Minor release with the light interface (#439)

JuliaAI · Feb 12, 2020 · 3573d8a · tlienart · Feb 12, 2020 · 3573d8a
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diff --git a/Project.toml b/Project.toml
@@ -1,39 +1,34 @@
 name = "MLJ"
 uuid = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "0.8.0"
+version = "0.9.0"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
 ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
-Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
-DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
-InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJModels = "d491faf4-2d78-11e9-2867-c94bc002c0b7"
+MLJScientificTypes = "2e2323e0-db8b-457b-ae0d-bdfb3bc63afd"
 MLJTuning = "03970b2e-30c4-11ea-3135-d1576263f10f"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-ScientificTypes = "321657f4-b219-11e9-178b-2701a2544e81"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
 
 [compat]
 CategoricalArrays = "^0.7"
 ComputationalResources = "^0.3"
-Distributions = "^0.21"
-DocStringExtensions = "^0.8"
-MLJBase = "^0.10"
-MLJTuning = "^0.1.1"
-MLJModels = "^0.7"
+Distributions = "^0.21,^0.22"
+MLJBase = "^0.11"
+MLJModels = "^0.8"
+MLJScientificTypes = "^0.1"
+MLJTuning = "^0.1"
 ProgressMeter = "^1.1"
-ScientificTypes = "^0.5.1"
 StatsBase = "^0.32"
 Tables = "^0.2"
 julia = "1"

diff --git a/README.md b/README.md
@@ -95,7 +95,7 @@ The MLJ universe is made out of several repositories some of which can be used i
 
 * (⟂) [MLJBase.jl](https://github.com/alan-turing-institute/MLJBase.jl) offers essential tools to load and interpret data, describe ML models and use metrics; it is the repository you should interface with if you wish to make your package accessible via MLJ,
 * [MLJ.jl](https://github.com/alan-turing-institute/MLJ.jl) offers tools to compose, tune and evaluate models,
-* [MLJModels.jl](https://github.com/alan-turing-institute/MLJModels.jl) contains interfaces to a number of important model-providing packages such as,  [DecisionTree.jl](https://github.com/bensadeghi/DecisionTree.jl), [ScikitLearn.jl](https://github.com/bensadeghi/ScikitLearn.jl) or [XGBoost.jl](https://github.com/dmlc/XGBoost.jl) as well as a few built-in transformations (one hot encoding, standardisation, ...), it also hosts the *model registry* which keeps track of all models accessible via MLJ,
+* [MLJModels.jl](https://github.com/alan-turing-institute/MLJModels.jl) contains interfaces to a number of important model-providing packages such as,  [DecisionTree.jl](https://github.com/bensadeghi/DecisionTree.jl), [ScikitLearn.jl](https://github.com/cstjean/ScikitLearn.jl) or [XGBoost.jl](https://github.com/dmlc/XGBoost.jl) as well as a few built-in transformations (one hot encoding, standardisation, ...), it also hosts the *model registry* which keeps track of all models accessible via MLJ,
 * (⟂) [ScientificTypes.jl](https://github.com/alan-turing-institute/ScientificTypes.jl) a lightweight package to help MLJ articulate it's conventions about how different types of data (`2.71`, `"male"`, `CategoricalArray{Int}`, etc ) should be *interpreted* by models (`Continuous`, `Textual`, `AbstractArray{Multiclass}`, etc). 
 * (⟂) [MLJLinearModels.jl](https://github.com/alan-turing-institute/MLJLinearModels.jl) an experimental package for a wide range of penalised linear models such as Lasso, Elastic-Net, Robust regression, LAD regression, etc.
 * [MLJFlux.jl](https://github.com/alan-turing-institute/MLJFlux.jl) an experimental package to use Flux within MLJ.

