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https://github.com/FULU-Foundation/OrcaSlicer-bambulab.git
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2ae2672ee9
Fixing dep build script on Windows and removing some warnings. Use bundled igl by default. Not building with the dependency scripts if not explicitly stated. This way, it will stay in Fix the libigl patch to include C source files in header only mode.
268 lines
7.9 KiB
C++
268 lines
7.9 KiB
C++
// This file is part of libigl, a simple c++ geometry processing library.
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//
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// Copyright (C) 2013 Alec Jacobson <alecjacobson@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla Public License
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// v. 2.0. If a copy of the MPL was not distributed with this file, You can
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// obtain one at http://mozilla.org/MPL/2.0/.
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#include "cat.h"
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#include <cstdio>
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// Bug in unsupported/Eigen/SparseExtra needs iostream first
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#include <iostream>
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#include <unsupported/Eigen/SparseExtra>
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// Sparse matrices need to be handled carefully. Because C++ does not
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// Template:
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// Scalar sparse matrix scalar type, e.g. double
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template <typename Scalar>
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IGL_INLINE void igl::cat(
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const int dim,
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const Eigen::SparseMatrix<Scalar> & A,
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const Eigen::SparseMatrix<Scalar> & B,
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Eigen::SparseMatrix<Scalar> & C)
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{
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assert(dim == 1 || dim == 2);
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using namespace Eigen;
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// Special case if B or A is empty
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if(A.size() == 0)
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{
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C = B;
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return;
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}
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if(B.size() == 0)
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{
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C = A;
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return;
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}
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#if false
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// This **must** be DynamicSparseMatrix, otherwise this implementation is
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// insanely slow
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DynamicSparseMatrix<Scalar, RowMajor> dyn_C;
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if(dim == 1)
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{
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assert(A.cols() == B.cols());
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dyn_C.resize(A.rows()+B.rows(),A.cols());
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}else if(dim == 2)
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{
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assert(A.rows() == B.rows());
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dyn_C.resize(A.rows(),A.cols()+B.cols());
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}else
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{
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fprintf(stderr,"cat.h: Error: Unsupported dimension %d\n",dim);
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}
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dyn_C.reserve(A.nonZeros()+B.nonZeros());
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// Iterate over outside of A
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for(int k=0; k<A.outerSize(); ++k)
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{
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// Iterate over inside
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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dyn_C.coeffRef(it.row(),it.col()) += it.value();
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}
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}
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// Iterate over outside of B
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for(int k=0; k<B.outerSize(); ++k)
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{
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// Iterate over inside
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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int r = (dim == 1 ? A.rows()+it.row() : it.row());
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int c = (dim == 2 ? A.cols()+it.col() : it.col());
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dyn_C.coeffRef(r,c) += it.value();
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}
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}
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C = SparseMatrix<Scalar>(dyn_C);
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#elif false
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std::vector<Triplet<Scalar> > CIJV;
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CIJV.reserve(A.nonZeros() + B.nonZeros());
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{
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// Iterate over outside of A
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for(int k=0; k<A.outerSize(); ++k)
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{
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// Iterate over inside
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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CIJV.emplace_back(it.row(),it.col(),it.value());
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}
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}
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// Iterate over outside of B
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for(int k=0; k<B.outerSize(); ++k)
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{
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// Iterate over inside
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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int r = (dim == 1 ? A.rows()+it.row() : it.row());
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int c = (dim == 2 ? A.cols()+it.col() : it.col());
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CIJV.emplace_back(r,c,it.value());
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}
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}
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}
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C = SparseMatrix<Scalar>(
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dim == 1 ? A.rows()+B.rows() : A.rows(),
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dim == 1 ? A.cols() : A.cols()+B.cols());
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C.reserve(A.nonZeros() + B.nonZeros());
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C.setFromTriplets(CIJV.begin(),CIJV.end());
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#else
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C = SparseMatrix<Scalar>(
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dim == 1 ? A.rows()+B.rows() : A.rows(),
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dim == 1 ? A.cols() : A.cols()+B.cols());
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Eigen::VectorXi per_col = Eigen::VectorXi::Zero(C.cols());
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if(dim == 1)
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{
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assert(A.outerSize() == B.outerSize());
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for(int k = 0;k<A.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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per_col(k)++;
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}
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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per_col(k)++;
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}
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}
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}else
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{
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for(int k = 0;k<A.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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per_col(k)++;
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}
