Merge pull request #1027 from JuliaAI/dev

For a 1.9.2 release

Author: ablaom

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJBase"
 uuid = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "1.9.1"
+version = "1.9.2"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"

src/composition/learning_networks/nodes.jl

@@ -270,8 +270,8 @@ _formula(stream::IO, X::AbstractNode, indent) =
     (print(stream, repeat(' ', indent));_formula(stream, X, 0, indent))
 _formula(stream::IO, X::Source, depth, indent) = show(stream, X)
 function _formula(stream, X::Node, depth, indent)
-    operation_name = string(typeof(X.operation).name.mt.name)
-    anti = max(length(operation_name) - INDENT)
+    operation_name = simple_repr(X.operation)
+    anti = max(length(operation_name) - INDENT, 0)
     print(stream, operation_name, "(")
     n_args = length(X.args)
     if X.machine !== nothing
@@ -287,9 +287,9 @@ function _formula(stream, X::Node, depth, indent)
         _formula(stream, X.args[k],
                         depth + 1,
                         indent + length(operation_name) - anti )
-        k == n_args || print(stream, ",")
+        print(stream, ",")
     end
-    print(stream, ")")
+    print(stream, crind(indent), ")")
 end
 
 function Base.show(io::IO, ::MIME"text/plain", X::Node)
@@ -303,7 +303,7 @@ function Base.show(io::IO, ::MIME"text/plain", X::Node)
     _formula(io, X, 4)
 end
 
-# for displaying withing other objects:
+# for displaying within other objects:
 function Base.show(stream::IO, object::Node)
     str = simple_repr(typeof(object)) * " $(handle(object))"
     mach = object.machine

src/operations.jl

@@ -108,8 +108,6 @@ inverse_transform(mach::Machine; rows=:) =
                                 "must be explictly specified, "*
                                 "as in `inverse_transform(mach, X)`. "))
 
-_symbol(f) = Base.Core.Typeof(f).name.mt.name
-
 # catches improperly deserialized machines and silently fits the machine if it is
 # untrained and has no training arguments:
 function _check_and_fit_if_warranted!(mach)

src/show.jl

@@ -92,27 +92,12 @@ show_as_constructed(object) = show_as_constructed(typeof(object))
 show_compact(object) = show_compact(typeof(object))
 show_handle(object) = false
 
-# simplified string rep of an Type:
 function simple_repr(T)
-    repr = string(T.name.name)
-    parameters = T.parameters
-
-    # # add abbreviated type parameters:
-    # p_string = ""
-    # if length(parameters) > 0
-    #     p = parameters[1]
-    #     if p isa DataType
-    #         p_string = simple_repr(p)
-    #     elseif p isa Symbol
-    #         p_string = string(":", p)
-    #     end
-    #     if length(parameters) > 1
-    #         p_string *= ",…"
-    #     end
-    # end
-    # isempty(p_string) || (repr *= "{"*p_string*"}")
-
-    return repr
+    # get rid of type parameters:
+    output = split(repr(T), "{") |> first
+    # get rid of qualifiers:
+    output = split(output, ".") |> last
+    return output
 end
 
 # short version of showing a `MLJType` object:
@@ -165,7 +150,7 @@ function fancy(stream, object::MLJType, current_depth, depth, n)
         show(stream, object)
     else
         prefix = MLJModelInterface.name(object)
-        anti = max(length(prefix) - INDENT)
+        anti = max(length(prefix) - INDENT, 0)
         print(stream, prefix, "(")
         names = propertynames(object)
         n_names = length(names)

test/composition/learning_networks/nodes.jl

@@ -481,6 +481,17 @@ y = source(7)
     end
 end
 
+@testset "show for nodes" begin
+    # https://github.com/JuliaAI/MLJBase.jl/issues/1022
+    X, y = make_blobs(3)
+    X, y = source.([X, y])
+    mach = machine(Standardizer(), X)
+    W = transform(mach, X)
+    str = sprint(show, MIME("text/plain"), W)
+    # smoke test:
+    @test contains(str, "formula:\n    transform")
+end
+
 end # module
 
 true

test/show.jl

@@ -1,5 +1,24 @@
 using .Models
 
+module FooFoo
+
+struct FooBar{T}
+    x::T
+end
+
+end
+
+using .FooFoo
+
+@testset "simple_repr" begin
+    @test MLJBase.simple_repr(typeof(fill(3, 1))) == "Vector"
+    @test MLJBase.simple_repr(typeof(FooFoo.FooBar(3))) == "FooBar"
+    # with module qualifiers within type parameters
+    object = FooFoo.FooBar(FooFoo.FooBar(rand(3)))
+    T = typeof(object) # Main.FooFoo.FooBar{Main.FooFoo.FooBar{Vector{Float64}}}
+    @test MLJBase.simple_repr(T) == "FooBar"
+end
+
 @testset "display of models" begin
     io = IOBuffer()
     show(io, KNNRegressor())