These data are already preprocessed so they are already syncronized and they are of the same size. However, when I tried running, MATLAB says: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN. What seems to be the problem with this and how can this be fixed?
% load data
clear;
clc;
ld1 = load(‘CALT23A.mat’);
ld2 = load(‘CALT23D.mat’);
ld3 = load(‘CALT23M.mat’);
ld4 = load(‘CALT23S.mat’);
ld5 = load(‘CALT23K.mat’);
%%
% Accelerometer
accx = mean([ld1.Acceleration.X ld2.Acceleration.X ld3.Acceleration.X ld4.Acceleration.X],2,’omitnan’);
accy = mean([ld1.Acceleration.Y ld2.Acceleration.Y ld3.Acceleration.Y ld4.Acceleration.Y],2,’omitnan’);
accz = mean([ld1.Acceleration.Z ld2.Acceleration.Z ld3.Acceleration.Z ld4.Acceleration.Z],2,’omitnan’);
accelerometerReadings = [accx accy accz];
% Gyroscope
angx = mean([ld1.AngularVelocity.X ld2.AngularVelocity.X ld3.AngularVelocity.X ld5.AngularVelocity.X],2,’omitnan’);
angy = mean([ld1.AngularVelocity.Y ld2.AngularVelocity.Y ld3.AngularVelocity.Y ld5.AngularVelocity.Y],2,’omitnan’);
angz = mean([ld1.AngularVelocity.Z ld2.AngularVelocity.Z ld3.AngularVelocity.Z ld5.AngularVelocity.Z],2,’omitnan’);
gyroscopeReadings = [angx angy angz];
% Magnetometer
magx = mean([ld1.MagneticField.X ld2.MagneticField.X ld3.MagneticField.X ld4.MagneticField.X],2,’omitnan’);
magy = mean([ld1.MagneticField.Y ld2.MagneticField.Y ld3.MagneticField.Y ld4.MagneticField.Y],2,’omitnan’);
magz = mean([ld1.MagneticField.Z ld2.MagneticField.Z ld3.MagneticField.Z ld4.MagneticField.Z],2,’omitnan’);
magnetometerReadings = [magx magy magz];
%GPS
lat = mean([ld1.Position.latitude ld2.Position.latitude ld3.Position.latitude ld4.Position.latitude],2,’omitnan’);
long = mean([ld1.Position.longitude ld2.Position.longitude ld3.Position.longitude ld4.Position.longitude],2,’omitnan’);
speed = mean([ld1.Position.speed ld2.Position.speed ld3.Position.speed ld4.Position.speed],2,’omitnan’);
gps_speed_combined = speed;
%% IMU Filter (indirect Kalman Filter)
fuse = imufilter(‘SampleRate’,100, ‘DecimationFactor’,1,’AccelerometerNoise’,0.5,’GyroscopeNoise’,0.01);
q1 = fuse(accelerometerReadings, gyroscopeReadings);
orient1 = eulerd(q1, ‘ZYX’,’frame’);
f = figure;
f.Position(1:4) = [100 20 1100 600];
plot(orient1(:,3)); hold off
grid on
axis tight
xlabel(‘Time (sec)’);
ylabel(‘Angle (deg)’);
title(‘Orientation Estimate using IMU Filter’)
saveas(gcf, ‘imufilter.png’)These data are already preprocessed so they are already syncronized and they are of the same size. However, when I tried running, MATLAB says: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN. What seems to be the problem with this and how can this be fixed?
% load data
clear;
clc;
ld1 = load(‘CALT23A.mat’);
ld2 = load(‘CALT23D.mat’);
ld3 = load(‘CALT23M.mat’);
ld4 = load(‘CALT23S.mat’);
ld5 = load(‘CALT23K.mat’);
%%
% Accelerometer
accx = mean([ld1.Acceleration.X ld2.Acceleration.X ld3.Acceleration.X ld4.Acceleration.X],2,’omitnan’);
accy = mean([ld1.Acceleration.Y ld2.Acceleration.Y ld3.Acceleration.Y ld4.Acceleration.Y],2,’omitnan’);
accz = mean([ld1.Acceleration.Z ld2.Acceleration.Z ld3.Acceleration.Z ld4.Acceleration.Z],2,’omitnan’);
accelerometerReadings = [accx accy accz];
% Gyroscope
angx = mean([ld1.AngularVelocity.X ld2.AngularVelocity.X ld3.AngularVelocity.X ld5.AngularVelocity.X],2,’omitnan’);
angy = mean([ld1.AngularVelocity.Y ld2.AngularVelocity.Y ld3.AngularVelocity.Y ld5.AngularVelocity.Y],2,’omitnan’);
angz = mean([ld1.AngularVelocity.Z ld2.AngularVelocity.Z ld3.AngularVelocity.Z ld5.AngularVelocity.Z],2,’omitnan’);
gyroscopeReadings = [angx angy angz];
% Magnetometer
