Enable and fix -Wdouble-conversion warnings

15 files changed, 25 insertions, 24 deletions

diff --git a/test/fastmath.cpp b/test/fastmath.cpp
index efdd5b313..438e6b2e5 100644
--- a/test/fastmath.cpp
+++ b/test/fastmath.cpp
@@ -49,7 +49,7 @@ void check_inf_nan(bool dryrun) {
     VERIFY( !m.allFinite() );
     VERIFY(  m.hasNaN() );
   }
-  m(4) /= 0.0;
+  m(4) /= T(0.0);
   if(dryrun)
   {
     std::cout << "std::isfinite(" << m(4) << ") = "; check((std::isfinite)(m(4)),false); std::cout << "  ; numext::isfinite = "; check((numext::isfinite)(m(4)), false); std::cout << "\n";
diff --git a/test/geo_hyperplane.cpp b/test/geo_hyperplane.cpp
index c1cc691c9..e77702bc7 100644
--- a/test/geo_hyperplane.cpp
+++ b/test/geo_hyperplane.cpp
@@ -97,9 +97,9 @@ template<typename Scalar> void lines()
     Vector u = Vector::Random();
     Vector v = Vector::Random();
     Scalar a = internal::random<Scalar>();
-    while (abs(a-1) < 1e-4) a = internal::random<Scalar>();
-    while (u.norm() < 1e-4) u = Vector::Random();
-    while (v.norm() < 1e-4) v = Vector::Random();
+    while (abs(a-1) < Scalar(1e-4)) a = internal::random<Scalar>();
+    while (u.norm() < Scalar(1e-4)) u = Vector::Random();
+    while (v.norm() < Scalar(1e-4)) v = Vector::Random();
 
     HLine line_u = HLine::Through(center + u, center + a*u);
     HLine line_v = HLine::Through(center + v, center + a*v);
@@ -111,14 +111,14 @@ template<typename Scalar> void lines()
     Vector result = line_u.intersection(line_v);
 
     // the lines should intersect at the point we called "center"
-    if(abs(a-1) > 1e-2 && abs(v.normalized().dot(u.normalized()))<0.9)
+    if(abs(a-1) > Scalar(1e-2) && abs(v.normalized().dot(u.normalized()))<Scalar(0.9))
       VERIFY_IS_APPROX(result, center);
 
     // check conversions between two types of lines
     PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
     HLine line_u2(pl);
     CoeffsType converted_coeffs = line_u2.coeffs();
-    if(line_u2.normal().dot(line_u.normal())<0.)
+    if(line_u2.normal().dot(line_u.normal())<Scalar(0))
       converted_coeffs = -line_u2.coeffs();
     VERIFY(line_u.coeffs().isApprox(converted_coeffs));
   }
diff --git a/test/geo_quaternion.cpp b/test/geo_quaternion.cpp
index 761bb52b4..25130c19a 100644
--- a/test/geo_quaternion.cpp
+++ b/test/geo_quaternion.cpp
@@ -30,7 +30,7 @@ template<typename QuatType> void check_slerp(const QuatType& q0, const QuatType&
   Scalar largeEps = test_precision<Scalar>();
 
   Scalar theta_tot = AA(q1*q0.inverse()).angle();
-  if(theta_tot>EIGEN_PI)
+  if(theta_tot>Scalar(EIGEN_PI))
     theta_tot = Scalar(2.*EIGEN_PI)-theta_tot;
   for(Scalar t=0; t<=Scalar(1.001); t+=Scalar(0.1))
   {
@@ -115,8 +115,8 @@ template<typename Scalar, int Options> void quaternion(void)
   // Do not execute the test if the rotation angle is almost zero, or
   // the rotation axis and v1 are almost parallel.
   if (abs(aa.angle()) > 5*test_precision<Scalar>()
-      && (aa.axis() - v1.normalized()).norm() < 1.99
-      && (aa.axis() + v1.normalized()).norm() < 1.99) 
+      && (aa.axis() - v1.normalized()).norm() < Scalar(1.99)
+      && (aa.axis() + v1.normalized()).norm() < Scalar(1.99))
   {
     VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
   }
diff --git a/test/geo_transformations.cpp b/test/geo_transformations.cpp
index 51f90036d..48393a5c6 100644
--- a/test/geo_transformations.cpp
+++ b/test/geo_transformations.cpp
@@ -466,7 +466,7 @@ template<typename Scalar, int Mode, int Options> void transformations()
     Scalar a2 = R0.slerp(Scalar(k+1)/Scalar(path_steps), R1).angle();
     l += std::abs(a2-a1);
   }
-  VERIFY(l<=EIGEN_PI*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
+  VERIFY(l<=Scalar(EIGEN_PI)*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
   
