From c10aa2502c2cdc62bef95eea898d02e175431bda Mon Sep 17 00:00:00 2001 From: Wolfgang Bangerth Date: Mon, 13 May 2019 03:18:37 -0600 Subject: [PATCH] Fix a couple of comments. --- .../headers/automatic_and_symbolic_differentiation.h | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/doc/doxygen/headers/automatic_and_symbolic_differentiation.h b/doc/doxygen/headers/automatic_and_symbolic_differentiation.h index ff8f13cec9..5b34e36da8 100644 --- a/doc/doxygen/headers/automatic_and_symbolic_differentiation.h +++ b/doc/doxygen/headers/automatic_and_symbolic_differentiation.h @@ -525,8 +525,8 @@ * is able to achieve for this example). * * Due to the sophisticated CAS that forms the foundation of symbolic operations, the types of - * manipulations are not necessarily restricted to differentiation alone, but rather may span an - * range spectra of manipulations relevant to discrete differential calculus, topics in pure + * manipulations are not necessarily restricted to differentiation alone, but rather may span a + * spectrum of manipulations relevant to discrete differential calculus, topics in pure * mathematics, and more. * The documentation for the SymPy library gives * plenty of examples that highlight what a fully-fledged CAS is capable of. @@ -538,7 +538,7 @@ * In fact, this class can be used as a "drop-in" replacement for arithmetic types in many * situations, transforming the operations from being numeric to symbolic in nature; this is * made especially easy when classes are templated on the underlying number type. - * Being focused on numerical simulation of PDE's, the functionality of the CAS that is exposed + * Being focused on numerical simulation of PDEs, the functionality of the CAS that is exposed * within deal.II focuses on symbolic expression creation, manipulation, and differentiation. * * As a final note, it is important to recognize a major deficiency in deal.II's current implementation -- 2.39.5