Mercurial > repos > alg_tools / changeset

--- a/README.md	Tue Dec 06 08:58:49 2022 +0200
+++ b/README.md	Wed Dec 07 06:57:26 2022 +0200
@@ -5,22 +5,22 @@
 iterative algorithms and (abstract) numerical computing in Rust. Former versions
 of the package were for Julia. They are no longer mintained. Included are:
 
-  * [Linear operator][], [mapping][], [Euclidean space][], and [norm][]
-    abstractions. Matrices and vectors are supported via [nalgebra].
+  * [Linear operator], [mapping], [Euclidean space], and [norm] abstractions.
+    Matrices and vectors are supported via [nalgebra].
     There is also abstraction for [`AXPY`][AXPY] and [`GEMV`][GEMV] operations.
-  * Small (on stack) [vectors][]  and [cubes][] that implement the relevant
+  * Small (on stack) [vectors] and [cubes] that implement the relevant
     abstractions and vector space operations.
-  * Multi-dimensional [linear grids][], including the familiar-from-Matlab
+  * Multi-dimensional [linear grids], including the familiar-from-Matlab
     one-dimensional [`linspace`][linspace].
-  * [Algorithm iterator abstraction][] for generically implementing
+  * [Algorithm iterator abstraction] for generically implementing
     intermittent verbosity and stopping rules in iterative algorithms.
-  * The algorithm iterators can employ a [logger][] to store intermittent results
-    (e.g. function values) in memory to later [write][] into a csv-file.
+  * The algorithm iterators can employ a [logger] to store intermittent results
+    (e.g. function values) in memory to later [write] into a csv-file.
   * Additional [iterators and iteration tools][], especially variants of `map`
     with predictable type signatures.
-  * The `Float` and [associated traits][] build upon [num_traits][] to
+  * The `Float` and [associated traits] build upon [num_traits] to
     conveniently write code that works with any floating point number type.
-  * Geometrical [bisection trees][] for efficient representations of sums of
+  * Geometrical [bisection trees] for efficient representations of sums of
     functions and branch-and-bound optimisation.
 
 ## Building the documentation