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Tutorial page 7: more typical example for .all(), minor copy-editing.
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@ -37,8 +37,8 @@ The \em trace of a matrix, as returned by the function \c trace(), is the sum of
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\subsection TutorialReductionsVisitorsBroadcastingReductionsNorm Norm reductions
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Eigen also provides reductions to obtain the norm or squared norm of a vector with \link DenseBase::norm() norm() \endlink and \link DenseBase::squaredNorm() squaredNorm() \endlink respectively.
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These operations can also operate on objects such as Matrices or Arrays, as shown in the following example:
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Eigen also provides reductions to obtain the Euclidean norm or squared norm of a vector with \link MatrixBase::norm() norm() \endlink and \link Matrix::squaredNorm() squaredNorm() \endlink respectively.
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These operations can also operate on matrices; in that case, they use the Frobenius norm. The following example shows these methods.
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<table class="tutorial_code"><tr><td>
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Example: \include Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp
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@ -51,11 +51,11 @@ Output:
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\subsection TutorialReductionsVisitorsBroadcastingReductionsBool Boolean-like reductions
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Another interesting type of reductions are the ones that deal with \b true and \b false values:
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- \link DenseBase::all() all() \endlink returns \b true if all of the coefficients in a given Matrix or \link ArrayBase Array \endlink are \b true .
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- \link DenseBase::any() any() \endlink returns \b true if at least one of the coefficients in a given Matrix or \link ArrayBase Array \endlink are \b true .
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- \link DenseBase::count() count() \endlink returns the number of \b true coefficients in a given Matrix or \link ArrayBase Array \endlink.
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- \link DenseBase::all() all() \endlink returns \b true if all of the coefficients in a given Matrix or Array are \b true .
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- \link DenseBase::any() any() \endlink returns \b true if at least one of the coefficients in a given Matrix or Array is \b true .
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- \link DenseBase::count() count() \endlink returns the number of \b true coefficients in a given Matrix or Array.
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Their behaviour can be seen in the following example:
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These are typically used in conjunction with the coefficient-wise comparison and equality operators provided by Array. For instance, <tt>array > 0</tt> is an %Array of the same size as \c array , with \b true at those positions where the corresponding coefficient of \c array is positive. Thus, <tt>(array > 0).all()</tt> tests whether all coefficients of \c array are positive. This can be seen in the following example:
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<table class="tutorial_code"><tr><td>
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Example: \include Tutorial_ReductionsVisitorsBroadcasting_reductions_bool.cpp
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@ -67,15 +67,15 @@ Output:
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\section TutorialReductionsVisitorsBroadcastingVisitors Visitors
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Visitors are useful when the location of a coefficient inside a Matrix or
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\link ArrayBase Array \endlink wants to be obtained. The simplest example are the
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Visitors are useful when one wants to obtain the location of a coefficient inside
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a Matrix or Array. The simplest examples are
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\link MatrixBase::maxCoeff() maxCoeff(&x,&y) \endlink and
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\link MatrixBase::minCoeff() minCoeff(&x,&y) \endlink, that can be used to find
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\link MatrixBase::minCoeff() minCoeff(&x,&y)\endlink, which can be used to find
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the location of the greatest or smallest coefficient in a Matrix or
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\link ArrayBase Array \endlink:
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Array.
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The arguments passed to a visitor are pointers to the variables where the
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row and column position are to be stored. These variables are of type
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row and column position are to be stored. These variables should be of type
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\link DenseBase::Index Index \endlink (FIXME: link ok?), as shown below:
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<table class="tutorial_code"><tr><td>
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@ -91,11 +91,11 @@ as if it was a typical reduction operation.
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\section TutorialReductionsVisitorsBroadcastingPartialReductions Partial reductions
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Partial reductions are reductions that can operate column- or row-wise on a Matrix or
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\link ArrayBase Array \endlink, applying the reduction operation on each column or row and
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Array, applying the reduction operation on each column or row and
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returning a column or row-vector with the corresponding values. Partial reductions are applied
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with \link DenseBase::colwise() colwise() \endlink or \link DenseBase::rowwise() rowwise() \endlink.
