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Commit 40586023 authored by Achilles Kappis's avatar Achilles Kappis
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Add function to calculate signals from ideal point sources in the time domain

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Sound Fields/MATLAB/Functions/ptSrcFieldTD.m 0 → 100644
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%% Signal generated by point sources in the time-domain
% --------------------------------------------------
% Author: Achilles Kappis
% e-mail: axilleaz@protonmail.com
%
% Date: 13/09/2024 (DD/MM/YYYY)
%
% Copyright: MIT
% --------------------------------------------------
% Functionality: Calculate the signals generated by ideal point sources in
% the time-domain.
% --------------------------------------------------
% Input
%
% sPos [numeric]: The Cartesian coordinates of the source positions. This
% must be an Nx3 matrix where N is the number of sources.
%
% rPos [numeric]: The Cartesian coordinates of the receiver positions. This
% must be an Mx3 matrix where M is the number of receivers.
%
% fs [numeric]: The sampling frequency. This is required in order to
% calculate the time-of-flight in samples and must be a
% positive real scalar.
%
% Q [numeric] (Optional): The source signals. This can be either an IxNxJ
% array, where I is the length of the source
% signals in samples and J is the number of
% trials/sound field realisations, or a real
% positive integer denoting the length of the
% source signals. In case the length of the source
% signals is given, the generated signals are
% zero-mean, (approximately) uniformly distributed
% and normalised to unity. [Default: 128].
%
% nTrials [numeric] (Optional): This is the number of trials/sound field
% realisations that will be generated. If "Q"
% is provided, this argument is ignored. It
% must be a positive real scalar.
% [Default: 1]
%
% c [numeric] (Optional): The speed of sound. [Default: 343].
%
% --------------------------------------------------
% Output
%
% rSig [numeric]: The signals at the receiver positions for all
% trials/sournd field realisations. This is an IxMxJ array.
%
% rSigMean [numeric]: The signals at the receiver positions averaged over
% all trials/sound field realisations. This is an IxM
% matrix.
%
% rSigMtx [numeric]: The signals at each receiver position due to each
% source for each trial/sound field realisation. This is
% an IxMxNxJ array.
%
% rSigMtxMean [numeric]: The signals at each receiver position due to each
% source averaged over the trials/sound field
% realisations. This is an IxMxN array.
%
% --------------------------------------------------
% Notes
%
% - It is the responsibility of the user to pick (or provide) adequately
% long source signals
%
% --------------------------------------------------
function [rSig, rSigMean, rSigMtx, rSigMtxMean] = ptSrcFieldTD(sPos, rPos, fs, Q, nTrials, c)
% ====================================================
% Check for number of arguments
% ====================================================
narginchk(3, 6);
nargoutchk(0, 4);
% ====================================================
% Validate input arguments
% ====================================================
% Validate mandatory arguments
validateattributes(sPos, "numeric", {'2d', 'real', 'nonnan', 'nonempty', 'finite', 'ncols', 3}, mfilename, "Cartesian coordinates of the source positions", 1);
validateattributes(rPos, "numeric", {'2d', 'real', 'nonnan', 'nonempty', 'finite', 'ncols', 3}, mfilename, "Cartesian coordinates of the receiver positions", 2);
validateattributes(fs, "numeric", {'scalar', 'real', 'nonnan', 'nonempty', 'finite', 'positive'}, mfilename, "The sampling frequency", 3);
% Validate optional arguments
if nargin > 3 && ~isempty(Q)
if isscalar(Q)
validateattributes(Q, "numeric", {'scalar', 'real', 'nonnan', 'nonempty', 'finite', 'positive', 'integer'}, mfilename, "Length of source signals in samples", 4);
else
validateattributes(Q, "numeric", {'3d', 'real', 'nonnan', 'nonempty', 'finite', 'ncols', size(sPos, 1)}, mfilename, "Source signals", 4);
nTrials = size(Q, 3);
end
else
Q = 128;
end
if nargin > 4 && ~isempty(nTrials) && isscalar(Q)
validateattributes(nTrials, "numeric", {'scalar', 'positive', 'nonnan', 'nonempty', 'finite'}, mfilename, "Number of trials/sound field realisations", 5);
elseif nargin > 4 && isempty(nTrials)
nTrials = 1;
end
if nargin > 5 && ~isempty(c)
validateattributes(c, "numeric", {'scalar', 'nonempty', 'nonnan', 'finite', 'real', 'positive'}, mfilename, "The speed of sound", 6);
else
c = 343;
end
% ====================================================
% Pre-process data
% ====================================================
% Generate source signals
if isscalar(Q)
Q = rand(Q, size(sPos, 1), nTrials);
Q = Q - mean(Q);
Q = Q./max(abs(Q));
end
% Calculate source-receiver distances
dist = twoPtDist(sPos, rPos); % Distances
del = dist/c; % Delays in seconds
% ====================================================
% Calculate signals
% ====================================================
% Go through the trials/sound field realisations
for jIdx = size(Q, 3):-1:1
% Go through the sources (calculate for all receivers in one go)
for sIdx = size(dist, 1):-1:1
rSigMtx(:, :, sIdx, jIdx) = (1./dist(sIdx, :)) .* delayseq(Q(:, sIdx, jIdx), del(sIdx, :), fs);
end
end
% Sum source signals at each receiver position
rSig = squeeze(sum(rSigMtx, 3));
% ====================================================
% Calculate output arguments
% ====================================================
% Mean receiver signal over all trials/sound field realisations
if nargout > 1
rSigMean = squeeze(mean(rSig, 3));
end
% Mean receiver signal due to each source over all trials/sound field realisations
if nargout > 3
rSigMtxMean = squeeze(mean(rSigMtx, 4));
end
end
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