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| <li class="toctree-l1 current"><a class="reference internal" href="index.html">Quantiles Sketches</a><ul class="current"> |
| <li class="toctree-l2"><a class="reference internal" href="kll.html">KLL Sketch</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="req.html">Relative Error Quantiles (REQ) Sketch</a></li> |
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| <li class="toctree-l2 current"><a class="current reference internal" href="#">Quantiles Sketch (Deprecated)</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="#datasketches.quantiles_ints_sketch"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch</span></code></a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.deserialize"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.deserialize()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_normalized_rank_error()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.__init__"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.__init__()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_cdf"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_cdf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_max_value"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_max_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_min_value"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_min_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_pmf"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_pmf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_quantile"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_quantile</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_quantiles"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_quantiles</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.get_rank"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.get_rank</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.is_empty"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.is_empty</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.is_estimation_mode"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.is_estimation_mode</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.k"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.k</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.merge"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.merge</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.n"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.n</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.normalized_rank_error</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.num_retained"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.num_retained</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.serialize"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.serialize</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.to_string"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.to_string</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_ints_sketch.update"><code class="docutils literal notranslate"><span class="pre">quantiles_ints_sketch.update</span></code></a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="#datasketches.quantiles_floats_sketch"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch</span></code></a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.deserialize"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.deserialize()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_normalized_rank_error()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.__init__"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.__init__()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_cdf"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_cdf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_max_value"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_max_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_min_value"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_min_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_pmf"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_pmf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_quantile"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_quantile</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_quantiles"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_quantiles</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.get_rank"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.get_rank</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.is_empty"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.is_empty</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.is_estimation_mode"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.is_estimation_mode</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.k"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.k</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.merge"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.merge</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.n"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.n</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.normalized_rank_error</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.num_retained"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.num_retained</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.serialize"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.serialize</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.to_string"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.to_string</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_floats_sketch.update"><code class="docutils literal notranslate"><span class="pre">quantiles_floats_sketch.update</span></code></a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch</span></code></a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.deserialize"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.deserialize()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_normalized_rank_error()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.__init__"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.__init__()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_cdf"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_cdf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_max_value"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_max_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_min_value"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_min_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_pmf"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_pmf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_quantile"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_quantile</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_quantiles"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_quantiles</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.get_rank"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.get_rank</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.is_empty"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.is_empty</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.is_estimation_mode"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.is_estimation_mode</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.k"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.k</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.merge"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.merge</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.n"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.n</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.normalized_rank_error</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.num_retained"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.num_retained</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.serialize"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.serialize</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.to_string"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.to_string</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch.update"><code class="docutils literal notranslate"><span class="pre">quantiles_doubles_sketch.update</span></code></a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="#datasketches.quantiles_items_sketch"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch</span></code></a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.deserialize"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.deserialize()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_normalized_rank_error()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.