Month: August 2024
Intune Enrollment Issue with Entra Hybrid Joined Devices Managed by SCCM
Hello Team,
We have successfully configured Entra Hybrid Join for all Windows devices and enabled the MDM scope for all users in Intune. While the devices are registering as Entra Hybrid Joined, they are not enrolling into Intune as expected.
We have observed that these devices have the SCCM client installed, and we suspect that this might be the reason for the enrollment issue.
Could someone please advise whether it is possible to enroll devices into Intune while they are still managed by SCCM and have the SCCM client installed? If there are any specific configurations or steps required to achieve this, your guidance would be greatly appreciated.
Hello Team,We have successfully configured Entra Hybrid Join for all Windows devices and enabled the MDM scope for all users in Intune. While the devices are registering as Entra Hybrid Joined, they are not enrolling into Intune as expected.We have observed that these devices have the SCCM client installed, and we suspect that this might be the reason for the enrollment issue.Could someone please advise whether it is possible to enroll devices into Intune while they are still managed by SCCM and have the SCCM client installed? If there are any specific configurations or steps required to achieve this, your guidance would be greatly appreciated. Read More
Intune auto enrollment in Workgroup environment
Hello All,
We are planning to enroll Windows devices that are currently in a workgroup environment into Intune. While manual enrollment is an option, we are looking for guidance on how to automate this process to the greatest extent possible.
Could you please suggest an approach that would allow us to achieve maximum automation for this enrollment?
Thanks,
Hello All,We are planning to enroll Windows devices that are currently in a workgroup environment into Intune. While manual enrollment is an option, we are looking for guidance on how to automate this process to the greatest extent possible.Could you please suggest an approach that would allow us to achieve maximum automation for this enrollment?Thanks, Read More
Why doesn’t the figure show the text and fitting line?
Text in the left corner and fitting line is missing from my fiures, please make correction to my code:
% Define heights, FOVs, and SNR values to test
heights = [1000, 2000, 3000, 4000];
fovs = [0.2, 0.5, 1, 2, 5, 10];
snr_values = [0, 25, 50, 75, 100];
% Function to calculate performance metrics
calculate_r_squared = @(x, y) 1 – sum((y – x).^2) / sum((y – mean(y)).^2);
calculate_rmse = @(x, y) sqrt(mean((y – x).^2));
calculate_mape = @(x, y) mean(abs((y – x) ./ y)) * 100;
calculate_mae = @(x, y) mean(abs(y – x));
calculate_made = @(x, y) mean(abs(y – mean(x)));
% Initialize arrays to store performance metrics
performance_metrics = struct();
% Loop over height values
for h = heights
% Filter the data for the current height
idx = (lookup_table(:, 1) == h);
data_filtered = lookup_table(idx, :);
% Initialize arrays to store performance metrics for each FOV and SNR value
performance_metrics(h).r_squared_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).r_squared_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_a = zeros(length(fovs), length(snr_values));
% Plot optimal_r_input vs. optimal_r_interp
figure;
hold on;
colors = jet(length(fovs) * length(snr_values));
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_r_input = data_filtered(idx_fov_snr, 4);
optimal_r_interp = data_filtered(idx_fov_snr, 5);
% Scatter plot
if ~isempty(optimal_r_input)
scatter(optimal_r_input, optimal_r_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_r_input) > 1
model_r = fitlm(optimal_r_input, optimal_r_interp);
plot(model_r.Variables.x1, model_r.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_r = model_r.Rsquared.Ordinary;
rmse_r = calculate_rmse(optimal_r_input, optimal_r_interp);
mape_r = calculate_mape(optimal_r_input, optimal_r_interp);
mae_r = calculate_mae(optimal_r_input, optimal_r_interp);
made_r = calculate_made(optimal_r_input, optimal_r_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_r(fov_idx, snr_idx) = r_squared_r;
performance_metrics(h).rmse_r(fov_idx, snr_idx) = rmse_r;
