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| <div class="section" id="vectors"> |
| <h1>Vectors<a class="headerlink" href="#vectors" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyspark.ml.linalg.Vectors"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyspark.ml.linalg.</code><code class="sig-name descname">Vectors</code><a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Factory methods for working with vectors.</p> |
| <p class="rubric">Notes</p> |
| <p>Dense vectors are simply represented as NumPy array objects, |
| so there is no need to covert them for use in MLlib. For sparse vectors, |
| the factory methods in this class create an MLlib-compatible type, or users |
| can pass in SciPy’s <cite>scipy.sparse</cite> column vectors.</p> |
| <p class="rubric">Methods</p> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.linalg.Vectors.dense" title="pyspark.ml.linalg.Vectors.dense"><code class="xref py py-obj docutils literal notranslate"><span class="pre">dense</span></code></a>(*elements)</p></td> |
| <td><p>Create a dense vector of 64-bit floats from a Python list or numbers.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.linalg.Vectors.norm" title="pyspark.ml.linalg.Vectors.norm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">norm</span></code></a>(vector, p)</p></td> |
| <td><p>Find norm of the given vector.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.linalg.Vectors.sparse" title="pyspark.ml.linalg.Vectors.sparse"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sparse</span></code></a>(size, *args)</p></td> |
| <td><p>Create a sparse vector, using either a dictionary, a list of (index, value) pairs, or two separate arrays of indices and values (sorted by index).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.linalg.Vectors.squared_distance" title="pyspark.ml.linalg.Vectors.squared_distance"><code class="xref py py-obj docutils literal notranslate"><span class="pre">squared_distance</span></code></a>(v1, v2)</p></td> |
| <td><p>Squared distance between two vectors.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.linalg.Vectors.zeros" title="pyspark.ml.linalg.Vectors.zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros</span></code></a>(size)</p></td> |
| <td><p></p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Methods Documentation</p> |
| <dl class="py method"> |
| <dt id="pyspark.ml.linalg.Vectors.dense"> |
| <em class="property">static </em><code class="sig-name descname">dense</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span><span class="n">elements</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>float<span class="p">, </span>bytes<span class="p">, </span>numpy.ndarray<span class="p">, </span>Iterable<span class="p">[</span>float<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.ml.linalg.DenseVector.html#pyspark.ml.linalg.DenseVector" title="pyspark.ml.linalg.DenseVector">pyspark.ml.linalg.DenseVector</a><a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors.dense"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors.dense" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create a dense vector of 64-bit floats from a Python list or numbers.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span> |
| <span class="go">DenseVector([1.0, 2.0, 3.0])</span> |
| <span class="gp">>>> </span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">)</span> |
| <span class="go">DenseVector([1.0, 2.0])</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.ml.linalg.Vectors.norm"> |
| <em class="property">static </em><code class="sig-name descname">norm</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">vector</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.linalg.Vector.html#pyspark.ml.linalg.Vector" title="pyspark.ml.linalg.Vector">pyspark.ml.linalg.Vector</a></span></em>, <em class="sig-param"><span class="n">p</span><span class="p">:</span> <span class="n">NormType</span></em><span class="sig-paren">)</span> → numpy.float64<a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors.norm"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors.norm" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Find norm of the given vector.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.ml.linalg.Vectors.sparse"> |
| <em class="property">static </em><code class="sig-name descname">sparse</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">size</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="o">*</span><span class="n">args</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>bytes<span class="p">, </span>Tuple<span class="p">[</span>int<span class="p">, </span>float<span class="p">]</span><span class="p">, </span>Iterable<span class="p">[</span>float<span class="p">]</span><span class="p">, </span>Iterable<span class="p">[</span>Tuple<span class="p">[</span>int<span class="p">, </span>float<span class="p">]</span><span class="p">]</span><span class="p">, </span>Dict<span class="p">[</span>int<span class="p">, </span>float<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.ml.linalg.SparseVector.html#pyspark.ml.linalg.SparseVector" title="pyspark.ml.linalg.SparseVector">pyspark.ml.linalg.SparseVector</a><a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors.sparse"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors.sparse" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create a sparse vector, using either a dictionary, a list of |
| (index, value) pairs, or two separate arrays of indices and |
| values (sorted by index).</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl class="simple"> |
| <dt><strong>size</strong><span class="classifier">int</span></dt><dd><p>Size of the vector.</p> |
| </dd> |
| <dt><strong>args</strong></dt><dd><p>Non-zero entries, as a dictionary, list of tuples, |
| or two sorted lists containing indices and values.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Vectors</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="p">{</span><span class="mi">1</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="mf">5.5</span><span class="p">})</span> |
| <span class="go">SparseVector(4, {1: 1.0, 3: 5.5})</span> |
| <span class="gp">>>> </span><span class="n">Vectors</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="p">[(</span><span class="mi">1</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">),</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mf">5.5</span><span class="p">)])</span> |
| <span class="go">SparseVector(4, {1: 1.0, 3: 5.5})</span> |
| <span class="gp">>>> </span><span class="n">Vectors</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">5.5</span><span class="p">])</span> |
| <span class="go">SparseVector(4, {1: 1.0, 3: 5.5})</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.ml.linalg.Vectors.squared_distance"> |
| <em class="property">static </em><code class="sig-name descname">squared_distance</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">v1</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.linalg.Vector.html#pyspark.ml.linalg.Vector" title="pyspark.ml.linalg.Vector">pyspark.ml.linalg.Vector</a></span></em>, <em class="sig-param"><span class="n">v2</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.linalg.Vector.html#pyspark.ml.linalg.Vector" title="pyspark.ml.linalg.Vector">pyspark.ml.linalg.Vector</a></span></em><span class="sig-paren">)</span> → numpy.float64<a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors.squared_distance"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors.squared_distance" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Squared distance between two vectors. |
| a and b can be of type SparseVector, DenseVector, np.ndarray |
| or array.array.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">Vectors</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="p">[(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">a</span><span class="o">.</span><span class="n">squared_distance</span><span class="p">(</span><span class="n">b</span><span class="p">)</span> |
| <span class="go">51.0</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.ml.linalg.Vectors.zeros"> |
| <em class="property">static </em><code class="sig-name descname">zeros</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">size</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.ml.linalg.DenseVector.html#pyspark.ml.linalg.DenseVector" title="pyspark.ml.linalg.DenseVector">pyspark.ml.linalg.DenseVector</a><a class="reference internal" href="../../_modules/pyspark/ml/linalg.html#Vectors.zeros"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.linalg.Vectors.zeros" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
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