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| <div class="section" id="blockmatrix"> |
| <h1>BlockMatrix<a class="headerlink" href="#blockmatrix" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyspark.mllib.linalg.distributed.</code><code class="sig-name descname">BlockMatrix</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">blocks</span><span class="p">:</span> <span class="n">pyspark.rdd.RDD<span class="p">[</span>Tuple<span class="p">[</span>Tuple<span class="p">[</span>int<span class="p">, </span>int<span class="p">]</span><span class="p">, </span><a class="reference internal" href="pyspark.mllib.linalg.Matrix.html#pyspark.mllib.linalg.Matrix" title="pyspark.mllib.linalg.Matrix">pyspark.mllib.linalg.Matrix</a><span class="p">]</span><span class="p">]</span></span></em>, <em class="sig-param"><span class="n">rowsPerBlock</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">colsPerBlock</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">numRows</span><span class="p">:</span> <span class="n">int</span> <span class="o">=</span> <span class="default_value">0</span></em>, <em class="sig-param"><span class="n">numCols</span><span class="p">:</span> <span class="n">int</span> <span class="o">=</span> <span class="default_value">0</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Represents a distributed matrix in blocks of local matrices.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>blocks</strong><span class="classifier"><a class="reference internal" href="pyspark.RDD.html#pyspark.RDD" title="pyspark.RDD"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyspark.RDD</span></code></a></span></dt><dd><p>An RDD of sub-matrix blocks |
| ((blockRowIndex, blockColIndex), sub-matrix) that |
| form this distributed matrix. If multiple blocks |
| with the same index exist, the results for |
| operations like add and multiply will be |
| unpredictable.</p> |
| </dd> |
| <dt><strong>rowsPerBlock</strong><span class="classifier">int</span></dt><dd><p>Number of rows that make up each block. |
| The blocks forming the final rows are not |
| required to have the given number of rows.</p> |
| </dd> |
| <dt><strong>colsPerBlock</strong><span class="classifier">int</span></dt><dd><p>Number of columns that make up each block. |
| The blocks forming the final columns are not |
| required to have the given number of columns.</p> |
| </dd> |
| <dt><strong>numRows</strong><span class="classifier">int, optional</span></dt><dd><p>Number of rows of this matrix. If the supplied |
| value is less than or equal to zero, the number |
| of rows will be calculated when <cite>numRows</cite> is |
| invoked.</p> |
| </dd> |
| <dt><strong>numCols</strong><span class="classifier">int, optional</span></dt><dd><p>Number of columns of this matrix. If the supplied |
| value is less than or equal to zero, the number |
| of columns will be calculated when <cite>numCols</cite> is |
| invoked.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <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.mllib.linalg.distributed.BlockMatrix.add" title="pyspark.mllib.linalg.distributed.BlockMatrix.add"><code class="xref py py-obj docutils literal notranslate"><span class="pre">add</span></code></a>(other)</p></td> |
| <td><p>Adds two block matrices together.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.cache" title="pyspark.mllib.linalg.distributed.BlockMatrix.cache"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cache</span></code></a>()</p></td> |
| <td><p>Caches the underlying RDD.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.multiply" title="pyspark.mllib.linalg.distributed.BlockMatrix.multiply"><code class="xref py py-obj docutils literal notranslate"><span class="pre">multiply</span></code></a>(other)</p></td> |
| <td><p>Left multiplies this BlockMatrix by <cite>other</cite>, another BlockMatrix.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numCols" title="pyspark.mllib.linalg.distributed.BlockMatrix.numCols"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numCols</span></code></a>()</p></td> |
| <td><p>Get or compute the number of cols.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numRows" title="pyspark.mllib.linalg.distributed.BlockMatrix.numRows"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numRows</span></code></a>()</p></td> |
| <td><p>Get or compute the number of rows.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.persist" title="pyspark.mllib.linalg.distributed.BlockMatrix.persist"><code class="xref py py-obj docutils literal notranslate"><span class="pre">persist</span></code></a>(storageLevel)</p></td> |
| <td><p>Persists the underlying RDD with the specified storage level.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.subtract" title="pyspark.mllib.linalg.distributed.BlockMatrix.subtract"><code class="xref py py-obj docutils literal notranslate"><span class="pre">subtract</span></code></a>(other)</p></td> |
| <td><p>Subtracts the given block matrix <cite>other</cite> from this block matrix: <cite>this - other</cite>.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toCoordinateMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix.toCoordinateMatrix"><code class="xref py py-obj docutils literal notranslate"><span class="pre">toCoordinateMatrix</span></code></a>()</p></td> |
| <td><p>Convert this matrix to a CoordinateMatrix.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toIndexedRowMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix.toIndexedRowMatrix"><code class="xref py py-obj docutils literal notranslate"><span class="pre">toIndexedRowMatrix</span></code></a>()</p></td> |
| <td><p>Convert this matrix to an IndexedRowMatrix.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toLocalMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix.toLocalMatrix"><code class="xref py py-obj docutils literal notranslate"><span class="pre">toLocalMatrix</span></code></a>()</p></td> |
| <td><p>Collect the distributed matrix on the driver as a DenseMatrix.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.transpose" title="pyspark.mllib.linalg.distributed.BlockMatrix.transpose"><code class="xref py py-obj docutils literal notranslate"><span class="pre">transpose</span></code></a>()</p></td> |
| <td><p>Transpose this BlockMatrix.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.validate" title="pyspark.mllib.linalg.distributed.BlockMatrix.validate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validate</span></code></a>()</p></td> |
| <td><p>Validates the block matrix info against the matrix data (<cite>blocks</cite>) and throws an exception if any error is found.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Attributes</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.mllib.linalg.distributed.BlockMatrix.blocks" title="pyspark.mllib.linalg.distributed.BlockMatrix.blocks"><code class="xref py py-obj docutils literal notranslate"><span class="pre">blocks</span></code></a></p></td> |
