Implement multiplication for OffsetMatrix

.github/workflows/TagBot.yml

@@ -0,0 +1,11 @@
+name: TagBot
+on:
+  schedule:
+    - cron: 0 * * * *
+jobs:
+  TagBot:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: JuliaRegistries/TagBot@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}

.travis.yml

@@ -6,8 +6,23 @@ os:
 
 julia:
     - 1.0
-    - 1.3
+    - 1
     - nightly
 
 notifications:
     email: false
+
+after_success:
+  # push coverage results to Codecov
+  - julia -e 'using Pkg, OffsetArrays; cd(joinpath(dirname(pathof(OffsetArrays)), "..")); Pkg.add("Coverage"); using Coverage; Codecov.submit(Codecov.process_folder())'
+
+jobs:
+  include:
+    - stage: "Documentation"
+      julia: 1
+      os: linux
+      script:
+        - julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd()));
+                                               Pkg.instantiate()'
+        - julia --project=docs/ docs/make.jl
+      after_success: skip

Project.toml

@@ -1,14 +1,16 @@
 name = "OffsetArrays"
 uuid = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
-version = "0.11.4"
+version = "1.2.0"
 
 [compat]
 julia = "0.7, 1"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 CatIndices = "aafaddc9-749c-510e-ac4f-586e18779b91"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["CatIndices", "DelimitedFiles", "Test"]
+test = ["Aqua", "CatIndices", "DelimitedFiles", "Test", "LinearAlgebra"]

README.md

@@ -1,75 +1,53 @@
 # OffsetArrays.jl
 
+[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaArrays.github.io/OffsetArrays.jl/stable)
+[![Build Status](https://travis-ci.org/JuliaArrays/OffsetArrays.jl.svg?branch=master)](https://travis-ci.org/JuliaArrays/OffsetArrays.jl)
+[![codecov.io](http://codecov.io/github/JuliaArrays/OffsetArrays.jl/coverage.svg?branch=master)](http://codecov.io/github/JuliaArrays/OffsetArrays.jl?branch=master)
+[![PkgEval][pkgeval-img]][pkgeval-url]
+
 
 OffsetArrays provides Julia users with arrays that have arbitrary
 indices, similar to those found in some other programming languages
 like Fortran.
 
-```julia
-julia> using OffsetArrays
-
-julia> y = OffsetArray{Float64}(undef, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);
+## Usage
 
-julia> summary(y)
-"OffsetArrays.OffsetArray{Float64,8,Array{Float64,8}} with indices -1:1×-7:7×-128:512×-5:5×-1:1×-3:3×-2:2×-1:1"
+You can construct such arrays as follows:
 
-julia> y[-1,-7,-128,-5,-1,-3,-2,-1] = 14
-14
-
-julia> y[-1,-7,-128,-5,-1,-3,-2,-1] += 5
-19.0
-```
-
-## Example: Relativistic Notation
-Suppose we have a position vector `r = [:x, :y, :z]` which is naturally one-based, ie. `r[1] == :x`, `r[2] == :y`,  `r[3] == :z` and we also want to construct a relativistic position vector which includes time as the 0th component. This can be done with OffsetArrays like 
 ```julia
-julia> using OffsetArrays
-
-julia> r = [:x, :y, :z];
-
-julia> x = OffsetVector([:t, r...], 0:3)
-OffsetArray(::Array{Symbol,1}, 0:3) with eltype Symbol with indices 0:3:
- :t
- :x
- :y
- :z
-
-julia> x[0]
-:t
-
-julia> x[1:3]
-3-element Array{Symbol,1}:
- :x
- :y
- :z
+OA = OffsetArray(A, axis1, axis2, ...)
 ```
 
-## Example: Polynomials
-Suppose one wants to represent the Laurent polynomial
-```
-6/x + 5 - 2*x + 3*x^2 + x^3
-```
-in julia. The coefficients of this polynomial are a naturally `-1` based list, since the `n`th element of the list 
-(counting from `-1`) `6, 5, -2, 3, 1` is the coefficient corresponding to the `n`th power of `x`. This Laurent polynomial can be evaluated at say `x = 2` as follows.
-```julia
-julia> using OffsetArrays
+where you want `OA` to have axes `(axis1, axis2, ...)` and be indexed by values that
+fall within these axis ranges. Example:
 
-julia> coeffs = OffsetVector([6, 5, -2, 3, 1], -1:3)
-OffsetArray(::Array{Int64,1}, -1:3) with eltype Int64 with indices -1:3:
-  6
-  5
- -2
-  3
-  1
+```julia
+using OffsetArrays
+A = reshape(1:15, 3, 5)
+println("here is A:")
+display(A)
+OA = OffsetArray(A, -1:1, 0:4)    # OA will have axes (-1:1, 0:4)
+println("here is OA:")
+display(OA)
+@show OA[-1,0] OA[1,4]
+```
 
-julia> polynomial(x, coeffs) = sum(coeffs[n]*x^n for n in eachindex(coeffs))
-polynomial (generic function with 1 method)
+which prints out
 
