Fixed the case where scalars divide multivectors

src/math.jl

@@ -119,16 +119,27 @@ end
 
 # TODO: is it more efficient to define some more specific methods for some types?
 
-#---Scalar multiplication--------------------------------------------------------------------------#
+#---Scalar multiplication and division-------------------------------------------------------------#
 
-for op in (:*, :/, ://)
+@inline function *(x::AbstractCliffordNumber, y::Number)
+    data = map(_x -> (_x * y), Tuple(x))
+    return similar_type(typeof(x), eltype(data))(data)
+end
+
+# Don't assume commutative multiplication, just to be safe
+@inline function *(x::Number, y::AbstractCliffordNumber)
+    data = map(_y -> (x * _y), Tuple(y))
+    return similar_type(typeof(y), eltype(data))(data)
+end
+
+for op in (:/, ://)
     @eval begin
         @inline function $op(x::AbstractCliffordNumber, y::BaseNumber)
             data = map(_x -> $op(_x, y), Tuple(x))
             return similar_type(typeof(x), eltype(data))(data)
         end
         @inline function $op(x::BaseNumber, y::AbstractCliffordNumber)
-            data = map(_y -> $op(x, _y), Tuple(y))
+            data = Tuple(y') .* $op(x, sum(Tuple(y) .* Tuple(y')))
             return similar_type(typeof(y), eltype(data))(data)
         end
     end

test/operations.jl

@@ -85,6 +85,20 @@ end
     @test KVector{0,VGA(3)}(2) * KVector{0,VGA(3)}(3) === KVector{0,VGA(3)}(6)
 end
 
+@testset "Inverses" begin
+    k = KVector{1,VGA(3)}(1, 2, 3)
+    l = KVector{2,VGA(3)}(4, 5, 6)
+    # TODO: fix approximate equality methods to consolidate these tests
+    @test isscalar(k * (1 / k))
+    @test scalar(k * (1 / k)) ≈ 1
+    @test isscalar((1 / k) * k)
+    @test scalar((1 / k) * k) ≈ 1
+    @test isscalar(k * (1 / k))
+    @test scalar(k * (1 / k)) ≈ 1
+    @test isscalar((1 / k) * k)
+    @test scalar((1 / k) * k) ≈ 1
+end
+
 @testset "Contractions" begin
     k = KVector{1,VGA(3)}(1, 2, 3)
     l = KVector{2,VGA(3)}(4, 5, 6)