   // check basic features
   {
diff --git a/test/linearstructure.cpp b/test/linearstructure.cpp
index 292f33969..e7f4b3dc5 100644
--- a/test/linearstructure.cpp
+++ b/test/linearstructure.cpp
@@ -21,6 +21,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
   */
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
 
   Index rows = m.rows();
   Index cols = m.cols();
@@ -32,7 +33,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
              m3(rows, cols);
 
   Scalar s1 = internal::random<Scalar>();
-  while (abs(s1)<1e-3) s1 = internal::random<Scalar>();
+  while (abs(s1)<RealScalar(1e-3)) s1 = internal::random<Scalar>();
 
   Index r = internal::random<Index>(0, rows-1),
         c = internal::random<Index>(0, cols-1);
diff --git a/test/packetmath.cpp b/test/packetmath.cpp
index 37da6c86f..7f5a6512d 100644
--- a/test/packetmath.cpp
+++ b/test/packetmath.cpp
@@ -387,7 +387,7 @@ template<typename Scalar> void packetmath_real()
     data2[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
   }
 
-  if(internal::random<float>(0,1)<0.1)
+  if(internal::random<float>(0,1)<0.1f)
     data1[internal::random<int>(0, PacketSize)] = 0;
   CHECK_CWISE1_IF(PacketTraits::HasSqrt, std::sqrt, internal::psqrt);
   CHECK_CWISE1_IF(PacketTraits::HasLog, std::log, internal::plog);
diff --git a/test/qr_colpivoting.cpp b/test/qr_colpivoting.cpp
index 46c54b74f..ef3a6173b 100644
--- a/test/qr_colpivoting.cpp
+++ b/test/qr_colpivoting.cpp
@@ -206,7 +206,7 @@ template<typename MatrixType> void qr_kahan_matrix()
   RealScalar c = std::sqrt(1 - s*s);
   for (Index i = 0; i < rows; ++i) {
     m1(i, i) = pow(s, i);
-    m1.row(i).tail(rows - i - 1) = -pow(s, i) * c * MatrixType::Ones(1, rows - i - 1);
+    m1.row(i).tail(rows - i - 1) = -RealScalar(pow(s, i)) * c * MatrixType::Ones(1, rows - i - 1);
   }
   m1 = (m1 + m1.transpose()).eval();
   ColPivHouseholderQR<MatrixType> qr(m1);
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index cb8ebaedf..aa3882583 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -232,11 +232,11 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
       for (Index i=0; i<m2.rows(); ++i)
       {
         float x = internal::random<float>(0,1);
-        if (x<0.1)
+        if (x<0.1f)
         {
           // do nothing
         }
-        else if (x<0.5)
+        else if (x<0.5f)
         {
           countFalseNonZero++;
           m2.insert(i,j) = Scalar(0);
diff --git a/test/sparse_block.cpp b/test/sparse_block.cpp
index 8a6e0687c..582bf34c3 100644
--- a/test/sparse_block.cpp
+++ b/test/sparse_block.cpp
@@ -150,7 +150,7 @@ template<typename SparseMatrixType> void sparse_block(const SparseMatrixType& re
     DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
     SparseMatrixType m2(rows, cols);
     initSparse<Scalar>(density, refMat2, m2);
-    if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
+    if(internal::random<float>(0,1)>0.5f) m2.makeCompressed();
     Index j0 = internal::random<Index>(0,outer-2);
     Index j1 = internal::random<Index>(0,outer-2);
     Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp
index 7ec5270e8..501aeeaa6 100644
--- a/test/sparse_product.cpp
+++ b/test/sparse_product.cpp
@@ -245,7 +245,7 @@ template<typename SparseMatrixType> void sparse_product()
     for (int k=0; k<mS.outerSize(); ++k)
       for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
         if (it.index() == k)
-          it.valueRef() *= 0.5;
+          it.valueRef() *= Scalar(0.5);
 