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A simple example is obtaining the sum of the elements
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A simple example is obtaining the maximum of the elements
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in each column in a given matrix, storing the result in a row-vector:
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<table class="tutorial_code"><tr><td>
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@ -121,7 +121,7 @@ return a 'column-vector'</b>
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\subsection TutorialReductionsVisitorsBroadcastingPartialReductionsCombined Combining partial reductions with other operations
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It is also possible to use the result of a partial reduction to do further processing.
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Here there is another example that aims to find the the column whose sum of elements is the maximum
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Here is another example that aims to find the column whose sum of elements is the maximum
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within a matrix. With column-wise partial reductions this can be coded as:
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<table class="tutorial_code"><tr><td>
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@ -172,7 +172,7 @@ Output:
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It is important to point out that the vector to be added column-wise or row-wise must be of type Vector,
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and cannot be a Matrix. If this is not met then you will get compile-time error. This also means that
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broadcasting operations can only be applied with an object of type Vector, when operating with Matrix.
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The same applies for the \link ArrayBase Array \endlink class, where the equivalent for VectorXf is ArrayXf.
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The same applies for the Array class, where the equivalent for VectorXf is ArrayXf.
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Therefore, to perform the same operation row-wise we can do:
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@ -185,7 +185,7 @@ Output:
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</td></tr></table>
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\subsection TutorialReductionsVisitorsBroadcastingBroadcastingCombined Combining broadcasting with other operations
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Broadcasting can also be combined with other operations, such as Matrix or \link ArrayBase Array \endlink operations,
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Broadcasting can also be combined with other operations, such as Matrix or Array operations,
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reductions and partial reductions.
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Now that broadcasting, reductions and partial reductions have been introduced, we can dive into a more advanced example that finds
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@ -207,8 +207,8 @@ The line that does the job is
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We will go step by step to understand what is happening:
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- <tt>m.colwise() - v</tt> is a broadcasting operation, substracting <tt>v</tt> from each column in <tt>m</tt>. The result of this operation
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would be a new matrix whose size is the same as matrix <tt>m</tt>: \f[
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- <tt>m.colwise() - v</tt> is a broadcasting operation, subtracting <tt>v</tt> from each column in <tt>m</tt>. The result of this operation
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is a new matrix whose size is the same as matrix <tt>m</tt>: \f[
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\mbox{m.colwise() - v} =
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\begin{bmatrix}
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-1 & 21 & 4 & 7 \\
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@ -217,14 +217,14 @@ would be a new matrix whose size is the same as matrix <tt>m</tt>: \f[
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\f]
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- <tt>(m.colwise() - v).colwise().squaredNorm()</tt> is a partial reduction, computing the squared norm column-wise. The result of
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this operation would be a row-vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
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this operation is a row-vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
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\mbox{(m.colwise() - v).colwise().squaredNorm()} =
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\begin{bmatrix}
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1 & 505 & 32 & 50
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\end{bmatrix}
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\f]
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- Finally, <tt>minCoeff(&index)</tt> is used to obtain the index of the column in <tt>m</tt> that is closer to <tt>v</tt> in terms of Euclidean
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- Finally, <tt>minCoeff(&index)</tt> is used to obtain the index of the column in <tt>m</tt> that is closest to <tt>v</tt> in terms of Euclidean
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distance.
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\li \b Next: \ref TutorialGeometry
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@ -6,19 +6,16 @@ using namespace Eigen;
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int main()
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{
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MatrixXf m(2,2), n(2,2);
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ArrayXXf a(2,2);
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m << 0,2,
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a << 1,2,
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3,4;
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n << 1,2,
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3,4;
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cout << "m.all() = " << m.all() << endl;
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cout << "m.any() = " << m.any() << endl;
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cout << "m.count() = " << m.count() << endl;
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cout << "(a > 0).all() = " << (a > 0).all() << endl;
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cout << "(a > 0).any() = " << (a > 0).any() << endl;
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cout << "(a > 0).count() = " << (a > 0).count() << endl;
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cout << endl;
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cout << "n.all() = " << n.all() << endl;
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cout << "n.any() = " << n.any() << endl;
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cout << "n.count() = " << n.count() << endl;
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cout << "(a > 2).all() = " << (a > 2).all() << endl;
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cout << "(a > 2).any() = " << (a > 2).any() << endl;
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cout << "(a > 2).count() = " << (a > 2).count() << endl;
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}
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