{__contains__:[0,1,1,""],__init__:[0,1,1,""],__weakref__:[0,2,1,""],index:[0,1,1,""],is_empty:[0,1,1,""],query:[0,1,1,""]},"datasketch.MinHashLSHForest":{__contains__:[0,1,1,""],__init__:[0,1,1,""],__weakref__:[0,2,1,""],add:[0,1,1,""],index:[0,1,1,""],is_empty:[0,1,1,""],query:[0,1,1,""]},"datasketch.WeightedMinHash":{__eq__:[0,1,1,""],__init__:[0,1,1,""],__len__:[0,1,1,""],__weakref__:[0,2,1,""],copy:[0,1,1,""],digest:[0,1,1,""],jaccard:[0,1,1,""]},"datasketch.WeightedMinHashGenerator":{__init__:[0,1,1,""],__weakref__:[0,2,1,""],minhash:[0,1,1,""]},"datasketch.experimental.aio.lsh":{AsyncMinHashLSH:[0,0,1,""]},"datasketch.experimental.aio.lsh.AsyncMinHashLSH":{__init__:[0,1,1,""],__weakref__:[0,2,1,""],close:[0,1,1,""],delete_session:[0,1,1,""],get_counts:[0,1,1,""],get_subset_counts:[0,1,1,""],has_key:[0,1,1,""],insert:[0,1,1,""],insertion_session:[0,1,1,""],is_empty:[0,1,1,""],query:[0,1,1,""],remove:[0,1,1,""]},datasketch:{HyperLogLog:[0,0,1,""],HyperLogLogPlusPlus:[0,0,1,""],LeanMinHash:[0,0,1,""],MinHash:[0,0,1,""],MinHashLSH:[0,0,1,""],MinHashLSHEnsemble:[0,0,1,""],MinHashLSHForest:[0,0,1,""],WeightedMinHash:[0,0,1,""],WeightedMinHashGenerator:[0,0,1,""]}},objnames:{"0":["py","class","Python 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