magx = mean([ld1.MagneticField.X ld2.MagneticField.X ld3.MagneticField.X ld4.MagneticField.X],2,’omitnan’);
magy = mean([ld1.MagneticField.Y ld2.MagneticField.Y ld3.MagneticField.Y ld4.MagneticField.Y],2,’omitnan’);
magz = mean([ld1.MagneticField.Z ld2.MagneticField.Z ld3.MagneticField.Z ld4.MagneticField.Z],2,’omitnan’);
magnetometerReadings = [magx magy magz];
%GPS
lat = mean([ld1.Position.latitude ld2.Position.latitude ld3.Position.latitude ld4.Position.latitude],2,’omitnan’);
long = mean([ld1.Position.longitude ld2.Position.longitude ld3.Position.longitude ld4.Position.longitude],2,’omitnan’);
speed = mean([ld1.Position.speed ld2.Position.speed ld3.Position.speed ld4.Position.speed],2,’omitnan’);
gps_speed_combined = speed;
%% IMU Filter (indirect Kalman Filter)
fuse = imufilter(‘SampleRate’,100, ‘DecimationFactor’,1,’AccelerometerNoise’,0.5,’GyroscopeNoise’,0.01);
q1 = fuse(accelerometerReadings, gyroscopeReadings);
orient1 = eulerd(q1, ‘ZYX’,’frame’);
f = figure;
f.Position(1:4) = [100 20 1100 600];
plot(orient1(:,3)); hold off
grid on
axis tight
xlabel(‘Time (sec)’);
ylabel(‘Angle (deg)’);
title(‘Orientation Estimate using IMU Filter’)
saveas(gcf, ‘imufilter.png’) These data are already preprocessed so they are already syncronized and they are of the same size. However, when I tried running, MATLAB says: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN. What seems to be the problem with this and how can this be fixed?
% load data
clear;
clc;
ld1 = load(‘CALT23A.mat’);
ld2 = load(‘CALT23D.mat’);
ld3 = load(‘CALT23M.mat’);
ld4 = load(‘CALT23S.mat’);
ld5 = load(‘CALT23K.mat’);
%%
% Accelerometer
accx = mean([ld1.Acceleration.X ld2.Acceleration.X ld3.Acceleration.X ld4.Acceleration.X],2,’omitnan’);
accy = mean([ld1.Acceleration.Y ld2.Acceleration.Y ld3.Acceleration.Y ld4.Acceleration.Y],2,’omitnan’);
accz = mean([ld1.Acceleration.Z ld2.Acceleration.Z ld3.Acceleration.Z ld4.Acceleration.Z],2,’omitnan’);
accelerometerReadings = [accx accy accz];
% Gyroscope
angx = mean([ld1.AngularVelocity.X ld2.AngularVelocity.X ld3.AngularVelocity.X ld5.AngularVelocity.X],2,’omitnan’);
angy = mean([ld1.AngularVelocity.Y ld2.AngularVelocity.Y ld3.AngularVelocity.Y ld5.AngularVelocity.Y],2,’omitnan’);
angz = mean([ld1.AngularVelocity.Z ld2.AngularVelocity.Z ld3.AngularVelocity.Z ld5.AngularVelocity.Z],2,’omitnan’);
gyroscopeReadings = [angx angy angz];
% Magnetometer
magx = mean([ld1.MagneticField.X ld2.MagneticField.X ld3.MagneticField.X ld4.MagneticField.X],2,’omitnan’);
magy = mean([ld1.MagneticField.Y ld2.MagneticField.Y ld3.MagneticField.Y ld4.MagneticField.Y],2,’omitnan’);
magz = mean([ld1.MagneticField.Z ld2.MagneticField.Z ld3.MagneticField.Z ld4.MagneticField.Z],2,’omitnan’);
magnetometerReadings = [magx magy magz];
%GPS
lat = mean([ld1.Position.latitude ld2.Position.latitude ld3.Position.latitude ld4.Position.latitude],2,’omitnan’);
long = mean([ld1.Position.longitude ld2.Position.longitude ld3.Position.longitude ld4.Position.longitude],2,’omitnan’);
speed = mean([ld1.Position.speed ld2.Position.speed ld3.Position.speed ld4.Position.speed],2,’omitnan’);
gps_speed_combined = speed;
%% IMU Filter (indirect Kalman Filter)
fuse = imufilter(‘SampleRate’,100, ‘DecimationFactor’,1,’AccelerometerNoise’,0.5,’GyroscopeNoise’,0.01);
q1 = fuse(accelerometerReadings, gyroscopeReadings);
orient1 = eulerd(q1, ‘ZYX’,’frame’);
f = figure;
f.Position(1:4) = [100 20 1100 600];
plot(orient1(:,3)); hold off
grid on
axis tight
xlabel(‘Time (sec)’);
ylabel(‘Angle (deg)’);
title(‘Orientation Estimate using IMU Filter’)
saveas(gcf, ‘imufilter.png’) matrix, singular MATLAB Answers — New Questions