-julia> polynomial(2.0, coeffs)
-24.0
 ```
-Notice our use of the `eachindex` function which does not assume that the given array starts at `1`.
-
-## Notes on supporting OffsetArrays
+here is A:
+3×5 reshape(::UnitRange{Int64}, 3, 5) with eltype Int64:
+ 1  4  7  10  13
+ 2  5  8  11  14
+ 3  6  9  12  15
+here is OA:
+OffsetArray(reshape(::UnitRange{Int64}, 3, 5), -1:1, 0:4) with eltype Int64 with indices -1:1×0:4:
+ 1  4  7  10  13
+ 2  5  8  11  14
+ 3  6  9  12  15
+OA[-1, 0] = 1
+OA[1, 4] = 15
+```
 
-Julia supports generic programming with arrays that doesn't require you to assume that indices start with 1, see the [documentation](http://docs.julialang.org/en/latest/devdocs/offset-arrays/).
+[pkgeval-img]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/O/OffsetArrays.svg
+[pkgeval-url]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/report.html

appveyor.yml

@@ -1,7 +1,7 @@
 environment:
   matrix:
   - julia_version: 1.0
-  - julia_version: 1.3
+  - julia_version: 1
   - julia_version: nightly
 
 platform:

docs/.gitignore

@@ -0,0 +1,2 @@
+build/
+site/

docs/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+
+[compat]
+Documenter = "0.24"

docs/make.jl

@@ -0,0 +1,14 @@
+using Documenter
+using OffsetArrays
+
+makedocs(
+    sitename = "OffsetArrays",
+    format = Documenter.HTML(prettyurls = get(ENV, "CI", nothing) == "true"),
+    pages = ["index.md", "internals.md", "reference.md"],
+    modules = [OffsetArrays],
+    doctestfilters = [r"at \./.*", r"at /home.*", r"top-level scope.*", r"\[\d*\]\s*$"],   # for backtraces
+)
+
+deploydocs(
+    repo = "github.com:JuliaArrays/OffsetArrays.jl.git"
+)

docs/src/index.md

@@ -0,0 +1,121 @@
+# OffsetArrays.jl
+
+OffsetArrays provides Julia users with arrays that have arbitrary
+indices, similar to those found in some other programming languages
+like Fortran. Below is the basic usage found in the README, followed
+by a couple of short examples illustrating circumstances in which
+OffsetArrays can be useful. For a lengthier discussion, see
+[this blog post](https://julialang.org/blog/2017/04/offset-arrays/).
+
+## Usage
+
+You can construct such arrays as follows:
+
+```julia
+OA = OffsetArray(A, axis1, axis2, ...)
+```
+
+where you want `OA` to have axes `(axis1, axis2, ...)` and be indexed by values that
+fall within these axis ranges. Example:
+
+```julia
+using OffsetArrays
+A = Float64.(reshape(1:15, 3, 5))
+println("Here is A:")
+display(A)
+OA = OffsetArray(A, -1:1, 0:4)    # OA will have axes (-1:1, 0:4)
+println("Here is OA:")
+display(OA)
+@show OA[-1,0] OA[1,4]
+```
+
+gives the output
+
+```julia
+here is A:
+3×5 Array{Float64,2}:
+ 1.0  4.0  7.0  10.0  13.0
+ 2.0  5.0  8.0  11.0  14.0
+ 3.0  6.0  9.0  12.0  15.0
+here is OA:
+3×5 OffsetArray(::Array{Float64,2}, -1:1, 0:4) with eltype Float64 with indices -1:1×0:4:
+ 1.0  4.0  7.0  10.0  13.0
+ 2.0  5.0  8.0  11.0  14.0
+ 3.0  6.0  9.0  12.0  15.0
+OA[-1, 0] = 1.0
+OA[1, 4] = 15.0
+```
+
+OffsetArrays works for arbitrary dimensionality:
+
+```julia
+julia> using OffsetArrays
+
+julia> y = OffsetArray{Float64}(undef, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);
+
+julia> summary(y)
+"OffsetArrays.OffsetArray{Float64,8,Array{Float64,8}} with indices -1:1×-7:7×-128:512×-5:5×-1:1×-3:3×-2:2×-1:1"
+
+julia> y[-1,-7,-128,-5,-1,-3,-2,-1] = 14
+14
+
+julia> y[-1,-7,-128,-5,-1,-3,-2,-1] += 5
+19.0
+```
+
+You can use `OffsetArrays.no_offset_view(A)` if you want to return a view of the data in `A` but where indexing starts at 1.
+
+## Example: Relativistic Notation
+
+Suppose we have a position vector `r = [:x, :y, :z]` which is naturally one-based, ie. `r[1] == :x`, `r[2] == :y`,  `r[3] == :z` and we also want to construct a relativistic position vector which includes time as the 0th component. This can be done with OffsetArrays like
+
+```jldoctest
+julia> using OffsetArrays
+
+julia> r = [:x, :y, :z];
+
+julia> x = OffsetVector([:t, r...], 0:3)
+4-element OffsetArray(::Array{Symbol,1}, 0:3) with eltype Symbol with indices 0:3:
+ :t
+ :x
+ :y
+ :z
+
+julia> x[0]
+:t
+
+julia> x[1:3]
+3-element Array{Symbol,1}:
+ :x
+ :y
+ :z
+```
+
+## Example: Polynomials
+
+Suppose one wants to represent the Laurent polynomial
+```
+6/x + 5 - 2*x + 3*x^2 + x^3
+```
+in julia. The coefficients of this polynomial are a naturally `-1` based list, since the `n`th element of the list
+(counting from `-1`) `6, 5, -2, 3, 1` is the coefficient corresponding to the `n`th power of `x`. This Laurent polynomial can be evaluated at say `x = 2` as follows.
+
+```jldoctest
+julia> using OffsetArrays
+
+julia> coeffs = OffsetVector([6, 5, -2, 3, 1], -1:3)
+5-element OffsetArray(::Array{Int64,1}, -1:3) with eltype Int64 with indices -1:3:
+  6
+  5
+ -2
+  3
+  1
+
+julia> polynomial(x, coeffs) = sum(coeffs[n]*x^n for n in eachindex(coeffs))
+polynomial (generic function with 1 method)
+
+julia> polynomial(2.0, coeffs)
+24.0
+```
+
+Notice our use of the `eachindex` function which does not assume that the given array starts at `1`.