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📁 Java方面的数值算法
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                  double&nbsp;a)</PRE>
<DL>
<DD>adds a to the specified element, growing the matrix if necessary.
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>i</CODE> - <DD><CODE>j</CODE> - <DD><CODE>a</CODE> - 
<DT><B>Returns:</B><DD>new value</DL>
</DD>
</DL>
<HR>

<A NAME="normalise(double)"><!-- --></A><H3>
normalise</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A> <B>normalise</B>(double&nbsp;rowsum)</PRE>
<DL>
<DD>normalise rows to rowsum
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>rowsum</CODE> - for each row
<DT><B>Returns:</B><DD>vector of old row sums</DL>
</DD>
</DL>
<HR>

<A NAME="normaliseRows()"><!-- --></A><H3>
normaliseRows</H3>
<PRE>
public void <B>normaliseRows</B>()</PRE>
<DL>
<DD>normalise by major dimension (rows)
<P>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="normaliseCols()"><!-- --></A><H3>
normaliseCols</H3>
<PRE>
public void <B>normaliseCols</B>()</PRE>
<DL>
<DD>normalise by minor dimension (columns), expensive.
<P>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="copy()"><!-- --></A><H3>
copy</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A> <B>copy</B>()</PRE>
<DL>
<DD>copy the matrix and its elements
<P>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="times(net.sf.javaml.clustering.mcl.SparseVector)"><!-- --></A><H3>
times</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A> <B>times</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A>&nbsp;v)</PRE>
<DL>
<DD>immutable multiply this times the vector: A * x, i.e., rowwise.
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - 
<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="vectorTimes(net.sf.javaml.clustering.mcl.SparseVector)"><!-- --></A><H3>
vectorTimes</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A> <B>vectorTimes</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A>&nbsp;v)</PRE>
<DL>
<DD>immutable multiply the vector times this: x' * A, i.e., colwise.
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - 
<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="timesTransposed(net.sf.javaml.clustering.mcl.SparseMatrix)"><!-- --></A><H3>
timesTransposed</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A> <B>timesTransposed</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A>&nbsp;m)</PRE>
<DL>
<DD>mutable multiply this matrix (A) with M : A * M'
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>m</CODE> - 
<DT><B>Returns:</B><DD>modified this</DL>
</DD>
</DL>
<HR>

<A NAME="times(net.sf.javaml.clustering.mcl.SparseMatrix)"><!-- --></A><H3>
times</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A> <B>times</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A>&nbsp;m)</PRE>
<DL>
<DD>immutable multiply this matrix (A) with M : A * M
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>m</CODE> - 
<DT><B>Returns:</B><DD>matrix product</DL>
</DD>
</DL>
<HR>

<A NAME="matrixTimes(net.sf.javaml.clustering.mcl.SparseMatrix)"><!-- --></A><H3>
matrixTimes</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A> <B>matrixTimes</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A>&nbsp;m)</PRE>
<DL>
<DD>immutable multiply matrix M with this (A) : M * A
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>m</CODE> - 
<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="transpose()"><!-- --></A><H3>
transpose</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A> <B>transpose</B>()</PRE>
<DL>
<DD>immutable transpose.
<P>
<DD><DL>

<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="getColum(int)"><!-- --></A><H3>
getColum</H3>
<PRE>
public <A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A> <B>getColum</B>(int&nbsp;i)</PRE>
<DL>
<DD>get a column of the sparse matrix (expensive).
<P>
<DD><DL>

<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="hadamardProduct(net.sf.javaml.clustering.mcl.SparseMatrix)"><!-- --></A><H3>
hadamardProduct</H3>
<PRE>
public void <B>hadamardProduct</B>(<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseMatrix.html" title="class in net.sf.javaml.clustering.mcl">SparseMatrix</A>&nbsp;m)</PRE>
<DL>
<DD>mutable Hadamard product
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>m</CODE> - </DL>
</DD>
</DL>
<HR>

<A NAME="hadamardPower(double)"><!-- --></A><H3>
hadamardPower</H3>
<PRE>
public void <B>hadamardPower</B>(double&nbsp;s)</PRE>
<DL>
<DD>mutable m2 = m .^ s
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>s</CODE> - </DL>
</DD>
</DL>
<HR>

<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE>toString</CODE> in class <CODE>java.util.AbstractCollection&lt;<A HREF="../../../../../net/sf/javaml/clustering/mcl/SparseVector.html" title="class in net.sf.javaml.clustering.mcl">SparseVector</A>&gt;</CODE></DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="toStringDense()"><!-- --></A><H3>
toStringDense</H3>
<PRE>
public java.lang.String <B>toStringDense</B>()</PRE>
<DL>
<DD>prints a dense representation
<P>
<DD><DL>

<DT><B>Returns:</B><DD></DL>
</DD>
</DL>
<HR>

<A NAME="prune(double)"><!-- --></A><H3>
prune</H3>
<PRE>
public void <B>prune</B>(double&nbsp;threshold)</PRE>
<DL>
<DD>prune all values whose magnitude is below threshold
<P>
<DD><DL>
</DL>
</DD>
</DL>
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