Add antidifferentiation for monomials

src/DynamicPolynomials.jl

@@ -84,6 +84,7 @@ include("promote.jl")
 include("operators.jl")
 include("comp.jl")
 
+include("anti_diff.jl")
 include("diff.jl")
 include("subs.jl")
 

src/anti_diff.jl

@@ -0,0 +1,10 @@
+function MP.antidifferentiate(m::Monomial{V,M}, x::Variable{V,M}) where {V,M}
+    z = copy(m.z)
+    i = findfirst(isequal(x), MP.variables(m))
+    if (i === nothing || i == 0) || m.z[i] == 0
+        Monomial(MP.variables(m), z) * x
+    else
+        z[i] += 1
+        Monomial(MP.variables(m), z) / (m.z[i] + 1)
+    end
+end

test/mono.jl

@@ -141,6 +141,24 @@ import MultivariatePolynomials as MP
         @test m.z == [2, 1, 1, 0, 0]
     end
 
+    @testset "Antidifferentiation" begin
+	      @ncpolyvar x y z
+
+        @info typeof(x)
+
+        m = x
+        mi = DynamicPolynomials.MP.antidifferentiate(m, y)
+        @test mi == x * y
+
+        m = x^3
+        mi = DynamicPolynomials.MP.antidifferentiate(m, x)
+        @test mi == (x^4 / 4)
+
+        m = Monomial([x, y, z], [1, 2, 3])
+        mi = DynamicPolynomials.MP.antidifferentiate(m, z)
+        @test mi == (x*y^2*z^4) / 4
+    end
+
     @testset "Evaluation" begin
         @polyvar x y
         @test (x^2 * y)(3, 2) == 18