Merge pull request #108 from ErikQQY/qqy/better_bench

Add better benchmarks

.github/workflows/Benchmark.yml

@@ -0,0 +1,55 @@
+name: Benchmarks
+on:
+  push:
+    branches:
+      - master
+  pull_request:
+    branches:
+      - master
+
+concurrency:
+  # Skip intermediate builds: always.
+  # Cancel intermediate builds: only if it is a pull request build.
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
+jobs:
+  benchmark:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: '1'
+          arch: x64
+      - uses: actions/cache@v4
+        env:
+          cache-name: cache-artifacts
+        with:
+          path: ~/.julia/artifacts
+          key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
+          restore-keys: |
+            ${{ runner.os }}-test-${{ env.cache-name }}-
+            ${{ runner.os }}-test-
+            ${{ runner.os }}-
+      - name: Run benchmark
+        run: |
+          cd bench
+          julia --project --color=yes -e '
+            using Pkg;
+            Pkg.develop(PackageSpec(path=joinpath(pwd(), "..")));
+            Pkg.instantiate();
+            include("runbenchmarks.jl")'
+      - name: Parse & Upload Benchmark Results
+        uses: benchmark-action/github-action-benchmark@v1
+        with:
+          name: Benchmark Results
+          tool: 'julia'
+          output-file-path: bench/benchmark_results.json
+          summary-always: true
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          comment-always: true
+          alert-threshold: "200%"
+          fail-on-alert: true
+          benchmark-data-dir-path: benchmarks
+          auto-push: ${{ github.event_name != 'pull_request' }}

bench/.JuliaFormatter.toml

@@ -0,0 +1,9 @@
+style = "sciml"
+whitespace_in_kwargs = false
+always_use_return = true
+margin = 92
+indent = 4
+format_docstrings = true
+separate_kwargs_with_semicolon = true
+always_for_in = true
+annotate_untyped_fields_with_any = false

bench/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+FractionalDiffEq = "c7492dd8-6170-483b-af64-cefb6c377d9a"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"

bench/README.md

@@ -0,0 +1,10 @@
+# FractionalDiffEq.jl Continuous Benchmarking
+
+Currently we use the BenchmarkTools.jl package to benchmark the performance of FractionalDiffEq.jl over time.
+
+This is built using https://github.com/benchmark-action/github-action-benchmark/ so it
+allows for nice visualizations of the benchmark results in github pages and produces warnings on PRs if the benchmarks regress.
+
+## Current Benchmarks
+
+1. Small VGG Net for CIFAR-10

bench/runbenchmarks.jl

@@ -0,0 +1,25 @@
+using BenchmarkTools: BenchmarkTools, BenchmarkGroup, @btime, @benchmarkable
+using FractionalDiffEq
+using Statistics: median
+
+const SUITE = BenchmarkGroup()
+
+α = [0.8, 0.8]
+u0 = [0.2, 0.03]
+
+function Brusselator!(du, u, p, t)
+    a, μ = 1, 4
+    du[1] = a-(μ+1)*u[1]+(u[1])^2*u[2]
+    du[2] = μ*u[1]-(u[1])^2*u[1]
+end
+
+prob = FODEProblem(Brusselator!, α, u0, (0, 20))
+
+SUITE["FLMM"]["BDF"] = @benchmarkable solve(prob, BDF(), dt=0.01)
+SUITE["FLMM"]["Trapezoid"] = @benchmarkable solve(prob, Trapezoid(), dt=0.01)
+SUITE["FLMM"]["NewtonGregory"] = @benchmarkable solve(prob, NewtonGregory(), dt=0.01)
+
+BenchmarkTools.tune!(SUITE)
+results = BenchmarkTools.run(SUITE; verbose=true)
+
+BenchmarkTools.save(joinpath(@__DIR__, "benchmark_results.json"), median(results))

docs/src/get_started.md

@@ -2,7 +2,7 @@
 
 We would use a simple example -- [Relaxation Oscillation Process](https://encyclopediaofmath.org/wiki/Relaxation_oscillation) to show you how to use FractionalDiffEq.jl to solve fractional differential equations.🙂
 
-The mathematical model of the fractional order Relaxation Oscillation can be abstracted as an IVP:
+The mathematical model of the fractional order relaxation oscillation can be abstracted as an IVP:
 
 ```math
 D^{1.8}y(t)+y(t)=1,\ (t>0)
@@ -39,7 +39,7 @@ To provide users with a simple way to solve fractional differential equations, w
 
 ## Step 1: Defining a Problem
 
-First, we need to specify the problem we want to solve. Just by passing the parameters —— describing function, orders, initial condition and time span:
+First, we need to specify the problem we want to solve. Just by passing the parameters —— describing function, orders, initial condition and time span to construct a fractional ordinary differential equation problem:
 
 ```julia
 using FractionalDiffEq
@@ -52,13 +52,13 @@ The ```FODEProblem``` is a class of fractional differential equations, describin
 
 ## Step 2: Solving a Problem
 
-After defining a problem, we can solve it by calling the ```solve``` function:
+After defining a problem, we can solve it by choosing a numerical algorithm and calling the ```solve``` function:
 
 ```julia
 sol = solve(prob, Alg(), dt=0.01)
 ```
 
-Note that there are different algorithms for differential fractional differential equations, such as FODE, FDDE and DODE, we need to choose a suitable algorithm for a specific problem. For all the algorithms, please refer to [the algorithms documentation](@ref algorithms).
+Note that there are different algorithms for different fractional differential equations, such as FODE, FDDE and DODE, we need to choose a suitable algorithm for a specific problem. For all the algorithms, please refer to [the algorithms documentation](@ref algorithms).
 
 ## Step 3: Analyzing the Solution
 

src/FractionalDiffEq.jl

@@ -39,18 +39,18 @@ include("fode/explicit_pi.jl")
 include("fode/implicit_pi_rectangle.jl")
 include("fode/implicit_pi_trapzoid.jl")
 include("fode/grunwald_letnikov.jl")
-include("fode/NonLinear.jl")
+include("fode/nonlinearalg.jl")
 include("fode/newton_polynomials.jl")
 include("fode/atangana_seda.jl")
 
 # System of fractal-fractional ordinary differential equations
 include("ffode/atangana_seda.jl")
 
 # Fractional delay differential equations
-include("delay/DelayPECE.jl")
+include("delay/pece.jl")
 include("delay/product_integral.jl")
 include("delay/matrix_form.jl")
-include("delay/DelayABM.jl")
+include("delay/abm.jl")
 
 # Distributed order differential equations
 include("dode/utils.jl")