use more similars

src/Filters/filt.jl

@@ -77,7 +77,7 @@ function filt!(out::AbstractArray, f::SecondOrderSections{:z}, x::AbstractArray,
 end
 
 filt(f::SecondOrderSections{:z,T,G}, x::AbstractArray{S}, si=_zerosi(f, x)) where {T,G,S<:Number} =
-    filt!(Array{promote_type(T, G, S)}(undef, size(x)), f, x, si)
+    filt!(similar(x, promote_type(T, G, S)), f, x, si)
 
 ## Biquad
 _zerosi(::Biquad{:z,T}, ::AbstractArray{S}) where {T,S} =
@@ -112,7 +112,7 @@ function filt!(out::AbstractArray, f::Biquad{:z}, x::AbstractArray,
 end
 
 filt(f::Biquad{:z,T}, x::AbstractArray{S}, si=_zerosi(f, x)) where {T,S<:Number} =
-    filt!(Array{promote_type(T, S)}(undef, size(x)), f, x, si)
+    filt!(similar(x, promote_type(T, S)), f, x, si)
 
 ## For arbitrary filters, convert to SecondOrderSections
 filt(f::FilterCoefficients{:z}, x) = filt(convert(SecondOrderSections, f), x)
@@ -227,7 +227,7 @@ Apply the [stateful filter](@ref stateful-filter-objects) `f` on `x`.
     output array `out` to `filt!(out, f, x)`.
 """
 filt(f::DF2TFilter{<:FilterCoefficients{:z},<:Array{T}}, x::AbstractVector{V}) where {T,V} =
-    filt!(Vector{promote_type(T, V)}(undef, length(x)), f, x)
+    filt!(similar(x, promote_type(T, V)), f, x)
 
 # Fall back to SecondOrderSections
 DF2TFilter(coef::FilterCoefficients{:z}) = DF2TFilter(convert(SecondOrderSections, coef))
@@ -435,7 +435,7 @@ function tdfilt!(out::AbstractArray, h::AbstractVector{H}, x::AbstractArray) whe
 end
 
 filt(h::AbstractVector{H}, x::AbstractArray{T}) where {H,T} =
-    filt!(Array{promote_type(H, T)}(undef, size(x)), h, x)
+    filt!(similar(x, promote_type(H, T)), h, x)
 
 #
 # fftfilt and filt
@@ -449,7 +449,7 @@ using an FFT-based overlap-save algorithm.
 """
 function fftfilt(b::AbstractVector{T}, x::AbstractArray{T},
                  nfft::Integer=optimalfftfiltlength(length(b), length(x))) where T<:Real
-    _fftfilt!(Array{T}(undef, size(x)), b, x, nfft)
+    _fftfilt!(similar(x, T), b, x, nfft)
 end
 
 """
@@ -516,7 +516,7 @@ end
 # Filter x using FIR filter b, heuristically choosing to perform convolution in
 # the time domain using tdfilt or in the frequency domain using fftfilt
 function filt(b::AbstractVector{T}, x::AbstractArray{T}) where T<:Number
-    filt_choose_alg!(Array{T}(undef, size(x)), b, x)
+    filt_choose_alg!(similar(x, T), b, x)
 end
 
 # Like filt but mutates output array

src/dspbase.jl

@@ -12,7 +12,7 @@ state vector `si` (defaults to zeros).
 """
 function filt(b::Union{AbstractVector, Number}, a::Union{AbstractVector, Number},
               x::AbstractArray{T}, si::AbstractArray{S} = _zerosi(b,a,T)) where {T,S}
-    filt!(Array{promote_type(eltype(b), eltype(a), T, S)}(undef, size(x)), b, a, x, si)
+    filt!(similar(x, promote_type(eltype(b), eltype(a), T, S)), b, a, x, si)
 end
 
 # in-place filtering: returns results in the out argument, which may shadow x
@@ -63,7 +63,7 @@ function filt!(out::AbstractArray, b::Union{AbstractVector, Number}, a::Union{Ab
     else
         initial_si = si
         si = similar(si, axes(si, 1))
-        for col = 1:ncols
+        for col in axes(x, 2)
             # Reset the filter state
             copyto!(si, view(initial_si, :, N > 1 ? col : 1))
             if as > 1

src/multitaper.jl

@@ -693,7 +693,7 @@ end
 function allocate_output(config::MTCoherenceConfig{T}) where {T}
     n_chan = config.cs_config.n_channels
     n_freqs = length(config.cs_config.freq)
-    return Array{real(T)}(undef, n_chan, n_chan, n_freqs)
+    return Array{real(T),3}(undef, n_chan, n_chan, n_freqs)
 end
 
 """

test/dsp.jl

@@ -59,7 +59,7 @@ end
         @test conv(f32a, b) ≈ fexp
         @test conv(fb, a) ≈ fexp
 
-        offset_arr = OffsetArray{Int}(undef, -1:2)
+        offset_arr = OffsetVector{Int}(undef, -1:2)
         offset_arr[:] = a
         @test conv(offset_arr, 1:3) == OffsetVector(expectation, 0:5)
         # Issue #352
@@ -106,7 +106,7 @@ end
         @test conv(f32a, b) ≈ fexp
         @test conv(fb, a) ≈ fexp
 
-        offset_arr = OffsetArray{Int}(undef, -1:1, -1:1)
+        offset_arr = OffsetMatrix{Int}(undef, -1:1, -1:1)
         offset_arr[:] = a
         @test conv(offset_arr, b) == OffsetArray(expectation, 0:3, 0:3)
     end

test/multitaper.jl

@@ -251,7 +251,7 @@ end
     sin_1 = sin.(2π * 12.0 * t)  # 12 Hz sinusoid signal
     sin_2 = sin.(2π * 12.0 * t .+ π)
     noise = vec(readdlm(joinpath(@__DIR__, "data", "noise.txt"))) # generated by `rand(1024) * 2 .- 1`
-    more_noisy = Array{Float64}(undef, 1, 2, n_samples)
+    more_noisy = Array{Float64,3}(undef, 1, 2, n_samples)
     more_noisy[1, 1, :] = sin_1
     more_noisy[1, 2, :] .= sin_1 .+ 3 * noise