Merge pull request #495 from SciML/ChrisRackauckas-patch-6

Test master

README.md

@@ -9,7 +9,6 @@ stochastic differential equations solvers and utilities. While completely indepe
 and usable on its own, users interested in using this
 functionality should check out [DifferentialEquations.jl](https://github.com/SciML/DifferentialEquations.jl).
 
-
 ## API
 
 StochasticDiffEq.jl is part of the JuliaDiffEq common interface, but can be used independently of DifferentialEquations.jl. The only requirement is that the user passes an StochasticDiffEq.jl algorithm to `solve`. For example, we can solve the [SDE tutorial from the docs](https://diffeq.sciml.ai/stable/tutorials/sde_example/) using the `SRIW1()` algorithm:

test/noindex_tests.jl

@@ -9,6 +9,7 @@ Base.axes(x::NoIndexArray) = axes(x.x)
 Base.similar(x::NoIndexArray, dims::Union{Integer, AbstractUnitRange}...) = NoIndexArray(similar(x.x, dims...))
 Base.copyto!(x::NoIndexArray, y::NoIndexArray) = NoIndexArray(copyto!(x.x, y.x))
 Base.copy(x::NoIndexArray) = NoIndexArray(copy(x.x))
+Base.zero(x::NoIndexArray) = NoIndexArray(zero(x.x))
 Base.fill!(x::NoIndexArray, y) = NoIndexArray(fill!(x.x, y))
 Base.mapreduce(f, op, x::NoIndexArray; kwargs...) = mapreduce(f, op, x.x; kwargs...)
 Base.any(f::Function, x::NoIndexArray; kwargs...) = any(f, x.x; kwargs...)