performance_metrics(h).mape_r(fov_idx, snr_idx) = mape_r;
performance_metrics(h).mae_r(fov_idx, snr_idx) = mae_r;
performance_metrics(h).made_r(fov_idx, snr_idx) = made_r;
% Display text with performance metrics
text(mean(optimal_r_input), mean(optimal_r_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_r)], …
[‘RMSE = ‘, num2str(rmse_r)], …
[‘MAPE = ‘, num2str(mape_r), ‘%’], …
[‘MAE = ‘, num2str(mae_r)], …
[‘MADE = ‘, num2str(made_r)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal R_{e} (mum)’);
ylabel(‘Optimal R_{e} interp (mum)’);
title([‘Plot of optimal R_{e} and optimal R_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
% Plot optimal_a_input vs. optimal_a_interp
figure;
hold on;
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_a_input = data_filtered(idx_fov_snr, 6);
optimal_a_interp = data_filtered(idx_fov_snr, 7);
% Scatter plot
if ~isempty(optimal_a_input)
scatter(optimal_a_input, optimal_a_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_a_input) > 1
model_a = fitlm(optimal_a_input, optimal_a_interp);
plot(model_a.Variables.x1, model_a.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_a = model_a.Rsquared.Ordinary;
rmse_a = calculate_rmse(optimal_a_input, optimal_a_interp);
mape_a = calculate_mape(optimal_a_input, optimal_a_interp);
mae_a = calculate_mae(optimal_a_input, optimal_a_interp);
made_a = calculate_made(optimal_a_input, optimal_a_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_a(fov_idx, snr_idx) = r_squared_a;
performance_metrics(h).rmse_a(fov_idx, snr_idx) = rmse_a;
performance_metrics(h).mape_a(fov_idx, snr_idx) = mape_a;
performance_metrics(h).mae_a(fov_idx, snr_idx) = mae_a;
performance_metrics(h).made_a(fov_idx, snr_idx) = made_a;
% Display text with performance metrics
text(mean(optimal_a_input), mean(optimal_a_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_a)], …
[‘RMSE = ‘, num2str(rmse_a)], …
[‘MAPE = ‘, num2str(mape_a), ‘%’], …
[‘MAE = ‘, num2str(mae_a)], …
[‘MADE = ‘, num2str(made_a)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal alpha_{e} (m^{-1})’);
ylabel(‘Optimal alpha_{e} interp (m^{-1})’);
title([‘Plot of optimal alpha_{e} vs optimal alpha_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
endText in the left corner and fitting line is missing from my fiures, please make correction to my code:
% Define heights, FOVs, and SNR values to test
heights = [1000, 2000, 3000, 4000];
fovs = [0.2, 0.5, 1, 2, 5, 10];
snr_values = [0, 25, 50, 75, 100];
% Function to calculate performance metrics
calculate_r_squared = @(x, y) 1 – sum((y – x).^2) / sum((y – mean(y)).^2);
calculate_rmse = @(x, y) sqrt(mean((y – x).^2));
calculate_mape = @(x, y) mean(abs((y – x) ./ y)) * 100;
calculate_mae = @(x, y) mean(abs(y – x));
calculate_made = @(x, y) mean(abs(y – mean(x)));
% Initialize arrays to store performance metrics
performance_metrics = struct();
% Loop over height values
for h = heights
% Filter the data for the current height
idx = (lookup_table(:, 1) == h);
data_filtered = lookup_table(idx, :);
% Initialize arrays to store performance metrics for each FOV and SNR value
performance_metrics(h).r_squared_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).r_squared_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_a = zeros(length(fovs), length(snr_values));
% Plot optimal_r_input vs. optimal_r_interp
figure;
hold on;
colors = jet(length(fovs) * length(snr_values));
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_r_input = data_filtered(idx_fov_snr, 4);
optimal_r_interp = data_filtered(idx_fov_snr, 5);
% Scatter plot
if ~isempty(optimal_r_input)
scatter(optimal_r_input, optimal_r_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_r_input) > 1
model_r = fitlm(optimal_r_input, optimal_r_interp);
plot(model_r.Variables.x1, model_r.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_r = model_r.Rsquared.Ordinary;
rmse_r = calculate_rmse(optimal_r_input, optimal_r_interp);
mape_r = calculate_mape(optimal_r_input, optimal_r_interp);
mae_r = calculate_mae(optimal_r_input, optimal_r_interp);
made_r = calculate_made(optimal_r_input, optimal_r_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_r(fov_idx, snr_idx) = r_squared_r;
