From 5efd5ed821dac8fdb5839ae0f5008b0e8f219de4 Mon Sep 17 00:00:00 2001 From: Jean-Paul Pelteret Date: Wed, 20 Feb 2019 12:22:22 +0100 Subject: [PATCH] Small grammatical fixes to documentation of ADHelpers. --- .../deal.II/differentiation/ad/ad_helpers.h | 36 +++++++++---------- 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/include/deal.II/differentiation/ad/ad_helpers.h b/include/deal.II/differentiation/ad/ad_helpers.h index f884ee4694..bc00902024 100644 --- a/include/deal.II/differentiation/ad/ad_helpers.h +++ b/include/deal.II/differentiation/ad/ad_helpers.h @@ -115,8 +115,8 @@ namespace Differentiation * * // Indicate that we are about to start tracing the operations for * // function evaluation on the tape. If this tape has already been used - * // (i.e. the operations are already recorded) then we (optionally) load - * // the tape and reuse this data. + * // (i.e. the operations are already recorded) then we (optionally) + * // load the tape and reuse this data. * const bool is_recording * = ad_helper.start_recording_operations(tape_index); * if (is_recording == true) @@ -198,11 +198,11 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\mathbf{f}(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * @param[in] n_dependent_variables The number of scalar functions to be * defined that will have a sensitivity to the given independent * variables. In the computation of $\mathbf{f}(\mathbf{X})$, this will - * be the number of outputs $\mathbf{f}$, i.e. the dimension of the + * be the number of outputs $\mathbf{f}$, i.e., the dimension of the * image space. */ ADHelperBase(const unsigned int n_independent_variables, @@ -324,11 +324,11 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\mathbf{f}(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * @param[in] n_dependent_variables The number of scalar functions to be * defined that will have a sensitivity to the given independent * variables. In the computation of $\mathbf{f}(\mathbf{X})$, this will - * be the number of outputs $\mathbf{f}$, i.e. the dimension of the + * be the number of outputs $\mathbf{f}$, i.e., the dimension of the * image space. * @param[in] clear_registered_tapes A flag that indicates the that * list of @p registered_tapes must be cleared. @@ -867,11 +867,11 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\mathbf{f}(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * @param[in] n_dependent_variables The number of scalar functions to be * defined that will have a sensitivity to the given independent * variables. In the computation of $\mathbf{f}(\mathbf{X})$, this will - * be the number of outputs $\mathbf{f}$, i.e. the dimension of the + * be the number of outputs $\mathbf{f}$, i.e., the dimension of the * image space. */ ADHelperCellLevelBase(const unsigned int n_independent_variables, @@ -964,7 +964,7 @@ namespace Differentiation //@{ /** - * Set the values for the independent variables $\mathbf{X}$, i.e. the + * Set the values for the independent variables $\mathbf{X}$, i.e., the * linearization point. * * @param[in] dof_values A vector field associated with local @@ -986,7 +986,7 @@ namespace Differentiation set_dof_values(const std::vector &dof_values); /** - * Set the values for the independent variables $\mathbf{X}$, i.e. the + * Set the values for the independent variables $\mathbf{X}$, i.e., the * linearization point. * * @param[in] values A vector field from which the values of all @@ -1252,7 +1252,7 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\Psi(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * * @note There is only one dependent variable associated with the total * energy attributed to the local finite element. That is to say, this @@ -1568,11 +1568,11 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\mathbf{r}(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * @param[in] n_dependent_variables The number of scalar functions to be * defined that will have a sensitivity to the given independent * variables. In the computation of $\mathbf{r}(\mathbf{X})$, this will - * be the number of outputs $\mathbf{r}$, i.e. the dimension of the + * be the number of outputs $\mathbf{r}$, i.e., the dimension of the * image space. */ ADHelperResidualLinearization(const unsigned int n_independent_variables, @@ -2682,11 +2682,11 @@ namespace Differentiation * that will be used in the definition of the functions that it is * desired to compute the sensitivities of. In the computation of * $\mathbf{f}(\mathbf{X})$, this will be the number of inputs - * $\mathbf{X}$, i.e. the dimension of the domain space. + * $\mathbf{X}$, i.e., the dimension of the domain space. * @param[in] n_dependent_variables The number of scalar functions to be * defined that will have a sensitivity to the given independent * variables. In the computation of $\mathbf{f}(\mathbf{X})$, this will - * be the number of outputs $\mathbf{f}$, i.e. the dimension of the + * be the number of outputs $\mathbf{f}$, i.e., the dimension of the * image space. */ ADHelperPointLevelFunctionsBase( @@ -2982,7 +2982,7 @@ namespace Differentiation * * // Indicate that we are about to start tracing the operations for * // function evaluation on the tape. If this tape has already been - * // used (i.e., the operations are already recorded) then we + * // used (i.e. the operations are already recorded) then we * // (optionally) load the tape and reuse this data. * const bool is_recording * = ad_helper.start_recording_operations(tape_index); @@ -3203,7 +3203,7 @@ namespace Differentiation * @f] * * @param[in] gradient The gradient of the scalar function with respect to - * all independent variables, i.e. that returned by compute_gradient(). + * all independent variables, i.e., that returned by compute_gradient(). * @param[in] extractor_row An extractor associated with the input field * variables. This effectively defines which components of the global set * of independent variables this field is associated with. @@ -3226,7 +3226,7 @@ namespace Differentiation * @f] * * @param[in] hessian The Hessian of the scalar function with respect to - * all independent variables, i.e. that returned by compute_hessian(). + * all independent variables, i.e., that returned by compute_hessian(). * @param[in] extractor_row An extractor associated with the input field * variables for which the first index of the Hessian is extracted. * @param[in] extractor_col An extractor associated with the input field -- 2.39.5