​

I have a text file with time(1st column) and voltage amplitude (2nd column). How do I plot a spectrogram plotting time vs instantaneous frequency vs amplitude? Could you please help me plot it? I will really appreciate it.
I have attached the text file and a picture of the time domain representation of the signal.I have a text file with time(1st column) and voltage amplitude (2nd column). How do I plot a spectrogram plotting time vs instantaneous frequency vs amplitude? Could you please help me plot it? I will really appreciate it.
I have attached the text file and a picture of the time domain representation of the signal. I have a text file with time(1st column) and voltage amplitude (2nd column). How do I plot a spectrogram plotting time vs instantaneous frequency vs amplitude? Could you please help me plot it? I will really appreciate it.
I have attached the text file and a picture of the time domain representation of the signal. spectrogram, fft MATLAB Answers — New Questions

​

Dear Sir/Madam,
I just wanted to know how to create sensor network on matlab with different layers like physical,data link layer and network layer.Dear Sir/Madam,
I just wanted to know how to create sensor network on matlab with different layers like physical,data link layer and network layer. Dear Sir/Madam,
I just wanted to know how to create sensor network on matlab with different layers like physical,data link layer and network layer. sensor network MATLAB Answers — New Questions

​

I have a dataset comprising a cube of images, with dimension 256x320x151. I need tu cut it down to a dataset with dimension 256x320x10, while keeping all the other attributes invariate, as they have useful information on the data acquisition parameters.
I have tried the code:
h5disp(‘PCA_cube – Copia.h5’)
fileattrib(‘PCA_cube – Copia.h5′,’+w’);
fid = H5F.open(‘PCA_cube – Copia.h5′,’H5F_ACC_RDWR’,’H5P_DEFAULT’);
dset_id = H5D.open(fid,’/Cube/Images’);
H5D.set_extent(dset_id,[320,256,10]); % C-style indexing
H5D.close(dset_id);
H5F.close(fid);
h5read(PCA_cube – Copia.h5′, ‘/Cube/Images’)
However I get the error message: "Error using hdf5lib2 : The HDF5 library encountered an error and produced the following stack trace information:H5D__set_extent dataset has contiguous storage"
I’m adding also some information on the file structure:

Any help or suggestion is much welcome!I have a dataset comprising a cube of images, with dimension 256x320x151. I need tu cut it down to a dataset with dimension 256x320x10, while keeping all the other attributes invariate, as they have useful information on the data acquisition parameters.
I have tried the code:
h5disp(‘PCA_cube – Copia.h5’)
fileattrib(‘PCA_cube – Copia.h5′,’+w’);
fid = H5F.open(‘PCA_cube – Copia.h5′,’H5F_ACC_RDWR’,’H5P_DEFAULT’);
dset_id = H5D.open(fid,’/Cube/Images’);
H5D.set_extent(dset_id,[320,256,10]); % C-style indexing
H5D.close(dset_id);
H5F.close(fid);
h5read(PCA_cube – Copia.h5′, ‘/Cube/Images’)
However I get the error message: "Error using hdf5lib2 : The HDF5 library encountered an error and produced the following stack trace information:H5D__set_extent dataset has contiguous storage"
I’m adding also some information on the file structure:

Any help or suggestion is much welcome! I have a dataset comprising a cube of images, with dimension 256x320x151. I need tu cut it down to a dataset with dimension 256x320x10, while keeping all the other attributes invariate, as they have useful information on the data acquisition parameters.
I have tried the code:
h5disp(‘PCA_cube – Copia.h5’)
fileattrib(‘PCA_cube – Copia.h5′,’+w’);
fid = H5F.open(‘PCA_cube – Copia.h5′,’H5F_ACC_RDWR’,’H5P_DEFAULT’);
dset_id = H5D.open(fid,’/Cube/Images’);
H5D.set_extent(dset_id,[320,256,10]); % C-style indexing
H5D.close(dset_id);
H5F.close(fid);
h5read(PCA_cube – Copia.h5′, ‘/Cube/Images’)
However I get the error message: "Error using hdf5lib2 : The HDF5 library encountered an error and produced the following stack trace information:H5D__set_extent dataset has contiguous storage"
I’m adding also some information on the file structure:

Any help or suggestion is much welcome! h5, hdf5lib2, dataset, hdf5 MATLAB Answers — New Questions

​

I can use the following line
opts = detectImportOptions(workbookFile,’Sheet’,sheetName,’Range’,Range);
containing an excel range name (see name manager) in Range and the corresponding sheet name in sheetName. The thing is, excel already allows me to set range names for the whole workbook. So, no need to specify the sheet name. I’d like my script to be agnostic to changes in sheet names or positions.
How can I do that?
If I launch without sheetName
opts = detectImportOptions(workbookFile,’Range’,Range);
Matlab doesn’t find my range, although the range name in excel is given with "Scope: Workbook".I can use the following line
opts = detectImportOptions(workbookFile,’Sheet’,sheetName,’Range’,Range);
containing an excel range name (see name manager) in Range and the corresponding sheet name in sheetName. The thing is, excel already allows me to set range names for the whole workbook. So, no need to specify the sheet name. I’d like my script to be agnostic to changes in sheet names or positions.
How can I do that?
If I launch without sheetName
opts = detectImportOptions(workbookFile,’Range’,Range);
Matlab doesn’t find my range, although the range name in excel is given with "Scope: Workbook". I can use the following line
opts = detectImportOptions(workbookFile,’Sheet’,sheetName,’Range’,Range);
containing an excel range name (see name manager) in Range and the corresponding sheet name in sheetName. The thing is, excel already allows me to set range names for the whole workbook. So, no need to specify the sheet name. I’d like my script to be agnostic to changes in sheet names or positions.
How can I do that?
If I launch without sheetName
opts = detectImportOptions(workbookFile,’Range’,Range);
Matlab doesn’t find my range, although the range name in excel is given with "Scope: Workbook". excel MATLAB Answers — New Questions

​

Im having issue where i think the index is looking for instances of detected circles but it either is not filling the index or maybe there isnt enough to fill the array but im having issue getting this to work. its from the help documentation so i expected it to just work but im still having trouble and thus am having trouble understanding how to use imfindcircles. I tried using edge(canny) and using a binary image to see if that would make it easier to find circles but im still hvaing issues.

A = imread(‘coins.png’);
imshow(A)
[centers, radii, metric] = imfindcircles(A,[15 30]);
centersStrong5 = centers(1:5,:);
radiiStrong5 = radii(1:5);
metricStrong5 = metric(1:5);
viscircles(centersStrong5, radiiStrong5,’EdgeColor’,’b’);Im having issue where i think the index is looking for instances of detected circles but it either is not filling the index or maybe there isnt enough to fill the array but im having issue getting this to work. its from the help documentation so i expected it to just work but im still having trouble and thus am having trouble understanding how to use imfindcircles. I tried using edge(canny) and using a binary image to see if that would make it easier to find circles but im still hvaing issues.

