minor NEWs fixes

Author: ericphanson

NEWS.md

@@ -3,25 +3,25 @@
 ## Breaking changes
 
 * Changes to the `sign` of atoms:
-    * The sign of `sumlargesteigs` has been changed from `Positive` to  `NoSign()` instead of `Positive()`, to allow non-positive-semidefinite inputs. This has the potential
-  to break code that required that sign to be positive. If you run into this problem, please file an issue so we can figure out a workaround. [#412](https://github.com/jump-dev/Convex.jl/pull/412)
-    * The sign of `eigmin` and `eigmax` has been changed from `Positive` to  `NoSign()`. This is a bugfix because in general `eigmin` and `eigmax` do not need to return a positive quantity (for non-positive-semidefinite inputs). Again, this has the potential to break code that required that sign to be positive. If you run into this problem, please file an issue so we can figure out a workaround. [#413](https://github.com/jump-dev/Convex.jl/pull/413)
+    * The sign of `sumlargesteigs` has been changed from `Positive` to  `NoSign()` instead of `Positive()`, to allow non-positive-semidefinite inputs ([#409](https://github.com/jump-dev/Convex.jl/pull/409)). This has the potential
+  to break code that required that sign to be positive. If you run into this problem, please file an issue so we can figure out a workaround.
+    * The sign of `eigmin` and `eigmax` has been changed from `Positive` to  `NoSign()` ([#413](https://github.com/jump-dev/Convex.jl/pull/413)). This is a bugfix because in general `eigmin` and `eigmax` do not need to return a positive quantity (for non-positive-semidefinite inputs). Again, this has the potential to break code that required that sign to be positive. If you run into this problem, please file an issue so we can figure out a workaround.
 * Removal of deprecations:
-    * `lambdamin` and `lambdamax` has been deprecated to `eigmin` and `eigmax` since Convex v0.13.0. This deprecation has been removed, so your code must be updated to call `eigmin` or `eigmax` instead. [#412](https://github.com/jump-dev/Convex.jl/pull/412)
-    * `norm(x, p)` where `x` is a matrix expression has been deprecated to `opnorm(x,p)` since Convex v0.8.0. This deprecation has been removed, so your code must be updated to call `opnorm(x, p)` instead. Currently, `norm(x,p)` for a matrix
-    expression `x` will error, but in Convex.jl v0.15.0 it will return `norm(vec(x), p)`. [#412](https://github.com/jump-dev/Convex.jl/pull/412)
-    * `Convex.clearmemory()` has been deprecated and unnecessary since Convex v0.12.5. This deprecation has been removed, so if this function is in your code, just delete it. [#412](https://github.com/jump-dev/Convex.jl/pull/412)
-    * `vecnorm(x, p)` has been deprecated to `norm(vec(x), p)` since Convex v0.8.0. This deprecation has been removed, so your code must be updated to call `norm(vec(x),p)` instead.
+    * `lambdamin` and `lambdamax` has been deprecated to `eigmin` and `eigmax` since Convex v0.13.0. This deprecation has been removed, so your code must be updated to call `eigmin` or `eigmax` instead ([#412](https://github.com/jump-dev/Convex.jl/pull/412)).
+    * `norm(x, p)` where `x` is a matrix expression has been deprecated to `opnorm(x,p)` since Convex v0.8.0. This deprecation has been removed, so your code must be updated to call `opnorm(x, p)` instead ([#412](https://github.com/jump-dev/Convex.jl/pull/412)). Currently, `norm(x,p)` for a matrix
+    expression `x` will error, but in Convex.jl v0.15.0 it will return `norm(vec(x), p)`.
+    * `Convex.clearmemory()` has been deprecated and unnecessary since Convex v0.12.5. This deprecation has been removed, so if this function is in your code, just delete it ([#412](https://github.com/jump-dev/Convex.jl/pull/412)).
+    * `vecnorm(x, p)` has been deprecated to `norm(vec(x), p)` since Convex v0.8.0. This deprecation has been removed, so your code must be updated to call `norm(vec(x),p)` instead ([#412](https://github.com/jump-dev/Convex.jl/pull/412)).
 * Other changes:
-    * `Convex.DCP_WARNINGS` was introduced in Convex v0.13.1 to allow turning off Convex.jl's DCP warnings. This has been removed in favor of the function `Convex.emit_dcp_warnings()`. [Commit 481fa02](https://github.com/jump-dev/Convex.jl/commit/481fa02b84bfec6bf7c809ea93d6ba8004193b83)
+    * `Convex.DCP_WARNINGS` was introduced in Convex v0.13.1 to allow turning off Convex.jl's DCP warnings. This has been removed in favor of the function `Convex.emit_dcp_warnings()` ([Commit 481fa02](https://github.com/jump-dev/Convex.jl/commit/481fa02b84bfec6bf7c809ea93d6ba8004193b83)).
 
