Remove MutableArithemetics code to new package PolynomialsMutableArit…

…hmetics (#445)

* WIP

* edits

* move MutableArithmetics to separate package

* rm tests for MA

* replace tab with space

.github/workflows/downstream.yml

@@ -18,6 +18,7 @@ jobs:
         os: [ubuntu-latest]
         package:
           - {user: jverzani, repo: SpecialPolynomials.jl, group: All}
+          - {user: jverzani, repo: PolynomialsMutableArithmetics.jl, group: All}
 
     steps:
       - uses: actions/checkout@v2

Project.toml

@@ -2,15 +2,13 @@ name = "Polynomials"
 uuid = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
 license = "MIT"
 author = "JuliaMath"
-version = "3.1.8"
+version = "3.2.0"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-MutableArithmetics = "d8a4904e-b15c-11e9-3269-09a3773c0cb0"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 
 [compat]
-MutableArithmetics = "0.3,1"
 RecipesBase = "0.7, 0.8, 1"
 julia = "1.6"
 

README.md

@@ -119,6 +119,7 @@ may be noticeable in some use cases. This is amplified when the coefficients
 are for instance `BigInt` or `BigFloat` which are mutable themself.
 This can be avoided by modifying existing polynomials to contain the result
 of the operation using the [MutableArithmetics (MA) API](https://github.com/jump-dev/MutableArithmetics.jl).
+
 Consider for instance the following arrays of polynomials
 ```julia
 using Polynomials
@@ -127,34 +128,55 @@ p(d) = Polynomial(big.(1:d))
 A = [p(d) for i in 1:m, j in 1:n]
 b = [p(d) for i in 1:n]
 ```
+
 In this case, the arrays are mutable objects for which the elements are mutable
 polynomials which have mutable coefficients (`BigInt`s).
 These three nested levels of mutable objects communicate with the MA
 API in order to reduce allocation.
 Calling `A * b` requires approximately 40 MiB due to 2 M allocations
-as it does not exploit any mutability. Using
+as it does not exploit any mutability.
+
+Using
+
+```julia
+using PolynomialsMutableArithmetics
+```
+
+to register `Polynomials` with `MutableArithmetics`, then multiplying with:
+
 ```julia
 using MutableArithmetics
 const MA = MutableArithmetics
 MA.operate(*, A, b)
 ```
-exploits the mutability and hence only allocate approximately 70 KiB due to 4 k
-allocations. If the resulting vector is already allocated, e.g.,
+
+exploits the mutability and hence only allocates approximately 70 KiB due to 4 k
+allocations.
+
+If the resulting vector is already allocated, e.g.,
+
 ```julia
 z(d) = Polynomial([zero(BigInt) for i in 1:d])
 c = [z(2d - 1) for i in 1:m]
 ```
+
 then we can exploit its mutability with
+
 ```julia
-MA.mutable_operate!(MA.add_mul, c, A, b)
+MA.operate!(MA.add_mul, c, A, b)
 ```
-to reduce the allocation down to 48 bytes due to 3 allocations. These remaining
-allocations are due to the `BigInt` buffer used to store the result of
-intermediate multiplications. This buffer can be preallocated with
+
+to reduce the allocation down to 48 bytes due to 3 allocations.
+
+These remaining allocations are due to the `BigInt` buffer used to
+store the result of intermediate multiplications. This buffer can be
+preallocated with:
+
 ```julia
 buffer = MA.buffer_for(MA.add_mul, typeof(c), typeof(A), typeof(b))
-MA.mutable_buffered_operate!(buffer, MA.add_mul, c, A, b)
+MA.buffered_operate!(buffer, MA.add_mul, c, A, b)
 ```
+
 then the second line is allocation-free.
 
 The `MA.@rewrite` macro rewrite an expression into an equivalent code that
@@ -174,7 +196,7 @@ c = MA.operate(*, A1, b1)
 MA.mutable_operate!(MA.add_mul, c, A2, b2)
 ```
 
-*Note that currently, only the `Polynomial` implements the API and it only
+*Note that currently, only the `Polynomial` type implements the API and it only
 implements part of it.*
 
 ### Integrals and Derivatives

src/Polynomials.jl

@@ -14,7 +14,6 @@ include("common.jl")
 
 # Polynomials
 include("polynomials/standard-basis.jl")
-include("polynomials/mutable-arithmetics.jl")
 include("polynomials/Polynomial.jl")
 include("polynomials/ImmutablePolynomial.jl")
 include("polynomials/SparsePolynomial.jl")

src/common.jl

@@ -818,8 +818,8 @@ Base.:-(p::P) where {P <: AbstractPolynomial} = _convert(p, -coeffs(p))
 
 Base.:*(p::AbstractPolynomial, c::Number) = scalar_mult(p, c)
 Base.:*(c::Number, p::AbstractPolynomial) = scalar_mult(c, p)
-Base.:*(c::T, p::P) where {T, P <: AbstractPolynomial{T}} = scalar_mult(c, p)
-Base.:*(p::P, c::T) where {T, P <: AbstractPolynomial{T}} = scalar_mult(p, c)
+Base.:*(c::T, p::P) where {T, X, P <: AbstractPolynomial{T,X}} = scalar_mult(c, p)
+Base.:*(p::P, c::T) where {T, X, P <: AbstractPolynomial{T,X}} = scalar_mult(p, c)
 
 # implicitly identify c::Number with a constant polynomials
 Base.:+(c::Number, p::AbstractPolynomial) = +(p, c)

src/polynomials/Polynomial.jl

@@ -50,7 +50,6 @@ struct Polynomial{T, X} <: StandardBasisPolynomial{T, X}
 end
 
 @register Polynomial
-@register_mutable_arithmetic Polynomial
 
 
 

test/StandardBasis.jl

@@ -1525,29 +1525,6 @@ end
     end
 end
 
-import MutableArithmetics
-const MA = MutableArithmetics
-
-function alloc_test(f, n)
-    f() # compile
-    @test n == @allocated f()
-end
-
-@testset "Mutable arithmetics" begin
-    d = m = n = 4
-    p(d) = Polynomial(big.(1:d))
-    z(d) = Polynomial([zero(BigInt) for i in 1:d])
-    A = [p(d) for i in 1:m, j in 1:n]
-    b = [p(d) for i in 1:n]
-    c = [z(2d - 1) for i in 1:m]
-    buffer = MA.buffer_for(MA.add_mul, typeof(c), typeof(A), typeof(b))
-    @test buffer isa BigInt
-    c = [z(2d - 1) for i in 1:m]
-    MA.buffered_operate!(buffer, MA.add_mul, c, A, b)
-    @test c == A * b
-    @test c == MA.operate(*, A, b)
-    @test 0 == @allocated MA.buffered_operate!(buffer, MA.add_mul, c, A, b)
-end
 
 @testset "SparsePolynomial" begin
     @test Polynomials.minimumexponent(SparsePolynomial) == typemin(Int)