A = imread(‘coins.png’);
imshow(A)
[centers, radii, metric] = imfindcircles(A,[15 30]);
centersStrong5 = centers(1:5,:);
radiiStrong5 = radii(1:5);
metricStrong5 = metric(1:5);
viscircles(centersStrong5, radiiStrong5,’EdgeColor’,’b’); Im having issue where i think the index is looking for instances of detected circles but it either is not filling the index or maybe there isnt enough to fill the array but im having issue getting this to work. its from the help documentation so i expected it to just work but im still having trouble and thus am having trouble understanding how to use imfindcircles. I tried using edge(canny) and using a binary image to see if that would make it easier to find circles but im still hvaing issues.

A = imread(‘coins.png’);
imshow(A)
[centers, radii, metric] = imfindcircles(A,[15 30]);
centersStrong5 = centers(1:5,:);
radiiStrong5 = radii(1:5);
metricStrong5 = metric(1:5);
viscircles(centersStrong5, radiiStrong5,’EdgeColor’,’b’); imfindcircles, matlab, hough transform, edge detection, image processing toolbox MATLAB Answers — New Questions

​

I am trying to animate a trajectory following a marker.
Here is the problematic part of my code:
figure(1)
axis([0, ceil(max(x)), 0, ceil(max(y))])
daspect([1 1 1])
grid on
xlabel(‘x (m)’), ylabel(‘y (m)’), title(‘Bouncing Projectile’), subtitle([‘{theta} = ‘, num2str(theta), ‘°, u = ‘, num2str(u), ‘ ms^{-1}, h = ‘, num2str(h), ‘ m, g = ‘, num2str(g), ‘ ms^{-2}, C = ‘, num2str(C), ‘, N = ‘, num2str(N)])

h = animatedline(‘Color’, ‘b’);
p = plot(x(1), y(1), ‘o’, ‘MarkerEdgeColor’, ‘red’, ‘MarkerFaceColor’, ‘red’);

for k = 1:length(x)
p.XData = x(k);
p.YData = y(k);
addpoints(h, x(k), y(k));
drawnow limitrate
pause(dt)
end

Whithout the code for the marker, the program runs well. However, for some strange reason, adding the code for the marker seems to create an error:

Error using matlab.graphics.animation.AnimatedLine/addpoints
Value must be a handle.
Error in file (line 54)
addpoints(h, x(k), y(k));

A graph is produced when I run the program, however the axes are not labeled, there is no title, and only one point is plotted.
What mistake have I made?I am trying to animate a trajectory following a marker.
Here is the problematic part of my code:
figure(1)
axis([0, ceil(max(x)), 0, ceil(max(y))])
daspect([1 1 1])
grid on
xlabel(‘x (m)’), ylabel(‘y (m)’), title(‘Bouncing Projectile’), subtitle([‘{theta} = ‘, num2str(theta), ‘°, u = ‘, num2str(u), ‘ ms^{-1}, h = ‘, num2str(h), ‘ m, g = ‘, num2str(g), ‘ ms^{-2}, C = ‘, num2str(C), ‘, N = ‘, num2str(N)])

h = animatedline(‘Color’, ‘b’);
p = plot(x(1), y(1), ‘o’, ‘MarkerEdgeColor’, ‘red’, ‘MarkerFaceColor’, ‘red’);

for k = 1:length(x)
p.XData = x(k);
p.YData = y(k);
addpoints(h, x(k), y(k));
drawnow limitrate
pause(dt)
end

Whithout the code for the marker, the program runs well. However, for some strange reason, adding the code for the marker seems to create an error:

Error using matlab.graphics.animation.AnimatedLine/addpoints
Value must be a handle.
Error in file (line 54)
addpoints(h, x(k), y(k));