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -6,23 +6,24 @@ DecisionTree = "7806a523-6efd-50cb-b5f6-3fa6f1930dbb"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
-Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 LossFunctions = "30fc2ffe-d236-52d8-8643-a9d8f7c094a7"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
+MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
+MLJModels = "d491faf4-2d78-11e9-2867-c94bc002c0b7"
+MLJScientificTypes = "2e2323e0-db8b-457b-ae0d-bdfb3bc63afd"
 MLJTuning = "03970b2e-30c4-11ea-3135-d1576263f10f"
 Missings = "e1d29d7a-bbdc-5cf2-9ac0-f12de2c33e28"
 MultivariateStats = "6f286f6a-111f-5878-ab1e-185364afe411"
 NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-ScientificTypes = "321657f4-b219-11e9-178b-2701a2544e81"
 TypedTables = "9d95f2ec-7b3d-5a63-8d20-e2491e220bb9"
 
 [compat]
-DecisionTree = "0.8, 0.9.1"
-Documenter = "^0.22,0.23"
-MLJBase = "^0.10"
-ScientificTypes = "^0.5"
+Documenter = "^0.24"
+MLJBase = "^0.11"
+MLJModelInterface = "^0.1"
+MLJModels = "^0.8"
+MLJScientificTypes = "^0.1"
+MLJTuning = "^0.1"
 julia = "1.2"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,50 +1,58 @@
 if Base.HOME_PROJECT[] !== nothing
     Base.HOME_PROJECT[] = abspath(Base.HOME_PROJECT[])
 end
+
 using Pkg
 using Documenter
 using MLJ
-using MLJBase
-using MLJTuning
-using MLJModels
-using ScientificTypes
+import MLJBase
+import MLJTuning
+import MLJModels
+import MLJScientificTypes
+import MLJModelInterface
+using CategoricalArrays # avoid types like CategoricalArrays.Categorica
+using LossFunctions
+
+const MMI = MLJModelInterface
 
 # using Literate
 # Literate.markdown("common_mlj_workflows.jl", ".",
 #                   codefence = "```@example workflows" => "```")
 
-pages = Any["Getting Started"=>"index.md",
-            "Common MLJ Workflows" => "common_mlj_workflows.md",
-            "Model Search" => "model_search.md",
-            "Machines" => "machines.md",
-            "Evaluating Model Performance"=>"evaluating_model_performance.md",
-            "Performance Measures"=> "performance_measures.md",
-            "Tuning Models" => "tuning_models.md",
-            "Learning Curves" => "learning_curves.md",
-            "Built-in Transformers" => "built_in_transformers.md",
-            "Composing Models" => "composing_models.md",
-            "Homogeneous Ensembles" => "homogeneous_ensembles.md",
-            "Simple User Defined Models" => "simple_user_defined_models.md",
-            "Adding Models for General Use" => "adding_models_for_general_use.md",
-            "Benchmarking" => "benchmarking.md",
-            "Internals"=>"internals.md",
-            "Glossary"=>"glossary.md",
-            "API"=>"api.md",
-            "MLJ Cheatsheet" => "mlj_cheatsheet.md",
-            "MLJ News"=>"NEWS.md",
-            "FAQ" => "frequently_asked_questions.md",
-            "Julia BlogPost"=>"julia_blogpost.md",
-            "Acceleration and Parallelism"=>"acceleration_and_parallelism.md"]
+pages = [
+    "Getting Started" => "index.md",
+    "Common MLJ Workflows" => "common_mlj_workflows.md",
+    "Model Search" => "model_search.md",
+    "Machines" => "machines.md",
+    "Evaluating Model Performance" => "evaluating_model_performance.md",
+    "Performance Measures" => "performance_measures.md",
+    "Tuning Models" => "tuning_models.md",
+    "Learning Curves" => "learning_curves.md",
+    "Built-in Transformers" => "built_in_transformers.md",
+    "Composing Models" => "composing_models.md",
+    "Homogeneous Ensembles" => "homogeneous_ensembles.md",
+    "Simple User Defined Models" => "simple_user_defined_models.md",
+    "Adding Models for General Use" => "adding_models_for_general_use.md",
+    "Benchmarking" => "benchmarking.md",
+    "Internals" => "internals.md",
+    "Glossary" => "glossary.md",
+    # "API" => "api.md", # NOTE: commented as currently empty
+    "MLJ Cheatsheet" => "mlj_cheatsheet.md",
+    "MLJ News" => "NEWS.md",
+    "FAQ" => "frequently_asked_questions.md",
+    "Julia BlogPost" => "julia_blogpost.md",
+    "Acceleration and Parallelism" => "acceleration_and_parallelism.md"
+    ]
 