__init__"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.__init__()</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_cdf"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_cdf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_max_value"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_max_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_min_value"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_min_value</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_pmf"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_pmf</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_quantile"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_quantile</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_quantiles"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_quantiles</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.get_rank"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.get_rank</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.is_empty"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.is_empty</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.is_estimation_mode"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.is_estimation_mode</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.k"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.k</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.merge"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.merge</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.n"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.n</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.normalized_rank_error"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.normalized_rank_error</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.num_retained"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.num_retained</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.serialize"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.serialize</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.to_string"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.to_string</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="#datasketches.quantiles_items_sketch.update"><code class="docutils literal notranslate"><span class="pre">quantiles_items_sketch.update</span></code></a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../frequency/index.html">Frequency Sketches</a></li> |
| </ul> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../vector/index.html">Vector Sketches</a></li> |
| </ul> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../sampling/index.html">Random Sampling Sketches</a></li> |
| </ul> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../helper/index.html">Helper Classes</a></li> |
| </ul> |
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| <li class="breadcrumb-item active">Quantiles Sketch (Deprecated)</li> |
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| |
| <section id="quantiles-sketch-deprecated"> |
| <h1>Quantiles Sketch (Deprecated)<a class="headerlink" href="#quantiles-sketch-deprecated" title="Link to this heading"></a></h1> |
| <p>This is a deprecated quantiles sketch that is included for cross-language compatibility. |
| Most new projects will favor the KLL sketch over this one, or the REQ sketch for higher accuracy |
| at the very edge of a distribution.</p> |
| <p>This is a stochastic streaming sketch that enables near-real time analysis of the |
| approximate distribution from a very large stream in a single pass. |
| The analysis is obtained using <cite>get_rank()</cite> and <cite>get_quantile()</cite> functions, |
| the Probability Mass Function from <cite>get_pmf()`</cite> and the Cumulative Distribution Function from <cite>get_cdf</cite>.</p> |
| <p>Consider a large stream of one million values such as packet sizes coming into a network node. |
| The natural rank of any specific size value is its index in the hypothetical sorted |
| array of values. |
| The normalized rank is the natural rank divided by the stream size, |
| in this case one million. |
| The value corresponding to the normalized rank of <cite>0.5</cite> represents the 50th percentile or median |
| value of the distribution, or <cite>get_quantile(0.5)</cite>. |
| Similarly, the 95th percentile is obtained from <cite>get_quantile(0.95)</cite>.</p> |
| <p>From the min and max values, for example, 1 and 1000 bytes, |
| you can obtain the PMF from <cite>get_pmf(100, 500, 900)</cite> that will result in an array of |
| 4 fractional values such as {.4, .3, .2, .1}, which means that |
| 40% of the values were < 100, |
| 30% of the values were ≥ 100 and < 500, |
| 20% of the values were ≥ 500 and < 900, and |
| 10% of the values were ≥ 900. |
| A frequency histogram can be obtained by multiplying these fractions by <cite>get_n()</cite>, |
| which is the total count of values received. |
| The <cite>get_cdf()`</cite> works similarly, but produces the cumulative distribution instead.</p> |
| <p>As of November 2021, this implementation produces serialized sketches which are binary-compatible |
| with the equivalent Java implementation only when template parameter T = double |
| (64-bit double precision values).</p> |
| <p>The accuracy of this sketch is a function of the configured value <cite>k</cite>, which also affects |
| the overall size of the sketch. Accuracy of this quantile sketch is always with respect to |
| the normalized rank. A <cite>k</cite> of 128 produces a normalized, rank error of about 1.7%. |
| For example, the median item returned from <cite>get_quantile(0.5)</cite> will be between the actual items |
| from the hypothetically sorted array of input items at normalized ranks of 0.483 and 0.517, with |
| a confidence of about 99%.</p> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <p>For the <a class="reference internal" href="#datasketches.quantiles_items_sketch" title="datasketches.quantiles_items_sketch"><code class="xref py py-class docutils literal notranslate"><span class="pre">quantiles_items_sketch</span></code></a>, objects must be comparable with <code class="docutils literal notranslate"><span class="pre">__lt__</span></code>.</p> |
| </div> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <p>Serializing and deserializing a <a class="reference internal" href="#datasketches.quantiles_items_sketch" title="datasketches.quantiles_items_sketch"><code class="xref py py-class docutils literal notranslate"><span class="pre">quantiles_items_sketch</span></code></a> requires the use of a <a class="reference internal" href="../helper/serde.html#datasketches.PyObjectSerDe" title="datasketches.PyObjectSerDe"><code class="xref py py-class docutils literal notranslate"><span class="pre">PyObjectSerDe</span></code></a>.</p> |