A graph is produced when I run the program, however the axes are not labeled, there is no title, and only one point is plotted.
What mistake have I made? I am trying to animate a trajectory following a marker.
Here is the problematic part of my code:
figure(1)
axis([0, ceil(max(x)), 0, ceil(max(y))])
daspect([1 1 1])
grid on
xlabel(‘x (m)’), ylabel(‘y (m)’), title(‘Bouncing Projectile’), subtitle([‘{theta} = ‘, num2str(theta), ‘°, u = ‘, num2str(u), ‘ ms^{-1}, h = ‘, num2str(h), ‘ m, g = ‘, num2str(g), ‘ ms^{-2}, C = ‘, num2str(C), ‘, N = ‘, num2str(N)])

h = animatedline(‘Color’, ‘b’);
p = plot(x(1), y(1), ‘o’, ‘MarkerEdgeColor’, ‘red’, ‘MarkerFaceColor’, ‘red’);

for k = 1:length(x)
p.XData = x(k);
p.YData = y(k);
addpoints(h, x(k), y(k));
drawnow limitrate
pause(dt)
end

Whithout the code for the marker, the program runs well. However, for some strange reason, adding the code for the marker seems to create an error:

Error using matlab.graphics.animation.AnimatedLine/addpoints
Value must be a handle.
Error in file (line 54)
addpoints(h, x(k), y(k));

A graph is produced when I run the program, however the axes are not labeled, there is no title, and only one point is plotted.
What mistake have I made? matlab MATLAB Answers — New Questions

​

My Mathworks account seems to be corrupted or hacked.
At the time of login, i could see the initials of another anonymous person for brief time.
Later it shows my account initals, VB
The number of answers, count is also showing incorrectly. it has not changed since 2 3 weeks. despite answering enough questions.
Anyone has idea how to solve this problem.My Mathworks account seems to be corrupted or hacked.
At the time of login, i could see the initials of another anonymous person for brief time.
Later it shows my account initals, VB
The number of answers, count is also showing incorrectly. it has not changed since 2 3 weeks. despite answering enough questions.
Anyone has idea how to solve this problem. My Mathworks account seems to be corrupted or hacked.
At the time of login, i could see the initials of another anonymous person for brief time.
Later it shows my account initals, VB
The number of answers, count is also showing incorrectly. it has not changed since 2 3 weeks. despite answering enough questions.
Anyone has idea how to solve this problem. mathworks account, answers, count, login MATLAB Answers — New Questions

​

I would like to create http message bodies with fields that contain dashes. I haven’t been able to find a workaround for Matlab disallowing hyphens (dashes) in the var names.
Here is what I’m trying to do – for illustration – I have an underscore in place of a hyphen the "test_var" (below)
Even after generating the RequestMessage (req1 below), you cannot change "test_var" to "test-var" because the RequestMessage is still storing the request as a struct (not as a string which could be modified).

method = matlab.net.http.RequestMethod.POST;
header = matlab.net.http.HeaderField(‘Content-Type’, ‘application/json’);
header = addFields(header,’User-Agent’, ‘my-client/99.9’);
header = addFields(header,’Accept’, ‘application/json’);

% Struct approach
struct1 = struct(‘login’, ‘me’, ‘password’, ‘pw123’, ‘test_var’, true)
body1 = matlab.net.http.MessageBody(struct1)
req1 = matlab.net.http.RequestMessage(method,header,body1)
show(req1)
POST
Content-Type: application/json
User-Agent: my-client/99.9
Accept: application/json

{"login":"me","password":"pw123","test_var":true}

req1.Body.Data

ans =

struct with fields:

login: ‘me’
password: ‘pw123’
test_var: 1I would like to create http message bodies with fields that contain dashes. I haven’t been able to find a workaround for Matlab disallowing hyphens (dashes) in the var names.
Here is what I’m trying to do – for illustration – I have an underscore in place of a hyphen the "test_var" (below)
Even after generating the RequestMessage (req1 below), you cannot change "test_var" to "test-var" because the RequestMessage is still storing the request as a struct (not as a string which could be modified).

method = matlab.net.http.RequestMethod.POST;
header = matlab.net.http.HeaderField(‘Content-Type’, ‘application/json’);
header = addFields(header,’User-Agent’, ‘my-client/99.9’);
header = addFields(header,’Accept’, ‘application/json’);

% Struct approach
struct1 = struct(‘login’, ‘me’, ‘password’, ‘pw123’, ‘test_var’, true)
body1 = matlab.net.http.MessageBody(struct1)
req1 = matlab.net.http.RequestMessage(method,header,body1)
show(req1)
POST
Content-Type: application/json
User-Agent: my-client/99.9
Accept: application/json

