Run Julia template engine for CI purposes

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2020, Thomas A. Christensen II
+Copyright (c) 2021, Thomas A. Christensen II <25492070+MillironX@users.noreply.github.com> and contributors
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

Project.toml

@@ -1,12 +1,13 @@
 name = "BeefBLUP"
-uuid = "03993faf-e476-444a-86c9-f31e8122fa24"
+uuid = "4c4dd571-0773-455e-9a95-72727008e3f4"
-authors = ["Thomas A. Christensen II <25492070+MillironX@users.noreply.github.com>"]
+authors = ["Thomas A. Christensen II <25492070+MillironX@users.noreply.github.com> and contributors"]
-version = "0.3.0"
+version = "0.1.0"
 
-[deps]
+[compat]
-ArgParse = "c7e460c6-2fb9-53a9-8c5b-16f535851c63"
+julia = "1.3"
-CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+
-DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+[extras]
-Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-Gtk = "4c0ca9eb-093a-5379-98c5-f87ac0bbbf44"
+
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+[targets]
+test = ["Test"]

README.md

@@ -1,82 +1,3 @@
-# [:cow:]: beefblup
+# BeefBLUP
 
-[![GitHub license](https://img.shields.io/github/license/MillironX/beefblup)](https://github.com/MillironX/beefblup/blob/master/LICENSE.md)
+[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://MillironX.github.io/BeefBLUP.jl/stable) [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://MillironX.github.io/BeefBLUP.jl/dev) [![Build Status](https://travis-ci.com/MillironX/BeefBLUP.jl.svg?branch=master)](https://travis-ci.com/MillironX/BeefBLUP.jl) [![Coverage](https://codecov.io/gh/MillironX/BeefBLUP.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/MillironX/BeefBLUP.jl) [![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle)
-[![Join the chat at https://gitter.im/beefblup/community](https://badges.gitter.im/beefblup/community.svg)](https://gitter.im/beefblup/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
-[![Github all releases](https://img.shields.io/github/downloads/MillironX/beefblup/total.svg)](https://GitHub.com/MillironX/beefblup/releases)
-
-beefblup is a program for ranchers to calculate expected breeding
-values (EBVs) for their own beef cattle. It is intended to be usable by anyone
-without requiring any prior knowledge of computer programming or linear algebra.
-Why? It's part of my effort to
-**\#KeepEPDsReal**
-
-## Installation
-
-1. [Download and install Julia](https://julialang.org/downloads/platform/)
-2. Download the [beefblup ZIP
-   file](https://github.com/MillironX/beefblup/archive/refs/tags/v0.2.zip) and unzip it   someplace memorable
-3. In your file explorer, copy the address of the "beefblup" folder
-4. Launch Julia
-5. Type `cd("<the address copied in step 5")` and press **Enter** (For example,
-   `cd("C:\Users\MillironX\Documents\beefblup")`)
-6. Type the `]` key
-7. Type `activate .` and press **Enter**
-8. Type `instantiate` and press **Enter**
-9. Installation is done: you can close the Julia window
-
-## How to Use
-
-1. Make a copy of the "sample.csv" spreadsheet and replace the data with your own
-   1. The trait you wish to calculate EBVs for always goes in the rightmost column
-   2. If you wish to add more contemporary group traits to your analysis, include them before the rightmost column
-2. Save and close
-3. In your file explorer, copy the address of the "beefblup" folder
-4. Launch Julia
-5. Type `cd("<the address copied in step 5")` and press **Enter** (For example,
-   `cd("C:\Users\MillironX\Documents\beefblup")`)
-6. Type the `]` key
-7. Type `activate .` and press **Enter**
-8. Press **Backspace**
-9. Type `include("src/beefblup.jl")` and press **Enter**
-10. Select the spreadsheet you created in steps 1-4
-11. Follow the on-screen prompts
-12. **#KeepEPDsReal!**
-
-## For Programmers
-
-> **Also Note:** beefblup was written on, and has only been tested with Julia
-> v1.2.0 and higher. While this shouldn't affect most everyday users, it might
-> affect you if you are stuck on the current LTS version of Julia (v1.0.5).
-
-### Development Roadmap
-
-| Version | Feature                                                                             | Status             |
-| ------- | ----------------------------------------------------------------------------------- | ------------------ |
-| v0.1    | Julia port of original MATLAB script                                                | :heavy_check_mark: |
-| v0.2    | Spreadsheet format redesign                                                         | :heavy_check_mark: |
-| v0.3    | API rewrite (change to function calls and package format instead of script running) |                    |
-| v0.4    | Add GUI for all options                                                             |                    |
-| v0.5    | Automatically calculated Age-Of-Dam, Year, and Season fixed-effects                 |                    |
-| v0.6    | Repeated measurement BLUP (aka dairyblup)                                           |                    |
-| v0.7    | Multiple trait BLUP                                                                 |                    |
-| v0.8    | Maternal effects BLUP                                                               |                    |
-| v0.9    | Genomic BLUP                                                                        |                    |
-| v0.10   | beefblup binaries                                                                   |                    |
-| v1.0    | [Finally, RELEASE!!!](https://youtu.be/1CBjxGdgC1w?t=282)                           |                    |
-
-### Bug Reports
-
-For every bug report, please include at least the following:
-
-- Platform (Windows, Mac, Fedora, etc)
-- Julia version
-- beefblup version
-- How you are running Julia (From PowerShell, via the REPL, etc.)
-- A beefblup spreadsheet that can be used to recreate the issue
-- Description of the problem
-- Expected behavior
-- A screenshot and/or REPL printout
-
-## License
-
-Distributed under the 3-Clause BSD License

