Special case division of/by a constant (#7)

* Special case division of/by a constant

* patch bump

* Update README.md

* Update README.md

Co-authored-by: Dave Kleinschmidt <dave.f.kleinschmidt@gmail.com>

Author: palday

Project.toml

@@ -1,7 +1,7 @@
 name = "RegressionFormulae"
 uuid = "545c379f-4ec2-4339-9aea-38f2fb6a8ba2"
 authors = ["Dave Kleinschmidt", "Phillip Alday"]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

README.md

@@ -27,6 +27,11 @@ using RegressionFormulae, StatsModels, GLM, DataFrames
 
 `a / b` expands to `a + fulldummy(a) & b`.
 
+Numeric constants are special cased so that `/` performs division, making it possible to e.g. convert time to speed in the formula:
+```julia
+julia> fit(MyModelType, @formula(time_in_milliseconds / 1000 ~ 1 + x), my_data)
+``` 
+
 ### Raising terms to a power ###
 
 Generate all main effects and interactions up to the specified order.  For

src/nesting.jl

@@ -45,7 +45,7 @@ function Base.:(/)(outer::InteractionTerm, inner::TermTuple)
 end
 
 function Base.:(/)(outer::AbstractTerm, inner::AbstractTerm)
-    throw(ArgumentError("nesting terms requires categorical grouping term, got $outer / $inner " *
+    throw(ArgumentError("Nesting terms requires categorical grouping term, got $outer / $inner " *
                         "Manually specify $outer as `CategoricalTerm` in hints/contrasts"))
 end
 
@@ -57,7 +57,10 @@ function StatsModels.apply_schema(
     length(t.args_parsed) == 2 ||
         throw(ArgumentError("malformed nesting term: $t (Exactly two arguments required)"))
 
+    any(x -> isa(x, ConstantTerm), t.args_parsed) && return t
+
     args = apply_schema.(t.args_parsed, Ref(sch), Mod)
 
     return first(args) / last(args)
 end
+

test/nesting.jl

@@ -4,7 +4,9 @@ using Test
 
 include("dummymod.jl")
 
-dat = (; y=zeros(3), a=["u","i","o"], b=["q","w","e"], c=["s","d","f"], x=1:3)
+# y must not be the multiplicative or additive identity
+# otherwise some of the tests will trivially pass
+dat = (; y=2*ones(3), a=["u","i","o"], b=["q","w","e"], c=["s","d","f"], x=1:3)
 
 @testset "error checking" begin
     sch = schema(dat)
@@ -13,6 +15,20 @@ dat = (; y=zeros(3), a=["u","i","o"], b=["q","w","e"], c=["s","d","f"], x=1:3)
     @test !RegressionFormulae._isfulldummy(term(:a))
 end
 
+@testset "division" begin
+    m = fit(DummyMod, @formula(y / 1000 ~ 1 + x), dat)
+    @test all(response(m) .≈ dat.y ./ 1000)
+
+    m = fit(DummyMod, @formula(1000 / y ~ 1 + x), dat)
+    @test all(response(m) .≈ 1000 ./ dat.y)
+
+    m = fit(DummyMod, @formula(y ~ 1 + 1000 / x), dat)
+    @test all(m.mm.m[:, 2] .≈ 1000 ./ dat.x)
+
+    m = fit(DummyMod, @formula(y ~ 1 + x / 1000), dat)
+    @test all(m.mm.m[:, 2] .≈ dat.x ./ 1000)
+end
+
 @testset "single nesting level" begin
     m = fit(DummyMod, @formula(y ~ 0 + a / b), dat)
     @test coefnames(m) == ["a: i", "a: o", "a: u",