| </div> |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch"> |
| <em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">quantiles_ints_sketch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#datasketches.quantiles_ints_sketch" title="Link to this definition"></a></dt> |
| <dd><p class="rubric">Static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.deserialize"> |
| <span class="sig-name descname"><span class="pre">deserialize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bytes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bytes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#datasketches.quantiles_ints_sketch" title="_datasketches.quantiles_ints_sketch"><span class="pre">_datasketches.quantiles_ints_sketch</span></a></span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.deserialize" title="Link to this definition"></a></dt> |
| <dd><p>Deserializes the sketch from a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">get_normalized_rank_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">as_pmf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error given parameters k and the pmf flag. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <p class="rubric">Non-static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.__init__"> |
| <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.__init__" title="Link to this definition"></a></dt> |
| <dd><p>Creates a classic quantiles sketch instance with the given value of k.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><p><strong>k</strong> (<em>int</em><em>, </em><em>optional</em>) – Controls the size/accuracy trade-off of the sketch. Default is 128.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_cdf"> |
| <span class="sig-name descname"><span class="pre">get_cdf</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_cdf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Cumulative Distribution Function (CDF), which is the cumulative analog of the PMF, of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_max_value"> |
| <span class="sig-name descname"><span class="pre">get_max_value</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_max_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the maximum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_min_value"> |
| <span class="sig-name descname"><span class="pre">get_min_value</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_min_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the minimum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_pmf"> |
| <span class="sig-name descname"><span class="pre">get_pmf</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_pmf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_quantile"> |
| <span class="sig-name descname"><span class="pre">get_quantile</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_quantile" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the data value associated with the given rank in a hypothetical sorted version of the input stream so far. |
| For quantiles_floats_sketch: if the sketch is empty this returns nan. For quantiles_ints_sketch: if the sketch is empty this throws a RuntimeError.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_quantiles"> |
| <span class="sig-name descname"><span class="pre">get_quantiles</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_quantiles" title="Link to this definition"></a></dt> |
| <dd><p>This returns an array that could have been generated by using get_quantile() for each normalized rank separately. |
| If the sketch is empty this returns an empty vector.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.get_rank"> |
| <span class="sig-name descname"><span class="pre">get_rank</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.get_rank" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the normalized rank of the given value from 0 to 1, inclusive. |
| The resulting approximation has a probabilistic guarantee that can be obtained from the get_normalized_rank_error(False) function. |
| With the parameter inclusive=true the weight of the given value is included into the rank.Otherwise the rank equals the sum of the weights of values less than the given value. |
| If the sketch is empty this returns nan.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.is_empty"> |
| <span class="sig-name descname"><span class="pre">is_empty</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.is_empty" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is empty, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.is_estimation_mode"> |
| <span class="sig-name descname"><span class="pre">is_estimation_mode</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.is_estimation_mode" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is in estimation mode, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.k"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">k</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.k" title="Link to this definition"></a></dt> |
| <dd><p>The configured parameter k</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.merge"> |
| <span class="sig-name descname"><span class="pre">merge</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.merge" title="Link to this definition"></a></dt> |
| <dd><p>Merges the provided sketch into this one</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.n"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.n" title="Link to this definition"></a></dt> |
| <dd><p>The length of the input stream</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">normalized_rank_error</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error for this sketch. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.num_retained"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">num_retained</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.num_retained" title="Link to this definition"></a></dt> |
| <dd><p>The number of retained items (samples) in the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.serialize"> |
| <span class="sig-name descname"><span class="pre">serialize</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.serialize" title="Link to this definition"></a></dt> |
| <dd><p>Serializes the sketch into a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.to_string"> |
| <span class="sig-name descname"><span class="pre">to_string</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.to_string" title="Link to this definition"></a></dt> |
| <dd><p>Produces a string summary of the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_ints_sketch.update"> |
| <span class="sig-name descname"><span class="pre">update</span></span><a class="headerlink" href="#datasketches.quantiles_ints_sketch.update" title="Link to this definition"></a></dt> |
| <dd><p>Overloaded function.</p> |
| <ol class="arabic simple"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">item:</span> <span class="pre">int)</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the given value</p> |
| <ol class="arabic simple" start="2"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">array:</span> <span class="pre">ndarray[dtype=int32])</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the values in the given array</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch"> |
| <em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">quantiles_floats_sketch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#datasketches.quantiles_floats_sketch" title="Link to this definition"></a></dt> |
| <dd><p class="rubric">Static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.deserialize"> |
