77 lines
1.9 KiB
Julia
77 lines
1.9 KiB
Julia
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module WASN
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using LinearAlgebra
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using DSP: conv
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using TxRxModels
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using ..RoomAcoustics: AbstractRoom, AbstractRIRConfig, ISM
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export Node, Event
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export synth_events
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struct Node
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rx::TxRxArray
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fs::Real
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δ::Real
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end
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function Node(rx, δ=0.0)
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Node(rx, δ)
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end
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struct Event
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tx::TxRx
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emission::Real
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fs::Real
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signal::AbstractVector
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end
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function synth_events(
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nodes::AbstractVector{<:Node},
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events::AbstractVector{<:Event},
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room::AbstractRoom,
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rir_config::AbstractRIRConfig,
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)
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hs = [ISM(nodes[i].rx, events[j].tx, room, rir_config) for i in eachindex(nodes), j in eachindex(events)]
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s = [[conv(h, events[j].signal) for h in hs[i, j]] for i in eachindex(nodes), j in eachindex(events)]
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(signals=s, hs=hs)
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end
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function synthesise(
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nodes::AbstractVector{<:Node},
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events::AbstractVector{<:Event},
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room::AbstractRoom,
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rir_config::AbstractRIRConfig,
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)
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# WARN: THIS FUNCTION ASSUMES NOW THAT ALL sampling rates are the same.
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fs = first(nodes).fs
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# Synthesise individual events for given nodes
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e_signals, h_s = synth_events(nodes, events, room, rir_config)
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# Find length of the output signal
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δ_max = [node.δ for node ∈ nodes] |> maximum;
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N = [ceil(Int, (events[j].emission + δ_max)*fs) + length(e_signals[1, j][1]) for j ∈ eachindex(events)] |> maximum
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# Allocate memory for output signals
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output = [zeros(N, node.rx.p |> length) for node ∈ nodes]
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for i ∈ eachindex(nodes), j ∈ eachindex(events)
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shift_n = floor(Int, (events[j].emission + nodes[i].δ)*fs)
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event = e_signals[i,j]
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for (idx, channel) in enumerate(event)
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output[i][shift_n:shift_n+length(channel)-1, idx] .= channel
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end
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end
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return (
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node_output = output,
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event_signals = e_signals,
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h = h_s,
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)
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end
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end # module WASN
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