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function dataout = iomega(datain, dt, datain_type, dataout_type)
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%
% IOMEGA is a MATLAB script for converting displacement, velocity, or
% acceleration time-series to either displacement, velocity, or
% acceleration times-series. The script takes an array of waveform data
% (datain), transforms into the frequency-domain in order to more easily
% convert into desired output form, and then converts back into the time
% domain resulting in output (dataout) that is converted into the desired
% form.
%
% Variables:
% ----------
%
% datain = input waveform data of type datain_type
%
% dataout = output waveform data of type dataout_type
%
% dt = time increment (units of seconds per sample)
%
% 1 - Displacement
% datain_type = 2 - Velocity
% 3 - Acceleration
%
% 1 - Displacement
% dataout_type = 2 - Velocity
% 3 - Acceleration
%
%
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% Make sure that datain_type and dataout_type are either 1, 2 or 3
if (datain_type < 1 || datain_type > 3)
error('Value for datain_type must be a 1, 2 or 3');
elseif (dataout_type < 1 || dataout_type > 3)
error('Value for dataout_type must be a 1, 2 or 3');
end
% Determine Number of points (next power of 2), frequency increment
% and Nyquist frequency
N = 2^nextpow2(max(size(datain)));
df = 1/(N*dt);
Nyq = 1/(2*dt);
% Save frequency array
iomega_array = 1i*2*pi*(-Nyq : df : Nyq-df);
iomega_exp = dataout_type - datain_type;
% Pad datain array with zeros (if needed)
size1 = size(datain,1);
size2 = size(datain,2);
if (N-size1 ~= 0 && N-size2 ~= 0)
if size1 > size2
datain = vertcat(datain,zeros(N-size1,1));
else
datain = horzcat(datain,zeros(1,N-size2));
end
end
% Transform datain into frequency domain via FFT and shift output (A)
% so that zero-frequency amplitude is in the middle of the array
% (instead of the beginning)
A = fft(datain);
A = fftshift(A);
% Convert datain of type datain_type to type dataout_type
for j = 1 : N
if iomega_array(j) ~= 0
A(j) = A(j) * (iomega_array(j) ^ iomega_exp);
else
A(j) = complex(0.0,0.0);
end
end
% Shift new frequency-amplitude array back to MATLAB format and
% transform back into the time domain via the inverse FFT.
A = ifftshift(A);
datain = ifft(A);
% Remove zeros that were added to datain in order to pad to next
% biggerst power of 2 and return dataout.
if size1 > size2
dataout = real(datain(1:size1,size2));
else
dataout = real(datain(size1,1:size2));
end
return |