     VERIFY_IS_APPROX(refS.adjoint(), refS);
     VERIFY_IS_APPROX(mS.adjoint(), mS);
diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp
index d95f301d5..b3e1dda25 100644
--- a/test/sparse_vector.cpp
+++ b/test/sparse_vector.cpp
@@ -12,7 +12,7 @@
 template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
 {
   double densityMat = (std::max)(8./(rows*cols), 0.01);
-  double densityVec = (std::max)(8./float(rows), 0.1);
+  double densityVec = (std::max)(8./(rows), 0.1);
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
   typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;
diff --git a/test/sparseqr.cpp b/test/sparseqr.cpp
index 50d1fcdf2..e8605fd21 100644
--- a/test/sparseqr.cpp
+++ b/test/sparseqr.cpp
@@ -54,7 +54,7 @@ template<typename Scalar> void test_sparseqr_scalar()
   
   b = dA * DenseVector::Random(A.cols());
   solver.compute(A);
-  if(internal::random<float>(0,1)>0.5)
+  if(internal::random<float>(0,1)>0.5f)
     solver.factorize(A);  // this checks that calling analyzePattern is not needed if the pattern do not change.
   if (solver.info() != Success)
   {
diff --git a/test/svd_common.h b/test/svd_common.h
index d8611b541..3588eefaa 100644
--- a/test/svd_common.h
+++ b/test/svd_common.h
@@ -141,14 +141,14 @@ void svd_least_square(const MatrixType& m, unsigned int computationOptions)
       using std::abs;
       
       SolutionType y(x);
-      y.row(k) = (1.+2*NumTraits<RealScalar>::epsilon())*x.row(k);
+      y.row(k) = (RealScalar(1)+2*NumTraits<RealScalar>::epsilon())*x.row(k);
       RealScalar residual_y = (m*y-rhs).norm();
       VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
       if(internal::is_same<RealScalar,float>::value) ++g_test_level;
       VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
       if(internal::is_same<RealScalar,float>::value) --g_test_level;
       
-      y.row(k) = (1.-2*NumTraits<RealScalar>::epsilon())*x.row(k);
+      y.row(k) = (RealScalar(1)-2*NumTraits<RealScalar>::epsilon())*x.row(k);
       residual_y = (m*y-rhs).norm();
       VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
       if(internal::is_same<RealScalar,float>::value) ++g_test_level;
diff --git a/test/svd_fill.h b/test/svd_fill.h
index 1bbe645ee..500954d47 100644
--- a/test/svd_fill.h
+++ b/test/svd_fill.h
@@ -54,7 +54,7 @@ void svd_fill_random(MatrixType &m, int Option = 0)
   }
   
   Matrix<Scalar,Dynamic,1> samples(7);
-  samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -1./NumTraits<RealScalar>::highest(), 1./NumTraits<RealScalar>::highest();
+  samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -RealScalar(1)/NumTraits<RealScalar>::highest(), RealScalar(1)/NumTraits<RealScalar>::highest();
   
   if(Option==Symmetric)
   {
diff --git a/test/triangular.cpp b/test/triangular.cpp
index 936c2aef3..3e120f406 100644
--- a/test/triangular.cpp
+++ b/test/triangular.cpp
@@ -65,7 +65,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
 
   m1 = MatrixType::Random(rows, cols);
   for (int i=0; i<rows; ++i)
-    while (numext::abs2(m1(i,i))<1e-1) m1(i,i) = internal::random<Scalar>();
+    while (numext::abs2(m1(i,i))<RealScalar(1e-1)) m1(i,i) = internal::random<Scalar>();
 
   Transpose<MatrixType> trm4(m4);
   // test back and forward subsitution with a vector as the rhs
@@ -78,7 +78,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
   m3 = m1.template triangularView<Lower>();
   VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
 
-  // test back and forward subsitution with a matrix as the rhs
+  // test back and forward substitution with a matrix as the rhs
   m3 = m1.template triangularView<Upper>();
   VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(m2)), largerEps));
   m3 = m1.template triangularView<Lower>();