diff --git a/Project.toml b/Project.toml
index fe0185a..417cd10 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "AbstractFFTs"
 uuid = "621f4979-c628-5d54-868e-fcf4e3e8185c"
-version = "1.0.0"
+version = "1.0.1"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -10,6 +10,7 @@ julia = "^1.0"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["Test"]
+test = ["Test", "Unitful"]
diff --git a/README.md b/README.md
index f11d5ce..89f7d48 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ Documentation:
 [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://JuliaMath.github.io/AbstractFFTs.jl/latest)
 
 This package is mainly not intended to be used directly.
-Instead, developers of packages that implement FFTs (such as [FFTW.jl](https://github.com/JuliaMath/FFTW.jl))
+Instead, developers of packages that implement FFTs (such as [FFTW.jl](https://github.com/JuliaMath/FFTW.jl) or [FastTransforms.jl](https://github.com/JuliaApproximation/FastTransforms.jl))
 extend the types/functions defined in `AbstractFFTs`.
 This allows multiple FFT packages to co-exist with the same underlying `fft(x)` and `plan_fft(x)` interface.
 
diff --git a/docs/src/implementations.md b/docs/src/implementations.md
index 4bdd8bd..632a602 100644
--- a/docs/src/implementations.md
+++ b/docs/src/implementations.md
@@ -6,6 +6,8 @@ The following packages extend the functionality provided by AbstractFFTs:
 
 * [FFTW.jl](https://github.com/JuliaMath/FFTW.jl): Bindings for the
   [FFTW](http://www.fftw.org) library. This also used to be part of Base Julia.
+* [FastTransforms.jl](https://github.com/JuliaApproximation/FastTransforms.jl):
+  Pure-Julia implementation of FFT, with support for arbitrary AbstractFloat types.
 
 ## Defining a new implementation
 
diff --git a/src/definitions.jl b/src/definitions.jl
index 6551747..e8bda0a 100644
--- a/src/definitions.jl
+++ b/src/definitions.jl
@@ -419,8 +419,8 @@ Broadcast.broadcasted(::typeof(*), x::Number, f::Frequencies) = Broadcast.broadc
 Broadcast.broadcasted(::typeof(/), f::Frequencies, x::Number) = Frequencies(f.n_nonnegative, f.n, f.multiplier / x)
 Broadcast.broadcasted(::typeof(\), x::Number, f::Frequencies) = Broadcast.broadcasted(/, f, x)
 
-Base.maximum(f::Frequencies) = (f.n_nonnegative - ifelse(f.multiplier >= 0, 1, f.n)) * f.multiplier
-Base.minimum(f::Frequencies) = (f.n_nonnegative - ifelse(f.multiplier >= 0, f.n, 1)) * f.multiplier
+Base.maximum(f::Frequencies{T}) where T = (f.n_nonnegative - ifelse(f.multiplier >= zero(T), 1, f.n)) * f.multiplier
+Base.minimum(f::Frequencies{T}) where T = (f.n_nonnegative - ifelse(f.multiplier >= zero(T), f.n, 1)) * f.multiplier
 Base.extrema(f::Frequencies) = (minimum(f), maximum(f))
 
 """
diff --git a/test/runtests.jl b/test/runtests.jl
index 4c6bb3f..afa6d0d 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -5,6 +5,8 @@ using AbstractFFTs: Plan
 using LinearAlgebra
 using Test
 
+import Unitful
+
 @testset "rfft sizes" begin
     A = rand(11, 10)
     @test @inferred(AbstractFFTs.rfft_output_size(A, 1)) == (6, 10)
@@ -131,7 +133,7 @@ end
                 @test f(freqs) == f(collect(freqs)) == f(fftshift(freqs))
             end
         end
-        for f in (fftfreq, rfftfreq), n in (8, 9), multiplier in (2, 1/3, -1/7)
+        for f in (fftfreq, rfftfreq), n in (8, 9), multiplier in (2, 1/3, -1/7, 1.0*Unitful.mm)
             freqs = f(n, multiplier)
             check_extrema(freqs)
         end