Merge 505de00 into 20e4eb4

.github/workflows/TagBot.yml

@@ -0,0 +1,14 @@
+name: TagBot
+on:
+  issue_comment:
+    types:
+      - created
+  workflow_dispatch:
+jobs:
+  TagBot:
+    if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
+    runs-on: ubuntu-latest
+    steps:
+      - uses: JuliaRegistries/TagBot@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/ci.yml

@@ -0,0 +1,54 @@
+name: CI
+on:
+  push:
+    branches: [master]
+    tags: ["*"]
+  pull_request:
+jobs:
+  test:
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - '1.0'
+          - '1' # automatically expands to the latest stable 1.x release of Julia
+          - 'nightly'
+        os:
+          - ubuntu-latest
+          - macOS-latest
+          - windows-latest
+        arch:
+          - x64
+          - x86
+        exclude:
+          - os: macOS-latest
+            arch: x86
+          - os: ubuntu-latest
+            arch: x86 # libhdf5 problems
+    steps:
+      - uses: actions/checkout@v2
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - uses: actions/cache@v1
+        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: Install Python Dependencies (for MLDatasets)
+        run: python -m pip install scipy
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-runtest@v1
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: coverallsapp/github-action@master
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          path-to-lcov: lcov.info

Project.toml

@@ -10,7 +10,7 @@ ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
-Distances = "0.9.0"
+Distances = "0.9.0, 0.10"
 ProgressMeter = "1.3.2"
 julia = "1.5"
 

README.md

@@ -1,11 +1,8 @@
 t-SNE (t-Stochastic Neighbor Embedding)
 =======================================
 
-[![Julia 0.6 Status](http://pkg.julialang.org/badges/TSne_0.6.svg)](http://pkg.julialang.org/?pkg=TSne&ver=0.6)
-[![Julia 0.7 Status](http://pkg.julialang.org/badges/TSne_0.7.svg)](http://pkg.julialang.org/?pkg=TSne&ver=0.7)
-
-[![Build Status](https://travis-ci.org/lejon/TSne.jl.svg?branch=master)](https://travis-ci.org/lejon/TSne.jl)
-[![Coverage Status](https://coveralls.io/repos/github/lejon/TSne.jl/badge.svg?branch=master)](https://coveralls.io/github/lejon/TSne.jl?branch=master)
+[![Build Status]((https://github.com/lejon/TSne.jl/workflows/CI/badge.svg)](https://github.com/lejon/TSne.jl/actions?query=workflow%3ACI+branch%3Amaster)
+[![Coverage Status](https://coveralls.io/repos/github/lejon/TSne.jl/badge.svg)](https://coveralls.io/github/lejon/TSne.jl)
 
 Julia implementation of L.J.P. van der Maaten and G.E. Hintons [t-SNE visualisation technique](https://lvdmaaten.github.io/tsne/).
 

examples/demo.jl

@@ -25,7 +25,7 @@ if ARGS[1] == "iris"
     using RDatasets
     println("Using Iris dataset.")
     iris = dataset("datasets","iris")
-    X = convert(Matrix{Float64}, iris[:, 1:4])
+    X = hcat(eachcol(iris)[1:4]...)
     labels = iris[:, 5]
     plotname = "iris"
     initial_dims = -1
@@ -37,7 +37,7 @@ elseif ARGS[1] == "mnist"
     X, labels = MNIST.traindata(Float64);
     npts = min(2500, size(X, 3), length(labels))
     labels = string.(labels[1:npts])
-    X = rescale(transpose(reshape(X[:, :, 1:npts], (28*28, :))))
+    X = rescale(transpose(reshape(X[:, :, 1:npts], (size(X, 1)*size(X, 2), :))))
     plotname = "mnist"
     initial_dims = 50
     iterations = 1000

test/test_tsne.jl

@@ -1,7 +1,7 @@
 @testset "tsne()" begin
     @testset "API tests" begin
         iris = dataset("datasets", "iris")
-        X = convert(Matrix{Float64}, iris[:, 1:4])
+        X = hcat(eachcol(iris)[1:4]...)
         Y = tsne(X, 2, -1, 10, 15, verbose=true)
         @test size(Y) == (150, 2)
         Y = tsne(X, 3, -1, 10, 15, verbose=false)
@@ -42,7 +42,7 @@
 
     @testset "Iris dataset" begin
         iris = dataset("datasets", "iris")
-        X = convert(Matrix{Float64}, iris[:, 1:4])
+        X = hcat(eachcol(iris)[1:4]...)
         # embed in 3D
         Y3d = tsne(X, 3, -1, 100, 15, progress=false)
         @test size(Y3d) == (150, 3)
@@ -56,11 +56,10 @@
         train_data, labels = MLDatasets.with_accept(true) do
                 MNIST.traindata(Float64)
         end
-        X_labels = labels[1:2500] .+ 1
         X = reshape(permutedims(train_data[:, :, 1:2500], (3, 1, 2)),
                     2500, size(train_data, 1)*size(train_data, 2))
         X .-= mean(X, dims=1)
-        X ./= std(X, dims=1)
+        X ./= map(x -> ifelse(x > 0, x, 1.0), std(X, dims=1))
 
         Y = tsne(X, 2, 50, 2000, 20, progress=true)
         @test size(Y) == (2500, 2)