Merge 55a4cb2 into 973c4e1

Project.toml

@@ -1,7 +1,7 @@
-name = "Transforms"
+name = "FeatureTransforms"
 uuid = "8fd68953-04b8-4117-ac19-158bf6de9782"
 authors = ["Invenia Technical Computing Corporation"]
-version = "0.1.1"
+version = "0.1.0"
 
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"

README.md

@@ -1,23 +1,23 @@
-# Transforms
+# FeatureTransforms
 
-[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://invenia.github.io/Transforms.jl/stable)
-[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://invenia.github.io/Transforms.jl/dev)
-[![Build Status](https://travis-ci.com/invenia/Transforms.jl.svg?branch=master)](https://travis-ci.com/invenia/Transforms.jl)
+[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://invenia.github.io/FeatureTransforms.jl/stable)
+[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://invenia.github.io/FeatureTransforms.jl/dev)
+[![Build Status](https://travis-ci.com/invenia/FeatureTransforms.jl.svg?branch=master)](https://travis-ci.com/invenia/FeatureTransforms.jl)
 [![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle)
 [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
 
-Transforms.jl provides utilities for performing feature engineering in machine learning pipelines.
-Transforms supports operations on `AbstractArrays` and [Tables](https://github.com/JuliaData/Tables.jl).
+FeatureTransforms.jl provides utilities for performing feature engineering in machine learning pipelines.
+FeatureTransforms supports operations on `AbstractArrays` and [Tables](https://github.com/JuliaData/Tables.jl).
 
 ## Installation
 ```julia
-julia> using Pkg; Pkg.add("Transforms")
+julia> using Pkg; Pkg.add("FeatureTransforms")
 ```
 
 ## Quickstart
 Load in the dependencies and construct some toy data.
 ```julia
-julia> using DataFrames, Transforms
+julia> using DataFrames, FeatureTransforms
 
 julia> df = DataFrame(:a=>[1, 2, 3, 4, 5], :b=>[5, 4, 3, 2, 1], :c=>[0, 1, 0, 1, 0])
 5×3 DataFrame
@@ -36,11 +36,11 @@ Note that non-mutating transformations do not necessarily return the same type,
 ```julia
 julia> p = Power(3);
 
-julia> Transforms.apply(df, p; cols=[:a])
+julia> FeatureTransforms.apply(df, p; cols=[:a])
 1-element Array{Array{Int64,1},1}:
  [1, 8, 27, 64, 125]
 
-julia> Transforms.apply!(df, p; cols=[:a])
+julia> FeatureTransforms.apply!(df, p; cols=[:a])
 5×3 DataFrame
  Row │ a      b      c     
      │ Int64  Int64  Int64 
@@ -57,7 +57,7 @@ But users may append the output to their data if they so wish.
 ```julia
 julia> lc = LinearCombination([1, -10]);
 
-julia> Transforms.apply(df, lc; cols=[:b, :c])
+julia> FeatureTransforms.apply(df, lc; cols=[:b, :c])
 5-element Array{Int64,1}:
   5
  -6

docs/Manifest.toml

@@ -91,7 +91,7 @@ uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
 deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
 uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
-[[Transforms]]
+[[FeatureTransforms]]
 path = ".."
 uuid = "8fd68953-04b8-4117-ac19-158bf6de9782"
 version = "0.1.0"

docs/Project.toml

@@ -1,3 +1,3 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
-Transforms = "8fd68953-04b8-4117-ac19-158bf6de9782"
+FeatureTransforms = "8fd68953-04b8-4117-ac19-158bf6de9782"

docs/make.jl

@@ -1,14 +1,14 @@
-using Transforms
+using FeatureTransforms
 using Documenter
 
 makedocs(;
-    modules=[Transforms],
+    modules=[FeatureTransforms],
     authors="Invenia Technical Computing Corporation",
-    repo="https://github.com/invenia/Transforms.jl/blob/{commit}{path}#L{line}",
-    sitename="Transforms.jl",
+    repo="https://github.com/invenia/FeatureTransforms.jl/blob/{commit}{path}#L{line}",
+    sitename="FeatureTransforms.jl",
     format=Documenter.HTML(;
         prettyurls=get(ENV, "CI", "false") == "true",
-        canonical="https://invenia.github.io/Transforms.jl",
+        canonical="https://invenia.github.io/FeatureTransforms.jl",
         assets=String[],
     ),
     pages=[
@@ -19,7 +19,7 @@ makedocs(;
 )
 
 deploydocs(;
-    repo="github.com/invenia/Transforms.jl",
+    repo="github.com/invenia/FeatureTransforms.jl",
     devbranch = "main",
     push_preview = true,
 )

docs/src/index.md

@@ -1,12 +1,12 @@
 ```@meta
-CurrentModule = Transforms
+CurrentModule = FeatureTransforms
 ```
 
-# Transforms
+# FeatureTransforms
 
