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Think I'm happy with all the new PBS tests
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@dingraha
dingraha committed May 2, 2024
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111 changes: 0 additions & 111 deletions src/proportional_bands.jl
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Expand Up @@ -972,117 +972,6 @@ end
return pbs_out
end

#"""
# combine(pbs::AbstractArray{<:AbstractProportionalBandSpectrum,N}, outcbands::AbstractProportionalBands{NO,:center}) where {N}

#Combine each input proportional band spectrum of `pbs` into one output proportional band spectrum using the proportional center bands indicated by `outcbands`.
#"""
#function combine(pbs::Union{AbstractArray{<:AbstractProportionalBandSpectrum,N},Base.RefValue{<:AbstractProportionalBandSpectrum}}, outcbands::AbstractProportionalBands{NO,:center}) where {N,NO}
# # Create the vector that will contain the new PBS.
# # An <:AbstractProportionalBandSpectrum is <:AbstractVector{TF}, so AbstractArray{<:AbstractProportionalBandSpectrum,N} is actually an Array of AbstractVectors.
# # So `eltype(eltype(pbs))` should give me the element type of the PBS.
# TFOut = promote_type(eltype(eltype(pbs)), eltype(outcbands))
# pbs_out = zeros(TFOut, length(outcbands))

# # Get the lower and upper edges of the output band spectrum.
# outbands_lower = lower_bands(outcbands)
# outbands_upper = upper_bands(outcbands)

# # Get the time period for this collection of PBSs.
# period = time_period(pbs)

# # Now start looping over each input PBS.
# for pbs_in in pbs

# # Get the lower and upper edges of this input band's spectrum.
# inbands_lower = lower_bands(pbs_in)
# inbands_upper = upper_bands(pbs_in)

# # So now I need to loop over each output band.
# # This is a lot of loops.
# for (idx_out, (fol, fou)) in enumerate(zip(outbands_lower, outbands_upper))
# # So now I have the boundaries of the frequencies I'm interested in in `fol` and `fou`.
# # What I'm looking for now is:
# #
# # * the first input band whose upper edge is greater than `fol`
# # * the last input band whose lower edge is less than `fou`.
# #
# # So, for the first input band whose upper edge is greater than `fol`, I should be able to do this:
# istart = searchsortedfirst(inbands_upper, fol)
# # For that, what if
# #
# # * All of `inbands_upper` are less than `fol`?
# # That would mean all of the `inband` frequencies are lower than and outside the current `outband`.
# # Then the docs for `searchsortedfirst` say that it will return `length(inbands_upper)+1`.
# # So if I started a view of the data from that index, it would obviously be empty, which is what I'd want.
# # * All of the `inbands_upper` are greater than `fol`?
# # Not necessarily a problem, unless, I guess, the lowest of `inbands_lower` is *also* greater than `fou`.
# # Then the entire input spectrum would be larger than this band.
# # But `searchsortedfirst` should just return `1`, and hopefully that would be the right thing.

# # Now I want the last input band whose lower edge is less than `fou`.
# # I should be able to get that from
# iend = searchsortedlast(inbands_lower, fou)
# # For that, what if
# #
# # * All of the `inbands_lower` are greater than `fou`?
# # That would mean all of the `inband` frequencies are greater than and outside the current `outband`.
# # The docs indicate `searchsortedlast` would return `firstindex(inbands_lower)-1` for that case, i.e. `0`.
# # That's what I'd want, I think.
# # * All of the `inbands_lower` are lower than `fou`?
# # Not necessarily a problem, unless the highest of `inbands_upper` are also lower than `fou`, which would mean the entire input spectrum is lower than this output band.


# # Now I have the first and last input bands relevant to this output band, and so I can start adding up the input PBS's contributions to this output band.
# # First, we need to check that there's something to do:
# # if (istart > n_inbands) || (iend < 1)
# # continue
# # else
# if (istart <= lastindex(pbs_in)) && (iend >= firstindex(pbs_in))
# # Get the time scaler associated with this PBS.
# scaler = time_scaler(pbs_in, period)

# # First, get the bandwidth of the first input band associated with this output band.
# fil_start = inbands_lower[istart]
# fiu_start = inbands_upper[istart]
# dfin_start = fiu_start - fil_start

# # Next, need to get the frequency overlap of the first input band and this output band.
# # For the lower edge of the overlap, it will usually be `fol`, unless there's a gap where `inbands_lower[istart]` is greater than `fol`.
# foverlapl_start = max(fol, fil_start)
# # For the upper edge of the overlap, it will usually be `fiu_start`, unless there's a gap where `inbands_upper[istart]` is less than `fou`.
# foverlapu_start = min(fou, fiu_start)

# # Now get the first band's contribution to the PBS.
# pbs_out[idx_out] += pbs_in[istart]/dfin_start*(foverlapu_start - foverlapl_start)*scaler

# # Now, think about the last band's contribution to the PBS.
# # First, we need to check if the first and last band are identicial, which would indicate that there's only one input band in this output band.
# if iend > istart
# # Now need to get the bandwidth associated with this input band.
# fil_end = inbands_lower[iend]
# fiu_end = inbands_upper[iend]
# dfin_end = fiu_end - fil_end

# # Next, need to get the frequency overlap of the last input band and this output band.
# foverlapl_end = max(fol, fil_end)
# foverlapu_end = min(fou, fiu_end)

# # Now we can get the last band's contribution to the PBS.
# pbs_out[idx_out] += pbs_in[iend]/dfin_end*(foverlapu_end - foverlapl_end)*scaler

# # Now we need the contribution of the input bands between `istart+1` and `iend-1`, inclusive.
# # Don't need to worry about incomplete overlap of the bands since these are "inside" this output band, so we can just directly sum them.
# pbs_in_v = @view pbs_in[istart+1:iend-1]
# pbs_out[idx_out] += sum(pbs_in_v)*scaler
# end
# end
# end
# end

# return ProportionalBandSpectrum(pbs_out, outcbands)
#end

"""
combine(pbs::AbstractArray{<:AbstractProportionalBandSpectrum,N}, outcbands::AbstractProportionalBands{NO,:center}) where {N}
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