Merge branch 'master' into compathelper/new_version/2024-10-15-00-11-…

…26-498-00928743823

.github/workflows/Documentation.yml

@@ -1,5 +1,4 @@
 name: Documentation
-# Modelled from DiffEqDocs
 
 on:
   push:
@@ -30,6 +29,7 @@ jobs:
         run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
       - name: "Build and deploy"
         env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
-          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
-        run: julia --project=docs/ docs/make.jl
+          DOCUMENTER_KEY_ASTROAUTOMATA: ${{ secrets.DOCUMENTER_KEY }}
+          DOCUMENTER_KEY_CAM: ${{ secrets.DAMTP_DEPLOY_KEY }}
+        run: |
+          julia --project=docs/ docs/make.jl

.github/workflows/check-format.yml

@@ -24,12 +24,8 @@ jobs:
       - name: "Cache dependencies"
         uses: julia-actions/cache@v2
       - name: Install JuliaFormatter and format
-        # This will use the latest version by default but you can set the version like so:
-        #
-        # julia  -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter", version="0.13.0"))'
         run: |
-          julia  -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter"))'
-          julia  -e 'using JuliaFormatter; format(".", verbose=true)'
+          julia --startup-file=no -e 'using Pkg; pkg"activate --temp"; pkg"add [email protected]"; using JuliaFormatter; format("."; verbose=true)'
       - name: "Format check"
         run: |
           julia -e '

.gitignore

@@ -1,14 +1,16 @@
 .dataset*.jl
 .hyperparams*.jl
+outputs
 *.csv
+*.bak
 *.bkup
 performance*txt
 *.out
 trials*
 **/__pycache__
 build
 dist
-Manifest.toml
+Manifest*.toml
 *.cov
 .coveralls.yml
 **/*tmp*.jl

Project.toml

@@ -1,7 +1,7 @@
 name = "SymbolicRegression"
 uuid = "8254be44-1295-4e6a-a16d-46603ac705cb"
 authors = ["MilesCranmer <[email protected]>"]
-version = "1.0.0-beta1"
+version = "1.0.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -14,18 +14,20 @@ Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 DynamicExpressions = "a40a106e-89c9-4ca8-8020-a735e8728b6b"
 DynamicQuantities = "06fc5a27-2a28-4c7c-a15d-362465fb6821"
 LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255"
+Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 LossFunctions = "30fc2ffe-d236-52d8-8643-a9d8f7c094a7"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-ProgressBars = "49802e3a-d2f1-5c88-81d8-b72133a6f568"
+ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
+StyledStrings = "f489334b-da3d-4c2e-b8f0-e476e12c162b"
 TOML = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
 
 [weakdeps]
@@ -40,34 +42,32 @@ SymbolicRegressionSymbolicUtilsExt = "SymbolicUtils"
 
 [compat]
 ADTypes = "^1.4.0"
-Compat = "^4.2"
-ConstructionBase = "<1.5.7, 1.5.8 - 1"
+Compat = "^4.16"
+ConstructionBase = "1.0.0 - 1.5.6"
+ConstructionBase = "1.0.0 - 1.5.7, 1.5.8 - 1"
 Dates = "1"
 DifferentiationInterface = "0.5, 0.6"
-DispatchDoctor = "0.4"
+DispatchDoctor = "^0.4.17"
 Distributed = "<0.0.1, 1"
-DynamicExpressions = "1"
+DynamicExpressions = "1.5.0"
 DynamicQuantities = "1"
-Enzyme = "0.12"
+Enzyme = "0.12, 0.13"
 JSON3 = "1"
 LineSearches = "7"
+Logging = "1"
 LossFunctions = "0.10, 0.11"
 MLJModelInterface = "~1.5, ~1.6, ~1.7, ~1.8, ~1.9, ~1.10, ~1.11"
 MacroTools = "0.4, 0.5"
-Optim = "~1.8, ~1.9"
+Optim = "~1.8, ~1.9, ~1.10"
 Pkg = "<0.0.1, 1"
 PrecompileTools = "1"
 Printf = "<0.0.1, 1"
-ProgressBars = "~1.4, ~1.5"
+ProgressMeter = "1.10"
 Random = "<0.0.1, 1"
 Reexport = "1"
 SpecialFunctions = "0.10.1, 1, 2"
 StatsBase = "0.33, 0.34"
+StyledStrings = "1"
 SymbolicUtils = "0.19, ^1.0.5, 2, 3"
 TOML = "<0.0.1, 1"
 julia = "1.10"
-
-[extras]
-Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
-JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
-SymbolicUtils = "d1185830-fcd6-423d-90d6-eec64667417b"