 ```@index
 ```
 
 ```@autodocs
-Modules = [Transforms]
+Modules = [FeatureTransforms]
 ```

src/Transforms.jl → src/FeatureTransforms.jl

@@ -1,4 +1,4 @@
-module Transforms
+module FeatureTransforms
 
 using Dates: TimeType, Period, Day, hour
 using Statistics: mean, std

src/transformers.jl

@@ -2,7 +2,7 @@
 """
     Transform
 
-Abstract supertype for all Transforms.
+Abstract supertype for all feature Transforms.
 """
 abstract type Transform end
 

test/linear_combination.jl

@@ -8,25 +8,25 @@
         expected = [-1]
 
         @testset "all inds" begin
-            @test Transforms.apply(x, lc) == expected
+            @test FeatureTransforms.apply(x, lc) == expected
             @test lc(x) == expected
         end
 
         @testset "dims not supported" begin
-            @test_throws  MethodError Transforms.apply(x, lc; dims=1)
+            @test_throws  MethodError FeatureTransforms.apply(x, lc; dims=1)
         end
 
         @testset "dimension mismatch" begin
             x = [1, 2, 3]
-            @test_throws DimensionMismatch Transforms.apply(x, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(x, lc)
         end
 
         @testset "specified inds" begin
             x = [1, 2, 3]
             inds = [2, 3]
             expected = [-1]
 
-            @test Transforms.apply(x, lc; inds=inds) == expected
+            @test FeatureTransforms.apply(x, lc; inds=inds) == expected
             @test lc(x; inds=inds) == expected
         end
     end
@@ -36,44 +36,44 @@
         expected = [0, 0, -2]
 
         @testset "all inds" begin
-            @test Transforms.apply(M, lc) == expected
+            @test FeatureTransforms.apply(M, lc) == expected
             @test lc(M) == expected
         end
 
         @testset "dims" begin
             @testset "dims = :" begin
                 d = Colon()
-                @test_throws ArgumentError Transforms.apply(M, lc; dims=d)
+                @test_throws ArgumentError FeatureTransforms.apply(M, lc; dims=d)
             end
 
             @testset "dims = 1" begin
                 d = 1
-                @test Transforms.apply(M, lc; dims=d) == expected
+                @test FeatureTransforms.apply(M, lc; dims=d) == expected
                 @test lc(M; dims=d) == expected
             end
 
             @testset "dims = 2" begin
                 d = 2
                 # There are 3 rows so trying to apply along dim 2 without specifying inds
                 # won't work
-                @test_throws DimensionMismatch Transforms.apply(M, lc; dims=d)
+                @test_throws DimensionMismatch FeatureTransforms.apply(M, lc; dims=d)
 
-                @test Transforms.apply(M, lc; dims=d, inds=[2, 3]) == [-1, -3]
+                @test FeatureTransforms.apply(M, lc; dims=d, inds=[2, 3]) == [-1, -3]
                 @test lc(M; dims=d, inds=[1, 3]) == [-2, -4]
             end
         end
 
         @testset "dimension mismatch" begin
             M = [1 1 1; 2 2 2]
-            @test_throws DimensionMismatch Transforms.apply(M, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(M, lc)
         end
 
         @testset "specified inds" begin
             M = [1 1 5; 2 2 4]
             inds = [2, 3]
             expected = [-4, -2]
 
-            @test Transforms.apply(M, lc; inds=inds) == expected
+            @test FeatureTransforms.apply(M, lc; inds=inds) == expected
             @test lc(M; inds=inds) == expected
         end
     end
@@ -83,40 +83,40 @@
         expected = [-1, -1]
 
         @testset "all inds" begin
-            @test Transforms.apply(A, lc) == expected
+            @test FeatureTransforms.apply(A, lc) == expected
             @test lc(A) == expected
         end
 
         @testset "dims" begin
             @testset "dims = :" begin
                 d = Colon()
-                @test_throws ArgumentError Transforms.apply(A, lc; dims=d)
+                @test_throws ArgumentError FeatureTransforms.apply(A, lc; dims=d)
             end
 
             @testset "dims = 1" begin
                 d = 1
-                @test Transforms.apply(A, lc; dims=d) == expected
+                @test FeatureTransforms.apply(A, lc; dims=d) == expected
                 @test lc(A; dims=d) == expected
             end
 
             @testset "dims = 2" begin
                 d = 2
-                @test Transforms.apply(A, lc; dims=d) == [-3, -3]
+                @test FeatureTransforms.apply(A, lc; dims=d) == [-3, -3]
                 @test lc(A; dims=d) == [-3, -3]
             end
         end
 
         @testset "dimension mismatch" begin
             A = AxisArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
-            @test_throws DimensionMismatch Transforms.apply(A, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(A, lc)
         end
 
         @testset "specified inds" begin
             A = AxisArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
             inds = [1, 2]
             expected = [-1, -1]
 
-            @test Transforms.apply(A, lc; inds=inds) == expected