| <td><p>The RDD of sub-matrix blocks ((blockRowIndex, blockColIndex), sub-matrix) that form this distributed matrix.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.colsPerBlock" title="pyspark.mllib.linalg.distributed.BlockMatrix.colsPerBlock"><code class="xref py py-obj docutils literal notranslate"><span class="pre">colsPerBlock</span></code></a></p></td> |
| <td><p>Number of columns that make up each block.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numColBlocks" title="pyspark.mllib.linalg.distributed.BlockMatrix.numColBlocks"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numColBlocks</span></code></a></p></td> |
| <td><p>Number of columns of blocks in the BlockMatrix.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numRowBlocks" title="pyspark.mllib.linalg.distributed.BlockMatrix.numRowBlocks"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numRowBlocks</span></code></a></p></td> |
| <td><p>Number of rows of blocks in the BlockMatrix.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix.rowsPerBlock" title="pyspark.mllib.linalg.distributed.BlockMatrix.rowsPerBlock"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rowsPerBlock</span></code></a></p></td> |
| <td><p>Number of rows that make up each block.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Methods Documentation</p> |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.add"> |
| <code class="sig-name descname">add</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">other</span><span class="p">:</span> <span class="n"><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.add"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.add" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Adds two block matrices together. The matrices must have the |
| same size and matching <cite>rowsPerBlock</cite> and <cite>colsPerBlock</cite> values. |
| If one of the sub matrix blocks that are being added is a |
| SparseMatrix, the resulting sub matrix block will also be a |
| SparseMatrix, even if it is being added to a DenseMatrix. If |
| two dense sub matrix blocks are added, the output block will |
| also be a DenseMatrix.</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">dm1</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dm2</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">sm</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</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="mi">3</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="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">blocks1</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm1</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks2</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm1</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks3</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">sm</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">mat1</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat2</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat3</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat1</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">mat2</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(6, 2, [2.0, 4.0, 6.0, 14.0, 16.0, 18.0, 8.0, 10.0, 12.0, 20.0, 22.0, 24.0], 0)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat1</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">mat3</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(6, 2, [8.0, 2.0, 3.0, 14.0, 16.0, 18.0, 4.0, 16.0, 18.0, 20.0, 22.0, 24.0], 0)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.cache"> |
| <code class="sig-name descname">cache</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.cache"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.cache" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Caches the underlying RDD.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.0.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.multiply"> |
| <code class="sig-name descname">multiply</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">other</span><span class="p">:</span> <span class="n"><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.multiply"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.multiply" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Left multiplies this BlockMatrix by <cite>other</cite>, another |
| BlockMatrix. The <cite>colsPerBlock</cite> of this matrix must equal the |
| <cite>rowsPerBlock</cite> of <cite>other</cite>. If <cite>other</cite> contains any SparseMatrix |
| blocks, they will have to be converted to DenseMatrix blocks. |
| The output BlockMatrix will only consist of DenseMatrix blocks. |
| This may cause some performance issues until support for |
| multiplying two sparse matrices is added.</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">dm1</span> <span class="o">=</span> <span class="n">Matrices</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">3</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dm2</span> <span class="o">=</span> <span class="n">Matrices</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">3</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dm3</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dm4</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">sm</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</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="mi">3</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="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">blocks1</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm1</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="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks2</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm3</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm4</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks3</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">sm</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm4</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">mat1</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks1</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="gp">>>> </span><span class="n">mat2</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat3</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat1</span><span class="o">.</span><span class="n">multiply</span><span class="p">(</span><span class="n">mat2</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(2, 2, [242.0, 272.0, 350.0, 398.0], 0)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat1</span><span class="o">.</span><span class="n">multiply</span><span class="p">(</span><span class="n">mat3</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(2, 2, [227.0, 258.0, 394.0, 450.0], 0)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.numCols"> |
