Switch to FastTransforms_jll

.appveyor.yml

@@ -1,18 +1,12 @@
-# Documentation: http://www.appveyor.com/docs/appveyor-yml/
-image: Visual Studio 2017
-
-cache: c:\tools\vcpkg\installed\
-
-platform: x64
-
 environment:
   matrix:
-  - julia_version: 1.0
-  - julia_version: 1.1
-  - julia_version: 1.2
   - julia_version: 1.3
   - julia_version: nightly
 
+platform:
+  - x86 # 32-bit
+  - x64 # 64-bit
+
 # # Uncomment the following lines to allow failures on nightly julia
 # # (tests will run but not make your overall status red)
 matrix:
@@ -32,10 +26,6 @@ notifications:
 
 install:
   - ps: iex ((new-object net.webclient).DownloadString("https://raw.githubusercontent.com/JuliaCI/Appveyor.jl/version-1/bin/install.ps1"))
-  - set PATH=%PATH%;c:\tools\vcpkg
-  - set PATH=%PATH%;C:\mingw-w64\x86_64-7.2.0-posix-seh-rt_v5-rev1\mingw64\bin\
-  - vcpkg install openblas:x64-windows fftw3[core,threads]:x64-windows mpfr:x64-windows mpir:x64-windows --recurse
-  - set PATH=c:\tools\vcpkg\installed\x64-windows\bin;%PATH%
 
 build_script:
   - echo "%JL_BUILD_SCRIPT%"

.cirrus.yml

@@ -0,0 +1,16 @@
+freebsd_instance:
+  image: freebsd-12-0-release-amd64
+task:
+  name: FreeBSD
+  env:
+    matrix:
+      - JULIA_VERSION: 1.3
+      - JULIA_VERSION: nightly
+  install_script:
+    - sh -c "$(fetch https://raw.githubusercontent.com/ararslan/CirrusCI.jl/master/bin/install.sh -o -)"
+  build_script:
+    - cirrusjl build
+  test_script:
+    - cirrusjl test
+  coverage_script:
+    - cirrusjl coverage codecov coveralls

.travis.yml

@@ -4,21 +4,11 @@ os:
   - linux
   - osx
 julia:
-  - 1.0
-  - 1.1
-  - 1.2
   - 1.3
   - nightly
 matrix:
   allow_failures:
     - julia: nightly
-addons:
-  apt:
-    packages: ['libquadmath0', 'libgomp1', 'libopenblas-dev', 'libfftw3-dev', 'libmpfr-dev']
-  homebrew:
-    packages: ['gcc@8', 'fftw', 'mpfr']
-    update: true
-
 notifications:
   email: false
 after_success:

Project.toml

@@ -1,13 +1,14 @@
 name = "FastTransforms"
 uuid = "057dd010-8810-581a-b7be-e3fc3b93f78c"
-version = "0.7.0"
+version = "0.8.0"
 
 [deps]
 AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
 BinaryProvider = "b99e7846-7c00-51b0-8f62-c81ae34c0232"
 DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2"
 FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
 FastGaussQuadrature = "442a2c76-b920-505d-bb47-c5924d526838"
+FastTransforms_jll = "34b6f7d7-08f9-5794-9e10-3819e4c7e49a"
 Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
@@ -24,4 +25,4 @@ FastGaussQuadrature = "0.4"
 Reexport = "0.2"
 SpecialFunctions = "0.8"
 ToeplitzMatrices = "0.6"
-julia = "1"
+julia = "≥ 1.3"

README.md

@@ -1,14 +1,14 @@
 # FastTransforms.jl
 
-[![Travis](https://travis-ci.org/JuliaApproximation/FastTransforms.jl.svg?branch=master)](https://travis-ci.org/JuliaApproximation/FastTransforms.jl) [![AppVeyor](https://ci.appveyor.com/api/projects/status/oba9qush15q3x8pb/branch/master?svg=true)](https://ci.appveyor.com/project/MikaelSlevinsky/fasttransforms-jl/branch/master) [![codecov](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl) [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/stable) [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/latest)
+[![Travis](https://travis-ci.org/JuliaApproximation/FastTransforms.jl.svg?branch=master)](https://travis-ci.org/JuliaApproximation/FastTransforms.jl) [![AppVeyor](https://ci.appveyor.com/api/projects/status/oba9qush15q3x8pb/branch/master?svg=true)](https://ci.appveyor.com/project/MikaelSlevinsky/fasttransforms-jl/branch/master) [![Cirrus](https://api.cirrus-ci.com/github/JuliaApproximation/FastTransforms.jl.svg)](https://cirrus-ci.com/github/JuliaApproximation/FastTransforms.jl) [![codecov](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl) [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/stable) [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/latest)
 
 `FastTransforms.jl` allows the user to conveniently work with orthogonal polynomials with degrees well into the millions.
 
 This package provides a Julia wrapper for the [C library](https://github.com/MikaelSlevinsky/FastTransforms) of the same name. Additionally, all three types of nonuniform fast Fourier transforms are available, as well as the Padua transform.
 
