Put adaptagrams into its own folder

1 files changed, 0 insertions, 140 deletions

diff --git a/src/libcola/sparse_matrix.h b/src/libcola/sparse_matrix.h
deleted file mode 100644
index f4ec85816..000000000
--- a/src/libcola/sparse_matrix.h
+++ /dev/null
@@ -1,140 +0,0 @@
-/*
- * vim: ts=4 sw=4 et tw=0 wm=0
- *
- * libcola - A library providing force-directed network layout using the 
- *           stress-majorization method subject to separation constraints.
- *
- * Copyright (C) 2006-2008  Monash University
- *
- * This library is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- * See the file LICENSE.LGPL distributed with the library.
- *
- * This library is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- *
- * Author(s):  Tim Dwyer
-*/
-
-/*
- * Yale Sparse Matrix implementation (from Wikipedia definition).
- * It stores an initial sparse n×n matrix M in row form using three arrays, A,
- * IA, JA. NZ denotes the number of nonzero entries in matrix M. The array A
- * then is of length NZ and holds all nonzero entries of M. The array IA stores
- * at IA(i) the position of the first element of row i in the sparse array A.
- * The length of row i is determined by IA(i+1) - IA(i). Therefore IA needs to
- * be of length N + 1. In array JA, the column index of the element A(j) is
- * stored. JA is of length NZ.
- */
-#ifndef _SPARSE_MATRIX_H
-#define _SPARSE_MATRIX_H
-
-#include <valarray>
-#include <map>
-#include <cstdio>
-
-#include "libvpsc/assertions.h"
-
-namespace cola {
-struct SparseMap {
-    SparseMap(unsigned n = 0) : n(n) {};
-    unsigned n;
-    typedef std::pair<unsigned, unsigned> SparseIndex;
-    typedef std::map<SparseIndex,double> SparseLookup;
-    typedef SparseLookup::const_iterator ConstIt;
-    SparseLookup lookup;
-    double& operator[](const SparseIndex& k) {
-        return lookup[k];
-    }
-    double& operator()(const unsigned i, const unsigned j) {
-        return lookup[std::make_pair(i,j)]; 
-    }
-    double getIJ(const unsigned i, const unsigned j) const {
-        COLA_ASSERT(i<n);
-        COLA_ASSERT(j<n);
-        ConstIt v=lookup.find(std::make_pair(i,j));
-        if(v!=lookup.end()) {
-            return v->second;
-        }
-        return 0;
-    }
-    size_t nonZeroCount() const {
-        return lookup.size();
-    }
-    void resize(unsigned n) {
-        this->n = n;
-    }
-    void clear() {
-        lookup.clear();
-    }
-};
-/*
- * Yale Sparse Matrix implementation (from Wikipedia definition).
- * It stores an initial sparse n×n matrix M in row form using three arrays, A,
- * IA, JA. NZ denotes the number of nonzero entries in matrix M. The array A
- * then is of length NZ and holds all nonzero entries of M. The array IA stores
- * at IA(i) the position of the first element of row i in the sparse array A.
- * The length of row i is determined by IA(i+1) - IA(i). Therefore IA needs to
- * be of length N + 1. In array JA, the column index of the element A(j) is
- * stored. JA is of length NZ.
- */
-class SparseMatrix {
-public:
-    SparseMatrix(SparseMap const & m)
-            : n(m.n), NZ((unsigned)m.nonZeroCount()), sparseMap(m), 
-              A(std::valarray<double>(NZ)), IA(std::valarray<unsigned>(n+1)), JA(std::valarray<unsigned>(NZ)) {
-        unsigned cnt=0;
-        int lastrow=-1;
-        for(SparseMap::ConstIt i=m.lookup.begin(); i!=m.lookup.end(); i++) {
-            SparseMap::SparseIndex p = i->first;
-            COLA_ASSERT(p.first<n);
-            COLA_ASSERT(p.second<n);
-            A[cnt]=i->second;
-            if((int)p.first!=lastrow) {
-                for(unsigned r=lastrow+1;r<=p.first;r++) {
-                    IA[r]=cnt;
-                }
-                lastrow=p.first;
-            }
-            JA[cnt]=p.second;
-            cnt++;
-        }
-        for(unsigned r=lastrow+1;r<=n;r++) {
-            IA[r]=NZ;
-        }
-    }
-    void rightMultiply(std::valarray<double> const & v, std::valarray<double> & r) const {
-        COLA_ASSERT(v.size()>=n);
-        COLA_ASSERT(r.size()>=n);
-        for(unsigned i=0;i<n;i++) {
-            r[i]=0;
-            for(unsigned j=IA[i];j<IA[i+1];j++) {
-                r[i]+=A[j]*v[JA[j]];
-            }
-        }
-    }
-    double getIJ(const unsigned i, const unsigned j) const {
-        return sparseMap.getIJ(i,j);
-    }
-    void print() const {
-        for(unsigned i=0;i<n;i++) {
-            for(unsigned j=0;j<n;j++) {
-                printf("%f ",getIJ(i,j));
-            }
-            printf("\n");
-        }
-    }
-    unsigned rowSize() const {
-        return n;
-    }
-private:
-    const unsigned n,NZ;
-    SparseMap const & sparseMap;
-    std::valarray<double> A;
-    std::valarray<unsigned> IA, JA;
-};
-} //namespace cola
-#endif /* _SPARSE_MATRIX_H */