right now the code is at an increment of 15 to test, but the final incremment will be 0.01
code needs to have an if statement within the while loop.

%range is the maximum achievable horizontal distance
% range angle is the angle that yields the maximum horizontaal distance
% use a whilel loop with a nested if statement to compute the maximum
% landing distance (range) ange the angle corrsesponding to the maximum
% landing distance (rangle angle) of the ME En 1010 ping pong cannon

function [range, rangeAngle] = ProjectileRange(d1, d2, v0)
thetaL = 90;
range = 0;
rangeAngle = 0;
[xLand] = LandingDistance(d1, d2, v0, thetaL);
while thetaL <= 90;
if xLand > range
range = xLand
rangeAngle = thetaL
end
thetaL = thetaL + 15;
end
end
%% test
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
[range, rangeAngle] = ProjectileRange(d1, d2, v0);
fprintf(‘The range is %.2f m at a launch angle of %.2f degrees’, range, rangeAngle)

this is what it prints:
The range is 0.00 m at a launch angle of 0.00 degrees>>

I need it to print "the range is 1.29 m at a launch angle of 41.6 degrees" when it has an incrememnt of 0.01right now the code is at an increment of 15 to test, but the final incremment will be 0.01
code needs to have an if statement within the while loop.

%range is the maximum achievable horizontal distance
% range angle is the angle that yields the maximum horizontaal distance
% use a whilel loop with a nested if statement to compute the maximum
% landing distance (range) ange the angle corrsesponding to the maximum
% landing distance (rangle angle) of the ME En 1010 ping pong cannon

function [range, rangeAngle] = ProjectileRange(d1, d2, v0)
thetaL = 90;
range = 0;
rangeAngle = 0;
[xLand] = LandingDistance(d1, d2, v0, thetaL);
while thetaL <= 90;
if xLand > range
range = xLand
rangeAngle = thetaL
end
thetaL = thetaL + 15;
end
end
%% test
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
[range, rangeAngle] = ProjectileRange(d1, d2, v0);
fprintf(‘The range is %.2f m at a launch angle of %.2f degrees’, range, rangeAngle)

this is what it prints:
The range is 0.00 m at a launch angle of 0.00 degrees>>

I need it to print "the range is 1.29 m at a launch angle of 41.6 degrees" when it has an incrememnt of 0.01 right now the code is at an increment of 15 to test, but the final incremment will be 0.01
code needs to have an if statement within the while loop.

%range is the maximum achievable horizontal distance
% range angle is the angle that yields the maximum horizontaal distance
% use a whilel loop with a nested if statement to compute the maximum
% landing distance (range) ange the angle corrsesponding to the maximum
% landing distance (rangle angle) of the ME En 1010 ping pong cannon

function [range, rangeAngle] = ProjectileRange(d1, d2, v0)
thetaL = 90;
range = 0;
rangeAngle = 0;
[xLand] = LandingDistance(d1, d2, v0, thetaL);
while thetaL <= 90;
if xLand > range
range = xLand
rangeAngle = thetaL
end
thetaL = thetaL + 15;
end
end
%% test
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
[range, rangeAngle] = ProjectileRange(d1, d2, v0);
fprintf(‘The range is %.2f m at a launch angle of %.2f degrees’, range, rangeAngle)

this is what it prints:
The range is 0.00 m at a launch angle of 0.00 degrees>>

I need it to print "the range is 1.29 m at a launch angle of 41.6 degrees" when it has an incrememnt of 0.01 while/if loop, answer is 0 when it should be a value MATLAB Answers — New Questions

​

Hi!
I am encountering a problem when I am trying to deploy a TFLite mode for semantic segmentation on Raspberry Pi. I was following this example by following openExample(‘deeplearning_shared/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample’)
Before running this example, I have installed the TFLite library on both the local Windows computer directly under "C:tensorflow-2.15.0" following this link:
https://www.mathworks.com/matlabcentral/answers/1631265-matlab-coder-how-do-i-build-tensorflow-lite-for-deep-learning-c-code-generation-and-deployment
and Raspberry Pi 4b (buster; 32bit OS) under "/home/pi/tensorflow/tensorflow/" following this:
https://qengineering.eu/install-tensorflow-2-lite-on-raspberry-pi-4.html
Additionally, the environment variables are set on both the local and raspi machines according to:
https://www.mathworks.com/help/deeplearning/ug/prerequisites-for-deep-learning-with-tensorflow-lite-models.html

While I had no problem with generating the MEX file on the local Windows computer with this section of codes in the example:
cfg = coder.config(‘mex’);
cfg.TargetLang = ‘C++’;
codegen -config cfg tflite_semantic_predict -args ones(257, 257,3,’single’)
I encountered errors when I tried to generate the MEX PIL function through
cfg = coder.config(‘lib’,’ecoder’,true);
cfg.TargetLang = ‘C++’;
cfg.VerificationMode = ‘PIL’;
hw = coder.hardware(‘Raspberry Pi’);
cfg.Hardware = hw;
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
I have attached the entire error message in the txt file. Part of the error message reads:
fatal error: kernels/register.h: No such file or directory
#include "kernels/register.h"
However, when I searched the directories indicated by the environment variables, I could find the kernels/register.h file on both the Windows and RPi machines under the PATH (in Windows) or LD_LIBRARY_PATH (in RPi) variables. Please see the attached screenshots.
Here is how I set the environmental variables. On RPI, I executed:
export TFLITE_PATH="/home/pi/tensorflow/tensorflow"
export LD_LIBRARY_PATH="/home/pi/tensorflow/tensorflow/tensorflow/lite"
export TFLITE_MODEL_PATH="/home/pi"
and on Windows, I directly edited the environmental variable TFLITE_PATH and amended Path variable.
I’d appreciate any advice on how to resolve this missing header file issue by MATLAB coder.
Thank you all!Hi!
I am encountering a problem when I am trying to deploy a TFLite mode for semantic segmentation on Raspberry Pi. I was following this example by following openExample(‘deeplearning_shared/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample’)
Before running this example, I have installed the TFLite library on both the local Windows computer directly under "C:tensorflow-2.15.0" following this link:
https://www.mathworks.com/matlabcentral/answers/1631265-matlab-coder-how-do-i-build-tensorflow-lite-for-deep-learning-c-code-generation-and-deployment
and Raspberry Pi 4b (buster; 32bit OS) under "/home/pi/tensorflow/tensorflow/" following this:
https://qengineering.eu/install-tensorflow-2-lite-on-raspberry-pi-4.html
Additionally, the environment variables are set on both the local and raspi machines according to:
https://www.mathworks.com/help/deeplearning/ug/prerequisites-for-deep-learning-with-tensorflow-lite-models.html

While I had no problem with generating the MEX file on the local Windows computer with this section of codes in the example:
cfg = coder.config(‘mex’);
cfg.TargetLang = ‘C++’;
codegen -config cfg tflite_semantic_predict -args ones(257, 257,3,’single’)
I encountered errors when I tried to generate the MEX PIL function through
cfg = coder.config(‘lib’,’ecoder’,true);
cfg.TargetLang = ‘C++’;
cfg.VerificationMode = ‘PIL’;
hw = coder.hardware(‘Raspberry Pi’);
cfg.Hardware = hw;
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
I have attached the entire error message in the txt file. Part of the error message reads:
fatal error: kernels/register.h: No such file or directory
#include "kernels/register.h"
However, when I searched the directories indicated by the environment variables, I could find the kernels/register.h file on both the Windows and RPi machines under the PATH (in Windows) or LD_LIBRARY_PATH (in RPi) variables. Please see the attached screenshots.
Here is how I set the environmental variables. On RPI, I executed:
export TFLITE_PATH="/home/pi/tensorflow/tensorflow"
export LD_LIBRARY_PATH="/home/pi/tensorflow/tensorflow/tensorflow/lite"
export TFLITE_MODEL_PATH="/home/pi"
and on Windows, I directly edited the environmental variable TFLITE_PATH and amended Path variable.
I’d appreciate any advice on how to resolve this missing header file issue by MATLAB coder.
Thank you all! Hi!
I am encountering a problem when I am trying to deploy a TFLite mode for semantic segmentation on Raspberry Pi. I was following this example by following openExample(‘deeplearning_shared/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample’)
Before running this example, I have installed the TFLite library on both the local Windows computer directly under "C:tensorflow-2.15.0" following this link:
https://www.mathworks.com/matlabcentral/answers/1631265-matlab-coder-how-do-i-build-tensorflow-lite-for-deep-learning-c-code-generation-and-deployment
and Raspberry Pi 4b (buster; 32bit OS) under "/home/pi/tensorflow/tensorflow/" following this:
https://qengineering.eu/install-tensorflow-2-lite-on-raspberry-pi-4.html
Additionally, the environment variables are set on both the local and raspi machines according to:
https://www.mathworks.com/help/deeplearning/ug/prerequisites-for-deep-learning-with-tensorflow-lite-models.html

While I had no problem with generating the MEX file on the local Windows computer with this section of codes in the example:
cfg = coder.config(‘mex’);
cfg.TargetLang = ‘C++’;
codegen -config cfg tflite_semantic_predict -args ones(257, 257,3,’single’)
I encountered errors when I tried to generate the MEX PIL function through
cfg = coder.config(‘lib’,’ecoder’,true);
cfg.TargetLang = ‘C++’;
cfg.VerificationMode = ‘PIL’;
hw = coder.hardware(‘Raspberry Pi’);
cfg.Hardware = hw;
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
I have attached the entire error message in the txt file. Part of the error message reads:
fatal error: kernels/register.h: No such file or directory
#include "kernels/register.h"
However, when I searched the directories indicated by the environment variables, I could find the kernels/register.h file on both the Windows and RPi machines under the PATH (in Windows) or LD_LIBRARY_PATH (in RPi) variables. Please see the attached screenshots.
Here is how I set the environmental variables. On RPI, I executed:
export TFLITE_PATH="/home/pi/tensorflow/tensorflow"
export LD_LIBRARY_PATH="/home/pi/tensorflow/tensorflow/tensorflow/lite"
export TFLITE_MODEL_PATH="/home/pi"
and on Windows, I directly edited the environmental variable TFLITE_PATH and amended Path variable.
I’d appreciate any advice on how to resolve this missing header file issue by MATLAB coder.
Thank you all! tflite, raspberry pi, deploy, semantic segmentation MATLAB Answers — New Questions

​

%% problem 2
% user-defined function to compute the horizontal distance
% traveled by a projectile knowing the launch angle, the initial velocity,
% and geometric parameters defining the initial coordinates of the projectile.
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
thetaL = 50;
g = 9.81; % gravitational acceleration in m/s^2

% call initial coords function and initial velocity function
[x0, y0] = InitialCoords(d1, d2, thetaL); % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL); % input units: m/s de,grees, output units: m/s

%Solve the y equation for tLand by calling your Quadratic function.
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
root = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root;

% plug tLand into the x eqn to get xLand
xLand = LandingDistance(d1, d2, v0, thetaL);
fprintf(‘For launch angle = %.1f degrees and v0 = %.1f m/s, the landing distance is %.2f m n’, thetaL, v0, xLand)

Error using LandingDistance
Too many output arguments.

Error in HW3_projectile (line 36)
xLand = LandingDistance(d1, d2, v0, thetaL);
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_____________________________________
function code
% landing distance function
function LandingDistance(d1, d2, v0, thetaL)
% x_Land –> the horizontal distance traveled by the projectile
g = 9.81; % gravitational acceleration in m/s^2
[x0, y0] = InitialCoords(d1, d2, thetaL) % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL) % input units: m/s de,grees, output units: m/s
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
[root] = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root
xLand = x0 + (v0x*tLand)
end

Not enough input arguments.

Error in LandingDistance (line 6)
[x0, y0] = InitialCoords(d1, d2, thetaL)
^^

>>%% problem 2
% user-defined function to compute the horizontal distance
% traveled by a projectile knowing the launch angle, the initial velocity,
% and geometric parameters defining the initial coordinates of the projectile.
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
thetaL = 50;
g = 9.81; % gravitational acceleration in m/s^2

% call initial coords function and initial velocity function
[x0, y0] = InitialCoords(d1, d2, thetaL); % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL); % input units: m/s de,grees, output units: m/s

%Solve the y equation for tLand by calling your Quadratic function.
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
root = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root;

% plug tLand into the x eqn to get xLand
xLand = LandingDistance(d1, d2, v0, thetaL);
fprintf(‘For launch angle = %.1f degrees and v0 = %.1f m/s, the landing distance is %.2f m n’, thetaL, v0, xLand)

Error using LandingDistance
Too many output arguments.

Error in HW3_projectile (line 36)
xLand = LandingDistance(d1, d2, v0, thetaL);
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_____________________________________
function code
% landing distance function
function LandingDistance(d1, d2, v0, thetaL)
% x_Land –> the horizontal distance traveled by the projectile
g = 9.81; % gravitational acceleration in m/s^2
[x0, y0] = InitialCoords(d1, d2, thetaL) % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL) % input units: m/s de,grees, output units: m/s
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
[root] = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root
xLand = x0 + (v0x*tLand)
end

Not enough input arguments.

Error in LandingDistance (line 6)
[x0, y0] = InitialCoords(d1, d2, thetaL)
^^

>> %% problem 2
% user-defined function to compute the horizontal distance
% traveled by a projectile knowing the launch angle, the initial velocity,
% and geometric parameters defining the initial coordinates of the projectile.
d1 = 0.0876;
d2 = 0.1190;
v0 = 3.2;
thetaL = 50;
g = 9.81; % gravitational acceleration in m/s^2

% call initial coords function and initial velocity function
[x0, y0] = InitialCoords(d1, d2, thetaL); % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL); % input units: m/s de,grees, output units: m/s

%Solve the y equation for tLand by calling your Quadratic function.
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
root = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root;

% plug tLand into the x eqn to get xLand
xLand = LandingDistance(d1, d2, v0, thetaL);
fprintf(‘For launch angle = %.1f degrees and v0 = %.1f m/s, the landing distance is %.2f m n’, thetaL, v0, xLand)

Error using LandingDistance
Too many output arguments.

Error in HW3_projectile (line 36)
xLand = LandingDistance(d1, d2, v0, thetaL);
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_____________________________________
function code
% landing distance function
function LandingDistance(d1, d2, v0, thetaL)
% x_Land –> the horizontal distance traveled by the projectile
g = 9.81; % gravitational acceleration in m/s^2
[x0, y0] = InitialCoords(d1, d2, thetaL) % input units: m, m, degrees, output units: m
[v0x, v0y] = InitialVelocityComponents(v0, thetaL) % input units: m/s de,grees, output units: m/s
a = -0.5*g; % g = acceleration due to gravity in m/s^2
b = v0y; % initial velocity in y direction
c = y0; % initial y position
plusOrMinus = -1;
[root] = Quadratic(a, b, c, plusOrMinus); % neg root
tLand = root
xLand = x0 + (v0x*tLand)
end

Not enough input arguments.

Error in LandingDistance (line 6)
[x0, y0] = InitialCoords(d1, d2, thetaL)
^^

>> error, not enough inputs, too many outputs MATLAB Answers — New Questions

​

Hello everyone,
I’m planning a new PC build and am currently undecided about which CPU to choose.
I understand that AMD CPUs have faced some slower performance in MATLAB due to Intel MKL but I understand it was solved with the AMD AOCL? Bench instruction results also seem to show a performance difference between Intel and AMD CPUs (but couldn’t check too many).
Intel CPUs seem to have some issues which probably have been solved for 14th gen with the new BIOS updates, and 15th gen is not quite mature. Their power dissipation is quite high.
For MATLAB, I plan to use the Parallel Computing and Optimization Toolboxes. Apart from MATLAB, ANSYS or other FEA software will be the most demanding applications, and I also plan to game from time to time.
I will pair this with an RTX3070 for the moment.
I was looking at the following CPUs:
Intel Ultra 7 265k – $230 / $600
Intel I9 14900k – $390 / $650
AMD Ryzen 7 9800x3D – $474 / $750
AMD Ryzen 7 9950X – $570 /$910
(Prices listed are current and include discounts, with $ CPU / $ CPU+Mobo+RAM)
Thank you!Hello everyone,
I’m planning a new PC build and am currently undecided about which CPU to choose.
I understand that AMD CPUs have faced some slower performance in MATLAB due to Intel MKL but I understand it was solved with the AMD AOCL? Bench instruction results also seem to show a performance difference between Intel and AMD CPUs (but couldn’t check too many).
Intel CPUs seem to have some issues which probably have been solved for 14th gen with the new BIOS updates, and 15th gen is not quite mature. Their power dissipation is quite high.
For MATLAB, I plan to use the Parallel Computing and Optimization Toolboxes. Apart from MATLAB, ANSYS or other FEA software will be the most demanding applications, and I also plan to game from time to time.
I will pair this with an RTX3070 for the moment.
I was looking at the following CPUs:
Intel Ultra 7 265k – $230 / $600
Intel I9 14900k – $390 / $650
AMD Ryzen 7 9800x3D – $474 / $750
AMD Ryzen 7 9950X – $570 /$910
(Prices listed are current and include discounts, with $ CPU / $ CPU+Mobo+RAM)
Thank you! Hello everyone,
I’m planning a new PC build and am currently undecided about which CPU to choose.
I understand that AMD CPUs have faced some slower performance in MATLAB due to Intel MKL but I understand it was solved with the AMD AOCL? Bench instruction results also seem to show a performance difference between Intel and AMD CPUs (but couldn’t check too many).
Intel CPUs seem to have some issues which probably have been solved for 14th gen with the new BIOS updates, and 15th gen is not quite mature. Their power dissipation is quite high.
For MATLAB, I plan to use the Parallel Computing and Optimization Toolboxes. Apart from MATLAB, ANSYS or other FEA software will be the most demanding applications, and I also plan to game from time to time.
I will pair this with an RTX3070 for the moment.
I was looking at the following CPUs:
Intel Ultra 7 265k – $230 / $600
Intel I9 14900k – $390 / $650
AMD Ryzen 7 9800x3D – $474 / $750
AMD Ryzen 7 9950X – $570 /$910
(Prices listed are current and include discounts, with $ CPU / $ CPU+Mobo+RAM)
Thank you! parallel computing toolbox, optimization, pc build, intel vs amd, cpu MATLAB Answers — New Questions

​

I’m looking for suggestions on how to approach a Simulink interface problem.
In case 1 below, both dashboard buttons have connections to constant S1 such that if you change either button, the other button will track.
In case 2 I’m looking to do something similar but with a constant and a button. If I entered 0b0 for desired state, then S2 would change to zero, and the button would shift to A. If I moved the button to B, then S2 would change back to 1, and Desired State would also change to 0b1.
This is a simplified test case of a more complex scenario I want to work up, where there is one binary input (e.g. 0b01010), and 5 buttons, and 5 constants.
In one direction, I could use a matlab function to call set_param if the binary input is changed to set the value of S2. But I am unsure about the other direction.I’m looking for suggestions on how to approach a Simulink interface problem.
In case 1 below, both dashboard buttons have connections to constant S1 such that if you change either button, the other button will track.
In case 2 I’m looking to do something similar but with a constant and a button. If I entered 0b0 for desired state, then S2 would change to zero, and the button would shift to A. If I moved the button to B, then S2 would change back to 1, and Desired State would also change to 0b1.
This is a simplified test case of a more complex scenario I want to work up, where there is one binary input (e.g. 0b01010), and 5 buttons, and 5 constants.
In one direction, I could use a matlab function to call set_param if the binary input is changed to set the value of S2. But I am unsure about the other direction. I’m looking for suggestions on how to approach a Simulink interface problem.
In case 1 below, both dashboard buttons have connections to constant S1 such that if you change either button, the other button will track.
In case 2 I’m looking to do something similar but with a constant and a button. If I entered 0b0 for desired state, then S2 would change to zero, and the button would shift to A. If I moved the button to B, then S2 would change back to 1, and Desired State would also change to 0b1.
This is a simplified test case of a more complex scenario I want to work up, where there is one binary input (e.g. 0b01010), and 5 buttons, and 5 constants.
In one direction, I could use a matlab function to call set_param if the binary input is changed to set the value of S2. But I am unsure about the other direction. simulink, dashboard, buttons, interface MATLAB Answers — New Questions

​

I’m getting an error at the following line:
options = optimoptions(‘ga’,’PopulationSize’,10,’MaxGenerations’,10);
The following message exemplifies the problem.
I’m using the version 9.10 (R2021a) of MATLAB and the version 4.5 (R2021a) of the Global Optimization Toolbox

Any suggestions will be appreciatedI’m getting an error at the following line:
options = optimoptions(‘ga’,’PopulationSize’,10,’MaxGenerations’,10);
The following message exemplifies the problem.
I’m using the version 9.10 (R2021a) of MATLAB and the version 4.5 (R2021a) of the Global Optimization Toolbox

Any suggestions will be appreciated I’m getting an error at the following line:
options = optimoptions(‘ga’,’PopulationSize’,10,’MaxGenerations’,10);
The following message exemplifies the problem.
I’m using the version 9.10 (R2021a) of MATLAB and the version 4.5 (R2021a) of the Global Optimization Toolbox

Any suggestions will be appreciated #unrecognized, optimoptions, #ga MATLAB Answers — New Questions

​

Hello everone,
I have a complex model which takes very long time to be built, too much time in simulation & may cause MATLAB to crash.
In my last trial, the CPU load was around 89% & memory usage was 90%.
I want to know what specs should I have to simulate large & complex model easily without heavy loading & taking much time, my currently specs are: CPU: 13th Gen Intel® Core™ i5-1335U 1.3 GHz // RAM: 16 GB DDR4 3200 MHz // GPU: Intel® Iris® Xe Graphics Family.Hello everone,
I have a complex model which takes very long time to be built, too much time in simulation & may cause MATLAB to crash.
In my last trial, the CPU load was around 89% & memory usage was 90%.
I want to know what specs should I have to simulate large & complex model easily without heavy loading & taking much time, my currently specs are: CPU: 13th Gen Intel® Core™ i5-1335U 1.3 GHz // RAM: 16 GB DDR4 3200 MHz // GPU: Intel® Iris® Xe Graphics Family. Hello everone,
I have a complex model which takes very long time to be built, too much time in simulation & may cause MATLAB to crash.
In my last trial, the CPU load was around 89% & memory usage was 90%.
I want to know what specs should I have to simulate large & complex model easily without heavy loading & taking much time, my currently specs are: CPU: 13th Gen Intel® Core™ i5-1335U 1.3 GHz // RAM: 16 GB DDR4 3200 MHz // GPU: Intel® Iris® Xe Graphics Family. simulation, simulink, matlab, specs, cpu load, model, complex MATLAB Answers — New Questions

​

I got this kind of model with S-Function Builder as shown in this image.

But When I build it, I got this error.
#’smex_builder.cpp’
was created successfully

###’smex_builder_wrapper.cpp’
was created successfully

###’smex_builder.tlc’
was created successfully
????? smex_builder.lib ??????? smex_builder.exp ???? smex_builder_wrapper.obj : error LNK2019: ?????????? OrtGetApiBase ??? "void __cdecl `dynamic initializer for ‘public: static struct OrtApi const * const Ort::Global::api_”(void)" (??__E?api_@?$Global@X@Ort@@2PEBUOrtApi@@EB@@YAXXZ) ???????? smex_builder.mexw64 : fatal error LNK1120: 1 ??????????

Also, I set parameter tab and library tab like this.
[Port and parameter] tab

[library] tab

I run " mex -setup C++" command and it shows Visual Studio 2022.
I use attached ONNX model as zip file.(out_modified_empty_model.onnx)
Structure of my onnx is like this.

Do you happen to know the solution?
I’m not sure about why this error… I’d be happy if you could give me any advice.

For your information,
I tried this C++ code in S-Function Builder Editor, but I can not figure out what is the cause and where I am missing.

#include "mex.h"
#include <math.h>
#include <onnxruntime_cxx_api.h>
#include <vector>
#include <memory>

extern std::unique_ptrOrt::Env g_env;
extern std::unique_ptrOrt::Session g_session;
extern std::vector<const char> g_input_node_names;
extern std::vector<const char*> g_output_node_names;

void smex_builder_Start_wrapper(void)
{

try {

g_env = std::make_uniqueOrt::Env(ORT_LOGGING_LEVEL_WARNING, "test");

Ort::SessionOptions session_options;
session_options.SetIntraOpNumThreads(1);
session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_EXTENDED);

const wchar_t model_path = L"out_modified_empty_model.onnx";
g_session = std::make_uniqueOrt::Session(g_env, model_path, session_options);

Ort::AllocatorWithDefaultOptions allocator;

size_t num_input_nodes = g_session->GetInputCount();
g_input_node_names.resize(num_input_nodes);
for (size_t i = 0; i < num_input_nodes; i++) {
auto input_name = g_session->GetInputNameAllocated(i, allocator);
g_input_node_names[i] = input_name.get();
}

size_t num_output_nodes = g_session->GetOutputCount();
g_output_node_names.resize(num_output_nodes);
for (size_t i = 0; i < num_output_nodes; i++) {
auto output_name = g_session->GetOutputNameAllocated(i, allocator);
g_output_node_names[i] = output_name.get();
}
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:InitError", "初期化エラー: %s", ex.what());
}

}

void smex_builder_Outputs_wrapper(const real_T *u0,
const real_T *u1,
const real_T *u2,
const real_T *u3,
const real_T *u4,
const real_T *u5,
const real_T *u6,
real_T *y0,
real_T y1)
{

mexErrMsgIdAndTxt("mySfunc:TestError", "mexErrMsgIdAndTxt のテストエラー");

try {

std::vector<float> input_data(7);

input_data[0] = static_cast<float>(*u0);
input_data[1] = static_cast<float>(*u1);
input_data[2] = static_cast<float>(*u2);
input_data[3] = static_cast<float>(*u3);
input_data[4] = static_cast<float>(u4);
input_data[5] = static_cast<float>(u5);
input_data[6] = static_cast<float>(u6);

std::vector<int64_t> input_shape = { 1, 7 };
Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
Ort::Value input_tensor = Ort::Value::CreateTensor<float>(
memory_info,
input_data.data(),
input_data.size(),
input_shape.data(),
input_shape.size()
);

auto output_tensors = g_session->Run(
Ort::RunOptions{ nullptr },
g_input_node_names.data(),
&input_tensor,
1,
g_output_node_names.data(),
g_output_node_names.size()
);

// Assuming your model outputs two tensors.
if (output_tensors.size() != 2) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"モデルは2つのテンソルを出力する必要があります。");
}

// Check the shape of the first output tensor.
float output_data0 = output_tensors[0].GetTensorMutableData<float>();
auto type_info0 = output_tensors[0].GetTensorTypeAndShapeInfo();
auto output_shape0 = type_info0.GetShape();

if (output_shape0.size() != 2 || output_shape0[0] != 1 || output_shape0[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル0の形状が不正です。期待される形状: (1, 1)");
}

// Check the shape of the second output tensor.
float output_data1 = output_tensors[1].GetTensorMutableData<float>();
auto type_info1 = output_tensors[1].GetTensorTypeAndShapeInfo();
auto output_shape1 = type_info1.GetShape();

if (output_shape1.size() != 2 || output_shape1[0] != 1 || output_shape1[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル1の形状が不正です。期待される形状: (1, 1)");
}
// Simulink出力ポートへの書き込み
y0[0] = static_cast<double>(output_data0[0]); // y0 に最初の出力
y1[0] = static_cast<double>(output_data1[0]); // y1 に2番目の出力
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:RuntimeError", "実行時エラー: %s", ex.what());
}

}

void smex_builder_Terminate_wrapper(void)
{

g_session.reset();
g_env.reset();
g_input_node_names.clear();
g_output_node_names.clear();

}I got this kind of model with S-Function Builder as shown in this image.

But When I build it, I got this error.
#’smex_builder.cpp’
was created successfully

###’smex_builder_wrapper.cpp’
was created successfully

###’smex_builder.tlc’
was created successfully
????? smex_builder.lib ??????? smex_builder.exp ???? smex_builder_wrapper.obj : error LNK2019: ?????????? OrtGetApiBase ??? "void __cdecl `dynamic initializer for ‘public: static struct OrtApi const * const Ort::Global::api_”(void)" (??__E?api_@?$Global@X@Ort@@2PEBUOrtApi@@EB@@YAXXZ) ???????? smex_builder.mexw64 : fatal error LNK1120: 1 ??????????

Also, I set parameter tab and library tab like this.
[Port and parameter] tab

[library] tab

I run " mex -setup C++" command and it shows Visual Studio 2022.
I use attached ONNX model as zip file.(out_modified_empty_model.onnx)
Structure of my onnx is like this.

Do you happen to know the solution?
I’m not sure about why this error… I’d be happy if you could give me any advice.

For your information,
I tried this C++ code in S-Function Builder Editor, but I can not figure out what is the cause and where I am missing.

#include "mex.h"
#include <math.h>
#include <onnxruntime_cxx_api.h>
#include <vector>
#include <memory>

extern std::unique_ptrOrt::Env g_env;
extern std::unique_ptrOrt::Session g_session;
extern std::vector<const char> g_input_node_names;
extern std::vector<const char*> g_output_node_names;

void smex_builder_Start_wrapper(void)
{

try {

g_env = std::make_uniqueOrt::Env(ORT_LOGGING_LEVEL_WARNING, "test");

Ort::SessionOptions session_options;
session_options.SetIntraOpNumThreads(1);
session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_EXTENDED);

const wchar_t model_path = L"out_modified_empty_model.onnx";
g_session = std::make_uniqueOrt::Session(g_env, model_path, session_options);

Ort::AllocatorWithDefaultOptions allocator;

size_t num_input_nodes = g_session->GetInputCount();
g_input_node_names.resize(num_input_nodes);
for (size_t i = 0; i < num_input_nodes; i++) {
auto input_name = g_session->GetInputNameAllocated(i, allocator);
g_input_node_names[i] = input_name.get();
}

size_t num_output_nodes = g_session->GetOutputCount();
g_output_node_names.resize(num_output_nodes);
for (size_t i = 0; i < num_output_nodes; i++) {
auto output_name = g_session->GetOutputNameAllocated(i, allocator);
g_output_node_names[i] = output_name.get();
}
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:InitError", "初期化エラー: %s", ex.what());
}

}

void smex_builder_Outputs_wrapper(const real_T *u0,
const real_T *u1,
const real_T *u2,
const real_T *u3,
const real_T *u4,
const real_T *u5,
const real_T *u6,
real_T *y0,
real_T y1)
{

mexErrMsgIdAndTxt("mySfunc:TestError", "mexErrMsgIdAndTxt のテストエラー");

try {

std::vector<float> input_data(7);

input_data[0] = static_cast<float>(*u0);
input_data[1] = static_cast<float>(*u1);
input_data[2] = static_cast<float>(*u2);
input_data[3] = static_cast<float>(*u3);
input_data[4] = static_cast<float>(u4);
input_data[5] = static_cast<float>(u5);
input_data[6] = static_cast<float>(u6);

std::vector<int64_t> input_shape = { 1, 7 };
Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
Ort::Value input_tensor = Ort::Value::CreateTensor<float>(
memory_info,
input_data.data(),
input_data.size(),
input_shape.data(),
input_shape.size()
);

auto output_tensors = g_session->Run(
Ort::RunOptions{ nullptr },
g_input_node_names.data(),
&input_tensor,
1,
g_output_node_names.data(),
g_output_node_names.size()
);

// Assuming your model outputs two tensors.
if (output_tensors.size() != 2) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"モデルは2つのテンソルを出力する必要があります。");
}

// Check the shape of the first output tensor.
float output_data0 = output_tensors[0].GetTensorMutableData<float>();
auto type_info0 = output_tensors[0].GetTensorTypeAndShapeInfo();
auto output_shape0 = type_info0.GetShape();

if (output_shape0.size() != 2 || output_shape0[0] != 1 || output_shape0[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル0の形状が不正です。期待される形状: (1, 1)");
}

// Check the shape of the second output tensor.
float output_data1 = output_tensors[1].GetTensorMutableData<float>();
auto type_info1 = output_tensors[1].GetTensorTypeAndShapeInfo();
auto output_shape1 = type_info1.GetShape();

if (output_shape1.size() != 2 || output_shape1[0] != 1 || output_shape1[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル1の形状が不正です。期待される形状: (1, 1)");
}
// Simulink出力ポートへの書き込み
y0[0] = static_cast<double>(output_data0[0]); // y0 に最初の出力
y1[0] = static_cast<double>(output_data1[0]); // y1 に2番目の出力
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:RuntimeError", "実行時エラー: %s", ex.what());
}

}

void smex_builder_Terminate_wrapper(void)
{

g_session.reset();
g_env.reset();
g_input_node_names.clear();
g_output_node_names.clear();

} I got this kind of model with S-Function Builder as shown in this image.

But When I build it, I got this error.
#’smex_builder.cpp’
was created successfully

###’smex_builder_wrapper.cpp’
was created successfully

###’smex_builder.tlc’
was created successfully
????? smex_builder.lib ??????? smex_builder.exp ???? smex_builder_wrapper.obj : error LNK2019: ?????????? OrtGetApiBase ??? "void __cdecl `dynamic initializer for ‘public: static struct OrtApi const * const Ort::Global::api_”(void)" (??__E?api_@?$Global@X@Ort@@2PEBUOrtApi@@EB@@YAXXZ) ???????? smex_builder.mexw64 : fatal error LNK1120: 1 ??????????

Also, I set parameter tab and library tab like this.
[Port and parameter] tab

[library] tab

I run " mex -setup C++" command and it shows Visual Studio 2022.
I use attached ONNX model as zip file.(out_modified_empty_model.onnx)
Structure of my onnx is like this.

Do you happen to know the solution?
I’m not sure about why this error… I’d be happy if you could give me any advice.

For your information,
I tried this C++ code in S-Function Builder Editor, but I can not figure out what is the cause and where I am missing.

#include "mex.h"
#include <math.h>
#include <onnxruntime_cxx_api.h>
#include <vector>
#include <memory>

extern std::unique_ptrOrt::Env g_env;
extern std::unique_ptrOrt::Session g_session;
extern std::vector<const char> g_input_node_names;
extern std::vector<const char*> g_output_node_names;

void smex_builder_Start_wrapper(void)
{

try {

g_env = std::make_uniqueOrt::Env(ORT_LOGGING_LEVEL_WARNING, "test");

Ort::SessionOptions session_options;
session_options.SetIntraOpNumThreads(1);
session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_EXTENDED);

const wchar_t model_path = L"out_modified_empty_model.onnx";
g_session = std::make_uniqueOrt::Session(g_env, model_path, session_options);

Ort::AllocatorWithDefaultOptions allocator;

size_t num_input_nodes = g_session->GetInputCount();
g_input_node_names.resize(num_input_nodes);
for (size_t i = 0; i < num_input_nodes; i++) {
auto input_name = g_session->GetInputNameAllocated(i, allocator);
g_input_node_names[i] = input_name.get();
}

size_t num_output_nodes = g_session->GetOutputCount();
g_output_node_names.resize(num_output_nodes);
for (size_t i = 0; i < num_output_nodes; i++) {
auto output_name = g_session->GetOutputNameAllocated(i, allocator);
g_output_node_names[i] = output_name.get();
}
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:InitError", "初期化エラー: %s", ex.what());
}

}

void smex_builder_Outputs_wrapper(const real_T *u0,
const real_T *u1,
const real_T *u2,
const real_T *u3,
const real_T *u4,
const real_T *u5,
const real_T *u6,
real_T *y0,
real_T y1)
{

mexErrMsgIdAndTxt("mySfunc:TestError", "mexErrMsgIdAndTxt のテストエラー");

try {

std::vector<float> input_data(7);

input_data[0] = static_cast<float>(*u0);
input_data[1] = static_cast<float>(*u1);
input_data[2] = static_cast<float>(*u2);
input_data[3] = static_cast<float>(*u3);
input_data[4] = static_cast<float>(u4);
input_data[5] = static_cast<float>(u5);
input_data[6] = static_cast<float>(u6);

std::vector<int64_t> input_shape = { 1, 7 };
Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
Ort::Value input_tensor = Ort::Value::CreateTensor<float>(
memory_info,
input_data.data(),
input_data.size(),
input_shape.data(),
input_shape.size()
);

auto output_tensors = g_session->Run(
Ort::RunOptions{ nullptr },
g_input_node_names.data(),
&input_tensor,
1,
g_output_node_names.data(),
g_output_node_names.size()
);

// Assuming your model outputs two tensors.
if (output_tensors.size() != 2) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"モデルは2つのテンソルを出力する必要があります。");
}

// Check the shape of the first output tensor.
float output_data0 = output_tensors[0].GetTensorMutableData<float>();
auto type_info0 = output_tensors[0].GetTensorTypeAndShapeInfo();
auto output_shape0 = type_info0.GetShape();

if (output_shape0.size() != 2 || output_shape0[0] != 1 || output_shape0[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル0の形状が不正です。期待される形状: (1, 1)");
}

// Check the shape of the second output tensor.
float output_data1 = output_tensors[1].GetTensorMutableData<float>();
auto type_info1 = output_tensors[1].GetTensorTypeAndShapeInfo();
auto output_shape1 = type_info1.GetShape();

if (output_shape1.size() != 2 || output_shape1[0] != 1 || output_shape1[1] != 1) {
mexErrMsgIdAndTxt("myOnnxSfunc:OutputError",
"出力テンソル1の形状が不正です。期待される形状: (1, 1)");
}
// Simulink出力ポートへの書き込み
y0[0] = static_cast<double>(output_data0[0]); // y0 に最初の出力
y1[0] = static_cast<double>(output_data1[0]); // y1 に2番目の出力
}
catch (const Ort::Exception& ex) {
mexErrMsgIdAndTxt("myOnnxSfunc:RuntimeError", "実行時エラー: %s", ex.what());
}

}

void smex_builder_Terminate_wrapper(void)
{

g_session.reset();
g_env.reset();
g_input_node_names.clear();
g_output_node_names.clear();

} s-function, c++ MATLAB Answers — New Questions

​

Hello, I am trying to plot two vectors of unequal lengths on the same set of axes. One potential solution I have thought of is to bin the longer vector, such that the number of bins equals the length of the smaller vector. Then, I could take the average within each bin. However, I dont know how I would go about doing this, or if there is some other way.
I would appreciate any help in trying to figure this out! Thank you!Hello, I am trying to plot two vectors of unequal lengths on the same set of axes. One potential solution I have thought of is to bin the longer vector, such that the number of bins equals the length of the smaller vector. Then, I could take the average within each bin. However, I dont know how I would go about doing this, or if there is some other way.
I would appreciate any help in trying to figure this out! Thank you! Hello, I am trying to plot two vectors of unequal lengths on the same set of axes. One potential solution I have thought of is to bin the longer vector, such that the number of bins equals the length of the smaller vector. Then, I could take the average within each bin. However, I dont know how I would go about doing this, or if there is some other way.
I would appreciate any help in trying to figure this out! Thank you! vectors, binning, average, plot MATLAB Answers — New Questions

​

in my code i am having FIM Function[ function [J_11, J_12, J_22] = FIM(para, Rx, beta, scale)]. i want to use this function in my dnn for MSE to calculate traces of CRLB. how i can doin my code i am having FIM Function[ function [J_11, J_12, J_22] = FIM(para, Rx, beta, scale)]. i want to use this function in my dnn for MSE to calculate traces of CRLB. how i can do in my code i am having FIM Function[ function [J_11, J_12, J_22] = FIM(para, Rx, beta, scale)]. i want to use this function in my dnn for MSE to calculate traces of CRLB. how i can do crlb, mse MATLAB Answers — New Questions

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