 ## Installation
 
-The build script, which works on macOS, Linux, and Windows systems, downloads precompiled binaries of the latest version of [FastTransforms](https://github.com/MikaelSlevinsky/FastTransforms) or builds them from source, as governed by the environment variable `FT_BUILD_FROM_SOURCE=true/false`. This library depends on `FFTW`, `MPFR`, and `OpenBLAS` (on Linux and Windows), which must be present for a successful build. With dependencies, installation may be as straightforward as:
+Installation, which uses [BinaryBuilder](https://github.com/JuliaPackaging/BinaryBuilder.jl) for Intel processors (Sandybridge and beyond), may be as straightforward as:
 
 ```julia
 pkg> add FastTransforms

deps/build.jl

@@ -1,7 +1,7 @@
 using BinaryProvider
 import Libdl
 
-version = v"0.2.9"
+version = v"0.2.12"
 
 if arch(platform_key_abi()) != :x86_64
     @warn "FastTransforms has only been tested on x86_64 architectures."
@@ -20,11 +20,7 @@ print_platform_error(p::MacOS) = "On MacOS\n\tbrew install gcc@8 fftw mpfr\n"
 print_platform_error(p::Linux) = "On Linux\n\tsudo apt-get install gcc-8 libblas-dev libopenblas-base libfftw3-dev libmpfr-dev\n"
 print_platform_error(p::Windows) = "On Windows\n\tvcpkg install openblas:x64-windows fftw3[core,threads]:x64-windows mpir:x64-windows mpfr:x64-windows\n"
 
-# Rationale is as follows: The build is pretty fast, so on Linux it is typically easiest
-# to just use the gcc of the system to build the library and include it. On MacOS, however,
-# we need to actually install a gcc first, because Apple's OS comes only shipped with clang,
-# so here we download the binary.
-ft_build_from_source = get(ENV, "FT_BUILD_FROM_SOURCE", Sys.isapple() ? "false" : "true")
+ft_build_from_source = get(ENV, "FT_BUILD_FROM_SOURCE", "false")
 if ft_build_from_source == "true"
     make = Sys.iswindows() ? "mingw32-make" : "make"
     compiler = Sys.isapple() ? "CC=gcc-8" : "CC=gcc"
@@ -51,19 +47,4 @@ if ft_build_from_source == "true"
         print_error()
     end
     println("FastTransforms built from source.")
-else
-    const GCC = BinaryProvider.detect_compiler_abi().gcc_version
-    namemap = Dict(:gcc4 => "gcc-4.9", :gcc5 => "gcc-5", :gcc6 => "gcc-6",
-                   :gcc7 => "gcc-7", :gcc8 => "gcc-8", :gcc9 => "gcc-9")
-    if !(GCC in keys(namemap))
-        error("Please ensure you have a version of gcc from gcc-4.9 to gcc-9.")
-    end
-    try
-        download("https://github.com/MikaelSlevinsky/FastTransforms/releases/download/" *
-                 "v$version/libfasttransforms.v$version.$(namemap[GCC]).$extension",
-                 joinpath(dirname(@__DIR__), "deps", "libfasttransforms.$extension"))
-    catch
-        print_error()
-    end
-    println("FastTransforms installed by downloading binaries.")
 end

src/FastTransforms.jl

@@ -1,7 +1,8 @@
 module FastTransforms
 
-using DSP, FastGaussQuadrature, Libdl, LinearAlgebra, SpecialFunctions, ToeplitzMatrices
-using Reexport
+using DSP, FastGaussQuadrature, LinearAlgebra
+using Reexport, SpecialFunctions, ToeplitzMatrices
+
 @reexport using AbstractFFTs
 @reexport using FFTW
 
@@ -19,11 +20,11 @@ import AbstractFFTs: Plan, ScaledPlan,
                      rfft_output_size, brfft_output_size,
                      plan_inv, normalization
 
+import DSP: conv
+
 import FFTW: dct, dct!, idct, idct!, plan_dct!, plan_idct!,
              plan_dct, plan_idct, fftwNumber
 
-import DSP: conv
-
 import FastGaussQuadrature: unweightedgausshermite
 
 import LinearAlgebra: mul!, lmul!, ldiv!

src/libfasttransforms.jl

@@ -1,8 +1,13 @@
-const libfasttransforms = find_library("libfasttransforms", [joinpath(dirname(@__DIR__), "deps")])
-
-if libfasttransforms ≡ nothing || length(libfasttransforms) == 0
-    error("FastTransforms is not properly installed. Please run Pkg.build(\"FastTransforms\") ",
-          "and restart Julia.")
+ft_build_from_source = get(ENV, "FT_BUILD_FROM_SOURCE", "false")
+if ft_build_from_source == "true"
+    using Libdl
+    const libfasttransforms = find_library("libfasttransforms", [joinpath(dirname(@__DIR__), "deps")])
+    if libfasttransforms ≡ nothing || length(libfasttransforms) == 0
+        error("FastTransforms is not properly installed. Please run Pkg.build(\"FastTransforms\") ",
+              "and restart Julia.")
+    end
+else
+    using FastTransforms_jll
 end
 
 function ft_fftw_plan_with_nthreads(n::Integer)

test/hermitetests.jl

@@ -7,7 +7,7 @@ hermitepoints(n) = FastGaussQuadrature.unweightedgausshermite( n )[1]
     @test hermitepoints(100_000)[end] ≈ 446.9720305443094
 
     @test weightedhermitetransform([1.0]) == [1.0]
-    @test weightedhermitetransform(exp.(-hermitepoints(2).^2/2)) == [1.0,0.0]
+    @test weightedhermitetransform(exp.(-hermitepoints(2).^2/2)) ≈ [1.0,0.0]
     @test weightedhermitetransform(exp.(-hermitepoints(3).^2/2)) ≈ [1.0,0.0,0.0]
     @test weightedhermitetransform(exp.(-hermitepoints(1000).^2/2)) ≈ [1.0; zeros(999)]
     @test weightedhermitetransform(exp.(-hermitepoints(3000).^2/2)) ≈ [1.0; zeros(2999)]