From: Wolfgang Bangerth Date: Wed, 24 Apr 2019 17:58:59 +0000 (-0700) Subject: Apply suggestions from code review X-Git-Tag: v9.1.0-rc1~173^2~2 X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=d34dc285bb3e087094c8edd34e15e6aa2996b1a8;p=dealii.git Apply suggestions from code review Co-Authored-By: rezarastak --- diff --git a/include/deal.II/base/derivative_form.h b/include/deal.II/base/derivative_form.h index cd0f43a16c..10f99f5e44 100644 --- a/include/deal.II/base/derivative_form.h +++ b/include/deal.II/base/derivative_form.h @@ -112,7 +112,7 @@ public: /** * Compute the Frobenius norm of this form, i.e., the expression * $\sqrt{\sum_{ij} |DF_{ij}|^2} = - * \sqrt{\sum_{ij} |\frac{\partial F_i}{\partial x_j}|}$. + * \sqrt{\sum_{ij} |\frac{\partial F_i}{\partial x_j}|^2}$. */ typename numbers::NumberTraits::real_type norm() const; @@ -129,7 +129,7 @@ public: * Assuming that the current object stores the Jacobian of a mapping * $\mathbf F$, then the current function computes the covariant form * of the derivative, namely $(\nabla \mathbf F) {\mathbf G}^{-1}$, where - * $\mathbf G = (\nabla \mathbf F)^{T}*(\nabla \mathbf F)$. If $\nabla \mathbf + * $\mathbf G = (\nabla \mathbf F)^{T}(\nabla \mathbf F)$. If $\nabla \mathbf * F$ is a square matrix (i.e., $\mathbf F: * {\mathbb R}^n \mapsto {\mathbb R}^n$), then this function * simplifies to computing $\nabla {\mathbf F}^{-T}$.