README.md

@@ -7,7 +7,7 @@ https://github.com/MilesCranmer/SymbolicRegression.jl/assets/7593028/f5b68f1f-98
 
 | Latest release | Documentation | Forums | Paper |
 | :---: | :---: | :---: | :---: |
-| [![version](https://juliahub.com/docs/SymbolicRegression/version.svg)](https://juliahub.com/ui/Packages/SymbolicRegression/X2eIS) | [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://astroautomata.com/SymbolicRegression.jl/dev/) | [![Discussions](https://img.shields.io/badge/discussions-github-informational)](https://github.com/MilesCranmer/PySR/discussions) | [![Paper](https://img.shields.io/badge/arXiv-2305.01582-b31b1b)](https://arxiv.org/abs/2305.01582) |
+| [![version](https://juliahub.com/docs/SymbolicRegression/version.svg)](https://juliahub.com/ui/Packages/SymbolicRegression/X2eIS) | [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://ai.damtp.cam.ac.uk/symbolicregression/dev/) | [![Discussions](https://img.shields.io/badge/discussions-github-informational)](https://github.com/MilesCranmer/PySR/discussions) | [![Paper](https://img.shields.io/badge/arXiv-2305.01582-b31b1b)](https://arxiv.org/abs/2305.01582) |
 
 | Build status | Coverage |
 | :---: | :---: |
@@ -110,7 +110,7 @@ where here we choose to evaluate the second equation.
 
 For fitting multiple outputs, one can use `MultitargetSRRegressor`
 (and pass an array of indices to `idx` in `predict` for selecting specific equations).
-For a full list of options available to each regressor, see the [API page](https://astroautomata.com/SymbolicRegression.jl/dev/api/).
+For a full list of options available to each regressor, see the [API page](https://ai.damtp.cam.ac.uk/symbolicregression/dev/api/).
 
 ### Low-Level Interface
 
@@ -495,4 +495,4 @@ done | vims -l 'f a--> ' | sort
 
 ## Search options
 
-See https://astroautomata.com/SymbolicRegression.jl/stable/api/#Options
+See https://ai.damtp.cam.ac.uk/symbolicregression/stable/api/#Options

docs/Project.toml

@@ -2,7 +2,10 @@
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DynamicExpressions = "a40a106e-89c9-4ca8-8020-a735e8728b6b"
 Gumbo = "708ec375-b3d6-5a57-a7ce-8257bf98657a"
+Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
+MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 SymbolicUtils = "d1185830-fcd6-423d-90d6-eec64667417b"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 Documenter = "0.27"

docs/make.jl

@@ -17,12 +17,9 @@ using SymbolicRegression:
     @extend_operators
 using DynamicExpressions
 
-DocMeta.setdocmeta!(
-    SymbolicRegression, :DocTestSetup, :(using LossFunctions); recursive=true
-)
-DocMeta.setdocmeta!(
-    SymbolicRegression, :DocTestSetup, :(using DynamicExpressions); recursive=true
-)
+include("utils.jl")
+process_literate_blocks("test")
+process_literate_blocks("examples")
 
 readme = open(dirname(@__FILE__) * "/../README.md") do io
     read(io, String)
@@ -88,19 +85,29 @@ open(dirname(@__FILE__) * "/src/index.md", "w") do io
     write(io, index_base)
 end
 
