315 lines
9.6 KiB
Julia
315 lines
9.6 KiB
Julia
module TxRxModels
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using Statistics
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using LinearAlgebra
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using StaticArrays
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export directivity_pattern,
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CardioidFamilyPattern,
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Omnidirectional,
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Subcardioid,
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Cardioid,
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Hypercardioid,
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Bidirectional
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export TxRx, TxRxArray
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export uniform_circle, fibonacci_sphere
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export linear_array, circular_array, fibonacci_array, physical_array
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abstract type AbstractDirectivityPattern end
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struct OmnidirectionalPattern <: AbstractDirectivityPattern end
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struct SubcardioidPattern <: AbstractDirectivityPattern end
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struct CardioidPattern <: AbstractDirectivityPattern end
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struct HypercardioidPattern <: AbstractDirectivityPattern end
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struct BidirectionalPattern <: AbstractDirectivityPattern end
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struct CardioidFamilyPattern{T<:Real} <: AbstractDirectivityPattern
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ρ::T
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function CardioidFamilyPattern(ρ::T) where {T<:Real}
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ρ < 0.0 && ρ > 1.0 && error("argument out of range, 0.0 ≤", ρ, " ≤ 1.0")
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new{T}(ρ)
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end
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end
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const Omnidirectional = OmnidirectionalPattern()
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const Subcardioid = SubcardioidPattern()
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const Cardioid = CardioidPattern()
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const Hypercardioid = HypercardioidPattern()
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const Bidirectional = BidirectionalPattern()
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abstract type AbstractTxRx end
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struct TxRx{T<:Real, D<:AbstractDirectivityPattern} <: AbstractTxRx
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position::SVector{3, T} # Position
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B::SMatrix{3, 3, T} # Orientation
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directivity::D # Directivity pattern
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noise::T # Noise floor [dB]
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end
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function TxRx(
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position,
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orientation=SMatrix{3,3}(1.0I),
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directivity_pattern=Omnidirectional,
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noise = -Inf
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)
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position = position |> SVector{3}
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orientation = orientation |> SMatrix{3, 3}
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TxRx(position, orientation, directivity_pattern, noise)
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end
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struct TxRxArray{T<:Real} <: AbstractTxRx
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txrx::Vector{<:TxRx{T}} # list of TxRxes in the local frame
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origin::SVector{3, T} # Position of the local origin in reference to the global origin
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B::SMatrix{3, 3, T} # Orientation of the array (local -> global)
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end
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function TxRxArray(
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txrx,
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origin=SVector{3}([0., 0., 0.]),
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orientation=SMatrix{3,3}(1.0I)
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)
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origin = origin |> SVector{3}
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TxRxArray(txrx, origin, orientation)
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end
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"""
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"""
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function cardioid_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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ρ::Real,
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)::Real
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r = [1., 0., 0.]
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ρ + (1-ρ) * r' * B' * d
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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txrx::TxRx,
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)::Real
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directivity_pattern(d, txrx.B, txrx.directivity)
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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dp::CardioidFamilyPattern,
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)::Real
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cardioid_pattern(d, B, dp.ρ)
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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::OmnidirectionalPattern,
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)::Real
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1
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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::SubcardioidPattern,
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)::Real
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cardioid_pattern(d, B, 0.75)
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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::CardioidPattern,
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)::Real
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cardioid_pattern(d, B, 0.50)
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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::HypercardioidPattern,
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)::Real
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cardioid_pattern(d, B, 0.25)
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end
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"""
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"""
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function directivity_pattern(
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d::SVector{3, <:Real},
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B::SMatrix{3, 3, <:Real},
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::BidirectionalPattern,
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)::Real
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cardioid_pattern(d, B, 0.00)
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end
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function uniform_circle(N::Integer)
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Δα = 2π / N
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[SVector{3}([cos(α), sin(α), 0]) for α ∈ 0:Δα:2π-Δα]
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end
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function fibonacci_sphere(N::Integer)
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function f(i, offset, up, N)
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y = i * offset - 1 + offset / 2
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r = sqrt(1 - y^2)
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ϕ = ((i + 1.0) % N) * up
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x = cos(ϕ) * r
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z = sin(ϕ) * r
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return SVector{3}([x, y, z])
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end
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offset = 2.0 / N
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up = π * (3.0 - √5.0)
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[f(i, offset, up, N) for i = 0:N-1]
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end
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function linear_array(N::Integer, L::Real)
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ΔL = L / (N - 1)
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L2 = L / 2
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[SVector{3}([x - L2, 0, 0]) for x ∈ 0.00:ΔL:(N-1)*ΔL]
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end
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function circular_array(N::Integer, r::Real)
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Δα = 2π / N
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[SVector{3}([r * cos(α), r * sin(α), 0]) for α ∈ 0:Δα:2π-Δα]
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end
