I do not want any dynamic memory allocation to be done in the C++ codegen. Here is the relevant Matlab code:
% Calculate cross-correlation matrix from a set of vectors (whose length
% can vary from one call to another). All 4 channels will have the length.
function [R] = xcorr_matrix(ch0,ch1,ch2,ch3,channelCount)

% channelCount is 2 or 4
% R is either 2×2 or 4×4 complex double matrix.
% ch0 … ch3 are complex single vectors.

N = int32(size(ch0,1));

% Convert ch0, …, ch3 to complex double
x_in = coder.nullcopy(complex(zeros(N,channelCount,’double’)));
switch channelCount
case 2
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
case 4
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
x_in(1:N,3) = ch2(1:N);
x_in(1:N,4) = ch3(1:N);
end

R = (x_in’ * x_in); % Compute cross-correlation matrix
Here is the C++ codegen result:
void xcorr_matrix(const creal32_T ch0_data[], const int ch0_size[1], % all the 4 ch_size will be the same value
const creal32_T ch1_data[], const int ch1_size[1],
const creal32_T ch2_data[], const int ch2_size[1],
const creal32_T ch3_data[], const int ch3_size[1],
int channelCount,
::coder::array<creal_T, 2U> &R)
{
::coder::array<creal_T, 2U> x_in;
R.set_size(channelCount, channelCount);
x_in.set_size(N, channelCount);
…
}
I think I can eliminate the x_in.set_size by not using x_in, and replace the matrix multiply with nested for-loops and using double casting; but am unsure how to define R (either 2×2 or 4×4) so as to remove the R.set_size allocations.
One idea I had was to try making R a fixed length 16 element vector, and just use 4 elements for the 2×2 R, and all 16 for the 4×4 R. Would be nicer to be able to use two indices for rows and columns.
Thanks in advance for your help.
PaulI do not want any dynamic memory allocation to be done in the C++ codegen. Here is the relevant Matlab code:
% Calculate cross-correlation matrix from a set of vectors (whose length
% can vary from one call to another). All 4 channels will have the length.
function [R] = xcorr_matrix(ch0,ch1,ch2,ch3,channelCount)

% channelCount is 2 or 4
% R is either 2×2 or 4×4 complex double matrix.
% ch0 … ch3 are complex single vectors.

N = int32(size(ch0,1));

% Convert ch0, …, ch3 to complex double
x_in = coder.nullcopy(complex(zeros(N,channelCount,’double’)));
switch channelCount
case 2
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
case 4
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
x_in(1:N,3) = ch2(1:N);
x_in(1:N,4) = ch3(1:N);
end

R = (x_in’ * x_in); % Compute cross-correlation matrix
Here is the C++ codegen result:
void xcorr_matrix(const creal32_T ch0_data[], const int ch0_size[1], % all the 4 ch_size will be the same value
const creal32_T ch1_data[], const int ch1_size[1],
const creal32_T ch2_data[], const int ch2_size[1],
const creal32_T ch3_data[], const int ch3_size[1],
int channelCount,
::coder::array<creal_T, 2U> &R)
{
::coder::array<creal_T, 2U> x_in;
R.set_size(channelCount, channelCount);
x_in.set_size(N, channelCount);
…
}
I think I can eliminate the x_in.set_size by not using x_in, and replace the matrix multiply with nested for-loops and using double casting; but am unsure how to define R (either 2×2 or 4×4) so as to remove the R.set_size allocations.
One idea I had was to try making R a fixed length 16 element vector, and just use 4 elements for the 2×2 R, and all 16 for the 4×4 R. Would be nicer to be able to use two indices for rows and columns.
Thanks in advance for your help.
Paul I do not want any dynamic memory allocation to be done in the C++ codegen. Here is the relevant Matlab code:
% Calculate cross-correlation matrix from a set of vectors (whose length
% can vary from one call to another). All 4 channels will have the length.
function [R] = xcorr_matrix(ch0,ch1,ch2,ch3,channelCount)

% channelCount is 2 or 4
% R is either 2×2 or 4×4 complex double matrix.
% ch0 … ch3 are complex single vectors.

N = int32(size(ch0,1));

% Convert ch0, …, ch3 to complex double
x_in = coder.nullcopy(complex(zeros(N,channelCount,’double’)));
switch channelCount
case 2
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
case 4
x_in(1:N,1) = ch0(1:N);
x_in(1:N,2) = ch1(1:N);
x_in(1:N,3) = ch2(1:N);
x_in(1:N,4) = ch3(1:N);
end

R = (x_in’ * x_in); % Compute cross-correlation matrix
Here is the C++ codegen result:
void xcorr_matrix(const creal32_T ch0_data[], const int ch0_size[1], % all the 4 ch_size will be the same value
const creal32_T ch1_data[], const int ch1_size[1],
const creal32_T ch2_data[], const int ch2_size[1],
const creal32_T ch3_data[], const int ch3_size[1],
int channelCount,
::coder::array<creal_T, 2U> &R)
{
::coder::array<creal_T, 2U> x_in;
R.set_size(channelCount, channelCount);
x_in.set_size(N, channelCount);
…
}
I think I can eliminate the x_in.set_size by not using x_in, and replace the matrix multiply with nested for-loops and using double casting; but am unsure how to define R (either 2×2 or 4×4) so as to remove the R.set_size allocations.
One idea I had was to try making R a fixed length 16 element vector, and just use 4 elements for the 2×2 R, and all 16 for the 4×4 R. Would be nicer to be able to use two indices for rows and columns.
Thanks in advance for your help.
Paul matlab, codegen, embedded coder, c++, dynamic memory allocation MATLAB Answers — New Questions

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