performance_metrics(h).rmse_r(fov_idx, snr_idx) = rmse_r;
performance_metrics(h).mape_r(fov_idx, snr_idx) = mape_r;
performance_metrics(h).mae_r(fov_idx, snr_idx) = mae_r;
performance_metrics(h).made_r(fov_idx, snr_idx) = made_r;
% Display text with performance metrics
text(mean(optimal_r_input), mean(optimal_r_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_r)], …
[‘RMSE = ‘, num2str(rmse_r)], …
[‘MAPE = ‘, num2str(mape_r), ‘%’], …
[‘MAE = ‘, num2str(mae_r)], …
[‘MADE = ‘, num2str(made_r)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal R_{e} (mum)’);
ylabel(‘Optimal R_{e} interp (mum)’);
title([‘Plot of optimal R_{e} and optimal R_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
% Plot optimal_a_input vs. optimal_a_interp
figure;
hold on;
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_a_input = data_filtered(idx_fov_snr, 6);
optimal_a_interp = data_filtered(idx_fov_snr, 7);
% Scatter plot
if ~isempty(optimal_a_input)
scatter(optimal_a_input, optimal_a_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_a_input) > 1
model_a = fitlm(optimal_a_input, optimal_a_interp);
plot(model_a.Variables.x1, model_a.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_a = model_a.Rsquared.Ordinary;
rmse_a = calculate_rmse(optimal_a_input, optimal_a_interp);
mape_a = calculate_mape(optimal_a_input, optimal_a_interp);
mae_a = calculate_mae(optimal_a_input, optimal_a_interp);
made_a = calculate_made(optimal_a_input, optimal_a_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_a(fov_idx, snr_idx) = r_squared_a;
performance_metrics(h).rmse_a(fov_idx, snr_idx) = rmse_a;
performance_metrics(h).mape_a(fov_idx, snr_idx) = mape_a;
performance_metrics(h).mae_a(fov_idx, snr_idx) = mae_a;
performance_metrics(h).made_a(fov_idx, snr_idx) = made_a;
% Display text with performance metrics
text(mean(optimal_a_input), mean(optimal_a_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_a)], …
[‘RMSE = ‘, num2str(rmse_a)], …
[‘MAPE = ‘, num2str(mape_a), ‘%’], …
[‘MAE = ‘, num2str(mae_a)], …
[‘MADE = ‘, num2str(made_a)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal alpha_{e} (m^{-1})’);
ylabel(‘Optimal alpha_{e} interp (m^{-1})’);
title([‘Plot of optimal alpha_{e} vs optimal alpha_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
end Text in the left corner and fitting line is missing from my fiures, please make correction to my code:
% Define heights, FOVs, and SNR values to test
heights = [1000, 2000, 3000, 4000];
fovs = [0.2, 0.5, 1, 2, 5, 10];
snr_values = [0, 25, 50, 75, 100];
% Function to calculate performance metrics
calculate_r_squared = @(x, y) 1 – sum((y – x).^2) / sum((y – mean(y)).^2);
calculate_rmse = @(x, y) sqrt(mean((y – x).^2));
calculate_mape = @(x, y) mean(abs((y – x) ./ y)) * 100;
calculate_mae = @(x, y) mean(abs(y – x));
calculate_made = @(x, y) mean(abs(y – mean(x)));
% Initialize arrays to store performance metrics
performance_metrics = struct();
% Loop over height values
for h = heights
% Filter the data for the current height
idx = (lookup_table(:, 1) == h);
data_filtered = lookup_table(idx, :);
% Initialize arrays to store performance metrics for each FOV and SNR value
performance_metrics(h).r_squared_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_r = zeros(length(fovs), length(snr_values));
performance_metrics(h).r_squared_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).rmse_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mape_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).mae_a = zeros(length(fovs), length(snr_values));
performance_metrics(h).made_a = zeros(length(fovs), length(snr_values));
% Plot optimal_r_input vs. optimal_r_interp
figure;
hold on;
colors = jet(length(fovs) * length(snr_values));
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_r_input = data_filtered(idx_fov_snr, 4);
optimal_r_interp = data_filtered(idx_fov_snr, 5);
% Scatter plot
if ~isempty(optimal_r_input)
scatter(optimal_r_input, optimal_r_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_r_input) > 1
model_r = fitlm(optimal_r_input, optimal_r_interp);
plot(model_r.Variables.x1, model_r.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_r = model_r.Rsquared.Ordinary;
rmse_r = calculate_rmse(optimal_r_input, optimal_r_interp);
