----- dim...@apache.org a écrit : > Author: dimpbx > Date: Sun Feb 21 21:46:12 2010 > New Revision: 912413 > > URL: http://svn.apache.org/viewvc?rev=912413&view=rev > Log: > MATH-432 fixed
The log should probably refer to MATH-342 Luc > > Modified: > > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java > > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/SingularValueDecompositionImpl.java > commons/proper/math/trunk/src/site/xdoc/changes.xml > > Modified: > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java > URL: > http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java?rev=912413&r1=912412&r2=912413&view=diff > ============================================================================== > --- > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java > (original) > +++ > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java > Sun Feb 21 21:46:12 2010 > @@ -479,6 +479,29 @@ > } > realEigenvalues[n - 1] = main[n - 1]; > e[n - 1] = 0.0; > + > + // Determine the largest main and secondary value in absolute > term. > + double maxAbsoluteValue=0.0; > + for (int i = 0; i < n; i++) { > + if (Math.abs(realEigenvalues[i])>maxAbsoluteValue) { > + maxAbsoluteValue=Math.abs(realEigenvalues[i]); > + } > + if (Math.abs(e[i])>maxAbsoluteValue) { > + maxAbsoluteValue=Math.abs(e[i]); > + } > + } > + // Make null any main and secondary value too small to be > significant > + if (maxAbsoluteValue!=0.0) { > + for (int i=0; i < n; i++) { > + if > (Math.abs(realEigenvalues[i])<=MathUtils.EPSILON*maxAbsoluteValue) { > + realEigenvalues[i]=0.0; > + } > + if > (Math.abs(e[i])<=MathUtils.EPSILON*maxAbsoluteValue) { > + e[i]=0.0; > + } > + } > + } > + > for (int j = 0; j < n; j++) { > int its = 0; > int m; > @@ -568,7 +591,7 @@ > } > > // Determine the largest eigen value in absolute term. > - double maxAbsoluteValue=0.0; > + maxAbsoluteValue=0.0; > for (int i = 0; i < n; i++) { > if (Math.abs(realEigenvalues[i])>maxAbsoluteValue) { > maxAbsoluteValue=Math.abs(realEigenvalues[i]); > > Modified: > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/SingularValueDecompositionImpl.java > URL: > http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/SingularValueDecompositionImpl.java?rev=912413&r1=912412&r2=912413&view=diff > ============================================================================== > --- > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/SingularValueDecompositionImpl.java > (original) > +++ > commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/SingularValueDecompositionImpl.java > Sun Feb 21 21:46:12 2010 > @@ -88,11 +88,12 @@ > // create A^T*A > // > for (int i = 0; i < n; i++) { > - for (int j = 0; j < n; j++) { > + for (int j = i; j < n; j++) { > matATA[i][j] = 0.0; > for (int k = 0; k < m; k++) { > matATA[i][j] += localcopy[k][i] * > localcopy[k][j]; > } > + matATA[j][i]=matATA[i][j]; > } > } > > @@ -101,11 +102,12 @@ > // create A*A^T > // > for (int i = 0; i < m; i++) { > - for (int j = 0; j < m; j++) { > + for (int j = i; j < m; j++) { > matAAT[i][j] = 0.0; > for (int k = 0; k < n; k++) { > matAAT[i][j] += localcopy[i][k] * > localcopy[j][k]; > } > + matAAT[j][i]=matAAT[i][j]; > } > } > int p; > > Modified: commons/proper/math/trunk/src/site/xdoc/changes.xml > URL: > http://svn.apache.org/viewvc/commons/proper/math/trunk/src/site/xdoc/changes.xml?rev=912413&r1=912412&r2=912413&view=diff > ============================================================================== > --- commons/proper/math/trunk/src/site/xdoc/changes.xml (original) > +++ commons/proper/math/trunk/src/site/xdoc/changes.xml Sun Feb 21 > 21:46:12 2010 > @@ -39,6 +39,12 @@ > </properties> > <body> > <release version="2.1" date="TBD" description="TBD"> > + <action dev="dimpbx" type="fix" issue="MATH-342"> > + In SVD, the matrices passed to EigenDecomposition are now > symmetric > + by construction (rather than simply by definition). In > EigenDecomposition, > + once the tridiagonal form is obtained, the non-significant > elements are > + set to 0. > + </action> > <action dev="dimpbx" type="fix" issue="MATH-333"> > A EigenDecompositionImpl simplified makes it possible to > compute > the SVD of a singular matrix (with the right number of > elements in --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
