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Merged
nalimilan merged 1 commit into from
Aug 6, 2025
Merged

Bump CategoricalArrays to 1 #324

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14 changes: 8 additions & 6 deletions src/contrasts.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -157,7 +157,9 @@ ContrastsMatrix(contrasts_matrix::ContrastsMatrix, levels::AbstractVector)
constructing a model matrix from a `ModelFrame` using different data.

"""
function ContrastsMatrix(contrasts::C, levels::AbstractVector{T}) where {C<:AbstractContrasts, T}
function ContrastsMatrix(contrasts::C, levels::AbstractVector) where {C<:AbstractContrasts}

u_levels = DataAPI.unwrap.(levels)

# if levels are defined on contrasts, use those, validating that they line up.
# what does that mean? either:
Expand All @@ -167,9 +169,9 @@ function ContrastsMatrix(contrasts::C, levels::AbstractVector{T}) where {C<:Abst
# better to filter data frame first
# 3. contrast levels missing from data: would have empty columns, generate a
# rank-deficient model matrix.
c_levels = something(DataAPI.levels(contrasts), levels)
c_levels = something(DataAPI.levels(contrasts), u_levels)

mismatched_levels = symdiff(c_levels, levels)
mismatched_levels = symdiff(c_levels, u_levels)
if !isempty(mismatched_levels)
throw(ArgumentError("contrasts levels not found in data or vice-versa: " *
"$mismatched_levels." *
Expand All @@ -179,7 +181,7 @@ function ContrastsMatrix(contrasts::C, levels::AbstractVector{T}) where {C<:Abst

# do conversion AFTER checking for levels so users get a nice error message
# when they've made a mistake with the level types
c_levels = convert(Vector{T}, c_levels)
c_levels = convert(Vector{eltype(u_levels)}, c_levels)

n = length(c_levels)
if n == 0
Expand Down Expand Up @@ -228,7 +230,7 @@ end

function StatsAPI.coefnames(C::AbstractContrasts, levels::AbstractVector, baseind::Integer)
not_base = [1:(baseind-1); (baseind+1):length(levels)]
levels[not_base]
DataAPI.unwrap.(levels[not_base])
end

Base.getindex(contrasts::ContrastsMatrix, rowinds, colinds) =
Expand Down Expand Up @@ -594,7 +596,7 @@ function contrasts_matrix(C::HypothesisCoding, baseind, n)
end

StatsAPI.coefnames(C::HypothesisCoding, levels::AbstractVector, baseind::Int) =
something(C.labels, levels[1:length(levels) .!= baseind])
something(C.labels, DataAPI.unwrap.(levels[1:length(levels) .!= baseind]))

DataAPI.levels(c::HypothesisCoding) = c.levels

Expand Down
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