Merge pull request #126 from iuliadmtru/remove_old_design

Remove old design

src/Survey.jl

@@ -11,7 +11,6 @@ using AlgebraOfGraphics
 using CategoricalArrays
 
 include("SurveyDesign.jl")
-include("design.jl")
 include("mean.jl")
 include("quantile.jl")
 include("total.jl")
@@ -25,7 +24,6 @@ include("show.jl")
 export load_data
 export AbstractSurveyDesign, SimpleRandomSample, StratifiedSample
 export SurveyDesign
-export design
 export by
 export ht_calc
 export dim, colnames, dimnames

src/boxplot.jl

@@ -23,11 +23,3 @@ function boxplot(design::AbstractSurveyDesign, x::Symbol, y::Symbol; kwargs...)
 
 	data * visual(BoxPlot) * map |> draw
 end
-
-function boxplot(design::design, x::Symbol, y::Symbol; kwargs...)
-    # TODO: change function, make it a wrapper
-	map = mapping(x, y; kwargs...)
-	data = AlgebraOfGraphics.data(design.variables)
-
-	data * visual(BoxPlot) * map |> draw
-end

src/dimnames.jl

@@ -13,7 +13,6 @@ julia> dim(srs)
 ```
 """
 dim(design::AbstractSurveyDesign) = size(design.data)
-dim(design::design) = size(design.variables)
 
 """
 	colnames(design)
@@ -50,7 +49,6 @@ julia> colnames(srs)
 ```
 """
 colnames(design::AbstractSurveyDesign) = names(design.data)
-colnames(design::design) = names(design.variables)
 
