Add fpc, fix svytotal and svymean

.github/workflows/documentation.yml

@@ -1,12 +1,6 @@
 name: Documentation
 
-on:
-    push:
-        branches:
-            - main
-    pull_request:
-        branches:
-            - main
+on: [push, pull_request]
     # can add tags if needed
 jobs:
     build:

src/SurveyDesign.jl

@@ -1,62 +1,96 @@
 # Helper function for nice printing
-function print_short(x::AbstractVector)
+function print_short(x)
+    # write floats in short form
+    if isa(x[1], Float64)
+        x = round.(x, sigdigits = 3)
+    end
+    # print short vectors or single values as they are, compress otherwise
     if length(x) < 3
         print(x)
     else
-        print( x[1], ", ", x[2], ", ", x[3], " ...", " (length = ", length(x), ")")
+        print( x[1], ", ", x[2], ", ", x[3], " ... ", last(x))
     end
 end
 
 """
 Supertype for every survey design type: `SimpleRandomSample`, `ClusterSample`
 and `StratifiedSample`.
+
+The data to a survey constructor is modified. To avoid this pass a copy of the data
+instead of the original.
 """
 abstract type AbstractSurveyDesign end
 
 """
-A `SimpleRandomSample` object contains survey design information needed to
-analyse surveys sampled by simple random sampling.
-TODO: documentation about user making a copy
-TODO: add fpc
-By default popsize is same sampsize, unless explicitly provided
+    SimpleRandomSample <: AbstractSurveyDesign
+
+Survey design sampled by simple random sampling.
+
+The population size is equal to the sample size unless `popsize` is explicitly provided.
 """
 struct SimpleRandomSample <: AbstractSurveyDesign
     data::DataFrame
-    sample_size::Int
-    pop_size::Int
-    function SimpleRandomSample(data::DataFrame; sample_size = nrow(data), pop_size = nrow(data), 
-                                weights = ones(nrow(data)), probs = 1 ./ weights)
-        # add frequency weights, probability weights and sample size columns
-        # TODO: make lines 28 & 29 use a helper function?
+    sampsize::UInt
+    popsize::Union{UInt,Nothing}
+    sampfraction::Real
+    fpc::Real
+    ignorefpc::Bool
+    function SimpleRandomSample(data::DataFrame;
+                                popsize = nothing,
+                                sampsize = nrow(data),
+                                weights = ones(nrow(data)), # Check the defaults
+                                probs = nothing,
+                                ignorefpc = true
+                                )
+        if isa(weights, Symbol)
+            weights = data[!, weights]
+        end
+        # set population size if it is not given; `weights` and `sampsize` must be given
+        if isnothing(popsize)
+            popsize = round(sum(weights)) |> UInt
+        end
+        # add frequency weights column to `data`
         data[!, :weights] = weights
-        data[!, :probs] = probs
+        # add probability weights column to `data`
+        data[!, :probs] = 1 ./ data[!, :weights]
+        # set sampling fraction
+        sampfraction = sampsize / popsize
+        # set fpc
+        fpc = ignorefpc ? 1 : 1 - (sampsize / popsize)
 
-        new(data, sample_size, pop_size)
+        new(data, sampsize, popsize, sampfraction, fpc, ignorefpc)
     end
 end
 
 # `show` method for printing information about a `SimpleRandomSample` after construction
-# TODO: change `show` to 3 argument method
-function Base.show(io::IO, design::SimpleRandomSample)
-    printstyled("Simple Random Sample:\n")
+function Base.show(io::IO, ::MIME"text/plain", design::SimpleRandomSample)
+    printstyled("Simple Random Sample:\n"; bold = true)
     printstyled("data: "; bold = true)
-    print(size(design.data)[1], "x", size(design.data)[2], " DataFrame")
+    print(size(design.data, 1), "x", size(design.data, 2), " DataFrame")
+    printstyled("\nweights: "; bold = true)
+    print_short(design.data.weights)
     printstyled("\nprobs: "; bold = true)
     print_short(design.data.probs)
-    # TODO: change fpc
     printstyled("\nfpc: "; bold = true)
-    print("\n    popsize: ")
-    print(design.pop_size)
-    print("\n    sampsize: ")
-    print(design.sample_size)
+    print_short(design.fpc)
+    printstyled("\n    popsize: "; bold = true)
+    print(design.popsize)
+    printstyled("\n    sampsize: "; bold = true)
+    print(design.sampsize)
 end
 