docs/Project.toml

@@ -0,0 +1,3 @@
+[deps]
+BeefBLUP = "4c4dd571-0773-455e-9a95-72727008e3f4"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"

docs/make.jl

@@ -0,0 +1,24 @@
+using BeefBLUP
+using Documenter
+
+DocMeta.setdocmeta!(BeefBLUP, :DocTestSetup, :(using BeefBLUP); recursive=true)
+
+makedocs(;
+    modules=[BeefBLUP],
+    authors="Thomas A. Christensen II <25492070+MillironX@users.noreply.github.com> and contributors",
+    repo="https://github.com/MillironX/BeefBLUP.jl/blob/{commit}{path}#{line}",
+    sitename="BeefBLUP.jl",
+    format=Documenter.HTML(;
+        prettyurls=get(ENV, "CI", "false") == "true",
+        canonical="https://MillironX.github.io/BeefBLUP.jl",
+        assets=String[],
+    ),
+    pages=[
+        "Home" => "index.md",
+    ],
+)
+
+deploydocs(;
+    repo="github.com/MillironX/BeefBLUP.jl",
+    devbranch="develop",
+)

docs/src/index.md

@@ -0,0 +1,14 @@
+```@meta
+CurrentModule = BeefBLUP
+```
+
+# BeefBLUP
+
+Documentation for [BeefBLUP](https://github.com/MillironX/BeefBLUP.jl).
+
+```@index
+```
+
+```@autodocs
+Modules = [BeefBLUP]
+```

src/BeefBLUP.jl

@@ -1,264 +1,5 @@
-# beefblup
-# Julia package for performing single-variate BLUP to find beef cattle
-# breeding values
-# (C) 2021 Thomas A. Christensen II
-# Licensed under BSD-3-Clause License
-# cSpell:includeRegExp #.*
-# cSpell:includeRegExp ("""|''')[^\1]*\1
-
 module BeefBLUP
 
-# Import the required packages
+# Write your package code here.
-using CSV
-using DataFrames
-using LinearAlgebra
-using Dates
-using Gtk
-
-# Main entry-level function - acts just like the script
-function beefblup()
-
-    # Ask for an input spreadsheet
-    path = open_dialog_native(
-    "Select a beefblup worksheet",
-    GtkNullContainer(),
-    ("*.csv", GtkFileFilter("*.csv", name="beefblup worksheet"))
-    )
-
-    # Ask for an output text filename
-    savepath = save_dialog_native(
-    "Save your beefblup results",
-    GtkNullContainer(),
-    (GtkFileFilter("*.txt", name="Results file"),
-    "*.txt")
-    )
-
-    # Ask for heritability
-    print("What is the heritability for this trait?> ")
-    h2 = parse(Float64, readline(stdin))
-
-    beefblup(path, savepath, h2)
 