mape_r = calculate_mape(optimal_r_input, optimal_r_interp);
mae_r = calculate_mae(optimal_r_input, optimal_r_interp);
made_r = calculate_made(optimal_r_input, optimal_r_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_r(fov_idx, snr_idx) = r_squared_r;
performance_metrics(h).rmse_r(fov_idx, snr_idx) = rmse_r;
performance_metrics(h).mape_r(fov_idx, snr_idx) = mape_r;
performance_metrics(h).mae_r(fov_idx, snr_idx) = mae_r;
performance_metrics(h).made_r(fov_idx, snr_idx) = made_r;
% Display text with performance metrics
text(mean(optimal_r_input), mean(optimal_r_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_r)], …
[‘RMSE = ‘, num2str(rmse_r)], …
[‘MAPE = ‘, num2str(mape_r), ‘%’], …
[‘MAE = ‘, num2str(mae_r)], …
[‘MADE = ‘, num2str(made_r)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal R_{e} (mum)’);
ylabel(‘Optimal R_{e} interp (mum)’);
title([‘Plot of optimal R_{e} and optimal R_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
% Plot optimal_a_input vs. optimal_a_interp
figure;
hold on;
c_idx = 1;
for fov_idx = 1:length(fovs)
for snr_idx = 1:length(snr_values)
fov = fovs(fov_idx);
snr = snr_values(snr_idx);
% Filter data for the current FOV and SNR
idx_fov_snr = (data_filtered(:, 2) == fov) & (data_filtered(:, 3) == snr);
optimal_a_input = data_filtered(idx_fov_snr, 6);
optimal_a_interp = data_filtered(idx_fov_snr, 7);
% Scatter plot
if ~isempty(optimal_a_input)
scatter(optimal_a_input, optimal_a_interp, 50, colors(c_idx, :), ‘filled’);
% Fit and plot linear regression line if there is sufficient data
if length(optimal_a_input) > 1
model_a = fitlm(optimal_a_input, optimal_a_interp);
plot(model_a.Variables.x1, model_a.Fitted, ‘Color’, colors(c_idx, :), ‘LineWidth’, 2);
% Calculate additional performance metrics
r_squared_a = model_a.Rsquared.Ordinary;
rmse_a = calculate_rmse(optimal_a_input, optimal_a_interp);
mape_a = calculate_mape(optimal_a_input, optimal_a_interp);
mae_a = calculate_mae(optimal_a_input, optimal_a_interp);
made_a = calculate_made(optimal_a_input, optimal_a_interp);
% Store the performance metrics for this FOV and SNR value
performance_metrics(h).r_squared_a(fov_idx, snr_idx) = r_squared_a;
performance_metrics(h).rmse_a(fov_idx, snr_idx) = rmse_a;
performance_metrics(h).mape_a(fov_idx, snr_idx) = mape_a;
performance_metrics(h).mae_a(fov_idx, snr_idx) = mae_a;
performance_metrics(h).made_a(fov_idx, snr_idx) = made_a;
% Display text with performance metrics
text(mean(optimal_a_input), mean(optimal_a_interp), …
{[‘SNR = ‘, num2str(snr), ‘ dB’], …
[‘R^2 = ‘, num2str(r_squared_a)], …
[‘RMSE = ‘, num2str(rmse_a)], …
[‘MAPE = ‘, num2str(mape_a), ‘%’], …
[‘MAE = ‘, num2str(mae_a)], …
[‘MADE = ‘, num2str(made_a)]}, …
‘FontSize’, 10, ‘Color’, colors(c_idx, :));
end
end
c_idx = c_idx + 1;
end
end
xlabel(‘Optimal alpha_{e} (m^{-1})’);
ylabel(‘Optimal alpha_{e} interp (m^{-1})’);
title([‘Plot of optimal alpha_{e} vs optimal alpha_{e} interp for Height = ‘, num2str(h)]);
grid on;
hold off;
end figure, text MATLAB Answers — New Questions
Implementing Transfer Function In Simulink.
Hi, I have a transfer function and have been struggling to implement it properly into simulink. ,,, and all change with respect to time and I want to be able to get . Furthermore, and depend on which I pass into a Matlab Block that calculates and respectively.
I tried using the Varying Transfer Fcn block, but I’d like to implement it using signals and blocks.
Thanks in advance, I’d really appreciate the help!Hi, I have a transfer function and have been struggling to implement it properly into simulink. ,,, and all change with respect to time and I want to be able to get . Furthermore, and depend on which I pass into a Matlab Block that calculates and respectively.
I tried using the Varying Transfer Fcn block, but I’d like to implement it using signals and blocks.
Thanks in advance, I’d really appreciate the help! Hi, I have a transfer function and have been struggling to implement it properly into simulink. ,,, and all change with respect to time and I want to be able to get . Furthermore, and depend on which I pass into a Matlab Block that calculates and respectively.
I tried using the Varying Transfer Fcn block, but I’d like to implement it using signals and blocks.