| <code class="sig-name descname">numCols</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → int<a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.numCols"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numCols" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get or compute the number of cols.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numCols</span><span class="p">())</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numCols</span><span class="p">())</span> |
| <span class="go">6</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.numRows"> |
| <code class="sig-name descname">numRows</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → int<a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.numRows"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numRows" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get or compute the number of rows.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numRows</span><span class="p">())</span> |
| <span class="go">6</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numRows</span><span class="p">())</span> |
| <span class="go">7</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.persist"> |
| <code class="sig-name descname">persist</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">storageLevel</span><span class="p">:</span> <span class="n">pyspark.storagelevel.StorageLevel</span></em><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.persist"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.persist" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Persists the underlying RDD with the specified storage level.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.0.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.subtract"> |
| <code class="sig-name descname">subtract</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">other</span><span class="p">:</span> <span class="n"><a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.subtract"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.subtract" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Subtracts the given block matrix <cite>other</cite> from this block matrix: |
| <cite>this - other</cite>. The matrices must have the same size and |
| matching <cite>rowsPerBlock</cite> and <cite>colsPerBlock</cite> values. If one of |
| the sub matrix blocks that are being subtracted is a |
| SparseMatrix, the resulting sub matrix block will also be a |
| SparseMatrix, even if it is being subtracted from a DenseMatrix. |
| If two dense sub matrix blocks are subtracted, the output block |
| will also be a DenseMatrix.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.0.0.</span></p> |
| </div> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">dm1</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</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">6</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dm2</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">sm</span> <span class="o">=</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">sparse</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</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="mi">3</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="mi">2</span><span class="p">],</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="gp">>>> </span><span class="n">blocks1</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm1</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks2</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm1</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">blocks3</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">sm</span><span class="p">),</span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dm2</span><span class="p">)])</span> |
| <span class="gp">>>> </span><span class="n">mat1</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat2</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat3</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat1</span><span class="o">.</span><span class="n">subtract</span><span class="p">(</span><span class="n">mat2</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(6, 2, [-4.0, -7.0, -4.0, 4.0, 7.0, 4.0, -6.0, -5.0, -10.0, 6.0, 5.0, 10.0], 0)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat2</span><span class="o">.</span><span class="n">subtract</span><span class="p">(</span><span class="n">mat3</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(6, 2, [6.0, 8.0, 9.0, -4.0, -7.0, -4.0, 10.0, 9.0, 9.0, -6.0, -5.0, -10.0], 0)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.toCoordinateMatrix"> |
| <code class="sig-name descname">toCoordinateMatrix</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.mllib.linalg.distributed.CoordinateMatrix.html#pyspark.mllib.linalg.distributed.CoordinateMatrix" title="pyspark.mllib.linalg.distributed.CoordinateMatrix">pyspark.mllib.linalg.distributed.CoordinateMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.toCoordinateMatrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toCoordinateMatrix" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert this matrix to a CoordinateMatrix.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</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="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</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="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</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="o">.</span><span class="n">toCoordinateMatrix</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">mat</span><span class="o">.</span><span class="n">entries</span><span class="o">.</span><span class="n">take</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> |
| <span class="go">[MatrixEntry(0, 0, 1.0), MatrixEntry(0, 1, 2.0), MatrixEntry(1, 0, 7.0)]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.toIndexedRowMatrix"> |
| <code class="sig-name descname">toIndexedRowMatrix</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.mllib.linalg.distributed.IndexedRowMatrix.html#pyspark.mllib.linalg.distributed.IndexedRowMatrix" title="pyspark.mllib.linalg.distributed.IndexedRowMatrix">pyspark.mllib.linalg.distributed.IndexedRowMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.toIndexedRowMatrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toIndexedRowMatrix" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert this matrix to an IndexedRowMatrix.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">toIndexedRowMatrix</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># This BlockMatrix will have 6 effective rows, due to</span> |
| <span class="gp">>>> </span><span class="c1"># having two sub-matrix blocks stacked, each with 3 rows.</span> |
| <span class="gp">>>> </span><span class="c1"># The ensuing IndexedRowMatrix will also have 6 rows.</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numRows</span><span class="p">())</span> |
| <span class="go">6</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># This BlockMatrix will have 2 effective columns, due to</span> |
| <span class="gp">>>> </span><span class="c1"># having two sub-matrix blocks stacked, each with 2 columns.</span> |
