Apply suggestions from code review

- foreach
- move test_quinn
- eps -> atol

test/FilterTestHelpers.jl

@@ -58,11 +58,10 @@ function tffilter_accuracy(f1, f2, accurate_f)
     accuracy_check(loss(a1, accurate_a), loss(a2, accurate_a), "a")
 end
 
-function zpkfilter_accuracy(f1, f2, accurate_f; relerr=1, compare_gain_at=nothing, eps=0.0)
+function zpkfilter_accuracy(f1, f2, accurate_f; relerr=1, compare_gain_at=nothing, atol=0.0)
     z1, p1 = sort(f1.z; lt), sort(f1.p; lt)
     z2, p2 = sort(f2.z; lt), sort(f2.p; lt)
     accurate_z, accurate_p = sort(accurate_f.z; lt), sort(accurate_f.p; lt)
-    atol = eps
     if !isempty(z1) || !isempty(z2) || !isempty(accurate_z)
         @test ≈(z1, accurate_z; atol)
         @test ≈(z2, accurate_z; atol)

test/estimation.jl

@@ -52,22 +52,23 @@ end
 end
 
 @testset "quinn" begin
-    ### real input
-    fs = 100
-    t = range(0, 5; step=1/fs)
-    fr = 28.3
-    sr = cospi.(2 * fr * t .+ 1 / 4.2)
     function test_quinn(f, s, args...)
         (f_est_real, maxiter) = quinn(s, args...)
         @test maxiter == false
         @test isapprox(f_est_real, f; atol=1e-3)
         return nothing
     end
+    ### real input
+    fs = 100
+    t = range(0, 5; step=1/fs)
+    fr = 28.3
+    sr = cospi.(2 * fr * t .+ 1 / 4.2)
     test_quinn(fr, sr, 50, fs)
     # use default initial guess
     test_quinn(fr, sr, fs) # initial guess given by Jacobsen
     # use default fs
     test_quinn(fr / fs, sr) # fs = 1.0, initial guess given by Jacobsen
+
     ### complex input
     fc = -40.3
     sc = cispi.(2 * fc * t .+ 1 / 1.4)

test/filt_stream.jl

@@ -324,7 +324,7 @@ function test_arbitrary(Th, x, resampleRate, numFilters::Integer)
 
     results = (naiveResult, statelessResult, statefulResult, piecewiseResult)
     commonLen = minimum(length, results)
-    resize!.(results, commonLen)
+    foreach(x -> resize!(x, commonLen), results)
 
     @test naiveResult ≈ statelessResult
     @test naiveResult ≈ statefulResult

test/filter_design.jl

@@ -266,7 +266,7 @@ end
 
     f = Elliptic(20, 0.1, 10)
     zpkfilter_eq(f, matlab_f)
-    zpkfilter_accuracy(f, matlab_f, Elliptic(BigFloat, 20, 0.1, 10), eps=1e-9)
+    zpkfilter_accuracy(f, matlab_f, Elliptic(BigFloat, 20, 0.1, 10), atol=1e-9)
 
     # 19 pole elliptic filter prototype with 0.1 dB passband ripple and 10
     # dB stopband ripple from MATLAB 2013b:
@@ -309,7 +309,7 @@ end
 
     f = Elliptic(19, 0.1, 10)
     zpkfilter_eq(f, matlab_f)
-    zpkfilter_accuracy(f, matlab_f, Elliptic(BigFloat, 19, 0.1, 10), eps=4e-9)
+    zpkfilter_accuracy(f, matlab_f, Elliptic(BigFloat, 19, 0.1, 10), atol=4e-9)
 end
 
 #