 end
-
-function beefblup(datafile::String, h2::Float64)
-    # Assume the data is named the same as the file without the trailing extension
-    dataname = join(split(datafile, ".")[1:end - 1])
-
-    # Create a new results name
-    resultsfile = string(dataname, "_results.txt")
-
-    # Pass this info on to the worker
-    beefblup(datafile, resultsfile, h2)
-end
-
-# Main worker function, can perform all the work if given all the user input
-function beefblup(path::String, savepath::String, h2::Float64)
-
-    # Import data from a suitable spreadsheet
-    data = DataFrame(CSV.File(path))
-
-    # Sort the array by date
-    sort!(data, :birthdate)
-
-    # Define fields to hold id values for animals and their parents
-    numanimals = length(data.id)
-
-    # Find the index values for animals and their parents
-    dam = indexin(data.dam, data.id)
-    sire = indexin(data.sire, data.id)
-
-    # Extract all of the fixed effects
-    fixedfx = select(data, Not([:id, :birthdate, :sire, :dam]))[:,1:end - 1]
-
-    # Find any columns that need to be deleted
-    for i in 1:ncol(fixedfx)
-        if length(unique(fixedfx[:,i])) <= 1
-            @warn string("column '", names(fixedfx)[i], "' does not have any unique animals and will be removed from this analysis")
-            DataFrames.select!(fixedfx, Not(i))
-        end
-    end
-
-    # Determine how many contemporary groups there are
-    numtraits = ncol(fixedfx)
-    numgroups = ones(1, numtraits)
-    for i in 1:numtraits
-        numgroups[i] = length(unique(fixedfx[:,i]))
-    end
-
-    # If there are more groups than animals, then the analysis cannot continue
-    if sum(numgroups) >= numanimals
-        throw(ErrorException("there are more contemporary groups than animals"))
-    end
-
-    # Define a "normal" animal as one of the last in the groups, provided that
-    # all traits do not have null values
-    normal = Array{String}(undef, 1, numtraits)
-    for i in 1:numtraits
-        for j in numanimals:-1:1
-            if !ismissing(fixedfx[j,i])
-                normal[i] = string(fixedfx[j,i])
-                break
-            end
-        end
-    end
-
-    # Form the fixed-effect matrix
-    X = zeros(Int8, numanimals, floor(Int, sum(numgroups)) - length(numgroups) + 1)
-    X[:,1] = ones(Int8, 1, numanimals)
-
-    # Create an external counter that will increment through both loops
-    counter = 2
-
-    # Store the traits in a string array
-    adjustedtraits =
-    Array{String}(undef,floor(Int, sum(numgroups)) - length(numgroups))
-    # Iterate through each group
-    for i in 1:length(normal)
-        # Find the traits that are present in this trait
-        localdata = string.(fixedfx[:,i])
-        traits = unique(localdata)
-        # Remove the normal version from the analysis
-        effecttraits = traits[findall(x -> x != normal[i], traits)]
-        # Iterate inside of the group
-        for j in 1:(length(effecttraits))
-            matchedindex = findall(x -> x == effecttraits[j], localdata)
-            X[matchedindex, counter] .= 1
-            # Add this trait to the string
-            adjustedtraits[counter - 1] = traits[j]
-            # Increment the big counter
-            counter = counter + 1
-        end
-    end
-
-    # Create an empty matrix for the additive relationship matrix
-    A = zeros(numanimals, numanimals)
-
-    # Create the additive relationship matrix by the FORTRAN method presented by
-    # Henderson
-    for i in 1:numanimals
-        if !isnothing(dam[i]) && !isnothing(sire[i])
-            for j in 1:(i - 1)
-                A[j,i] = 0.5 * (A[j,sire[i]] + A[j,dam[i]])
-                A[i,j] = A[j,i]
