Merge pull request #1 from SKopecz/hr/package

create package infrastructure and CI tests

.github/dependabot.yml

@@ -0,0 +1,7 @@
+# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
+version: 2
+updates:
+  - package-ecosystem: "github-actions"
+    directory: "/" # Location of package manifests
+    schedule:
+      interval: "monthly"

.github/workflows/CI.yml

@@ -0,0 +1,115 @@
+name: CI
+
+on:
+  pull_request:
+    branches:
+      - main
+  push:
+    branches:
+      - main
+
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    name: ${{ matrix.os }} - Julia ${{ matrix.version }} - ${{ github.event_name }}
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - '1'
+          - '1.8'
+        os:
+          - ubuntu-latest
+        include:
+          - version: '1'
+            os: macOS-latest
+          - version: '1'
+            os: windows-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+      - uses: julia-actions/cache@v1
+      - uses: julia-actions/julia-buildpkg@v1
+        env:
+          GKSwstype: "100" # for Plots/GR
+      - uses: julia-actions/julia-runtest@v1
+        env:
+          GKSwstype: "100" # for Plots/GR
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: codecov/codecov-action@v3
+        with:
+          file: lcov.info
+      # The standard setup of Coveralls is just annoying for parallel builds, see, e.g.,
+      # https://github.com/trixi-framework/Trixi.jl/issues/691
+      # https://github.com/coverallsapp/github-action/issues/47
+      # https://github.com/coverallsapp/github-action/issues/67
+      # This standard setup is reproduced below for completeness.
+      # - uses: coverallsapp/github-action@master
+      #   with:
+      #     github-token: ${{ secrets.GITHUB_TOKEN }}
+      #     flag-name: run-${{ matrix.version }}-${{ github.run_id }}
+      #     parallel: true
+      #     path-to-lcov: ./lcov.info
+      # Instead, we use a more tedious approach:
+      # - Store all individual coverage files as artifacts (directly below)
+      # - Download and merge individual coverage reports in another step
+      # - Upload only the merged coverage report to Coveralls
+      - shell: bash
+        run: |
+          cp ./lcov.info ./lcov-${{ matrix.version }}-${{ github.run_id }}.info
+      - uses: actions/upload-artifact@v3
+        with:
+          name: lcov-${{ matrix.version }}-${{ github.run_id }}
+          path: ./lcov-${{ matrix.version }}-${{ github.run_id }}.info
+
+  finish:
+    needs: test
+    runs-on: ubuntu-latest
+    steps:
+      # The standard setup of Coveralls is just annoying for parallel builds, see, e.g.,
+      # https://github.com/trixi-framework/Trixi.jl/issues/691
+      # https://github.com/coverallsapp/github-action/issues/47
+      # https://github.com/coverallsapp/github-action/issues/67
+      # This standard setup is reproduced below for completeness.
+      # - name: Coveralls Finished
+      #   uses: coverallsapp/github-action@master
+      #   with:
+      #     github-token: ${{ secrets.GITHUB_TOKEN }}
+      #     parallel-finished: true
+      # Instead, we use the more tedious approach described above.
+      # At first, we check out the repository and download all artifacts
+      # (and list files for debugging).
+      - uses: actions/checkout@v4
+      - uses: actions/download-artifact@v3
+      - run: ls -R
+      # Next, we merge the individual coverage files and upload
+      # the combined results to Coveralls.
+      - name: Merge lcov files using Coverage.jl
+        shell: julia --color=yes {0}
+        run: |
+          using Pkg
+          Pkg.activate(temp=true)
+          Pkg.add("Coverage")
+          using Coverage
+          coverage = LCOV.readfolder(".")
+          for cov in coverage
+            cov.filename = replace(cov.filename, "\\" => "/")
+          end
+          filter!(c -> basename(c.filename) != "precompile.jl", coverage)
+          coverage = merge_coverage_counts(coverage)
+          @show covered_lines, total_lines = get_summary(coverage)
+          LCOV.writefile("./lcov.info", coverage)
+      # TODO: Activate this when the package becomes public
+      # - uses: coverallsapp/github-action@master
+      #   with:
+      #     github-token: ${{ secrets.GITHUB_TOKEN }}
+      #     path-to-lcov: ./lcov.info
+      # Upload merged coverage data as artifact for debugging
+      - uses: actions/upload-artifact@v3
+        with:
+          name: lcov
+          path: ./lcov.info
+      # That's it
+      - run: echo "Finished testing"

.github/workflows/CompatHelper.yml

@@ -0,0 +1,26 @@
+name: CompatHelper
+
+on:
+  schedule:
+    - cron: 0 0 * * *
+  issues:
+    types: [opened, reopened]
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        julia-version: [1]
+        julia-arch: [x86]
+        os: [ubuntu-latest]
+    steps:
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: ${{ matrix.julia-version }}
+      - name: Pkg.add("CompatHelper")
+        run: julia -e 'using Pkg; Pkg.add("CompatHelper")'
+      - name: CompatHelper.main()
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: julia -e 'using CompatHelper; CompatHelper.main(; subdirs=["", "docs", "examples", "test"])'

