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RFC: Sparse ModelMatrix support #1040

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merged 11 commits into from
Aug 26, 2016
Merged

RFC: Sparse ModelMatrix support #1040

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c61a0ec
Parametrize ModelMatrix container type
Aug 20, 2016
d46fc37
Eliminate hardcoded model matrix container type when constructing fro…
Aug 20, 2016
288552c
More idiomatic model matrix constructor and relaxed container type re…
Aug 21, 2016
e1b068e
Generalize modelmat_cols output typing
Aug 21, 2016
4a9a65f
Generalize expandcols output types
Aug 21, 2016
fd12a5d
Added sparse ModelMatrix creation tests
Aug 21, 2016
ff6f706
More explicit model matrix constructor type output testing
Aug 21, 2016
f94dd83
Rename ModelMatrixContainer and remove unneeded variables/methods
Aug 21, 2016
dd0ae91
Split value assignment onto two lines
Aug 22, 2016
db58318
Fix test result spacing and incorrect method signature documentation
Aug 22, 2016
25935c0
Docstring updates
Aug 26, 2016
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2 changes: 1 addition & 1 deletion src/statsmodels/formula.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -352,7 +352,7 @@ modelmat_cols{T<:AbstractFloatMatrix}(::Type{T}, v::DataVector) = convert(T, res
modelmat_cols{T<:AbstractFloatMatrix}(::Type{T}, v::Vector) = convert(T, reshape(v, length(v), 1))

"""
modelmat_cols(T::Type{AbstractFloatMatrix}, v::PooledDataVector, contrast::ContrastsMatrix)
modelmat_cols(::Type{T}, v::PooledDataVector, contrast::ContrastsMatrix)
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You should also mention the restriction T<:AbstractFloatMatrix as a type parameter.


Construct `ModelMatrix` columns of type `T` based on specified contrasts, ensuring that
levels align properly.
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84 changes: 42 additions & 42 deletions test/formula.jl
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Expand Up @@ -405,41 +405,41 @@ d[:n] = 1.:8
mf = ModelFrame(n ~ 0 + x, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m == [1 0
0 1
1 0
0 1
1 0
0 1
1 0
0 1]
0 1
1 0
0 1
1 0
0 1
1 0
0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["x: a", "x: b"]

## No first-order term for interaction
mf = ModelFrame(n ~ 1 + x + x&y, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m[:, 2:end] == [-1 -1 0
1 0 -1
-1 1 0
1 0 1
-1 -1 0
1 0 -1
-1 1 0
1 0 1]
1 0 -1
-1 1 0
1 0 1
-1 -1 0
1 0 -1
-1 1 0
1 0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["(Intercept)", "x: b", "x: a & y: d", "x: b & y: d"]

## When both terms of interaction are non-redundant:
mf = ModelFrame(n ~ 0 + x&y, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m == [1 0 0 0
0 1 0 0
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
0 0 1 0
0 0 0 1]
0 1 0 0
0 0 1 0
0 0 0 1
1 0 0 0
0 1 0 0
0 0 1 0
0 0 0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["x: a & y: c", "x: b & y: c",
"x: a & y: d", "x: b & y: d"]
Expand All @@ -457,13 +457,13 @@ mm = ModelMatrix(mf)
mf = ModelFrame(n ~ 0 + x&y + x&z, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m == [1 0 0 0 -1 0
0 1 0 0 0 -1
0 0 1 0 -1 0
0 0 0 1 0 -1
1 0 0 0 1 0
0 1 0 0 0 1
0 0 1 0 1 0
0 0 0 1 0 1]
0 1 0 0 0 -1
0 0 1 0 -1 0
0 0 0 1 0 -1
1 0 0 0 1 0
0 1 0 0 0 1
0 0 1 0 1 0
0 0 0 1 0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["x: a & y: c", "x: b & y: c",
"x: a & y: d", "x: b & y: d",
Expand All @@ -475,13 +475,13 @@ mm = ModelMatrix(mf)
mf = ModelFrame(n ~ 0 + x&y + x&z + x&y&z, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m == [1 0 0 0 -1 0 1 0
0 1 0 0 0 -1 0 1
0 0 1 0 -1 0 -1 0
0 0 0 1 0 -1 0 -1
1 0 0 0 1 0 -1 0
0 1 0 0 0 1 0 -1
0 0 1 0 1 0 1 0
0 0 0 1 0 1 0 1]
0 1 0 0 0 -1 0 1
0 0 1 0 -1 0 -1 0
0 0 0 1 0 -1 0 -1
1 0 0 0 1 0 -1 0
0 1 0 0 0 1 0 -1
0 0 1 0 1 0 1 0
0 0 0 1 0 1 0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["x: a & y: c", "x: b & y: c",
"x: a & y: d", "x: b & y: d",
Expand All @@ -494,13 +494,13 @@ mm = ModelMatrix(mf)
mf = ModelFrame(n ~ 0 + x + x&y + x&z, d, contrasts=cs)
mm = ModelMatrix(mf)
@test mm.m == [1 0 -1 0 -1 0
0 1 0 -1 0 -1
1 0 1 0 -1 0
0 1 0 1 0 -1
1 0 -1 0 1 0
0 1 0 -1 0 1
1 0 1 0 1 0
0 1 0 1 0 1]
0 1 0 -1 0 -1
1 0 1 0 -1 0
0 1 0 1 0 -1
1 0 -1 0 1 0
0 1 0 -1 0 1
1 0 1 0 1 0
0 1 0 1 0 1]
@test mm.m == ModelMatrix{sparsetype}(mf).m
@test coefnames(mf) == ["x: a", "x: b",
"x: a & y: d", "x: b & y: d",
Expand Down