+            @test FeatureTransforms.apply(A, lc; inds=inds) == expected
             @test lc(A; inds=inds) == expected
         end
     end
@@ -126,40 +126,40 @@
         expected = [-1, -1]
 
         @testset "all inds" begin
-            @test Transforms.apply(A, lc) == expected
+            @test FeatureTransforms.apply(A, lc) == expected
             @test lc(A) == expected
         end
 
         @testset "dims" begin
             @testset "dims = :" begin
                 d = Colon()
-                @test_throws ArgumentError Transforms.apply(A, lc; dims=d)
+                @test_throws ArgumentError FeatureTransforms.apply(A, lc; dims=d)
             end
 
             @testset "dims = 1" begin
                 d = 1
-                @test Transforms.apply(A, lc; dims=d) == expected
+                @test FeatureTransforms.apply(A, lc; dims=d) == expected
                 @test lc(A; dims=d) == expected
             end
 
             @testset "dims = 2" begin
                 d = 2
-                @test Transforms.apply(A, lc; dims=d) == [-3, -3]
+                @test FeatureTransforms.apply(A, lc; dims=d) == [-3, -3]
                 @test lc(A; dims=d) == [-3, -3]
             end
         end
 
         @testset "dimension mismatch" begin
             A = KeyedArray([1 2 3; 4 5 6], foo=["a", "b"], bar=["x", "y", "z"])
-            @test_throws DimensionMismatch Transforms.apply(A, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(A, lc)
         end
 
         @testset "specified inds" begin
             A = KeyedArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
             inds = [1, 2]
             expected = [-1, -1]
 
-            @test Transforms.apply(A, lc; inds=inds) == expected
+            @test FeatureTransforms.apply(A, lc; inds=inds) == expected
             @test lc(A; inds=inds) == expected
         end
     end
@@ -169,33 +169,33 @@
         expected = [-3, -3, -3]
 
         @testset "all cols" begin
-            @test Transforms.apply(nt, lc) == expected
+            @test FeatureTransforms.apply(nt, lc) == expected
             @test lc(nt) == expected
         end
 
         @testset "dims not supported" begin
-            @test_throws MethodError Transforms.apply(nt, lc; dims=1)
+            @test_throws MethodError FeatureTransforms.apply(nt, lc; dims=1)
         end
 
         @testset "dimension mismatch" begin
             nt = (a = [1, 2, 3], b = [4, 5, 6], c = [1, 1, 1])
-            @test_throws DimensionMismatch Transforms.apply(nt, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(nt, lc)
         end
 
         @testset "specified cols" begin
             nt = (a = [1, 2, 3], b = [4, 5, 6], c = [1, 1, 1])
             cols = [:a, :b]
             expected = [-3, -3, -3]
 
-            @test Transforms.apply(nt, lc; cols=cols) == expected
+            @test FeatureTransforms.apply(nt, lc; cols=cols) == expected
             @test lc(nt; cols=cols) == expected
         end
 
         @testset "single col" begin
             lc_single = LinearCombination([-1])
 
-            @test Transforms.apply(nt, lc_single; cols=:a) == [-1, -2, -3]
-            @test Transforms.apply(nt, lc_single; cols=[:a]) == [-1, -2, -3]
+            @test FeatureTransforms.apply(nt, lc_single; cols=:a) == [-1, -2, -3]
+            @test FeatureTransforms.apply(nt, lc_single; cols=[:a]) == [-1, -2, -3]
             @test lc_single(nt; cols=:a) == [-1, -2, -3]
         end
     end
@@ -205,33 +205,33 @@
         expected = [-3, -3, -3]
 
         @testset "all cols" begin
-            @test Transforms.apply(df, lc) == expected
+            @test FeatureTransforms.apply(df, lc) == expected
             @test lc(df) == expected
         end
 
         @testset "dims not supported" begin
-            @test_throws MethodError Transforms.apply(df, lc; dims=1)
+            @test_throws MethodError FeatureTransforms.apply(df, lc; dims=1)
         end
 
         @testset "dimension mismatch" begin
             df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6], :c => [1, 1, 1])
-            @test_throws DimensionMismatch Transforms.apply(df, lc)
+            @test_throws DimensionMismatch FeatureTransforms.apply(df, lc)
         end
 
         @testset "specified cols" begin
             df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6], :c => [1, 1, 1])
             cols = [:b, :c]
             expected = [3, 4, 5]
 
-            @test Transforms.apply(df, lc; cols=cols) == expected
+            @test FeatureTransforms.apply(df, lc; cols=cols) == expected
             @test lc(df; cols=cols) == expected
         end
 
         @testset "single col" begin
             lc_single = LinearCombination([-1])
 
-            @test Transforms.apply(df, lc_single; cols=:a) == [-1, -2, -3]
-            @test Transforms.apply(df, lc_single; cols=[:a]) == [-1, -2, -3]
+            @test FeatureTransforms.apply(df, lc_single; cols=:a) == [-1, -2, -3]
+            @test FeatureTransforms.apply(df, lc_single; cols=[:a]) == [-1, -2, -3]
             @test lc_single(df; cols=:a) == [-1, -2, -3]
         end
     end