Add cdfnorm to available functions. (#57)

* Add gitignore

* Add cdfnorm, tests, and some small tweaks

* CI mod and remove test manifest

* Try commenting ssh key

* Remove old stuff

* Increment minor version, as substantial features have been added

* Re-enable documentar key

Author: Crown421

.gitignore

@@ -0,0 +1,4 @@
+## Build folder of Documenter.jl
+docs/build/
+Manifest.toml
+.vscode

Project.toml

@@ -1,6 +1,6 @@
 name = "IntelVectorMath"
 uuid = "c8ce9da6-5d36-5c03-b118-5a70151be7bc"
-version = "0.4.3"
+version = "0.5.0"
 
 [deps]
 MKL_jll = "856f044c-d86e-5d09-b602-aeab76dc8ba7"

README.md

@@ -12,7 +12,7 @@ This package provides bindings to the Intel MKL [Vector Mathematics Functions](h
 This is often substantially faster than broadcasting Julia's built-in functions, especially when applying a transcendental function over a large array.
 Until Julia 0.6 the package was registered as `VML.jl`.
 
-Similar packages are [Yeppp.jl](https://github.com/JuliaMath/Yeppp.jl), which wraps the open source Yeppp library, and [AppleAccelerate.jl](https://github.com/JuliaMath/AppleAccelerate.jl), which provides access to macOS's Accelerate framework.
+Similar packages are [Yeppp.jl](https://github.com/JuliaMath/Yeppp.jl), which wraps the open-source Yeppp library, and [AppleAccelerate.jl](https://github.com/JuliaMath/AppleAccelerate.jl), which provides access to macOS's Accelerate framework.
 
 ### Warning for macOS
 There is currently [the following](https://github.com/JuliaPackaging/BinaryBuilder.jl/issues/700) issue between the `CompilerSupportLibraries_jll` artifact, which is used for example by `SpecialFunctions.jl`, and `MKL_jll`. Unless `MKL_jll` is loaded first, there might be wrong results coming from a small number of function for particular input array lengths. If you are unsure which, if any, your used packages might load this artifact, loading `IntelVectorMath` as the very first package should be fine. 
@@ -33,11 +33,11 @@ julia> ] build IntelVectorMath
 If this does not work, please open an issue and include the output of `<packagedir>/deps/build.log`.
 
 #### Renaming from VML
-If you used this package prior to its renaming, you may have to run `] rm VML` first. Otherwise there will be a conflict due to the UUID.  
+If you used this package prior to its renaming, you may have to run `] rm VML` first. Otherwise, there will be a conflict due to the UUID.  
 
 ## Using IntelVectorMath
 After loading `IntelVectorMath`, you have the supported function listed below, for example `IntelVectorMath.sin(rand(100))`. These should provide a significant speed-up over broadcasting the Base functions.
-Since the package name is quite long, an alias `IVM` is also exported to allow `IVM.sin(rand(100))` after `using` the package.
+As the package name is quite long, the alias `IVM` is also exported to allow `IVM.sin(rand(100))` after `using` the package.
 If you `import` the package, you can add this alias via `const IVM = IntelVectorMath`. Equally, you can replace `IVM` with another alias of your choice.
 
 #### Example
@@ -216,7 +216,7 @@ Allocating | Mutating
 
 ### Binary functions
 
-Allocating forms have signature `f(A, B)`. Mutating forms have
+Allocating forms have signature `f(A, B)`. Mutating forms have the
 signature `f!(out, A, B)`.
 
 Allocating | Mutating
@@ -240,7 +240,7 @@ Next steps for this package
 * [x] Add tests for mutating functions
 * [x] Add own dependency management via BinaryProvider
 * [ ] Update function list in README
-* [ ] Adopt Julia 1.3 artifact system, breaking backwards compatibility
+* [x] Adopt Julia 1.3 artifact system, breaking backwards compatibility
 
 
 

src/IntelVectorMath.jl

@@ -76,6 +76,7 @@ unary_real = (
     (:inv_sqrt, :inv_sqrt!, :InvSqrt),
     (:pow2o3, :pow2o3!, :Pow2o3),
     (:pow3o2, :pow3o2!, :Pow3o2),
+    (:cdfnorm, :cdfnorm!, :CdfNorm),
 )
 
 binary_real = (

test/common.jl

@@ -46,6 +46,7 @@ const base_unary_real = (
     (Main, :inv_cbrt, (0, 1000)),
     (Main, :pow2o3, (-1000, 1000)),
     (Main, :pow3o2, (0, 1000)),
+    (Main, :cdfnorm, (-4, 4)),
 )
 
 const base_binary_real = (

test/nonbase-functions.jl

@@ -14,6 +14,9 @@ pow(x, y) = x^y
 # divide
 divide(x, y) = x / y
 
+# cdfnorm
+cdfnorm(x) = 0.5 * (1 + SpecialFunctions.erf(x / sqrt(2)))
+
 # :lgamma
 # Redefining for testing to avoid deprecation warning
 SpecialFunctions.lgamma(x::Union{Float64,Float32}) = (logabsgamma(x))[1]