 """
-A `StratifiedSample` object holds information necessary for surveys sampled by
-stratification.
+    StratifiedSample <: AbstractSurveyDesign
+
+Survey design sampled by stratification.
 """
 struct StratifiedSample <: AbstractSurveyDesign
     data::DataFrame
+    sampsize::UInt
+    popsize::Union{UInt,Nothing}
+    sampfraction::Real
+    fpc::Real
+    nofpc::Bool
     function StratifiedSample(data::DataFrame, strata::AbstractVector; weights = ones(nrow(data)), probs = 1 ./ weights)
         # add frequency weights, probability weights and sample size columns
         data[!, :weights] = weights
@@ -72,40 +106,45 @@ end
 
 # `show` method for printing information about a `StratifiedSample` after construction
 function Base.show(io::IO, design::StratifiedSample)
-    printstyled("Stratified Sample:\n")
+    printstyled("Stratified Sample:\n"; bold = true)
     printstyled("data: "; bold = true)
-    print(size(design.data)[1], "x", size(design.data)[2], " DataFrame")
+    print(size(design.data, 1), "x", size(design.data, 2), " DataFrame")
+    printstyled("\nweights: "; bold = true)
+    print_short(design.data.weights)
     printstyled("\nprobs: "; bold = true)
     print_short(design.data.probs)
     printstyled("\nstrata: "; bold = true)
     print_short(design.data.strata)
-    # TODO: change fpc
     printstyled("\nfpc: "; bold = true)
-    print("\n    popsize: ")
-    print_short(design.data.popsize)
-    print("\n    sampsize: ")
-    print_short(design.data.sampsize)
+    print_short(design.fpc)
+    printstyled("\n    popsize: "; bold = true)
+    print(design.popsize)
+    printstyled("\n    sampsize: "; bold = true)
+    print(design.sampsize)
 end
 
 """
-A `ClusterSample` object holds information necessary for surveys sampled by
-clustering.
+    ClusterSample <: AbstractSurveyDesign
+
+Survey design sampled by clustering.
 """
 struct ClusterSample <: AbstractSurveyDesign
     data::DataFrame
 end
 
 # `show` method for printing information about a `ClusterSample` after construction
 function Base.show(io::IO, design::ClusterSample)
-    printstyled("Simple Random Sample:\n")
+    printstyled("Cluster Sample:\n"; bold = true)
     printstyled("data: "; bold = true)
-    print(size(design.data)[1], "x", size(design.data)[2], " DataFrame")
+    print(size(design.data, 1), "x", size(design.data, 2), " DataFrame")
+    printstyled("\nweights: "; bold = true)
+    print_short(design.data.weights)
     printstyled("\nprobs: "; bold = true)
     print_short(design.data.probs)
-    # TODO: change fpc
     printstyled("\nfpc: "; bold = true)
-    print("\n    popsize: ")
-    print_short(design.data.popsize)
-    print("\n    sampsize: ")
-    print_short(design.data.sampsize)
+    print_short(design.fpc)
+    printstyled("\n    popsize: "; bold = true)
+    print(design.popsize)
+    printstyled("\n    sampsize: "; bold = true)
+    print(design.sampsize)
 end

src/dimnames.jl

@@ -3,14 +3,12 @@
 Get the dimensions of a `SurveyDesign`.
 
 ```jldoctest
-julia> using Survey
-
 julia> apisrs = load_data("apisrs");
 
 julia> srs = SimpleRandomSample(apisrs);
 
 julia> dim(srs)
-(200, 44)
+(200, 42)
 ```
 """
 dim(design::AbstractSurveyDesign) = size(design.data)
@@ -19,8 +17,6 @@ dim(design::AbstractSurveyDesign) = size(design.data)
 Method for `svydesign` object.
 
 ```jldoctest
-julia> using Survey
-
 julia> apistrat = load_data("apistrat");
 
 julia> dstrat = svydesign(data = apistrat, id = :1, strata = :stype, weights = :pw, fpc = :fpc);
@@ -36,14 +32,12 @@ dim(design::svydesign) = size(design.variables)
 Get the column names of a `SurveyDesign`.
 