-            end
-            A[i,i] = 1 + 0.5 * A[sire[i], dam[i]]
-        elseif !isnothing(dam[i]) && isnothing(sire[i])
-        for j in 1:(i - 1)
-            A[j,i] = 0.5 * A[j,dam[i]]
-            A[i,j] = A[j,i]
-        end
-        A[i,i] = 1
-    elseif isnothing(dam[i]) && !isnothing(sire[i])
-        for j in 1:(i - 1)
-            A[j,i] = 0.5 * A[j,sire[i]]
-            A[i,j] = A[j,i]
-        end
-        A[i,i] = 1
-    else
-        for j in 1:(i - 1)
-            A[j,i] = 0
-            A[i,j] = 0
-        end
-        A[i,i] = 1
-        end
-    end
-
-    # Extract the observed data
-    Y = convert(Array{Float64}, data[:,end])
-
-    # The random effects matrix
-    Z = Matrix{Int}(I, numanimals, numanimals)
-
-    # Remove items where there is no data
-    nullobs = findall(isnothing, Y)
-    Z[nullobs, nullobs] .= 0
-
-    # Calculate heritability
-    λ = (1 - h2) / h2
-
-    # Use the mixed-model equations
-    MME = [X' * X X' * Z; Z' * X (Z' * Z) + (inv(A) .* λ)]
-    MMY = [X' * Y; Z' * Y]
-    solutions = MME \ MMY
-
-    # Find the accuracies
-    diaginv = diag(inv(MME))
-    reliability = ones(Float64, length(diaginv)) - diaginv .* λ
-
-    # Find how many traits we found BLUE for
-    numgroups = numgroups .- 1
-
-    # Extract the names of the traits
-    fixedfxnames = names(fixedfx)
-    traitname = names(data)[end]
-
-    # Start printing results to output
-    fileID = open(savepath, "w")
-    write(fileID, "beefblup Results Report\n")
-    write(fileID, "Produced using beefblup (")
-    write(fileID, "https://github.com/millironx/beefblup")
-    write(fileID, ")\n\n")
-    write(fileID, "Input:\t")
-    write(fileID, path)
-    write(fileID, "\nAnalysis performed:\t")
-    write(fileID, string(Dates.today()))
-    write(fileID, "\nTrait examined:\t")
-    write(fileID, traitname)
-    write(fileID, "\n\n")
-
-    # Print base population stats
-    write(fileID, "Base Population:\n")
-    for i in 1:length(normal)
-        write(fileID, "\t")
-        write(fileID, fixedfxnames[i])
-        write(fileID, ":\t")
-        write(fileID, normal[i])
-        write(fileID, "\n")
-    end
-    write(fileID, "\tMean ")
-    write(fileID, traitname)
-    write(fileID, ":\t")
-    write(fileID, string(solutions[1]))
-    write(fileID, "\n\n")
-
-    # Contemporary group adjustments
-    counter = 2
-    write(fileID, "Contemporary Group Effects:\n")
-    for i in 1:length(numgroups)
-        write(fileID, "\t")
-        write(fileID, fixedfxnames[i])
-        write(fileID, "\tEffect\tReliability\n")
-        for j in 1:numgroups[i]
-            write(fileID, "\t")
-            write(fileID, adjustedtraits[counter - 1])
-            write(fileID, "\t")
-            write(fileID, string(solutions[counter]))
-            write(fileID, "\t")
-            write(fileID, string(reliability[counter]))
-            write(fileID, "\n")
-
-            counter = counter + 1
-        end
-        write(fileID, "\n")
-    end
-    write(fileID, "\n")
-
-    # Expected breeding values
-    write(fileID, "Expected Breeding Values:\n")
-    write(fileID, "\tID\tEBV\tReliability\n")
-    for i in 1:numanimals
-        write(fileID, "\t")
-        write(fileID, string(data.id[i]))
-        write(fileID, "\t")
-        write(fileID, string(solutions[i + counter - 1]))
-        write(fileID, "\t")
-        write(fileID, string(reliability[i + counter - 1]))
-        write(fileID, "\n")
-    end
-
-    write(fileID, "\n - END REPORT -")
-    close(fileID)
-
-end
-end

test/runtests.jl

@@ -1,2 +1,6 @@
 using BeefBLUP
 using Test
+
+@testset "BeefBLUP.jl" begin
+    # Write your tests here.
+end