| <span class="sig-name descname"><span class="pre">deserialize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bytes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bytes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#datasketches.quantiles_floats_sketch" title="_datasketches.quantiles_floats_sketch"><span class="pre">_datasketches.quantiles_floats_sketch</span></a></span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.deserialize" title="Link to this definition"></a></dt> |
| <dd><p>Deserializes the sketch from a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">get_normalized_rank_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">as_pmf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error given parameters k and the pmf flag. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <p class="rubric">Non-static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.__init__"> |
| <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.__init__" title="Link to this definition"></a></dt> |
| <dd><p>Creates a classic quantiles sketch instance with the given value of k.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><p><strong>k</strong> (<em>int</em><em>, </em><em>optional</em>) – Controls the size/accuracy trade-off of the sketch. Default is 128.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_cdf"> |
| <span class="sig-name descname"><span class="pre">get_cdf</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_cdf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Cumulative Distribution Function (CDF), which is the cumulative analog of the PMF, of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_max_value"> |
| <span class="sig-name descname"><span class="pre">get_max_value</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_max_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the maximum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_min_value"> |
| <span class="sig-name descname"><span class="pre">get_min_value</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_min_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the minimum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_pmf"> |
| <span class="sig-name descname"><span class="pre">get_pmf</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_pmf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_quantile"> |
| <span class="sig-name descname"><span class="pre">get_quantile</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_quantile" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the data value associated with the given rank in a hypothetical sorted version of the input stream so far. |
| For quantiles_floats_sketch: if the sketch is empty this returns nan. For quantiles_ints_sketch: if the sketch is empty this throws a RuntimeError.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_quantiles"> |
| <span class="sig-name descname"><span class="pre">get_quantiles</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_quantiles" title="Link to this definition"></a></dt> |
| <dd><p>This returns an array that could have been generated by using get_quantile() for each normalized rank separately. |
| If the sketch is empty this returns an empty vector.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.get_rank"> |
| <span class="sig-name descname"><span class="pre">get_rank</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.get_rank" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the normalized rank of the given value from 0 to 1, inclusive. |
| The resulting approximation has a probabilistic guarantee that can be obtained from the get_normalized_rank_error(False) function. |
| With the parameter inclusive=true the weight of the given value is included into the rank.Otherwise the rank equals the sum of the weights of values less than the given value. |
| If the sketch is empty this returns nan.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.is_empty"> |
| <span class="sig-name descname"><span class="pre">is_empty</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.is_empty" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is empty, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.is_estimation_mode"> |
| <span class="sig-name descname"><span class="pre">is_estimation_mode</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.is_estimation_mode" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is in estimation mode, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.k"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">k</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.k" title="Link to this definition"></a></dt> |
| <dd><p>The configured parameter k</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.merge"> |
| <span class="sig-name descname"><span class="pre">merge</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.merge" title="Link to this definition"></a></dt> |
| <dd><p>Merges the provided sketch into this one</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.n"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.n" title="Link to this definition"></a></dt> |
| <dd><p>The length of the input stream</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">normalized_rank_error</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error for this sketch. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.num_retained"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">num_retained</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.num_retained" title="Link to this definition"></a></dt> |
| <dd><p>The number of retained items (samples) in the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.serialize"> |
| <span class="sig-name descname"><span class="pre">serialize</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.serialize" title="Link to this definition"></a></dt> |
| <dd><p>Serializes the sketch into a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.to_string"> |
| <span class="sig-name descname"><span class="pre">to_string</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.to_string" title="Link to this definition"></a></dt> |
| <dd><p>Produces a string summary of the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_floats_sketch.update"> |
| <span class="sig-name descname"><span class="pre">update</span></span><a class="headerlink" href="#datasketches.quantiles_floats_sketch.update" title="Link to this definition"></a></dt> |
| <dd><p>Overloaded function.</p> |
| <ol class="arabic simple"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">item:</span> <span class="pre">float)</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the given value</p> |
| <ol class="arabic simple" start="2"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">array:</span> <span class="pre">ndarray[dtype=float32])</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the values in the given array</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch"> |
| <em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">quantiles_doubles_sketch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch" title="Link to this definition"></a></dt> |
| <dd><p class="rubric">Static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.deserialize"> |
| <span class="sig-name descname"><span class="pre">deserialize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bytes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bytes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#datasketches.quantiles_doubles_sketch" title="_datasketches.quantiles_doubles_sketch"><span class="pre">_datasketches.quantiles_doubles_sketch</span></a></span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.deserialize" title="Link to this definition"></a></dt> |