{"login":"me","password":"pw123","test_var":true}

req1.Body.Data

ans =

struct with fields:

login: ‘me’
password: ‘pw123’
test_var: 1 I would like to create http message bodies with fields that contain dashes. I haven’t been able to find a workaround for Matlab disallowing hyphens (dashes) in the var names.
Here is what I’m trying to do – for illustration – I have an underscore in place of a hyphen the "test_var" (below)
Even after generating the RequestMessage (req1 below), you cannot change "test_var" to "test-var" because the RequestMessage is still storing the request as a struct (not as a string which could be modified).

method = matlab.net.http.RequestMethod.POST;
header = matlab.net.http.HeaderField(‘Content-Type’, ‘application/json’);
header = addFields(header,’User-Agent’, ‘my-client/99.9’);
header = addFields(header,’Accept’, ‘application/json’);

% Struct approach
struct1 = struct(‘login’, ‘me’, ‘password’, ‘pw123’, ‘test_var’, true)
body1 = matlab.net.http.MessageBody(struct1)
req1 = matlab.net.http.RequestMessage(method,header,body1)
show(req1)
POST
Content-Type: application/json
User-Agent: my-client/99.9
Accept: application/json

{"login":"me","password":"pw123","test_var":true}

req1.Body.Data

ans =

struct with fields:

login: ‘me’
password: ‘pw123’
test_var: 1 #messagebody, #requestmessage MATLAB Answers — New Questions

​

I have conducted neural network on my dataset with 228 rows and 7 columns but don’t know how to obtain my training and testing datasets and their prediction values. I want to export this values.

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 20-Jul-2024 16:31:01
%
% This script assumes these variables are defined:
%
% data – input data.
% data_1 – target data.

x = data’;
t = data_1′;

% Choose a Training Function
% For a list of all training functions type: help nntrain
% ‘trainlm’ is usually fastest.
% ‘trainbr’ takes longer but may be better for challenging problems.
% ‘trainscg’ uses less memory. Suitable in low memory situations.
trainFcn = ‘trainlm’; % Levenberg-Marquardt backpropagation.

% Create a Fitting Network
hiddenLayerSize = 4;
net = fitnet(hiddenLayerSize,trainFcn);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,x,t);

% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)

% View the Network
view(net)

% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotregression(t,y)
%figure, plotfit(net,x,t)I have conducted neural network on my dataset with 228 rows and 7 columns but don’t know how to obtain my training and testing datasets and their prediction values. I want to export this values.

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 20-Jul-2024 16:31:01
%
% This script assumes these variables are defined:
%
% data – input data.
% data_1 – target data.

x = data’;
t = data_1′;

% Choose a Training Function
% For a list of all training functions type: help nntrain
% ‘trainlm’ is usually fastest.
% ‘trainbr’ takes longer but may be better for challenging problems.
% ‘trainscg’ uses less memory. Suitable in low memory situations.
trainFcn = ‘trainlm’; % Levenberg-Marquardt backpropagation.

% Create a Fitting Network
hiddenLayerSize = 4;
net = fitnet(hiddenLayerSize,trainFcn);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,x,t);

% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)

% View the Network
view(net)

% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotregression(t,y)
%figure, plotfit(net,x,t) I have conducted neural network on my dataset with 228 rows and 7 columns but don’t know how to obtain my training and testing datasets and their prediction values. I want to export this values.

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 20-Jul-2024 16:31:01
%
% This script assumes these variables are defined:
%
% data – input data.
% data_1 – target data.

x = data’;
t = data_1′;

% Choose a Training Function
% For a list of all training functions type: help nntrain
% ‘trainlm’ is usually fastest.
% ‘trainbr’ takes longer but may be better for challenging problems.
% ‘trainscg’ uses less memory. Suitable in low memory situations.
trainFcn = ‘trainlm’; % Levenberg-Marquardt backpropagation.

% Create a Fitting Network
hiddenLayerSize = 4;
net = fitnet(hiddenLayerSize,trainFcn);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,x,t);

% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)

% View the Network
view(net)

% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotregression(t,y)
%figure, plotfit(net,x,t) nftool, train, test, predictions, export results MATLAB Answers — New Questions

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