| <span class="gp">>>> </span><span class="c1"># The ensuing IndexedRowMatrix will also have 2 columns.</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numCols</span><span class="p">())</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.toLocalMatrix"> |
| <code class="sig-name descname">toLocalMatrix</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → <a class="reference internal" href="pyspark.mllib.linalg.Matrix.html#pyspark.mllib.linalg.Matrix" title="pyspark.mllib.linalg.Matrix">pyspark.mllib.linalg.Matrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.toLocalMatrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.toLocalMatrix" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Collect the distributed matrix on the driver as a DenseMatrix.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># This BlockMatrix will have 6 effective rows, due to</span> |
| <span class="gp">>>> </span><span class="c1"># having two sub-matrix blocks stacked, each with 3 rows.</span> |
| <span class="gp">>>> </span><span class="c1"># The ensuing DenseMatrix will also have 6 rows.</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numRows</span><span class="p">)</span> |
| <span class="go">6</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># This BlockMatrix will have 2 effective columns, due to</span> |
| <span class="gp">>>> </span><span class="c1"># having two sub-matrix blocks stacked, each with 2</span> |
| <span class="gp">>>> </span><span class="c1"># columns. The ensuing DenseMatrix will also have 2 columns.</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">mat</span><span class="o">.</span><span class="n">numCols</span><span class="p">)</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.transpose"> |
| <code class="sig-name descname">transpose</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → <a class="reference internal" href="#pyspark.mllib.linalg.distributed.BlockMatrix" title="pyspark.mllib.linalg.distributed.BlockMatrix">pyspark.mllib.linalg.distributed.BlockMatrix</a><a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.transpose"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.transpose" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Transpose this BlockMatrix. Returns a new BlockMatrix |
| instance sharing the same underlying data. Is a lazy operation.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.0.0.</span></p> |
| </div> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">mat_transposed</span> <span class="o">=</span> <span class="n">mat</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">mat_transposed</span><span class="o">.</span><span class="n">toLocalMatrix</span><span class="p">()</span> |
| <span class="go">DenseMatrix(2, 6, [1.0, 4.0, 2.0, 5.0, 3.0, 6.0, 7.0, 10.0, 8.0, 11.0, 9.0, 12.0], 0)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.validate"> |
| <code class="sig-name descname">validate</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → None<a class="reference internal" href="../../_modules/pyspark/mllib/linalg/distributed.html#BlockMatrix.validate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.validate" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Validates the block matrix info against the matrix data (<cite>blocks</cite>) |
| and throws an exception if any error is found.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.0.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <p class="rubric">Attributes Documentation</p> |
| <dl class="py attribute"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.blocks"> |
| <code class="sig-name descname">blocks</code><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.blocks" title="Permalink to this definition">¶</a></dt> |
| <dd><p>The RDD of sub-matrix blocks |
| ((blockRowIndex, blockColIndex), sub-matrix) that form this |
| distributed matrix.</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">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span> |
| <span class="gp">... </span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))]),</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">blocks</span> <span class="o">=</span> <span class="n">mat</span><span class="o">.</span><span class="n">blocks</span> |
| <span class="gp">>>> </span><span class="n">blocks</span><span class="o">.</span><span class="n">first</span><span class="p">()</span> |
| <span class="go">((0, 0), DenseMatrix(3, 2, [1.0, 2.0, 3.0, 4.0, 5.0, 6.0], 0))</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.colsPerBlock"> |
| <code class="sig-name descname">colsPerBlock</code><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.colsPerBlock" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of columns that make up each block.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat</span><span class="o">.</span><span class="n">colsPerBlock</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.numColBlocks"> |
| <code class="sig-name descname">numColBlocks</code><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numColBlocks" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of columns of blocks in the BlockMatrix.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat</span><span class="o">.</span><span class="n">numColBlocks</span> |
| <span class="go">1</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.numRowBlocks"> |
| <code class="sig-name descname">numRowBlocks</code><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.numRowBlocks" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of rows of blocks in the BlockMatrix.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat</span><span class="o">.</span><span class="n">numRowBlocks</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.mllib.linalg.distributed.BlockMatrix.rowsPerBlock"> |
| <code class="sig-name descname">rowsPerBlock</code><a class="headerlink" href="#pyspark.mllib.linalg.distributed.BlockMatrix.rowsPerBlock" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of rows that make up each block.</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">blocks</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">([((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</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="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">])),</span> |
| <span class="gp">... </span> <span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">Matrices</span><span class="o">.</span><span class="n">dense</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">]))])</span> |
| <span class="gp">>>> </span><span class="n">mat</span> <span class="o">=</span> <span class="n">BlockMatrix</span><span class="p">(</span><span class="n">blocks</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mat</span><span class="o">.</span><span class="n">rowsPerBlock</span> |
| <span class="go">3</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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