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}
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for(int k = 0;k<B.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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per_col(A.cols() + k)++;
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}
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}
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}
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C.reserve(per_col);
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if(dim == 1)
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{
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for(int k = 0;k<A.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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C.insert(it.row(),k) = it.value();
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}
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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C.insert(A.rows()+it.row(),k) = it.value();
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}
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}
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}else
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{
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for(int k = 0;k<A.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (A,k); it; ++it)
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{
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C.insert(it.row(),k) = it.value();
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}
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}
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for(int k = 0;k<B.outerSize();++k)
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{
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for(typename SparseMatrix<Scalar>::InnerIterator it (B,k); it; ++it)
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{
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C.insert(it.row(),A.cols()+k) = it.value();
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}
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}
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}
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C.makeCompressed();
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#endif
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}
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template <typename Derived, class MatC>
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IGL_INLINE void igl::cat(
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const int dim,
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const Eigen::MatrixBase<Derived> & A,
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const Eigen::MatrixBase<Derived> & B,
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MatC & C)
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{
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assert(dim == 1 || dim == 2);
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// Special case if B or A is empty
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if(A.size() == 0)
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{
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C = B;
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return;
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}
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if(B.size() == 0)
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{
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C = A;
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return;
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}
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if(dim == 1)
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{
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assert(A.cols() == B.cols());
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C.resize(A.rows()+B.rows(),A.cols());
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C << A,B;
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}else if(dim == 2)
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{
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assert(A.rows() == B.rows());
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C.resize(A.rows(),A.cols()+B.cols());
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C << A,B;
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}else
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{
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fprintf(stderr,"cat.h: Error: Unsupported dimension %d\n",dim);
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}
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}
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template <class Mat>
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IGL_INLINE Mat igl::cat(const int dim, const Mat & A, const Mat & B)
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{
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assert(dim == 1 || dim == 2);
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Mat C;
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igl::cat(dim,A,B,C);
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return C;
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}
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template <class Mat>
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IGL_INLINE void igl::cat(const std::vector<std::vector< Mat > > & A, Mat & C)
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{
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using namespace std;
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// Start with empty matrix
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C.resize(0,0);
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for(const auto & row_vec : A)
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{
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// Concatenate each row horizontally
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// Start with empty matrix
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Mat row(0,0);
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for(const auto & element : row_vec)
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{
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row = cat(2,row,element);
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}
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// Concatenate rows vertically
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C = cat(1,C,row);
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}
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}
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#ifdef IGL_STATIC_LIBRARY
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// Explicit template instantiation
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// generated by autoexplicit.sh
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template Eigen::Matrix<double, -1, -1, 0, -1, -1> igl::cat<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(int, Eigen::Matrix<double, -1, -1, 0, -1, -1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1> const&);
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// generated by autoexplicit.sh
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template Eigen::SparseMatrix<double, 0, int> igl::cat<Eigen::SparseMatrix<double, 0, int> >(int, Eigen::SparseMatrix<double, 0, int> const&, Eigen::SparseMatrix<double, 0, int> const&);
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// generated by autoexplicit.sh
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template Eigen::Matrix<int, -1, -1, 0, -1, -1> igl::cat<Eigen::Matrix<int, -1, -1, 0, -1, -1> >(int, Eigen::Matrix<int, -1, -1, 0, -1, -1> const&, Eigen::Matrix<int, -1, -1, 0, -1, -1> const&);
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template void igl::cat<Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<double, -1, 1, 0, -1, 1> >(int, Eigen::MatrixBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> > const&, Eigen::MatrixBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> > const&, Eigen::Matrix<double, -1, 1, 0, -1, 1>&);
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template Eigen::Matrix<int, -1, 1, 0, -1, 1> igl::cat<Eigen::Matrix<int, -1, 1, 0, -1, 1> >(int, Eigen::Matrix<int, -1, 1, 0, -1, 1> const&, Eigen::Matrix<int, -1, 1, 0, -1, 1> const&);
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template Eigen::Matrix<double, -1, 1, 0, -1, 1> igl::cat<Eigen::Matrix<double, -1, 1, 0, -1, 1> >(int, Eigen::Matrix<double, -1, 1, 0, -1, 1> const&, Eigen::Matrix<double, -1, 1, 0, -1, 1> const&);
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template void igl::cat<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1> >(int, Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::Matrix<double, -1, -1, 0, -1, -1>&);
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template void igl::cat<Eigen::Matrix<int, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1> >(int, Eigen::MatrixBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::MatrixBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::Matrix<int, -1, -1, 0, -1, -1>&);
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#endif
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