 ## Other changes
 
-* updated `nuclearnorm` and `sumlargesteigs` to allow complex variables, and allow the argument of `sumlargesteigs` to be non-positive-semi-definite [#409](https://github.com/jump-dev/Convex.jl/pull/409). Thanks to @dstahlke!
+* updated `nuclearnorm` and `sumlargesteigs` to allow complex variables, and allow the argument of `sumlargesteigs` to be non-positive-semi-definite ([#409](https://github.com/jump-dev/Convex.jl/pull/409)). Thanks to @dstahlke!
 
 # Changes in v0.13.8
 
-* add unary `+` for `Sign` and `ComplexSign` to allow single-argument `hcat` and `vcat` to work [#405](https://github.com/jump-dev/Convex.jl/pull/405). Thanks to @dstahlke!
+* add unary `+` for `Sign` and `ComplexSign` to allow single-argument `hcat` and `vcat` to work ([#405](https://github.com/jump-dev/Convex.jl/pull/405)). Thanks to @dstahlke!
 
 # Changes in v0.13.7
 
@@ -41,14 +41,13 @@
   See the
   [docs](https://www.juliaopt.org/Convex.jl/dev/advanced/#Custom-Variable-Types-1)
   for more information. You can also add constraints directly to a variable
-  using `add_constraint!`. ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358))
+  using `add_constraint!` ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358)).
 * Accessors `vexity(x::Variable)`, `sign(x::Variable)`, and
   `evaluate(x::Variable)` should now be the preferred way to access properties
   of a variable; likewise use `set_value!` to set the initial value of a
-  variable. ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358))
+  variable ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358)).
 * To create integer or binary constraints, use the `VarType` enum (e.g.
-  `Variable(BinVar)`). Access or set this via `vartype` and `vartype!`.
-  ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358))
+  `Variable(BinVar)`). Access or set this via `vartype` and `vartype!` ([#358](https://github.com/JuliaOpt/Convex.jl/pull/358)).
 
 # Changes in v0.13.3
 
@@ -72,12 +71,12 @@
   one should pass a MathOptInterface optimizer constructor, such as
   `SCS.Optimizer`, or `() -> SCS.Optimizer(verbose=false)`.
 * `lambdamin` and `lambdamax` have been deprecated in favor of `eigmin` and
-  `eigmax`. ([#357](https://github.com/JuliaOpt/Convex.jl/pull/357))
+  `eigmax` ([#357](https://github.com/JuliaOpt/Convex.jl/pull/357)).
 * Many "internal" functions and types are no longer exported, such as the atoms,
   types corresponding to constraints and vexities, etc.
-  ([#357](https://github.com/JuliaOpt/Convex.jl/pull/357))
+  ([#357](https://github.com/JuliaOpt/Convex.jl/pull/357)).
 * `evaluate(x::Variable)` and `evaluate(c::Constant)` now return scalars and
-  vectors as appropriate, instead of `(1,1)`- and `(d,1)`-matrices.
+  vectors as appropriate, instead of `(1,1)`- and `(d,1)`-matrices
   ([#359](https://github.com/JuliaOpt/Convex.jl/pull/359)). This affects
   functions which used to return `(1,1)`-matrices; e.g., now
   `evaluate(quadform(...))` yields a scalar.