 """
 	dimnames(design)
@@ -69,4 +67,3 @@ julia> dimnames(srs)
 ```
 """
 dimnames(design::AbstractSurveyDesign) = [string.(1:size(design.data, 1)), names(design.data)]
-dimnames(design::design) = [string.(1:size(design.variables, 1)), names(design.variables)]

src/hist.jl

@@ -1,7 +1,6 @@
 sturges(n::Integer) = ceil(Int, log2(n)) + 1
 sturges(vec::AbstractVector) = ceil(Int, log2(length(vec))) + 1
 sturges(df::DataFrame, var::Symbol) = ceil(Int, log2(size(df[!, var], 1))) + 1
-sturges(design::design, var::Symbol) = sturges(design.variables, var)
 
 """
     sturges(design::SurveyDesign, var::Symbol)
@@ -22,7 +21,6 @@ sturges(design::AbstractSurveyDesign, var::Symbol) = sturges(design.data, var)
 
 freedman_diaconis(v::AbstractVector) = round(Int, length(v)^(1 / 3) * (maximum(v) - minimum(v)) / (2 * iqr(v)))
 freedman_diaconis(df::DataFrame, var::Symbol) = freedman_diaconis(df[!, var])
-freedman_diaconis(design::design, var::Symbol) = freedman_diaconis(design.variables[!, var])
 
 """
     freedman_diaconis(design::SurveyDesign, var::Symbol)
@@ -85,19 +83,3 @@ function hist(design::AbstractSurveyDesign, var::Symbol,
     			)
     hist(design, var, bins(design, var); kwargs...)
 end
-
-function hist(design::design, var::Symbol,
-				 bins::Union{Integer, AbstractVector} = freedman_diaconis(design, var);
-				 normalization = :density,
-				 kwargs...
-    			)
-	hist = histogram(bins = bins, normalization = normalization, kwargs...)
-	data(design.variables) * mapping(var, weights = :weights) * hist |> draw
-end
-
-function hist(design::design, var::Symbol,
-				 bins::Function;
-				 kwargs...
-    			)
-    hist(design, var, bins(design, var); kwargs...)
-end

src/plot.jl

@@ -18,7 +18,3 @@ save("scatter.png", s); nothing # hide
 function plot(design::AbstractSurveyDesign, x::Symbol, y::Symbol; kwargs...)
     data(design.data) * mapping(x, y, markersize = :weights) * visual(Scatter, marker = '￮') |> draw
 end
-
-function plot(design::design, x::Symbol, y::Symbol; kwargs...)
-	data(design.variables) * mapping(x, y, markersize = :weights) * visual(Scatter, marker = '￮') |> draw
-end

src/quantile.jl

@@ -30,15 +30,6 @@ function quantile(var, design::StratifiedSample, q)
     return df
 end
 
-function quantile(var, design::design, q)
-    x = design.variables[!, var]
-    w = design.variables.probs
-    df = DataFrame(tmp = Statistics.quantile(Float32.(x), weights(w), q))
-    rename!(df, :tmp => Symbol(string(q) .* "th percentile"))
-
-    return df
-end
-
 # Inner method for `by`
 function quantile(x, w, _, q)
     df = DataFrame(tmp = Statistics.quantile(Float32.(x), weights(w), q))

src/show.jl

@@ -64,19 +64,3 @@ function Base.show(io::IO, ::MIME"text/plain", design::SurveyDesign)
     printinfo(io, "sampfraction", makeshort(design.sampfraction))
     printinfo(io, "ignorefpc", string(design.ignorefpc); newline=false)
 end
-
-"Print information about a survey design initialized using `design`."
-function Base.show(io::IO, ::MIME"text/plain", design::design)
-    printstyled(io, "Survey Design:\n"; bold=true)
-    printstyled(io, "variables: "; bold=true)
-    println(io, size(design.variables, 1), "x", size(design.variables, 2), " DataFrame")
-    printinfo(io, "id", makeshort(design.id))
-    printinfo(io, "strata", makeshort(design.variables.strata))
-    printinfo(io, "probs", makeshort(design.variables.probs))
-    printinfo(io, "fpc:\n    popsize", makeshort(design.variables.popsize))
-    printinfo(io, "    sampsize", makeshort(design.variables.sampsize); newline=false)
-    printstyled("\nnest: "; bold=true)
-    print(design.nest)
-    printstyled("\ncheck_strat: "; bold=true)
-    print(design.check_strat)
-end

test/dimnames.jl

@@ -3,22 +3,14 @@
     apisrs = load_data("apisrs")
     # make a copy to not modify the original dataset
     apisrs_copy = copy(apisrs)
-    srs_new = SimpleRandomSample(apisrs_copy,popsize=:fpc,ignorefpc = true)
-    # make a new copy to use for the old design
-    apisrs_copy = copy(apisrs)
-    srs_old = design(id = :1, data = apisrs)
+    srs = SimpleRandomSample(apisrs_copy,popsize=:fpc,ignorefpc = true)
     # `dim`
-    @test dim(srs_new)[1] == dim(srs_old)[1]
-    @test dim(srs_new)[2] == 42
-    @test dim(srs_old)[2] == 45
+    @test dim(srs)[2] == 42
     # `colnames`
-    @test length(colnames(srs_new)) == dim(srs_new)[2]
-    @test length(colnames(srs_old)) == dim(srs_old)[2]
+    @test length(colnames(srs)) == dim(srs)[2]
     # `dimnames`
-    @test length(dimnames(srs_new)[1]) == parse(Int, last(dimnames(srs_new)[1]))
-    @test dimnames(srs_new)[2] == colnames(srs_new)
-    @test length(dimnames(srs_old)[1]) == parse(Int, last(dimnames(srs_old)[1]))
-    @test dimnames(srs_old)[2] == colnames(srs_old)
+    @test length(dimnames(srs)[1]) == parse(Int, last(dimnames(srs)[1]))
+    @test dimnames(srs)[2] == colnames(srs)
 
     # Stratified sampling tests
 end

test/quantile.jl

@@ -1,17 +1,11 @@
 @testset "quantile.jl" begin
     # SimpleRandomSample
-    apisrs = load_data("apisrs")
+    apisrs_original = load_data("apisrs")
 
-    srs_new = SimpleRandomSample(apisrs,popsize=:fpc,ignorefpc = true)
-    srs_old = design(id = :1, data = apisrs)
+	apisrs = copy(apisrs_original)
+    srs_new = SimpleRandomSample(apisrs; popsize=:fpc, ignorefpc=true)
     # 0.5th percentile
-    q_05_new = quantile(:api00, srs_new, 0.5)
-    q_05_old = quantile(:api00, srs_old, 0.5)
-    @test q_05_new == q_05_old
     # 0.25th percentile
-    q_025_new = quantile(:api00, srs_new, 0.25)
-    q_025_old = quantile(:api00, srs_old, 0.25)
-    @test q_025_new == q_025_old
 
     # StratifiedSample
 end