changed 'well known' to 'well-known'

2026-02-28 16:02:52 +01:00
parent 058401a608
commit e9fde2bb3f
11 changed files with 12 additions and 12 deletions
@@ -24,7 +24,7 @@ allows an explicit handling of mixed operations.
 \section Algebraic_foundationsAlgebraic Algebraic Structures

 The algebraic structure concepts introduced within this section are
-motivated by their well known counterparts in traditional algebra,
+motivated by their well-known counterparts in traditional algebra,
 but we also had to pay tribute to existing types and their restrictions.
 To keep the interface minimal,
 it was not desirable to cover all known algebraic structures,
@@ -69,7 +69,7 @@ their existence, the usual arithmetic and comparison operators are required
 to be realized via \cpp operator overloading.
 The division operator is reserved for division in fields.
 All other unary (e.g., sqrt) and binary functions
-(e.g., gcd, div) must be models of the well known \stl-concepts
+(e.g., gcd, div) must be models of the well-known \stl-concepts
 `AdaptableUnaryFunction` or `AdaptableBinaryFunction`
 concept and local to the traits class
 (e.g., \link AlgebraicStructureTraits::Sqrt `Algebraic_structure_traits<AS>::Sqrt()(x)` \endlink).
@@ -285,7 +285,7 @@ The `Vertex_conflict_2` predicate. The left-most, bottom-most and top-most circl
 What we essentially want to compute when we construct incrementally a
 Voronoi diagram, is whether the object to be inserted destroys an edge
 of the Voronoi diagram or not. In the case of points this is really
-easy and it amounts to the well known <I>incircle</I> test.
+easy and it amounts to the well-known <I>incircle</I> test.
 In the case
 of circles the situation is more complicated. We can have six possible
 outcomes as to what portion of an edge of the Apollonius diagram the
@@ -146051,7 +146051,7 @@ of geometric optics."
 , year =        1993
 , pages =       "37--42"
 , keywords =    "travelling salesman problem, heuristic, approximation algorithms, convex hulls"
-, comments =    "It is well known that the nearest insertion and cheapest
+, comments =    "It is well-known that the nearest insertion and cheapest
 insertion are a factor 2 apx for TSP, and this is tight.
 Interestingly, for pts in the plane, if you start with a tour
 consisting of the convex hull vertices, and continue with nearest or
@@ -257,7 +257,7 @@ const Face& f);
 /*! \name Modifying Functions (Euler Operators)
 The following Euler operations modify consistently the combinatorial
 structure of the halfedge data structure. The geometry remains unchanged.
-Note that well known graph operations are also captured with these
+Note that well-known graph operations are also captured with these
 Euler operators, for example an edge contraction is equal to a
 `join_vertex()` operation, or an edge removal to `join_face()`.

@@ -235,7 +235,7 @@ public:

 // The following Euler operations modify consistently the combinatorial
 // structure of the halfedge data structure. The geometry remains
-// unchanged. Note that well known graph operations are also captured with
+// unchanged. Note that well-known graph operations are also captured with
 // these Euler operators, for example an edge contraction is equal to a
 // `join_vertex()' operation, or an edge removal to `join_face()'.
 //
@@ -5469,7 +5469,7 @@ The following functionality has been added or changed:
    bounding boxes of more complicated geometries. Useful for (self-)
    intersection tests of surfaces etc.
 - 2D Snap Rounding (new package)
-    Snap Rounding is a well known method for converting
+    Snap Rounding is a well-known method for converting
    arbitrary-precision arrangements of segments into a fixed-precision
    representation. In the study of robust geometric computing, it can
    be classified as a finite precision approximation technique.
@@ -219,7 +219,7 @@ diagram. The points defining the power diagram are the projections of
 the points in \f$ \mathcal{P}\f$ onto \f$ \mathcal{H}\f$, each point weighted
 with its negative square distance to \f$ \mathcal{H}\f$. Algorithms for the
 computation of power diagrams via the dual regular triangulation are
-well known and for example provided by \cgal in the class
+well-known and for example provided by \cgal in the class
 `Regular_triangulation_2<Gt, Tds>`.

 \subsection InterpolationImplementation_1 Implementation
@@ -37,7 +37,7 @@ will be `(w,0)`.
 \param number_of_kd_trees The seventh parameter is briefly described later on this page; for a
 detailed description see \cgalCite{cgal:hp-isr-02}.

-Snap Rounding (SR, for short) is a well known method for converting
+Snap Rounding (SR, for short) is a well-known method for converting
 arbitrary-precision arrangements of segments into a fixed-precision
 representation \cgalCite{gght-srlse-97}, \cgalCite{gm-rad-98}, \cgalCite{h-psifp-99}. In
 the study of robust geometric computing, it can be classified as a
@@ -7,7 +7,7 @@
 \cgalPkgPicture{snap-detail.png}
 \cgalPkgSummaryBegin
 \cgalPkgAuthor{Eli Packer}
-\cgalPkgDesc{Snap Rounding is a well known method for converting arbitrary-precision arrangements of segments into a fixed-precision representation. In the study of robust geometric computing, it can be classified as a finite precision approximation technique. Iterated Snap Rounding is a modification of Snap Rounding in which each vertex is at least half-the-width-of-a-pixel away from any non-incident edge. This package supports both methods.}
+\cgalPkgDesc{Snap Rounding is a well-known method for converting arbitrary-precision arrangements of segments into a fixed-precision representation. In the study of robust geometric computing, it can be classified as a finite precision approximation technique. Iterated Snap Rounding is a modification of Snap Rounding in which each vertex is at least half-the-width-of-a-pixel away from any non-incident edge. This package supports both methods.}
 \cgalPkgManuals{Chapter_2D_Snap_Rounding,PkgSnapRounding2Ref}
 \cgalPkgSummaryEnd
 \cgalPkgShortInfoBegin
@@ -10,7 +10,7 @@ namespace CGAL {

 \section Snap_rounding_2Introduction Introduction

-Snap Rounding (SR, for short) is a well known method for converting
+Snap Rounding (SR, for short) is a well-known method for converting
 arbitrary-precision arrangements of segments into a fixed-precision
 representation \cgalCite{gght-srlse-97}, \cgalCite{gm-rad-98}, \cgalCite{h-psifp-99}. In
 the study of robust geometric computing, it can be classified
@@ -1,4 +1,4 @@
-Snap Rounding (SR, for short) is a well known method for converting
+Snap Rounding (SR, for short) is a well-known method for converting
 arbitrary-precision arrangements of segments into a fixed-precision
 representation [Good,Guib,Hobb]. In the study of robust geometric
 computing, it can be classified as a finite precision approximation