+DocMeta.setdocmeta!(
+    SymbolicRegression,
+    :DocTestSetup,
+    :(using LossFunctions, DynamicExpressions);
+    recursive=true,
+)
 makedocs(;
     sitename="SymbolicRegression.jl",
     authors="Miles Cranmer",
     doctest=true,
     strict=:doctest,
     clean=true,
     format=Documenter.HTML(;
-        canonical="https://astroautomata.com/SymbolicRegression.jl/stable"
+        canonical="https://ai.damtp.cam.ac.uk/symbolicregression/stable"
     ),
     pages=[
         "Contents" => "index_base.md",
         "Home" => "index.md",
-        "Examples" => "examples.md",
+        "Examples" => [
+            "Short Examples" => "examples.md",
+            "Template Expressions" => "examples/template_expression.md",
+            "Parameterized Expressions" => "examples/parameterized_function.md",
+        ],
         "API" => "api.md",
         "Losses" => "losses.md",
         "Types" => "types.md",
@@ -133,9 +140,16 @@ apply_to_a_href!(html.root) do element
     element.attributes["href"] = "#LossFunctions." * element.children[1].text
 end
 
-# Then, we write the new html to the file:
+# Then, we write the new html to the file, only if it has changed:
 open("docs/build/losses/index.html", "w") do io
     write(io, string(html))
 end
 
-deploydocs(; repo="github.com/MilesCranmer/SymbolicRegression.jl.git")
+if !haskey(ENV, "JL_LIVERELOAD")
+    ENV["DOCUMENTER_KEY"] = get(ENV, "DOCUMENTER_KEY_ASTROAUTOMATA", "")
+    deploydocs(; repo="github.com/MilesCranmer/SymbolicRegression.jl.git")
+
+    ENV["DOCUMENTER_KEY"] = get(ENV, "DOCUMENTER_KEY_CAM", "")
+    ENV["GITHUB_REPOSITORY"] = "ai-damtp-cam-ac-uk/symbolicregression.git"
+    deploydocs(; repo="github.com/ai-damtp-cam-ac-uk/symbolicregression.git")
+end

docs/src/api.md

@@ -60,3 +60,24 @@ Note that use of this function requires `SymbolicUtils.jl` to be installed and l
 ```@docs
 calculate_pareto_frontier
 ```
+
+## Logging
+
+```@docs
+SRLogger
+```
+
+The `SRLogger` allows you to track the progress of symbolic regression searches.
+It can wrap any `AbstractLogger` that implements the Julia logging interface,
+such as from TensorBoardLogger.jl or Wandb.jl.
+
+```julia
+using TensorBoardLogger
+
+logger = SRLogger(TBLogger("logs/run"), log_interval=2)
+
+model = SRRegressor(;
+    logger=logger,
+    kws...
+)
+```

docs/src/customization.md

@@ -36,19 +36,30 @@ You can create your own expression types by defining a new type that extends `Ab
 
 ```@docs
 AbstractExpression
-ExpressionInterface
 ```
 
 The interface is fairly flexible, and permits you define specific functional forms,
 extra parameters, etc. See the documentation of DynamicExpressions.jl for more details on what
-methods you need to implement. Then, for SymbolicRegression.jl, you would
+methods you need to implement. You can test the implementation of a given interface by using
+`ExpressionInterface` which makes use of `Interfaces.jl`:
+
+```@docs
+ExpressionInterface
+```
+
+Then, for SymbolicRegression.jl, you would
 pass `expression_type` to the `Options` constructor, as well as any
 `expression_options` you need (as a `NamedTuple`).
 
 If needed, you may need to overload `SymbolicRegression.ExpressionBuilder.extra_init_params` in
 case your expression needs additional parameters. See the method for `ParametricExpression`
 as an example.
 
+You can look at the files `src/ParametricExpression.jl` and `src/TemplateExpression.jl`
+for more examples of custom expression types, though note that `ParametricExpression` itself
+is defined in DynamicExpressions.jl, while that file just overloads some methods for
+SymbolicRegression.jl.
+
 ## Other Customizations
 
 Other internal abstract types include the following: