I working on inverse problem which is rank deficient and for that i am using tikhonov regularization , for minization i am using lsqnoneg to resolve it which is giving me good result but now i have to enforce a condition in each iteration of minimzation of lsqnoneg, however lsqnoneg oterations are automatic i cant control it manually althohg i used fmincon but it is not giving me the same results can some one help what algorithm should i use so that i can enforce my conditon during optimization iterations and it gives results like lsqnoneg,
Tikh_Output.IA_recovered_line_1 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_1);
Tikh_Output.IA_recovered_line_2 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_2);
here is my codeI working on inverse problem which is rank deficient and for that i am using tikhonov regularization , for minization i am using lsqnoneg to resolve it which is giving me good result but now i have to enforce a condition in each iteration of minimzation of lsqnoneg, however lsqnoneg oterations are automatic i cant control it manually althohg i used fmincon but it is not giving me the same results can some one help what algorithm should i use so that i can enforce my conditon during optimization iterations and it gives results like lsqnoneg,
Tikh_Output.IA_recovered_line_1 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_1);
Tikh_Output.IA_recovered_line_2 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_2);
here is my code I working on inverse problem which is rank deficient and for that i am using tikhonov regularization , for minization i am using lsqnoneg to resolve it which is giving me good result but now i have to enforce a condition in each iteration of minimzation of lsqnoneg, however lsqnoneg oterations are automatic i cant control it manually althohg i used fmincon but it is not giving me the same results can some one help what algorithm should i use so that i can enforce my conditon during optimization iterations and it gives results like lsqnoneg,
Tikh_Output.IA_recovered_line_1 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_1);
Tikh_Output.IA_recovered_line_2 = lsqnonneg(Combined_Coeff_Matrix,Combined_projection_line_2);
here is my code lsqnoneg, tikhonov, matlab, enforcecondition MATLAB Answers — New Questions

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i need to find thee DFT,DTFT and DFS of a continuous time signal, x(t)=sin200pit+3cos100piti need to find thee DFT,DTFT and DFS of a continuous time signal, x(t)=sin200pit+3cos100pit i need to find thee DFT,DTFT and DFS of a continuous time signal, x(t)=sin200pit+3cos100pit dft, dtft, dfs MATLAB Answers — New Questions

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I am using the input from an mcc usb-231 daq to feed data into my simulink model through a function block. The issue I am running into is that when the simulation first starts up. it takes almost an entire minute before my simulation begins simulating through the desktop realtime kernal.

Here is my function block.
function output = fcn()
coder.extrinsic(‘daq’,’read’,’addinput’); %lets simulink know to read commands as MATLAB commands
d = daq(‘mcc’);
addinput(d,’Board0′,0,’Voltage’)
data = read(d,’OutputFormat’,’Matrix’);
output = zeros(1,1);
output = data(1,1);

Is there a way to get rid of this initialization buffer at the start?I am using the input from an mcc usb-231 daq to feed data into my simulink model through a function block. The issue I am running into is that when the simulation first starts up. it takes almost an entire minute before my simulation begins simulating through the desktop realtime kernal.

Here is my function block.
function output = fcn()
coder.extrinsic(‘daq’,’read’,’addinput’); %lets simulink know to read commands as MATLAB commands
d = daq(‘mcc’);
addinput(d,’Board0′,0,’Voltage’)
data = read(d,’OutputFormat’,’Matrix’);
output = zeros(1,1);
output = data(1,1);

Is there a way to get rid of this initialization buffer at the start? I am using the input from an mcc usb-231 daq to feed data into my simulink model through a function block. The issue I am running into is that when the simulation first starts up. it takes almost an entire minute before my simulation begins simulating through the desktop realtime kernal.

Here is my function block.
function output = fcn()
coder.extrinsic(‘daq’,’read’,’addinput’); %lets simulink know to read commands as MATLAB commands
d = daq(‘mcc’);
addinput(d,’Board0′,0,’Voltage’)
data = read(d,’OutputFormat’,’Matrix’);
output = zeros(1,1);
output = data(1,1);

Is there a way to get rid of this initialization buffer at the start? simulink, data acquisition, matlab MATLAB Answers — New Questions

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I want to convert AMESim software supported AMETable data (.data files) to Simulink Lookup tables suppoerted data. When I tried with the below code and applie to the N-D lookup table in simulink I am having the following error.
% ———————————————–
% This script is developed to convert the AMESim Looukp table to Simulink
% supported format.
% It supports the AMESim [ 1D, {2D, …. 8D}, T1D(Multi 1D),
% T3D (Multi M1D), XY tables conversion to Simulink format
% ———————————————–
% Input = "filename.data"
% Output = LUT —> is a structure
% —> LUT.BP.Breakpoint holds the Breakpoints data
% —> LUT.BP.Lenth holds the number of elements in each breakpoint
% —> LUT.BP.Table_data holds the table data

fname = uigetfile({‘*.data’;’*.txt’}, ‘Select the .data file for conversion’); % To get the file from the user
if fname == 0
error(‘User not selected the file for conversion’);
else
LUT = AMETable_2_Simulink(fname); % Function call to the conversion function
end

function LUT = AMETable_2_Simulink(fname)
fid = fopen(fname, "r", "ieee-le", "UTF-8");
file_data = fscanf(fid, ‘%c’);
delimited_file_data = strsplit(file_data, {‘n’})’; % Splitting the file data by using new line delimiter
fclose(fid);
LUT_Dimns = strtrim(extractAfter(delimited_file_data{1},"format:")); % Finding the Table format type
% Declaring the empty arrays
x_ele = []; y_ele = []; z_ele = []; T_ele = [];
x1 = []; x2 = []; x3 = []; tbl = [];
x = []; y = []; z = []; tbl_data = [];
LUT = struct;
switch LUT_Dimns

case ‘1D’
% For 1D AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i}) % Checking if it not an empty line
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1})) %
x = [x; split_line(1)]; % Breakpoints for the Lookup Table
tbl = [tbl; split_line(2)]; % Table for the Lookup Table
end
end
end
LUT.BP.Breakpoint = str2double(x)’;
LUT.Table_data = str2double(tbl)’;
case ‘T1D’
% For T1D AMETable —> 2D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})]; % Table for the Lookup Table
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Tabledata’}); % Converting array2table
y = sort(unique(x2));
x = sort(unique(x1));
% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% Asigning the Breakpoints & Table_data to the Structure
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);
case ‘T3D’
% For T3D AMETable —> 3D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
next_split_line = strsplit(strtrim(delimited_file_data{i + 1}));
if length(next_split_line{2}) <= 3
x3 = [x3; str2double(split_line{1})]; % Breakpoints3 for the Lookup Table
else
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
end
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})];
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
if ~eq(length(x3), length(x1))
intrpl_z = repelem(x3(end), (length(x1) – length(x3)))’;
x3 = [x3; intrpl_z]; % Breakpoints3 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, x3, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’}); % Converting array2table

z = sort(unique(x3)); y = sort(unique(x2)); x = sort(unique(x1)); % Sorting of the data

% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
for m = 1:length(z)
zz = z(m);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy & a2tbl.Z_axis == zz, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, zz, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
end

% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% nanLocations = isnan(manpltd_tbl.Tabledata);
% nanLinearIndexes = find(nanLocations);
% nonNanLinearIndexes = setdiff(1:numel(manpltd_tbl.Tabledata), nanLinearIndexes);

% Filling the missing MAPS with the nearest values of the MAPS
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(3).Breakpoint = unique(manpltd_tbl.Z_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.BP(3).Lenth = length(unique(manpltd_tbl.Z_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);

case ‘XY’
% For XY AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(delimited_file_data{i});
if ~isnan(str2double(split_line{2}))
x = [x; split_line{2}];
y = [y; split_line{3}];
z = [z; split_line{4}];
end
end
end
LUT.BP(1).Breakpoint = x;
LUT.BP(2).Breakpoint = y;
LUT.Table_data = z;
otherwise
% For {2D, 3D…. 8D] AMETable —> 4D Lookup Table
LUT_Dimns = str2double(deblank(extractBefore(LUT_Dimns, ‘D’)));
n = 1;
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line(~cellfun(‘isempty’,split_line))))
if (n <= LUT_Dimns)
if ~isfield(LUT, ‘BP’)
k = i;
end
for j = 1:LUT_Dimns
LUT.BP(n).Lenth = str2double(split_line(~cellfun(‘isempty’,split_line)));
split_BP = strsplit(delimited_file_data{i+LUT_Dimns});
LUT.BP(n).Breakpoint = str2double(split_BP(~cellfun(‘isempty’,split_BP)));
break
end
n = n+1;
elseif i >= ( k + 2*LUT_Dimns)
line_table_data = str2double(split_line(~cellfun(‘isempty’,split_line)));
tbl = [tbl; line_table_data];
end
end
end
end
for j = 1:size(tbl, 1)
if j == 1
conv_table_dta = transpose(tbl(j, :));
else
TransCol = transpose(tbl(j, :));
conv_table_dta = [conv_table_dta; TransCol];
end
end
LUT.Table_data = reshape(conv_table_dta, LUT.BP(:).Lenth);
end
endI want to convert AMESim software supported AMETable data (.data files) to Simulink Lookup tables suppoerted data. When I tried with the below code and applie to the N-D lookup table in simulink I am having the following error.
% ———————————————–
% This script is developed to convert the AMESim Looukp table to Simulink
% supported format.
% It supports the AMESim [ 1D, {2D, …. 8D}, T1D(Multi 1D),
% T3D (Multi M1D), XY tables conversion to Simulink format
% ———————————————–
% Input = "filename.data"
% Output = LUT —> is a structure
% —> LUT.BP.Breakpoint holds the Breakpoints data
% —> LUT.BP.Lenth holds the number of elements in each breakpoint
% —> LUT.BP.Table_data holds the table data

fname = uigetfile({‘*.data’;’*.txt’}, ‘Select the .data file for conversion’); % To get the file from the user
if fname == 0
error(‘User not selected the file for conversion’);
else
LUT = AMETable_2_Simulink(fname); % Function call to the conversion function
end

function LUT = AMETable_2_Simulink(fname)
fid = fopen(fname, "r", "ieee-le", "UTF-8");
file_data = fscanf(fid, ‘%c’);
delimited_file_data = strsplit(file_data, {‘n’})’; % Splitting the file data by using new line delimiter
fclose(fid);
LUT_Dimns = strtrim(extractAfter(delimited_file_data{1},"format:")); % Finding the Table format type
% Declaring the empty arrays
x_ele = []; y_ele = []; z_ele = []; T_ele = [];
x1 = []; x2 = []; x3 = []; tbl = [];
x = []; y = []; z = []; tbl_data = [];
LUT = struct;
switch LUT_Dimns

case ‘1D’
% For 1D AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i}) % Checking if it not an empty line
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1})) %
x = [x; split_line(1)]; % Breakpoints for the Lookup Table
tbl = [tbl; split_line(2)]; % Table for the Lookup Table
end
end
end
LUT.BP.Breakpoint = str2double(x)’;
LUT.Table_data = str2double(tbl)’;
case ‘T1D’
% For T1D AMETable —> 2D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})]; % Table for the Lookup Table
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Tabledata’}); % Converting array2table
y = sort(unique(x2));
x = sort(unique(x1));
% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% Asigning the Breakpoints & Table_data to the Structure
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);
case ‘T3D’
% For T3D AMETable —> 3D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
next_split_line = strsplit(strtrim(delimited_file_data{i + 1}));
if length(next_split_line{2}) <= 3
x3 = [x3; str2double(split_line{1})]; % Breakpoints3 for the Lookup Table
else
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
end
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})];
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
if ~eq(length(x3), length(x1))
intrpl_z = repelem(x3(end), (length(x1) – length(x3)))’;
x3 = [x3; intrpl_z]; % Breakpoints3 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, x3, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’}); % Converting array2table

z = sort(unique(x3)); y = sort(unique(x2)); x = sort(unique(x1)); % Sorting of the data

% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
for m = 1:length(z)
zz = z(m);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy & a2tbl.Z_axis == zz, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, zz, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
end

% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% nanLocations = isnan(manpltd_tbl.Tabledata);
% nanLinearIndexes = find(nanLocations);
% nonNanLinearIndexes = setdiff(1:numel(manpltd_tbl.Tabledata), nanLinearIndexes);

% Filling the missing MAPS with the nearest values of the MAPS
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(3).Breakpoint = unique(manpltd_tbl.Z_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.BP(3).Lenth = length(unique(manpltd_tbl.Z_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);

case ‘XY’
% For XY AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(delimited_file_data{i});
if ~isnan(str2double(split_line{2}))
x = [x; split_line{2}];
y = [y; split_line{3}];
z = [z; split_line{4}];
end
end
end
LUT.BP(1).Breakpoint = x;
LUT.BP(2).Breakpoint = y;
LUT.Table_data = z;
otherwise
% For {2D, 3D…. 8D] AMETable —> 4D Lookup Table
LUT_Dimns = str2double(deblank(extractBefore(LUT_Dimns, ‘D’)));
n = 1;
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line(~cellfun(‘isempty’,split_line))))
if (n <= LUT_Dimns)
if ~isfield(LUT, ‘BP’)
k = i;
end
for j = 1:LUT_Dimns
LUT.BP(n).Lenth = str2double(split_line(~cellfun(‘isempty’,split_line)));
split_BP = strsplit(delimited_file_data{i+LUT_Dimns});
LUT.BP(n).Breakpoint = str2double(split_BP(~cellfun(‘isempty’,split_BP)));
break
end
n = n+1;
elseif i >= ( k + 2*LUT_Dimns)
line_table_data = str2double(split_line(~cellfun(‘isempty’,split_line)));
tbl = [tbl; line_table_data];
end
end
end
end
for j = 1:size(tbl, 1)
if j == 1
conv_table_dta = transpose(tbl(j, :));
else
TransCol = transpose(tbl(j, :));
conv_table_dta = [conv_table_dta; TransCol];
end
end
LUT.Table_data = reshape(conv_table_dta, LUT.BP(:).Lenth);
end
end I want to convert AMESim software supported AMETable data (.data files) to Simulink Lookup tables suppoerted data. When I tried with the below code and applie to the N-D lookup table in simulink I am having the following error.
% ———————————————–
% This script is developed to convert the AMESim Looukp table to Simulink
% supported format.
% It supports the AMESim [ 1D, {2D, …. 8D}, T1D(Multi 1D),
% T3D (Multi M1D), XY tables conversion to Simulink format
% ———————————————–
% Input = "filename.data"
% Output = LUT —> is a structure
% —> LUT.BP.Breakpoint holds the Breakpoints data
% —> LUT.BP.Lenth holds the number of elements in each breakpoint
% —> LUT.BP.Table_data holds the table data

fname = uigetfile({‘*.data’;’*.txt’}, ‘Select the .data file for conversion’); % To get the file from the user
if fname == 0
error(‘User not selected the file for conversion’);
else
LUT = AMETable_2_Simulink(fname); % Function call to the conversion function
end

function LUT = AMETable_2_Simulink(fname)
fid = fopen(fname, "r", "ieee-le", "UTF-8");
file_data = fscanf(fid, ‘%c’);
delimited_file_data = strsplit(file_data, {‘n’})’; % Splitting the file data by using new line delimiter
fclose(fid);
LUT_Dimns = strtrim(extractAfter(delimited_file_data{1},"format:")); % Finding the Table format type
% Declaring the empty arrays
x_ele = []; y_ele = []; z_ele = []; T_ele = [];
x1 = []; x2 = []; x3 = []; tbl = [];
x = []; y = []; z = []; tbl_data = [];
LUT = struct;
switch LUT_Dimns

case ‘1D’
% For 1D AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i}) % Checking if it not an empty line
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1})) %
x = [x; split_line(1)]; % Breakpoints for the Lookup Table
tbl = [tbl; split_line(2)]; % Table for the Lookup Table
end
end
end
LUT.BP.Breakpoint = str2double(x)’;
LUT.Table_data = str2double(tbl)’;
case ‘T1D’
% For T1D AMETable —> 2D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})]; % Table for the Lookup Table
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Tabledata’}); % Converting array2table
y = sort(unique(x2));
x = sort(unique(x1));
% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% Asigning the Breakpoints & Table_data to the Structure
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);
case ‘T3D’
% For T3D AMETable —> 3D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line{1}))
if length(split_line{2}) <= 3
next_split_line = strsplit(strtrim(delimited_file_data{i + 1}));
if length(next_split_line{2}) <= 3
x3 = [x3; str2double(split_line{1})]; % Breakpoints3 for the Lookup Table
else
x2 = [x2; str2double(split_line{1})]; % Breakpoints2 for the Lookup Table
end
else
x1 = [x1; str2double(split_line{1})]; % Breakpoints1 for the Lookup Table
tbl = [tbl; str2double(split_line{2})];
if ~eq(length(x2), length(x1))
intrpl_y = repelem(x2(end), (length(x1) – length(x2)))’;
x2 = [x2; intrpl_y]; % Breakpoints2 for the Lookup Table
end
if ~eq(length(x3), length(x1))
intrpl_z = repelem(x3(end), (length(x1) – length(x3)))’;
x3 = [x3; intrpl_z]; % Breakpoints3 for the Lookup Table
end
end
end
end
end

arr = [x1, x2, x3, tbl]; % Creating an array of all the data
a2tbl = array2table(arr, ‘VariableNames’, {‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’}); % Converting array2table

z = sort(unique(x3)); y = sort(unique(x2)); x = sort(unique(x1)); % Sorting of the data

% Sorting the data in ascending order and assing the NAN values to the missing MAPS
for k = 1:length(x)
xx = x(k);
for l = 1:length(y)
yy = y(l);
for m = 1:length(z)
zz = z(m);
table_indxed = a2tbl(a2tbl.X_axis == xx & a2tbl.Y_axis == yy & a2tbl.Z_axis == zz, :);
if isempty(table_indxed)
table_indxed = table(xx, yy, zz, NaN, ‘VariableNames’, …
{‘X_axis’, ‘Y_axis’, ‘Z_axis’, ‘Tabledata’});
end
if ~exist(‘manpltd_tbl’, ‘var’)
manpltd_tbl = table_indxed;
else
manpltd_tbl = [manpltd_tbl; table_indxed];
end
end
end
end

% Filling the missing MAPS with the nearest values of the MAPS
manpltd_tbl.Tabledata = fillmissing(manpltd_tbl.Tabledata, ‘nearest’);
% nanLocations = isnan(manpltd_tbl.Tabledata);
% nanLinearIndexes = find(nanLocations);
% nonNanLinearIndexes = setdiff(1:numel(manpltd_tbl.Tabledata), nanLinearIndexes);

% Filling the missing MAPS with the nearest values of the MAPS
LUT.BP(1).Breakpoint = unique(manpltd_tbl.X_axis);
LUT.BP(2).Breakpoint = unique(manpltd_tbl.Y_axis);
LUT.BP(3).Breakpoint = unique(manpltd_tbl.Z_axis);
LUT.BP(1).Lenth = length(unique(manpltd_tbl.X_axis));
LUT.BP(2).Lenth = length(unique(manpltd_tbl.Y_axis));
LUT.BP(3).Lenth = length(unique(manpltd_tbl.Z_axis));
LUT.Table_data = reshape(manpltd_tbl.Tabledata, LUT.BP(:).Lenth);

case ‘XY’
% For XY AMETable —> 1D Lookup Table
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(delimited_file_data{i});
if ~isnan(str2double(split_line{2}))
x = [x; split_line{2}];
y = [y; split_line{3}];
z = [z; split_line{4}];
end
end
end
LUT.BP(1).Breakpoint = x;
LUT.BP(2).Breakpoint = y;
LUT.Table_data = z;
otherwise
% For {2D, 3D…. 8D] AMETable —> 4D Lookup Table
LUT_Dimns = str2double(deblank(extractBefore(LUT_Dimns, ‘D’)));
n = 1;
for i = 2:length(delimited_file_data)
if ~isempty(delimited_file_data{i})
split_line = strsplit(strtrim(delimited_file_data{i}));
if ~isnan(str2double(split_line(~cellfun(‘isempty’,split_line))))
if (n <= LUT_Dimns)
if ~isfield(LUT, ‘BP’)
k = i;
end
for j = 1:LUT_Dimns
LUT.BP(n).Lenth = str2double(split_line(~cellfun(‘isempty’,split_line)));
split_BP = strsplit(delimited_file_data{i+LUT_Dimns});
LUT.BP(n).Breakpoint = str2double(split_BP(~cellfun(‘isempty’,split_BP)));
break
end
n = n+1;
elseif i >= ( k + 2*LUT_Dimns)
line_table_data = str2double(split_line(~cellfun(‘isempty’,split_line)));
tbl = [tbl; line_table_data];
end
end
end
end
for j = 1:size(tbl, 1)
if j == 1
conv_table_dta = transpose(tbl(j, :));
else
TransCol = transpose(tbl(j, :));
conv_table_dta = [conv_table_dta; TransCol];
end
end
LUT.Table_data = reshape(conv_table_dta, LUT.BP(:).Lenth);
end
end siemens – amesim, amesim, co-simulation, data exchange MATLAB Answers — New Questions

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openDRIVE(.xodr) 파일을 로드러너에 import 시 도로 형상이 깨집니다.
테스트 겸 직접 제작한 도로를 .xodr 포맷으로 추출 후 해당 파일을 로드러너에 올려도 상기 첨부 사진과 같이 도로 형상이 깨지는데 해결 방법이 있을까요.
When I import an openDRIVE (.xodr) file into my simulation software, the road geometry appears distorted. Even when I export a road that I created myself in .xodr format and load it into the simulation software, the road shape gets corrupted as shown in the attached images. Is there a solution to this issue?openDRIVE(.xodr) 파일을 로드러너에 import 시 도로 형상이 깨집니다.
테스트 겸 직접 제작한 도로를 .xodr 포맷으로 추출 후 해당 파일을 로드러너에 올려도 상기 첨부 사진과 같이 도로 형상이 깨지는데 해결 방법이 있을까요.
When I import an openDRIVE (.xodr) file into my simulation software, the road geometry appears distorted. Even when I export a road that I created myself in .xodr format and load it into the simulation software, the road shape gets corrupted as shown in the attached images. Is there a solution to this issue? openDRIVE(.xodr) 파일을 로드러너에 import 시 도로 형상이 깨집니다.
테스트 겸 직접 제작한 도로를 .xodr 포맷으로 추출 후 해당 파일을 로드러너에 올려도 상기 첨부 사진과 같이 도로 형상이 깨지는데 해결 방법이 있을까요.
When I import an openDRIVE (.xodr) file into my simulation software, the road geometry appears distorted. Even when I export a road that I created myself in .xodr format and load it into the simulation software, the road shape gets corrupted as shown in the attached images. Is there a solution to this issue? xodr, import MATLAB Answers — New Questions

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