 for p in pages
     println(first(p))
 end
 
 makedocs(
     sitename = "MLJ",
-    format = Documenter.HTML(),
-    modules = [MLJ, MLJBase, MLJTuning, MLJModels, ScientificTypes],
-    pages=pages)
+    format   = Documenter.HTML(),
+    modules  = [MLJ, MLJBase, MLJTuning, MLJModels, MLJScientificTypes, MLJModelInterface],
+    pages    = pages)
 
 # By default Documenter does not deploy docs just for PR
 # this causes issues with how we're doing things and ends

diff --git a/docs/src/ workflows_learning_curves.png → docs/src/_old/ workflows_learning_curves.png b/docs/src/ workflows_learning_curves.png → docs/src/_old/ workflows_learning_curves.png
diff --git a/docs/src/0.jpg → docs/src/_old/0.jpg b/docs/src/0.jpg → docs/src/_old/0.jpg
diff --git a/docs/src/0_small.jpg → docs/src/_old/0_small.jpg b/docs/src/0_small.jpg → docs/src/_old/0_small.jpg
diff --git a/docs/src/ATI_logo_black.png → docs/src/_old/ATI_logo_black.png b/docs/src/ATI_logo_black.png → docs/src/_old/ATI_logo_black.png
diff --git a/docs/src/common_mlj_workflows.ipynb → docs/src/_old/common_mlj_workflows.ipynb b/docs/src/common_mlj_workflows.ipynb → docs/src/_old/common_mlj_workflows.ipynb
diff --git a/docs/src/scitypes.xml → docs/src/_old/scitypes.xml b/docs/src/scitypes.xml → docs/src/_old/scitypes.xml
diff --git a/docs/src/scitypes_original.png → docs/src/_old/scitypes_original.png b/docs/src/scitypes_original.png → docs/src/_old/scitypes_original.png
diff --git a/docs/src/tiny_demo.ipynb → docs/src/_old/tiny_demo.ipynb b/docs/src/tiny_demo.ipynb → docs/src/_old/tiny_demo.ipynb
diff --git a/docs/src/tour.ipynb → docs/src/_old/tour.ipynb b/docs/src/tour.ipynb → docs/src/_old/tour.ipynb
diff --git a/docs/src/two_model_stack.dia → docs/src/_old/two_model_stack.dia b/docs/src/two_model_stack.dia → docs/src/_old/two_model_stack.dia
diff --git a/docs/src/two_parameter_tuning_plot.png → docs/src/_old/two_parameter_tuning_plot.png b/docs/src/two_parameter_tuning_plot.png → docs/src/_old/two_parameter_tuning_plot.png
diff --git a/docs/src/workflows_learning_curves_large.png → .../_old/workflows_learning_curves_large.png b/docs/src/workflows_learning_curves_large.png → .../_old/workflows_learning_curves_large.png
diff --git a/docs/src/workflows_tuning_plot_large.png → .../src/_old/workflows_tuning_plot_large.png b/docs/src/workflows_tuning_plot_large.png → .../src/_old/workflows_tuning_plot_large.png
diff --git a/docs/src/wrapped_ridge.dia → docs/src/_old/wrapped_ridge.dia b/docs/src/wrapped_ridge.dia → docs/src/_old/wrapped_ridge.dia
diff --git a/docs/src/acceleration_and_parallelism.md b/docs/src/acceleration_and_parallelism.md
@@ -8,7 +8,7 @@
     subject to breaking changes during minor or major releases without
     warning.
 
-### User-facing interface
+## User-facing interface
 
 To enable composable, extensible acceleration of core MLJ methods,
 [ComputationalResources.jl](https://github.com/timholy/ComputationalResources.jl)