new simplified API to fill sparse matrices (the old functions are

deprecated). Basically there are now only 2 functions to set a
coefficient:
1) mat.coeffRef(row,col) = value;
2) mat.insert(row,col) = value;
coeffRef has no limitation, insert assumes the coeff has not already
been set, and raises an assert otherwise.
In addition I added a much lower level, but more efficient filling
mechanism for
internal use only.

3 files changed, 41 insertions, 18 deletions

diff --git a/test/sparse.h b/test/sparse.h
index 80d99dc5b..eb2f98f5f 100644
--- a/test/sparse.h
+++ b/test/sparse.h
@@ -64,9 +64,11 @@ initSparse(double density,
            std::vector<Vector2i>* zeroCoords = 0,
            std::vector<Vector2i>* nonzeroCoords = 0)
 {
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
+  sparseMat.setZero();
+  sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
   for(int j=0; j<refMat.cols(); j++)
   {
+    sparseMat.startVec(j);
     for(int i=0; i<refMat.rows(); i++)
     {
       Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
@@ -85,7 +87,7 @@ initSparse(double density,
         
       if (v!=Scalar(0))
       {
-        sparseMat.fill(i,j) = v;
+        sparseMat.insertBack(j,i) = v;
         if (nonzeroCoords)
           nonzeroCoords->push_back(Vector2i(i,j));
       }
@@ -96,7 +98,7 @@ initSparse(double density,
       refMat(i,j) = v;
     }
   }
-  sparseMat.endFill();
+  sparseMat.finalize();
 }
 
 template<typename Scalar> void
@@ -107,9 +109,11 @@ initSparse(double density,
            std::vector<Vector2i>* zeroCoords = 0,
            std::vector<Vector2i>* nonzeroCoords = 0)
 {
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
+  sparseMat.setZero();
+  sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
   for(int j=0; j<refMat.cols(); j++)
   {
+    sparseMat.startVec(j); // not needed for DynamicSparseMatrix
     for(int i=0; i<refMat.rows(); i++)
     {
       Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
@@ -128,7 +132,7 @@ initSparse(double density,
         
       if (v!=Scalar(0))
       {
-        sparseMat.fill(i,j) = v;
+        sparseMat.insertBack(j,i) = v;
         if (nonzeroCoords)
           nonzeroCoords->push_back(Vector2i(i,j));
       }
@@ -139,7 +143,7 @@ initSparse(double density,
       refMat(i,j) = v;
     }
   }
-  sparseMat.endFill();
+  sparseMat.finalize();
 }
 
 template<typename Scalar> void
@@ -156,7 +160,7 @@ initSparse(double density,
     Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
     if (v!=Scalar(0))
     {
-      sparseVec.fill(i) = v;
+      sparseVec.insertBack(i) = v;
       if (nonzeroCoords)
         nonzeroCoords->push_back(i);
     }
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index 410ef96a6..cf58b30af 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -177,22 +177,39 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
     VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
     #endif
 
-    // test fillrand
+    // test insert (inner random)
     {
       DenseMatrix m1(rows,cols);
       m1.setZero();
       SparseMatrixType m2(rows,cols);
-      m2.startFill();
+      m2.reserve(10);
       for (int j=0; j<cols; ++j)
       {
         for (int k=0; k<rows/2; ++k)
         {
           int i = ei_random<int>(0,rows-1);
           if (m1.coeff(i,j)==Scalar(0))
-            m2.fillrand(i,j) = m1(i,j) = ei_random<Scalar>();
+            m2.insert(i,j) = m1(i,j) = ei_random<Scalar>();
         }
       }
-      m2.endFill();
+      m2.finalize();
+      VERIFY_IS_APPROX(m2,m1);
+    }
+    
+    // test insert (fully random)
+    {
+      DenseMatrix m1(rows,cols);
+      m1.setZero();
+      SparseMatrixType m2(rows,cols);
+      m2.reserve(10);
+      for (int k=0; k<rows*cols; ++k)
+      {
+        int i = ei_random<int>(0,rows-1);
+        int j = ei_random<int>(0,cols-1);
+        if (m1.coeff(i,j)==Scalar(0))
+          m2.insert(i,j) = m1(i,j) = ei_random<Scalar>();
+      }
+      m2.finalize();
       VERIFY_IS_APPROX(m2,m1);
     }
   
@@ -291,8 +308,9 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
     refM2.setZero();
     int countFalseNonZero = 0;
     int countTrueNonZero = 0;
-    m2.startFill();
     for (int j=0; j<m2.outerSize(); ++j)
+    {
+      m2.startVec(j);
       for (int i=0; i<m2.innerSize(); ++i)
       {
         float x = ei_random<float>(0,1);
@@ -303,15 +321,16 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
         else if (x<0.5)
         {
           countFalseNonZero++;
-          m2.fill(i,j) = Scalar(0);
+          m2.insertBack(j,i) = Scalar(0);
         }
         else
         {
           countTrueNonZero++;
-          m2.fill(i,j) = refM2(i,j) = Scalar(1);
+          m2.insertBack(j,i) = refM2(i,j) = Scalar(1);
         }
       }
-    m2.endFill();
+    }
+    m2.finalize();
     VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
     VERIFY_IS_APPROX(m2, refM2);
     m2.prune(1);
diff --git a/test/sparse_solvers.cpp b/test/sparse_solvers.cpp
index e1ec1ef35..ce19153ff 100644
--- a/test/sparse_solvers.cpp
+++ b/test/sparse_solvers.cpp
@@ -37,12 +37,12 @@ initSPD(double density,
     initSparse(density,aux,sparseMat,ForceNonZeroDiag);
     refMat += aux * aux.adjoint();
   }
-  sparseMat.startFill();
+  sparseMat.setZero();
   for (int j=0 ; j<sparseMat.cols(); ++j)
     for (int i=j ; i<sparseMat.rows(); ++i)
       if (refMat(i,j)!=Scalar(0))
-        sparseMat.fill(i,j) = refMat(i,j);
-  sparseMat.endFill();
+        sparseMat.insert(i,j) = refMat(i,j);
+  sparseMat.finalize();
 }
 
 template<typename Scalar> void sparse_solvers(int rows, int cols)