| <dd><p>Deserializes the sketch from a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">get_normalized_rank_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">as_pmf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error given parameters k and the pmf flag. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <p class="rubric">Non-static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.__init__"> |
| <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.__init__" title="Link to this definition"></a></dt> |
| <dd><p>Creates a classic quantiles sketch instance with the given value of k.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><p><strong>k</strong> (<em>int</em><em>, </em><em>optional</em>) – Controls the size/accuracy trade-off of the sketch. Default is 128.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_cdf"> |
| <span class="sig-name descname"><span class="pre">get_cdf</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_cdf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Cumulative Distribution Function (CDF), which is the cumulative analog of the PMF, of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_max_value"> |
| <span class="sig-name descname"><span class="pre">get_max_value</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_max_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the maximum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_min_value"> |
| <span class="sig-name descname"><span class="pre">get_min_value</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_min_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the minimum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_pmf"> |
| <span class="sig-name descname"><span class="pre">get_pmf</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_pmf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_quantile"> |
| <span class="sig-name descname"><span class="pre">get_quantile</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_quantile" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the data value associated with the given rank in a hypothetical sorted version of the input stream so far. |
| For quantiles_floats_sketch: if the sketch is empty this returns nan. For quantiles_ints_sketch: if the sketch is empty this throws a RuntimeError.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_quantiles"> |
| <span class="sig-name descname"><span class="pre">get_quantiles</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_quantiles" title="Link to this definition"></a></dt> |
| <dd><p>This returns an array that could have been generated by using get_quantile() for each normalized rank separately. |
| If the sketch is empty this returns an empty vector.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.get_rank"> |
| <span class="sig-name descname"><span class="pre">get_rank</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.get_rank" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the normalized rank of the given value from 0 to 1, inclusive. |
| The resulting approximation has a probabilistic guarantee that can be obtained from the get_normalized_rank_error(False) function. |
| With the parameter inclusive=true the weight of the given value is included into the rank.Otherwise the rank equals the sum of the weights of values less than the given value. |
| If the sketch is empty this returns nan.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.is_empty"> |
| <span class="sig-name descname"><span class="pre">is_empty</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.is_empty" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is empty, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.is_estimation_mode"> |
| <span class="sig-name descname"><span class="pre">is_estimation_mode</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.is_estimation_mode" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is in estimation mode, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.k"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">k</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.k" title="Link to this definition"></a></dt> |
| <dd><p>The configured parameter k</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.merge"> |
| <span class="sig-name descname"><span class="pre">merge</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.merge" title="Link to this definition"></a></dt> |
| <dd><p>Merges the provided sketch into this one</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.n"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.n" title="Link to this definition"></a></dt> |
| <dd><p>The length of the input stream</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">normalized_rank_error</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error for this sketch. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.num_retained"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">num_retained</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.num_retained" title="Link to this definition"></a></dt> |
| <dd><p>The number of retained items (samples) in the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.serialize"> |
| <span class="sig-name descname"><span class="pre">serialize</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.serialize" title="Link to this definition"></a></dt> |
| <dd><p>Serializes the sketch into a bytes object.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.to_string"> |
| <span class="sig-name descname"><span class="pre">to_string</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.to_string" title="Link to this definition"></a></dt> |
| <dd><p>Produces a string summary of the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_doubles_sketch.update"> |
| <span class="sig-name descname"><span class="pre">update</span></span><a class="headerlink" href="#datasketches.quantiles_doubles_sketch.update" title="Link to this definition"></a></dt> |
| <dd><p>Overloaded function.</p> |
| <ol class="arabic simple"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">item:</span> <span class="pre">float)</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the given value</p> |
| <ol class="arabic simple" start="2"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">update(self,</span> <span class="pre">array:</span> <span class="pre">ndarray[dtype=float64])</span> <span class="pre">-></span> <span class="pre">None</span></code></p></li> |
| </ol> |
| <p>Updates the sketch with the values in the given array</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch"> |
| <em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">quantiles_items_sketch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#datasketches.quantiles_items_sketch" title="Link to this definition"></a></dt> |
| <dd><p class="rubric">Static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.deserialize"> |
| <span class="sig-name descname"><span class="pre">deserialize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bytes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bytes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">serde</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../helper/serde.html#datasketches.PyObjectSerDe" title="_datasketches.PyObjectSerDe"><span class="pre">_datasketches.PyObjectSerDe</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#datasketches.quantiles_items_sketch" title="_datasketches.quantiles_items_sketch"><span class="pre">_datasketches.quantiles_items_sketch</span></a></span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.deserialize" title="Link to this definition"></a></dt> |
