71 lines
2.1 KiB
C
71 lines
2.1 KiB
C
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#ifndef IGL_REDUX_H
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#define IGL_REDUX_H
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#include <Eigen/Core>
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#include <Eigen/Sparse>
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namespace igl
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{
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// REDUX Perform reductions on the rows or columns of a SparseMatrix. This is
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// _similar_ to DenseBase::redux, but different in two important ways:
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// 1. (unstored) Zeros are **not** "visited", however if the first element
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// in the column/row does not appear in the first row/column then the
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// reduction is assumed to start with zero. In this way, "any", "all",
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// "count"(non-zeros) work as expected. This means it is **not** possible
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// to use this to count (implicit) zeros.
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// 2. This redux is more powerful in the sense that A and B may have
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// different types. This makes it possible to count the number of
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// non-zeros in a SparseMatrix<bool> A into a VectorXi B.
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//
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// Inputs:
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// A m by n sparse matrix
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// dim dimension along which to sum (1 or 2)
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// func function handle with the prototype `X(Y a, I i, J j, Z b)` where a
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// is the running value, b is A(i,j)
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// Output:
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// S n-long sparse vector (if dim == 1)
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// or
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// S m-long sparse vector (if dim == 2)
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template <typename AType, typename Func, typename DerivedB>
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inline void redux(
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const Eigen::SparseMatrix<AType> & A,
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const int dim,
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const Func & func,
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Eigen::PlainObjectBase<DerivedB> & B);
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}
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// Implementation
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#include "for_each.h"
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template <typename AType, typename Func, typename DerivedB>
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inline void igl::redux(
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const Eigen::SparseMatrix<AType> & A,
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const int dim,
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const Func & func,
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Eigen::PlainObjectBase<DerivedB> & B)
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{
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typedef typename Eigen::SparseMatrix<AType>::StorageIndex Index;
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assert((dim == 1 || dim == 2) && "dim must be 2 or 1");
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// Get size of input
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int m = A.rows();
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int n = A.cols();
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// resize output
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B = DerivedB::Zero(dim==1?n:m);
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const auto func_wrap = [&func,&B,&dim](const Index i, const Index j, const AType v)
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{
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if(dim == 1)
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{
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B(j) = i == 0? v : func(B(j),v);
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}else
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{
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B(i) = j == 0? v : func(B(i),v);
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}
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};
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for_each(A,func_wrap);
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}
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//#ifndef IGL_STATIC_LIBRARY
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//# include "redux.cpp"
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//#endif
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#endif
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