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function square_array(N::I, M::I, Lx::T, Ly::T) where {I<:Integer, T<:Real}
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Δx, Δy = Lx / N, Ly / N
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p = [SVector{3}([Δx*i, Δy*j, 0.0]) for i = 1:N for j = 1:M]
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p .- [mean(p)]
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end
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function fibonacci_array(N::Integer, r::Real)
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P = fibonacci_sphere(N)
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[SVector{3}(r .* p) for p in P]
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end
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function tetrahedron_array(r=1.0)
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[
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SVector{3}([+1,+1,+1] * r / √3 ),
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SVector{3}([+1,-1,-1] * r / √3 ),
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SVector{3}([-1,+1,-1] * r / √3 ),
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SVector{3}([-1,-1,+1] * r / √3 ),
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]
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end
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physical_array = (
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matrix_voice = (
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cartesian = [
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SVector{3}([+0.00000, +0.00000, +0.00000]),
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SVector{3}([-0.03813, +0.00358, +0.00000]),
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SVector{3}([-0.02098, +0.03204, +0.00000]),
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SVector{3}([+0.01197, +0.03638, +0.00000]),
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SVector{3}([+0.03591, +0.01332, +0.00000]),
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SVector{3}([+0.03281, -0.01977, +0.00000]),
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SVector{3}([+0.00500, -0.03797, +0.00000]),
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SVector{3}([-0.02657, -0.02758, +0.00000]),
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],
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),
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respeaker_6mic = (
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cartesian = (
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SVector{3}([-0.02320, +0.04010, +0.00000]),
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SVector{3}([-0.04630, +0.00000, +0.00000]),
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SVector{3}([-0.02320, -0.04010, +0.00000]),
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SVector{3}([+0.02320, -0.04010, +0.00000]),
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SVector{3}([+0.04630, +0.00000, +0.00000]),
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SVector{3}([+0.02320, +0.04010, +0.00000]),
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),
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),
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em32 = let
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r = 0.042
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sph = [ # source: https://mhacoustics.com/sites/default/files/EigenmikeReleaseNotesV18.pdf
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# r, θ φ
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SVector{3}([r, 69, 0]), # Channel 01
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SVector{3}([r, 90, 32]), # Channel 02
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SVector{3}([r, 111, 0]), # Channel 03
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SVector{3}([r, 90, 328]), # Channel 04
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SVector{3}([r, 32, 0]), # Channel 05
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SVector{3}([r, 55, 45]), # Channel 06
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SVector{3}([r, 90, 69]), # Channel 07
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SVector{3}([r, 125, 45]), # Channel 08
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SVector{3}([r, 148, 0]), # Channel 09
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SVector{3}([r, 125, 315]), # Channel 10
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SVector{3}([r, 90, 291]), # Channel 11
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SVector{3}([r, 55, 315]), # Channel 12
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SVector{3}([r, 21, 91]), # Channel 13
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SVector{3}([r, 58, 90]), # Channel 14
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SVector{3}([r, 121, 90]), # Channel 15
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SVector{3}([r, 159, 89]), # Channel 16
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SVector{3}([r, 69, 180]), # Channel 17
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SVector{3}([r, 90, 212]), # Channel 18
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SVector{3}([r, 111, 180]), # Channel 19
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SVector{3}([r, 90, 148]), # Channel 20
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SVector{3}([r, 32, 180]), # Channel 21
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SVector{3}([r, 55, 225]), # Channel 22
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SVector{3}([r, 90, 249]), # Channel 23
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SVector{3}([r, 125, 225]), # Channel 24
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SVector{3}([r, 148, 180]), # Channel 25
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SVector{3}([r, 125, 135]), # Channel 26
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SVector{3}([r, 90, 111]), # Channel 27
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SVector{3}([r, 55, 135]), # Channel 28
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SVector{3}([r, 21, 269]), # Channel 29
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SVector{3}([r, 58, 270]), # Channel 30
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SVector{3}([r, 122, 270]), # Channel 31
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SVector{3}([r, 159, 271]), # Channel 32
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];
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d2r((r, θ, φ)) = (r, θ*π/180., φ*π/180.)
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s2c((r, θ, φ)) = (r*sin(θ)*cos(φ), r*sin(θ)*sin(φ), r*cos(θ))
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(cartesian = sph .|> d2r .|> s2c, spherical = sph)
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end,
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zylia_zm1 = let
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r = 0.049
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sph = [ # Source: SPARTA Array2SH v1.6.8 plug-in
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SVector{3}([r, +0.0000000000000000, +90.00000000000000]), # Channel 01
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SVector{3}([r, +0.1752158999443054, +48.14300537109375]), # Channel 02
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SVector{3}([r, +120.09252166748050, +48.13568878173828]), # Channel 03
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SVector{3}([r, -119.94072723388670, +48.17926788330078]), # Channel 04
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SVector{3}([r, -82.167846679687500, +19.42138671875000]), # Channel 05
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SVector{3}([r, -37.613956451416020, +19.43202972412109]), # Channel 06
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SVector{3}([r, +37.885848999023440, +19.41517066955566]), # Channel 07
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SVector{3}([r, +82.290664672851560, +19.42664337158203]), # Channel 08
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SVector{3}([r, +157.87617492675780, +19.43287277221680]), # Channel 09
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SVector{3}([r, -157.59960937500000, +19.43940162658691]), # Channel 10
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SVector{3}([r, -142.11413574218750, -19.41517066955566]), # Channel 11
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SVector{3}([r, -97.709327697753910, -19.42664337158203]), # Channel 12
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SVector{3}([r, -22.123807907104490, -19.43287277221680]), # Channel 13
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SVector{3}([r, +22.400377273559570, -19.43940162658691]), # Channel 14
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SVector{3}([r, +97.832138061523440, -19.42138671875000]), # Channel 15
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SVector{3}([r, +142.38603210449220, -19.43202972412109]), # Channel 16
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SVector{3}([r, -179.82476806640620, -48.14300537109375]), # Channel 17
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SVector{3}([r, -59.907478332519530, -48.13568878173828]), # Channel 18
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SVector{3}([r, +60.059268951416020, -48.17926788330078]), # Channel 19
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];
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d2r((r, θ, φ)) = SVector{3}([r, (θ+180)*π/180., (φ-90)*π/180.])
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s2c((r, φ, θ)) = SVector{3}([r*sin(θ)*cos(φ), r*sin(θ)*sin(φ), r*cos(θ)])
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(cartesian = sph .|> d2r .|> s2c, spherical = sph)
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end
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);
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end # module TxRxModels
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