.github/workflows/DocPreviewCleanup.yml

@@ -0,0 +1,32 @@
+name: Doc Preview Cleanup
+
+on:
+  pull_request:
+    types: [closed]
+
+jobs:
+  doc-preview-cleanup:
+    # Do not run on forks to avoid authorization errors
+    # Source: https://github.community/t/have-github-action-only-run-on-master-repo-and-not-on-forks/140840/18
+    if: github.repository_owner == 'SKopecz'
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout gh-pages branch
+        uses: actions/checkout@v4
+        with:
+          ref: gh-pages
+
+      - name: Delete preview and history
+        shell: bash
+        run: |
+            git config user.name "Documenter.jl"
+            git config user.email "[email protected]"
+            git rm -rf --ignore-unmatch "previews/PR$PRNUM"
+            git commit -m "delete preview" --allow-empty
+            git branch gh-pages-new $(echo "delete history" | git commit-tree HEAD^{tree})
+        env:
+            PRNUM: ${{ github.event.number }}
+
+      - name: Push changes
+        run: |
+            git push --force origin gh-pages-new:gh-pages

.github/workflows/SpellCheck.yml

@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request, workflow_dispatch]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v4
+      - name: Check spelling
+        uses: crate-ci/[email protected]

.github/workflows/TagBot.yml

@@ -0,0 +1,15 @@
+name: TagBot
+on:
+  issue_comment:
+    types:
+      - created
+  workflow_dispatch:
+jobs:
+  TagBot:
+    if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
+    runs-on: ubuntu-latest
+    steps:
+      - uses: JuliaRegistries/TagBot@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          ssh: ${{ secrets.DOCUMENTER_KEY }}

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2023 Stefan Kopecz
+Copyright (c) 2023--present Stefan Kopecz, Hendrik Ranocha, and contributors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

Project.toml

@@ -1,9 +1,27 @@
+name = "PositiveIntegrators"
+uuid = "d1b20bf0-b083-4985-a874-dc5121669aa5"
+authors = ["Stefan Kopecz, Hendrik Ranocha, and contributors"]
+version = "0.1.0"
+
 [deps]
-BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
+FastBroadcast = "7034ab61-46d4-4ed7-9d0f-46aef9175898"
 Kwonly = "18d08c8c-0732-55ee-a446-91a51d7b4206"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
+MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-PrettyTables = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
+Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
+SimpleUnPack = "ce78b400-467f-4804-87d8-8f486da07d0a"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+
+[compat]
+FastBroadcast = "0.2"
+julia = "1.8"
+Kwonly = "0.1"
+LinearSolve = "2"
+MuladdMacro = "0.2"
+OrdinaryDiffEq = "6"
+Reexport = "1"
+SciMLBase = "2"
+SimpleUnPack = "1"

docs/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+
+[compat]
+Documenter = "1"

examples/01_example_proddest.jl

@@ -1,9 +1,9 @@
-# A production-destruction sytem (PDS) has the form 
+# A production-destruction system (PDS) has the form
 #   uᵢ'(t) = ∑ⱼ(pᵢⱼ(t) - dᵢⱼ(t))
-# with pᵢⱼ(t), dᵢⱼ ≥ 0. 
+# with pᵢⱼ(t), dᵢⱼ ≥ 0.
 #
-# Here, pᵢⱼ is a production term, i.e. a term with positive sign, in the ith equation with a corresponding 
-# destruction term, i.e. the same term with negative sign, in the jth equation. Positive terms of the ith equation 
+# Here, pᵢⱼ is a production term, i.e. a term with positive sign, in the ith equation with a corresponding
+# destruction term, i.e. the same term with negative sign, in the jth equation. Positive terms of the ith equation
 # without negative counterpart are gathered in pᵢᵢ. Similarly, dᵢᵢ contains the absolute values of the negative
 # terms without positive counterparts.
 #
@@ -13,19 +13,28 @@
 # Similarly, p₁₂ = 2 u₂ = d₂₁. Furthermore, we have p₁₁ = 3 u₁, d₁₁ = 0 and p₂₂ = 0, d₂₂ = 4 u₂.
 # Note that this representation is not unique!
 #
-# The PDS is conservative if dᵢⱼ == pⱼᵢ and pᵢᵢ == dᵢᵢ == 0. In this case only the matrix (pᵢⱼ) needs to be stored, 
-# because (dᵢⱼ) is the transpose of (pᵢⱼ). Furthermore, all diagonal elements of (pᵢⱼ) are zero. 
+# The PDS is conservative if dᵢⱼ == pⱼᵢ and pᵢᵢ == dᵢᵢ == 0. In this case only the matrix (pᵢⱼ) needs to be stored,
+# because (dᵢⱼ) is the transpose of (pᵢⱼ). Furthermore, all diagonal elements of (pᵢⱼ) are zero.
 # If the PDS is not conservative, we can store the additional production terms pᵢᵢ on the diagonal of (pᵢⱼ) and need to
 # store an additional vector for dᵢᵢ.
 #
 # Modified Patankar-Runge-Kutta (MPRK) schemes are based on the production-destruction representation of an ODE.
 #
-# In OrdinaryDiffEq an ODE u' = f(t,u) with t in tspan and parameters p is represented as an ODEProblem(f,u,tspan,p). To 
-# respresent f as a PDS the new problem type ProdDestODEProblem(P,D,u,tspan,p) was added. Here P is the matrix (pᵢⱼ) 
+# In OrdinaryDiffEq an ODE u' = f(t,u) with t in tspan and parameters p is represented as an ODEProblem(f,u,tspan,p). To
+# represent f as a PDS the new problem type ProdDestODEProblem(P,D,u,tspan,p) was added. Here P is the matrix (pᵢⱼ)
 # from above, with possibly nonzero diagonal elements. D is the vector to store dᵢᵢ.
 
