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<h2 title="Class BLAS" class="title">Class BLAS</h2>
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<pre>public class <span class="typeNameLabel">BLAS</span>
extends Object</pre>
<div class="block">BLAS routines for MLlib's vectors and matrices.</div>
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#BLAS--">BLAS</a></span>()</code>&nbsp;</td>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#axpy-double-org.apache.spark.ml.linalg.Vector-org.apache.spark.ml.linalg.Vector-">axpy</a></span>(double&nbsp;a,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</code>
<div class="block">y += a * x</div>
</td>
</tr>
<tr id="i1" class="rowColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#copy-org.apache.spark.ml.linalg.Vector-org.apache.spark.ml.linalg.Vector-">copy</a></span>(<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</code>
<div class="block">y = x</div>
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<tr id="i2" class="altColor">
<td class="colFirst"><code>static double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#dot-org.apache.spark.ml.linalg.Vector-org.apache.spark.ml.linalg.Vector-">dot</a></span>(<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</code>
<div class="block">dot(x, y)</div>
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<tr id="i3" class="rowColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#dspmv-int-double-org.apache.spark.ml.linalg.DenseVector-org.apache.spark.ml.linalg.DenseVector-double-org.apache.spark.ml.linalg.DenseVector-">dspmv</a></span>(int&nbsp;n,
double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;A,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;x,
double&nbsp;beta,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;y)</code>
<div class="block">y := alpha*A*x + beta*y</div>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#gemm-double-org.apache.spark.ml.linalg.Matrix-org.apache.spark.ml.linalg.DenseMatrix-double-org.apache.spark.ml.linalg.DenseMatrix-">gemm</a></span>(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
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double&nbsp;beta,
<a href="../../../../../org/apache/spark/ml/linalg/DenseMatrix.html" title="class in org.apache.spark.ml.linalg">DenseMatrix</a>&nbsp;C)</code>
<div class="block">C := alpha * A * B + beta * C</div>
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<tr id="i5" class="rowColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#gemm-double-org.apache.spark.ml.linalg.Matrix-org.apache.spark.ml.linalg.DenseMatrix-double-double:A-">gemm</a></span>(double&nbsp;alpha,
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double&nbsp;beta,
double[]&nbsp;CValues)</code>
<div class="block">CValues[0: A.numRows * B.numCols] := alpha * A * B + beta * CValues[0: A.numRows * B.numCols]</div>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#gemv-double-org.apache.spark.ml.linalg.Matrix-double:A-double-double:A-">gemv</a></span>(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
double[]&nbsp;x,
double&nbsp;beta,
double[]&nbsp;y)</code>
<div class="block">y[0: A.numRows] := alpha * A * x[0: A.numCols] + beta * y[0: A.numRows]</div>
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<tr id="i7" class="rowColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#gemv-double-org.apache.spark.ml.linalg.Matrix-org.apache.spark.ml.linalg.Vector-double-org.apache.spark.ml.linalg.DenseVector-">gemv</a></span>(double&nbsp;alpha,
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<div class="block">y := alpha * A * x + beta * y</div>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#scal-double-org.apache.spark.ml.linalg.Vector-">scal</a></span>(double&nbsp;a,
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<div class="block">x = a * x</div>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#spr-double-org.apache.spark.ml.linalg.Vector-org.apache.spark.ml.linalg.DenseVector-">spr</a></span>(double&nbsp;alpha,
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<div class="block">Adds alpha * x * x.t to a matrix in-place.</div>
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<tr id="i10" class="altColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#spr-double-org.apache.spark.ml.linalg.Vector-double:A-">spr</a></span>(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;v,
double[]&nbsp;U)</code>
<div class="block">Adds alpha * v * v.t to a matrix in-place.</div>
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<tr id="i11" class="rowColor">
<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/linalg/BLAS.html#syr-double-org.apache.spark.ml.linalg.Vector-org.apache.spark.ml.linalg.DenseMatrix-">syr</a></span>(double&nbsp;alpha,
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<div class="block">A := alpha * x * x^T^ + A</div>
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<pre>public&nbsp;BLAS()</pre>
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<pre>public static&nbsp;void&nbsp;axpy(double&nbsp;a,
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<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</pre>
<div class="block">y += a * x</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>a</code> - (undocumented)</dd>
<dd><code>x</code> - (undocumented)</dd>
<dd><code>y</code> - (undocumented)</dd>
</dl>
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<pre>public static&nbsp;double&nbsp;dot(<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</pre>
<div class="block">dot(x, y)</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>x</code> - (undocumented)</dd>
<dd><code>y</code> - (undocumented)</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre>public static&nbsp;void&nbsp;copy(<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;y)</pre>
<div class="block">y = x</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>x</code> - (undocumented)</dd>
<dd><code>y</code> - (undocumented)</dd>
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<pre>public static&nbsp;void&nbsp;scal(double&nbsp;a,
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<div class="block">x = a * x</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>a</code> - (undocumented)</dd>
<dd><code>x</code> - (undocumented)</dd>
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<pre>public static&nbsp;void&nbsp;spr(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;v,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;U)</pre>
<div class="block">Adds alpha * x * x.t to a matrix in-place. This is the same as BLAS's ?SPR.