 ```jldoctest
-julia> using Survey
-
 julia> apisrs = load_data("apisrs");
 
 julia> srs = SimpleRandomSample(apisrs);
 
 julia> colnames(srs)
-44-element Vector{String}:
+42-element Vector{String}:
  "Column1"
  "cds"
  "stype"
@@ -55,15 +49,15 @@ julia> colnames(srs)
  "cname"
  "cnum"
  ⋮
+ "avg.ed"
+ "full"
  "emer"
  "enroll"
  "api.stu"
  "pw"
  "fpc"
  "weights"
  "probs"
- "popsize"
- "sampsize"
 ```
 """
 colnames(design::AbstractSurveyDesign) = names(design.data)
@@ -72,8 +66,6 @@ colnames(design::AbstractSurveyDesign) = names(design.data)
 Method for `svydesign` objects.
 
 ```jldoctest
-julia> using Survey
-
 julia> apistrat = load_data("apistrat");
 
 julia> dstrat = svydesign(data = apistrat, id = :1, strata = :stype, weights = :pw, fpc = :fpc);
@@ -109,16 +101,14 @@ colnames(design::svydesign) = names(design.variables)
 Get the names of the rows and columns of a `SurveyDesign`.
 
 ```jldoctest
-julia> using Survey
-
 julia> apisrs = load_data("apisrs");
 
 julia> srs = SimpleRandomSample(apisrs);
 
 julia> dimnames(srs)
 2-element Vector{Vector{String}}:
  ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"  …  "191", "192", "193", "194", "195", "196", "197", "198", "199", "200"]
- ["Column1", "cds", "stype", "name", "sname", "snum", "dname", "dnum", "cname", "cnum"  …  "full", "emer", "enroll", "api.stu", "pw", "fpc", "weights", "probs", "popsize", "sampsize"]
+ ["Column1", "cds", "stype", "name", "sname", "snum", "dname", "dnum", "cname", "cnum"  …  "grad.sch", "avg.ed", "full", "emer", "enroll", "api.stu", "pw", "fpc", "weights", "probs"]
 ```
 """
 dimnames(design::AbstractSurveyDesign) = [string.(1:size(design.data, 1)), names(design.data)]
@@ -127,8 +117,6 @@ dimnames(design::AbstractSurveyDesign) = [string.(1:size(design.data, 1)), names
 Method for `svydesign` objects.
 
 ```jldoctest
-julia> using Survey
-
 julia> apistrat = load_data("apistrat");
 
 julia> dstrat = svydesign(data = apistrat, id = :1, strata = :stype, weights = :pw, fpc = :fpc);

src/svyboxplot.jl

@@ -10,8 +10,6 @@ The keyword arguments are all the arguments that can be passed to `mapping` in
 [AlgebraOfGraphics](https://docs.juliahub.com/AlgebraOfGraphics/CHIaw/0.4.7/).
 
 ```@example svyboxplot
-julia> using survey
-
 julia> apisrs = load_data("apisrs");
 
 julia> srs = SimpleRandomSample(apisrs);

src/svydesign.jl

@@ -11,19 +11,17 @@
 The `svydesign` object combines a data frame and all the survey design information needed to analyse it.
 
 ```jldoctest
-julia> using Survey;
-
 julia> apiclus1 = load_data("apiclus1");
 
 julia> dclus1 = svydesign(id= :dnum, weights= :pw, data = apiclus1, fpc= :fpc) |> print
 Survey Design:
 variables: 183x45 DataFrame
 id: dnum
-strata: 1, 1, 1 ... (length = 183)
-probs: 0.029544719150814778, 0.029544719150814778, 0.029544719150814778 ... (length = 183)
+strata: 1, 1, 1 ... 1
+probs: 0.029544719150814778, 0.029544719150814778, 0.029544719150814778 ... 0.029544719150814778
 fpc:
-    popsize: 757, 757, 757 ... (length = 183)
-    sampsize: 183, 183, 183 ... (length = 183)
+    popsize: 757, 757, 757 ... 757
+    sampsize: 183, 183, 183 ... 183
 nest: false
 check_strat: true
 ```

src/svyglm.jl

@@ -16,8 +16,6 @@ svyglm(formula, design, dist, link)
 The `svyglm` function can be used to fit glms on svydesign.
 
 ```jldoctest
-julia> using Survey
-
 julia> apiclus1 = load_data("apiclus1");
 
 julia> dclus1 = svydesign(id=:dnum, weights=:pw, data = apiclus1);

src/svyhist.jl

@@ -159,8 +159,6 @@ The `weights` argument should be a `Symbol` specifying a design variable.
 For the complete argument list see [Makie.hist](https://makie.juliaplots.org/stable/examples/plotting_functions/hist/).
 
 ```julia
-julia> using Survey
-
 julia> apisrs = load_data("apisrs");
 
 julia> srs = SimpleRandomSample(apisrs);