+# Install packages
+import Pkg
+Pkg.activate(@__DIR__)
+Pkg.develop(path = dirname(@__DIR__))
+Pkg.instantiate()
+
 # load new problem type for production-destruction systems
-include("../src/proddest.jl") 
+using PositiveIntegrators
+
+using OrdinaryDiffEq
+using SparseArrays
 
 ### Example 1: Linear model problem ######################################################################################
 # This is an example of a conservative PDS
@@ -35,12 +44,12 @@ include("../src/proddest.jl")
 # Standard: f(t,u) = [-5 1; 5 -1]*u
 #
 # PDS: P = [0 u₂; 5 u₁ 0], D = [0; 0]
-# 
-# We implent four variantions (in-place and out-of-place for both standard and PDS) of this ODE system and check that we 
-# obtain equivalent solutions with a standard solver of OrdinaryDiffEq.jl. 
+#
+# We implement four variations (in-place and out-of-place for both standard and PDS) of this ODE system and check that we
+# obtain equivalent solutions with a standard solver of OrdinaryDiffEq.jl.
 
 
-# inital values
+# initial values
 u0 = [0.9, 0.1]
 # time domain
 tspan = (0.0, 2.0)
@@ -87,7 +96,7 @@ sol_linmod_PDS_ip = solve(linmod_PDS_ip,Tsit5())
 @assert sol_linmod_f_op.u ≈ sol_linmod_f_ip.u ≈ sol_linmod_PDS_op.u ≈ sol_linmod_PDS_ip.u
 
 # check that we really do not use too many additional allocations for in-place implementations
-alloc1 = @allocated(solve(linmod_f_ip, Tsit5())) 
+alloc1 = @allocated(solve(linmod_f_ip, Tsit5()))
 alloc2 = @allocated(solve(linmod_PDS_ip, Tsit5()))
 @assert 0.95 < alloc1/alloc2 < 1.05
 
@@ -100,11 +109,11 @@ alloc2 = @allocated(solve(linmod_PDS_ip, Tsit5()))
 # Standard: f(t,u) = [u₁ - u₁ u₂; u₁ u₂ - u₂]
 #
 # PDS: P = [u₁ 0; u₁ u₂ 0], D = [0; u₂]
-# 
-# We implent four variantions (in-place and out-of-place for both standard and PDS) of this ODE system and check that we 
-# obtain equivalent solutions with a standard solver of OrdinaryDiffEq.jl. 
+#
+# We implement four variations (in-place and out-of-place for both standard and PDS) of this ODE system and check that we
+# obtain equivalent solutions with a standard solver of OrdinaryDiffEq.jl.
 
-# inital values
+# initial values
 u0 = [0.9, 0.1]
 # time domain
 tspan = (0.0, 20.0)
@@ -151,20 +160,20 @@ sol_lotvol_PDS_ip = solve(lotvol_PDS_ip,Tsit5())
 @assert sol_lotvol_f_op.u ≈ sol_lotvol_f_ip.u ≈ sol_lotvol_PDS_op.u ≈ sol_lotvol_PDS_ip.u
 
 # check that we really do not use too many additional allocations for in-place implementations
-alloc1 = @allocated(solve(lotvol_f_ip, Tsit5())) 
+alloc1 = @allocated(solve(lotvol_f_ip, Tsit5()))
 alloc2 = @allocated(solve(lotvol_PDS_ip, Tsit5()))
 @assert 0.95 < alloc1/alloc2 < 1.05
 
 ##########################################################################################################################
 ### Example 3: Linear advection discretized with finite differences and upwind, periodic boundary conditions #############
-# This is an example of a large conservative PDS, which requires the use of sparese matrices. 
-# 
-# We implent the in-place versions for the standard rhs and the PDS representation of this ODE system. In addition, we
-# compare the efficiency of dense and sparse matrices for the PDS version. 
+# This is an example of a large conservative PDS, which requires the use of sparese matrices.
+#
+# We implement the in-place versions for the standard rhs and the PDS representation of this ODE system. In addition, we
+# compare the efficiency of dense and sparse matrices for the PDS version.
 
 # number of nodes
 N = 1000;
-# inital data
+# initial data
 u0 = sin.(π*LinRange(0.0,1.0,N+1))[2:end]
 # time domain
 tspan = (0.0, 1.0)