Fast extrema computation for Frequencies (#45)

* Fast extrema computation for Frequencies

* simplified condition in extrema computation

Author: jishnub

src/definitions.jl

@@ -421,6 +421,10 @@ 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.extrema(f::Frequencies) = (minimum(f), maximum(f))
+
 """
     fftfreq(n, fs=1)
 Return the discrete Fourier transform (DFT) sample frequencies for a DFT of length `n`. The returned

test/runtests.jl

@@ -114,6 +114,18 @@ end
         @test 2 \ fftfreq(4, 1) === fftfreq(4, 1/2)
         @test 2 .\ fftfreq(4, 1) === fftfreq(4, 1/2)
     end
+
+    @testset "extrema" begin
+        function check_extrema(freqs)
+            for f in [minimum, maximum, extrema]
+                @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)
+            freqs = f(n, multiplier)
+            check_extrema(freqs)
+        end
+    end
 end
 
 @testset "normalization" begin