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Merge pull request #141 from junder873/add-typst-support
Add support for Typst tables
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‎Project.toml

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@@ -1,7 +1,7 @@
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name = "RegressionTables"
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uuid = "d519eb52-b820-54da-95a6-98e1306fdade"
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authors = ["Johannes Boehm <[email protected]>"]
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version = "0.7.2"
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version = "0.7.3"
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[deps]
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"

‎docs/src/api.md

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@@ -73,6 +73,7 @@ RegressionTables.add_blank
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RegressionTables.missing_vars
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RegressionTables.add_element!
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RegressionTables.find_vertical_gaps
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RegressionTables.extra_cell_space
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```
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## How Types are Displayed

‎docs/src/examples.md

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@@ -6,7 +6,7 @@ Setup for the following examples:
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```@meta
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DocTestSetup = quote # hide
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using RegressionTables, DataFrames, RDatasets, FixedEffectModels, GLM, MixedModels;
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df = dataset("datasets", "iris");
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df = RDatasets.dataset("datasets", "iris");
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df[!,:isSmall] = df[!,:SepalWidth] .< 2.9;
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rr1 = reg(df, @formula(SepalLength ~ SepalWidth));
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rr2 = reg(df, @formula(SepalLength ~ SepalWidth + PetalLength + fe(Species)));
@@ -1315,7 +1315,7 @@ Pseudo R2 0.006 0.006 0.297 0.297
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Displays whether or not the standard errors are clustered and in what ways.
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13171317
```jldoctest
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df_cigar = dataset("plm", "Cigar");
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df_cigar = RDatasets.dataset("plm", "Cigar");
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rr_c1 = reg(df_cigar, @formula(Sales ~ NDI + fe(State) + fe(Year)), Vcov.cluster(:State));
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rr_c2 = reg(df_cigar, @formula(Sales ~ NDI + Price + fe(State) + fe(Year)), Vcov.cluster(:State, :Year));
@@ -1429,4 +1429,88 @@ Subject | Prec & Load 855.252
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N 1,789 1,789 1,789
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Log Likelihood -14,685.198 -14,765.033 -14,711.866
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---------------------------------------------------------------
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```
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## Typst Support
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Similar to Latex, this package can produce Typst Tables. This requires Typst v0.11.
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```jldoctest
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regtable(rr1,rr2,rr3,rr4; render = TypstTable())
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# output
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#table(
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columns: (auto, auto, auto, auto, auto),
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align: (left, right, right, right, right),
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column-gutter: 1fr,
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stroke: none,
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table.hline(),
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[] , table.cell(colspan: 3, align: center)[SepalLength] , table.cell(colspan: 1, align: center)[SepalWidth],
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table.hline(start: 1, end: 4, stroke: 0.5pt), table.hline(start: 4, end: 5, stroke: 0.5pt),
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[] , [(1)], [(2)], [(3)], [(4)],
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table.hline(stroke: 0.7pt),
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[(Intercept)] , [6.526$""^(***)$], [], [], [],
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[] , [(0.479)], [], [], [],
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[SepalWidth] , [-0.223], [0.432$""^(***)$], [0.516$""^(***)$], [],
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[] , [(0.155)], [(0.081)], [(0.104)], [],
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[PetalLength] , [], [0.776$""^(***)$], [0.723$""^(***)$], [-0.188$""^(*)$],
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[] , [], [(0.064)], [(0.129)], [(0.083)],
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[PetalWidth] , [], [], [-0.625], [0.626$""^(***)$],
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[] , [], [], [(0.354)], [(0.123)],
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[PetalLength $times$ PetalWidth], [], [], [0.066], [],
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[] , [], [], [(0.067)], [],
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[SepalLength] , [], [], [], [0.378$""^(***)$],
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[] , [], [], [], [(0.066)],
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table.hline(stroke: 0.7pt),
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[Species Fixed Effects] , [], [Yes], [Yes], [Yes],
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[isSmall Fixed Effects] , [], [], [Yes], [],
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table.hline(stroke: 0.7pt),