| <dd><p>Deserializes the sketch from a bytes object using the provided serde.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">get_normalized_rank_error</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">as_pmf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error given parameters k and the pmf flag. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <p class="rubric">Non-static Methods:</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.__init__"> |
| <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">128</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.__init__" title="Link to this definition"></a></dt> |
| <dd><p>Creates a classic quantiles sketch instance with the given value of k.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><p><strong>k</strong> (<em>int</em><em>, </em><em>optional</em>) – Controls the size/accuracy trade-off of the sketch. Default is 128.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_cdf"> |
| <span class="sig-name descname"><span class="pre">get_cdf</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_cdf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Cumulative Distribution Function (CDF), which is the cumulative analog of the PMF, of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_max_value"> |
| <span class="sig-name descname"><span class="pre">get_max_value</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_max_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the maximum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_min_value"> |
| <span class="sig-name descname"><span class="pre">get_min_value</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_min_value" title="Link to this definition"></a></dt> |
| <dd><p>Returns the minimum value from the stream. If empty, quantiles_floats_sketch returns nan; quantiles_ints_sketch throws a RuntimeError</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_pmf"> |
| <span class="sig-name descname"><span class="pre">get_pmf</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_pmf" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of split points (values). |
| The resulting approximations have a probabilistic guarantee that can be obtained from the get_normalized_rank_error(True) function. |
| If the sketch is empty this returns an empty vector. |
| split_points is an array of m unique, monotonically increasing float values that divide the real number line into m+1 consecutive disjoint intervals. |
| The definition of an ‘interval’ is inclusive of the left split point (or minimum value) and exclusive of the right split point, with the exception that the last interval will include the maximum value. |
| It is not necessary to include either the min or max values in these split points.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_quantile"> |
| <span class="sig-name descname"><span class="pre">get_quantile</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_quantile" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the data value associated with the given rank in a hypothetical sorted version of the input stream so far. |
| For quantiles_floats_sketch: if the sketch is empty this returns nan. For quantiles_ints_sketch: if the sketch is empty this throws a RuntimeError.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_quantiles"> |
| <span class="sig-name descname"><span class="pre">get_quantiles</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_quantiles" title="Link to this definition"></a></dt> |
| <dd><p>This returns an array that could have been generated by using get_quantile() for each normalized rank separately. |
| If the sketch is empty this returns an empty vector.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.get_rank"> |
| <span class="sig-name descname"><span class="pre">get_rank</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.get_rank" title="Link to this definition"></a></dt> |
| <dd><p>Returns an approximation to the normalized rank of the given value from 0 to 1, inclusive. |
| The resulting approximation has a probabilistic guarantee that can be obtained from the get_normalized_rank_error(False) function. |
| With the parameter inclusive=true the weight of the given value is included into the rank.Otherwise the rank equals the sum of the weights of values less than the given value. |
| If the sketch is empty this returns nan.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.is_empty"> |
| <span class="sig-name descname"><span class="pre">is_empty</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.is_empty" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is empty, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.is_estimation_mode"> |
| <span class="sig-name descname"><span class="pre">is_estimation_mode</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.is_estimation_mode" title="Link to this definition"></a></dt> |
| <dd><p>Returns True if the sketch is in estimation mode, otherwise False</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.k"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">k</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.k" title="Link to this definition"></a></dt> |
| <dd><p>The configured parameter k</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.merge"> |
| <span class="sig-name descname"><span class="pre">merge</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.merge" title="Link to this definition"></a></dt> |
| <dd><p>Merges the provided sketch into this one</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.n"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.n" title="Link to this definition"></a></dt> |
| <dd><p>The length of the input stream</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.normalized_rank_error"> |
| <span class="sig-name descname"><span class="pre">normalized_rank_error</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.normalized_rank_error" title="Link to this definition"></a></dt> |
| <dd><p>Gets the normalized rank error for this sketch. |
| If pmf is True, returns the ‘double-sided’ normalized rank error for the get_PMF() function. |
| Otherwise, it is the ‘single-sided’ normalized rank error for all the other queries. |
| Constants were derived as the best fit to 99 percentile empirically measured max error in thousands of trials</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.num_retained"> |
| <em class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">num_retained</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.num_retained" title="Link to this definition"></a></dt> |
| <dd><p>The number of retained items (samples) in the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.serialize"> |
| <span class="sig-name descname"><span class="pre">serialize</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.serialize" title="Link to this definition"></a></dt> |
| <dd><p>Serializes the sketch into a bytes object using the provided serde.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.to_string"> |
| <span class="sig-name descname"><span class="pre">to_string</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.to_string" title="Link to this definition"></a></dt> |
| <dd><p>Produces a string summary of the sketch</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="datasketches.quantiles_items_sketch.update"> |
| <span class="sig-name descname"><span class="pre">update</span></span><a class="headerlink" href="#datasketches.quantiles_items_sketch.update" title="Link to this definition"></a></dt> |
| <dd><p>Updates the sketch with the given value</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| </section> |
| |
| |
| </div> |
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