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* move memory related stuff to util/Memory.h

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* clean ugly doxygen inheritence of expressions
* keep improving the documentation... slowly !
This commit is contained in:
Gael Guennebaud
2008-08-26 19:12:23 +00:00
parent 3e526dcdbd
commit 00a8d314c5
35 changed files with 445 additions and 188 deletions
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24
Eigen/src/Regression/Regression.h
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@@ -76,17 +76,17 @@
* Let's now describe precisely the parameters:
* @param numPoints the number of points
* @param points the array of pointers to the points on which to perform the linear regression
* @param retCoefficients pointer to the vector in which to store the result.
This vector must be of the same type and size as the
data points. The meaning of its coords is as follows.
For brevity, let \f$n=Size\f$,
\f$r_i=retCoefficients[i]\f$,
and \f$f=funcOfOthers\f$. Denote by
\f$x_0,\ldots,x_{n-1}\f$
the n coordinates in the n-dimensional space.
Then the result equation is:
\f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1}
+ r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f]
* @param result pointer to the vector in which to store the result.
This vector must be of the same type and size as the
data points. The meaning of its coords is as follows.
For brevity, let \f$n=Size\f$,
\f$r_i=retCoefficients[i]\f$,
and \f$f=funcOfOthers\f$. Denote by
\f$x_0,\ldots,x_{n-1}\f$
the n coordinates in the n-dimensional space.
Then the result equation is:
\f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1}
+ r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f]
* @param funcOfOthers Determines which coord to express as a function of the
others. Coords are numbered starting from 0, so that a
value of 0 means \f$x\f$, 1 means \f$y\f$,
@@ -183,7 +183,7 @@ void fitHyperplane(int numPoints,
VectorType diff = (*(points[i]) - mean).conjugate();
covMat += diff * diff.adjoint();
}
// now we just have to pick the eigen vector with smallest eigen value
SelfAdjointEigenSolver<CovMatrixType> eig(covMat);
result->start(size) = eig.eigenvectors().col(0);