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[_N_] , [150], [150], [150], [150],
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[_R_$""^2$] , [0.014], [0.863], [0.868], [0.635],
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[Within-_R_$""^2$] , [], [0.642], [0.598], [0.391],
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table.hline(),
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)
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```
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```jldoctest
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regtable(rr1, rr6, rr7; render = TypstTable())
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# output
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#table(
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columns: (auto, auto, auto, auto),
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align: (left, right, right, right),
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column-gutter: 1fr,
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stroke: none,
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table.hline(),
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[] , table.cell(colspan: 1, align: center)[SepalLength], table.cell(colspan: 2, align: center)[isSmall],
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table.hline(start: 1, end: 2, stroke: 0.5pt), table.hline(start: 2, end: 4, stroke: 0.5pt),
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[] , [(1)], [(2)], [(3)],
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table.hline(stroke: 0.7pt),
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[(Intercept)] , [6.526$""^(***)$], [-1.917], [10.189$""^(***)$],
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[] , [(0.479)], [(1.242)], [(2.607)],
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[SepalWidth] , [-0.223], [], [],
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[] , [(0.155)], [], [],
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[PetalLength] , [], [-0.773], [3.580$""^(***)$],
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[] , [], [(0.554)], [(0.708)],
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[PetalWidth] , [], [-3.782$""^(**)$], [-3.637$""^(**)$],
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[] , [], [(1.256)], [(1.127)],
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[Species: versicolor], [], [10.441$""^(***)$], [],
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[] , [], [(1.957)], [],
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[Species: virginica] , [], [13.230$""^(***)$], [],
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[] , [], [(2.636)], [],
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[SepalLength] , [], [], [-3.519$""^(***)$],
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[] , [], [], [(0.697)],
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table.hline(stroke: 0.7pt),
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[Estimator] , [OLS], [Binomial], [Binomial],
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table.hline(stroke: 0.7pt),
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[_N_] , [150], [150], [150],
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[_R_$""^2$] , [0.014], [], [],
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[Pseudo _R_$""^2$] , [0.006], [0.347], [0.297],
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table.hline(),
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)
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```

‎docs/src/index.md

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@@ -23,7 +23,7 @@ To install the package, type in the Julia command prompt
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```@example main_data
2424
using RegressionTables, DataFrames, FixedEffectModels, RDatasets, GLM
2525
26-
df = dataset("datasets", "iris")
26+
df = RDatasets.dataset("datasets", "iris")
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rr1 = reg(df, @formula(SepalLength ~ SepalWidth + fe(Species)))
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rr2 = reg(df, @formula(SepalLength ~ SepalWidth + PetalLength + fe(Species)))

‎docs/src/keep_drop_order.md

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@@ -2,7 +2,7 @@
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DocTestSetup = quote # hide
33
using RegressionTables, DataFrames, FixedEffectModels, RDatasets
44
5-
df = dataset("datasets", "iris")
5+
df = RDatasets.dataset("datasets", "iris")
66
df[!,:SpeciesDummy] = df[!,:Species]
77
88
rr1 = reg(df, @formula(SepalLength ~ SepalWidth + fe(SpeciesDummy)))

‎src/RegressionTables.jl

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@@ -37,7 +37,7 @@ module RegressionTables
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##############################################################################
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3939
export regtable, LatexTable, LatexTableStar, AsciiTable, HtmlTable, AbstractRenderType,
40-
AbstractAscii, AbstractLatex, AbstractHtml
40+
AbstractAscii, AbstractLatex, AbstractHtml, TypstTable, AbstractTypst
4141
export Nobs, R2, R2McFadden, R2CoxSnell, R2Nagelkerke,
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R2Deviance, AdjR2, AdjR2McFadden, AdjR2Deviance, DOF, LogLikelihood, AIC, BIC, AICC,
4343
FStat, FStatPValue, FStatIV, FStatIVPValue, R2Within, PseudoR2, AdjPseudoR2
@@ -65,6 +65,7 @@ module RegressionTables
6565
include("rendersettings/ascii.jl")
6666
include("rendersettings/latex.jl")
6767
include("rendersettings/html.jl")
68+
include("rendersettings/typst.jl")
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# main settings

‎src/datarow.jl

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@@ -267,7 +267,7 @@ function calc_widths(rows::Vector{DataRow{T}}) where {T<:AbstractRenderType}
267267
end
268268
end
269269
else
270-
out_lengths[i] = max(out_lengths[i], length(s))
270+
out_lengths[i] = max(out_lengths[i], length(s) + extra_cell_space(render))
271271
end
272272
end
273273
end
@@ -280,7 +280,10 @@ end
280280
Updates the widths of each column in the row. If lengths are provided, then it should equate to the total number
281281
of columns in the table, not the number of elements in the row.
282282
"""
283-
function update_widths!(row::DataRow{T}, new_lengths=length.(repr.(T(), row.data))) where {T}