<p></div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>U</code> - the upper triangular part of the matrix in a <a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg"><code>DenseVector</code></a>(column major)</dd>
<dd><code>alpha</code> - (undocumented)</dd>
<dd><code>v</code> - (undocumented)</dd>
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<pre>public static&nbsp;void&nbsp;dspmv(int&nbsp;n,
double&nbsp;alpha,
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<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;x,
double&nbsp;beta,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;y)</pre>
<div class="block">y := alpha*A*x + beta*y
<p></div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>n</code> - The order of the n by n matrix A.</dd>
<dd><code>A</code> - The upper triangular part of A in a <a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg"><code>DenseVector</code></a> (column major).</dd>
<dd><code>x</code> - The <a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg"><code>DenseVector</code></a> transformed by A.</dd>
<dd><code>y</code> - The <a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg"><code>DenseVector</code></a> to be modified in place.</dd>
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<pre>public static&nbsp;void&nbsp;spr(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;v,
double[]&nbsp;U)</pre>
<div class="block">Adds alpha * v * v.t to a matrix in-place. This is the same as BLAS's ?SPR.
<p></div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>U</code> - the upper triangular part of the matrix packed in an array (column major)</dd>
<dd><code>alpha</code> - (undocumented)</dd>
<dd><code>v</code> - (undocumented)</dd>
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<pre>public static&nbsp;void&nbsp;syr(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
<a href="../../../../../org/apache/spark/ml/linalg/DenseMatrix.html" title="class in org.apache.spark.ml.linalg">DenseMatrix</a>&nbsp;A)</pre>
<div class="block">A := alpha * x * x^T^ + A</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>alpha</code> - a real scalar that will be multiplied to x * x^T^.</dd>
<dd><code>x</code> - the vector x that contains the n elements.</dd>
<dd><code>A</code> - the symmetric matrix A. Size of n x n.</dd>
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<h4>gemm</h4>
<pre>public static&nbsp;void&nbsp;gemm(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
<a href="../../../../../org/apache/spark/ml/linalg/DenseMatrix.html" title="class in org.apache.spark.ml.linalg">DenseMatrix</a>&nbsp;B,
double&nbsp;beta,
<a href="../../../../../org/apache/spark/ml/linalg/DenseMatrix.html" title="class in org.apache.spark.ml.linalg">DenseMatrix</a>&nbsp;C)</pre>
<div class="block">C := alpha * A * B + beta * C</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>alpha</code> - a scalar to scale the multiplication A * B.</dd>
<dd><code>A</code> - the matrix A that will be left multiplied to B. Size of m x k.</dd>
<dd><code>B</code> - the matrix B that will be left multiplied by A. Size of k x n.</dd>
<dd><code>beta</code> - a scalar that can be used to scale matrix C.</dd>
<dd><code>C</code> - the resulting matrix C. Size of m x n. C.isTransposed must be false.</dd>
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<h4>gemm</h4>
<pre>public static&nbsp;void&nbsp;gemm(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
<a href="../../../../../org/apache/spark/ml/linalg/DenseMatrix.html" title="class in org.apache.spark.ml.linalg">DenseMatrix</a>&nbsp;B,
double&nbsp;beta,
double[]&nbsp;CValues)</pre>
<div class="block">CValues[0: A.numRows * B.numCols] := alpha * A * B + beta * CValues[0: A.numRows * B.numCols]</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>alpha</code> - a scalar to scale the multiplication A * B.</dd>
<dd><code>A</code> - the matrix A that will be left multiplied to B. Size of m x k.</dd>
<dd><code>B</code> - the matrix B that will be left multiplied by A. Size of k x n.</dd>
<dd><code>beta</code> - a scalar that can be used to scale matrix C.</dd>
<dd><code>CValues</code> - the values of matrix C. C.isTransposed is supposed to be false.</dd>
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<pre>public static&nbsp;void&nbsp;gemv(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
double[]&nbsp;x,
double&nbsp;beta,
double[]&nbsp;y)</pre>
<div class="block">y[0: A.numRows] := alpha * A * x[0: A.numCols] + beta * y[0: A.numRows]</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>alpha</code> - (undocumented)</dd>
<dd><code>A</code> - (undocumented)</dd>
<dd><code>x</code> - (undocumented)</dd>
<dd><code>beta</code> - (undocumented)</dd>
<dd><code>y</code> - (undocumented)</dd>
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<h4>gemv</h4>
<pre>public static&nbsp;void&nbsp;gemv(double&nbsp;alpha,
<a href="../../../../../org/apache/spark/ml/linalg/Matrix.html" title="interface in org.apache.spark.ml.linalg">Matrix</a>&nbsp;A,
<a href="../../../../../org/apache/spark/ml/linalg/Vector.html" title="interface in org.apache.spark.ml.linalg">Vector</a>&nbsp;x,
double&nbsp;beta,
<a href="../../../../../org/apache/spark/ml/linalg/DenseVector.html" title="class in org.apache.spark.ml.linalg">DenseVector</a>&nbsp;y)</pre>
<div class="block">y := alpha * A * x + beta * y</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>alpha</code> - a scalar to scale the multiplication A * x.</dd>
<dd><code>A</code> - the matrix A that will be left multiplied to x. Size of m x n.</dd>
<dd><code>x</code> - the vector x that will be left multiplied by A. Size of n x 1.</dd>
<dd><code>beta</code> - a scalar that can be used to scale vector y.</dd>
<dd><code>y</code> - the resulting vector y. Size of m x 1.</dd>
</dl>
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