283+
function update_widths!(
284+
row::DataRow{T},
285+
new_lengths=length.(repr.(T(), row.data)) .+ extra_cell_space(T())
286+
) where {T}
284287
#@assert length(row) == length(new_lengths) "Wrong number of lengths"
285288
render = T()
286289
if length(row.data) == length(new_lengths)

‎src/rendersettings/default.jl

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@@ -34,6 +34,13 @@ RegressionTables.interaction_combine(render::AbstractLatex) = " \\& "
3434
"""
3535
interaction_combine(render::AbstractRenderType) = " & "
3636

37+
"""
38+
extra_cell_space(render::AbstractRenderType)
39+
40+
Used to add extra space to the cell and defaults to 0.
41+
"""
42+
extra_cell_space(::AbstractRenderType) = 0
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3744
"""
3845
categorical_equal(render::AbstractRenderType)
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‎src/rendersettings/typst.jl

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abstract type AbstractTypst <: AbstractRenderType end
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struct TypstTable <: AbstractTypst end
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function tablestart(::AbstractTypst, align)
5+
cols = [c == 'l' ? "left" : c == 'r' ? "right" : "center" for c in align]
6+
cols_align = join(cols, ", ")
7+
cols = join(fill("auto", length(cols)), ", ")
8+
9+
"""
10+
#table(
11+
columns: ($cols),
12+
align: ($cols_align),
13+
column-gutter: 1fr,
14+
stroke: none,
15+
"""
16+
end
17+
18+
wrapper(::AbstractTypst, x) = "\$\"\"^($x)\$"
19+
20+
tableend(::AbstractTypst) = ")"
21+
22+
function Base.repr(rndr::AbstractTypst, val::Pair; align="c", args...)
23+
s = Base.repr(rndr, first(val); args...)
24+
if length(s) == 0 && length(last(val)) == 1
25+
s
26+
else
27+
multicolumn(rndr, s, length(last(val)), align)
28+
end
29+
end
30+
function multicolumn(rndr::AbstractTypst, s, cols::Int, align="c")
31+
x = if align == "c" || align == 'c'
32+
"center"
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elseif align == "l" || align == 'l'
34+
"left"
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elseif align == "r" || align == 'r'
36+
"right"
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end
38+
"table.cell(colspan: $cols, align: $x)[$s]"
39+
end
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41+
underline(::AbstractTypst, colmin::Int, colmax::Int) = "table.hline(start: $(colmin-1), end: $(colmax), stroke: 0.5pt)"
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toprule(x::AbstractTypst) = linestart(x) * "table.hline(), "
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midrule(x::AbstractTypst) = linestart(x) * "table.hline(stroke: 0.7pt), "
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bottomrule(x::AbstractTypst) = linestart(x) * "table.hline(), "
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linestart(::AbstractTypst) = " "
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lineend(::AbstractTypst) = ","
48+
tablestart(tab::RegressionTable{<:AbstractTypst}) = tablestart(tab.render, tab.align)
49+
colsep(::AbstractTypst) = ", "
50+
51+
label(::AbstractTypst, x::Type{Nobs}) = "_N_"
52+
label(::AbstractTypst, x::Type{R2}) = "_R_\$\"\"^2\$"
53+
label(::AbstractTypst, x::Type{FStat}) = "_F_"
54+
label_p(::AbstractTypst, ) = "_p_"
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56+
extra_cell_space(::AbstractTypst) = 2 # to account for "[]"
57+
58+
interaction_combine(::AbstractTypst) = " \$times\$ "
59+
60+
function Base.print(io::IO, row::DataRow{T}) where {T<:AbstractTypst}
61+
render = T()
62+
print(io, linestart(render))
63+
for (i, x) in enumerate(row.data)
64+
s = if isa(x, Pair)
65+
repr(render, x; align = row.align[i])
66+
else
67+
"[" * repr(render, x; align = row.align[i]) * "]"
68+
end
69+
print(io, make_padding(s, row.colwidths[i], row.align[i]))
70+
if i < length(row.data)
71+
print(io, colsep(render))
72+
end
73+
end
74+
print(io, lineend(render))
75+
if any(row.print_underlines)
76+
println(io)
77+
print(io, linestart(render))
78+
for (i, x) in enumerate(row.data)
79+
s = isa(x, Pair) ? repr(render, first(x)) : repr(render, x)
80+
if length(s) == 0 || !row.print_underlines[i]
81+
continue
82+
end
83+
if isa(x, Pair)
84+
print(io, underline(render, first(last(x)), last(last(x))))
85+
else
86+
print(io, underline(render, i,i))
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end
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print(io, colsep(render))
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end
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end
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end

‎test/GLFixedEffectModels.jl

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using GLFixedEffectModels, GLM, RDatasets, Test
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# include("src/RegressionTables.jl")
6-
df = dataset("datasets", "iris")
6+
df = RDatasets.dataset("datasets", "iris")
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df[!, :isSmall] = df[!, :SepalWidth] .< 2.9
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df[!, :isWide] = df[!, :SepalWidth] .> 2.5
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df[!, :binary] = @. ifelse(df[!, :PetalWidth] .> 1.0, 1.0, 0.0)

‎test/RegressionTables.jl

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using RegressionTables
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using FixedEffectModels, GLM, RDatasets, Test
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4-
df = dataset("datasets", "iris")
4+
df = RDatasets.dataset("datasets", "iris")
55
df[!, :isSmall] = df[!, :SepalWidth] .< 2.9
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df[!, :isWide] = df[!, :SepalWidth] .> 2.5
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‎test/default_changes.jl

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@@ -9,7 +9,7 @@ own test set
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using RegressionTables
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using FixedEffectModels, GLM, RDatasets, Test
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df = dataset("datasets", "iris")
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df = RDatasets.dataset("datasets", "iris")
1313
df[!, :isSmall] = df[!, :SepalWidth] .< 2.9
1414
df[!, :isWide] = df[!, :SepalWidth] .> 2.5
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