Thanks in advance, I’d really appreciate the help! transfer function, simulink MATLAB Answers — New Questions
signals matching between random modulations transmitter and humminbird sonar
hello i would like to ask how to match random signals of a transmitter to the signals of a humminbird imaging sonar so that the sonar is able to obtain imaging information from the random signals of the transmitter. is there a way of determining all the modulations of the sonar and the transmitter by scanning them. i will be using an sdr to send the random signals from the transmitter to the sonar. thanks very much.hello i would like to ask how to match random signals of a transmitter to the signals of a humminbird imaging sonar so that the sonar is able to obtain imaging information from the random signals of the transmitter. is there a way of determining all the modulations of the sonar and the transmitter by scanning them. i will be using an sdr to send the random signals from the transmitter to the sonar. thanks very much. hello i would like to ask how to match random signals of a transmitter to the signals of a humminbird imaging sonar so that the sonar is able to obtain imaging information from the random signals of the transmitter. is there a way of determining all the modulations of the sonar and the transmitter by scanning them. i will be using an sdr to send the random signals from the transmitter to the sonar. thanks very much. signals, match, transmitter, sonars MATLAB Answers — New Questions
Disappearing Contact Information
Ever since the airline fiasco, I and many others have been experiencing the loss of contact information and disappearing calendar information. Contacts I have had for decades suddenly disappear. Phone numbers, email addresses, and/or the entire contact. It is not our devices as it is happening on Apple and androids. It is occurring on PC’s and Macs. This is getting frustrating and aggravating. Important contact information keeps disappearing. I have had to re-enter information on family members, work associates, golf teams, etc. Someone had better look into this. Microsoft is getting an awful reputation.
Ever since the airline fiasco, I and many others have been experiencing the loss of contact information and disappearing calendar information. Contacts I have had for decades suddenly disappear. Phone numbers, email addresses, and/or the entire contact. It is not our devices as it is happening on Apple and androids. It is occurring on PC’s and Macs. This is getting frustrating and aggravating. Important contact information keeps disappearing. I have had to re-enter information on family members, work associates, golf teams, etc. Someone had better look into this. Microsoft is getting an awful reputation. Read More
Sensor Status – Not configured
Hi all,
I’ve installed the sensors on each DC following the setup process.
Even if there are no Health issues, the sensors status reports “Not Configured” and the healty status is marked as “Not Healthy”
However, I’m receiving data and alerts about accounts in the Identities section of the Microsoft Defender portal. So everything seems to be working properly.
Sensor version is: 2.239.18075.31594
Is that a glitch or do I have just to wait for it to be updated?
Will the sensor and health status be updated somewhen?
thanks for your support
Hi all,I’ve installed the sensors on each DC following the setup process.Even if there are no Health issues, the sensors status reports “Not Configured” and the healty status is marked as “Not Healthy” However, I’m receiving data and alerts about accounts in the Identities section of the Microsoft Defender portal. So everything seems to be working properly.Sensor version is: 2.239.18075.31594Is that a glitch or do I have just to wait for it to be updated?Will the sensor and health status be updated somewhen?thanks for your support Read More
Update bus selector by matlab script
Hi, is there a possibility to let a Bus Selector and Bus Creator update by a Matlab Script after I change the element name within a bus object?Hi, is there a possibility to let a Bus Selector and Bus Creator update by a Matlab Script after I change the element name within a bus object? Hi, is there a possibility to let a Bus Selector and Bus Creator update by a Matlab Script after I change the element name within a bus object? bus creator, bus selector, update MATLAB Answers — New Questions
plotting 2d graphs with decimals
I want to plot graph but gives me this error. this is the code i used
time_X_core224_6= readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","A3:A4401")
time_X_core224_7= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","G3:G4401")
time_X_core224_9= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","M3:M4401")
time_X_core224_28= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","S3:S4401")
time_X_core224_38= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","Y3:Y4401")
time_X_core156421= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AE3:AE4401")
Core224_6_KY = readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ4:BE4")
Core224_7_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ9:BE9")
Core224_9_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ14:BE14")
Core224_28_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ19:BE19")
Core224_38_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ24:BE24")
Core224_156421_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ29:BE29")
KY_Fig = plot(time_X_core224_6,Core224_6_KY)
Any solutions?I want to plot graph but gives me this error. this is the code i used
time_X_core224_6= readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","A3:A4401")
time_X_core224_7= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","G3:G4401")
time_X_core224_9= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","M3:M4401")
time_X_core224_28= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","S3:S4401")
time_X_core224_38= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","Y3:Y4401")
time_X_core156421= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AE3:AE4401")
Core224_6_KY = readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ4:BE4")
Core224_7_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ9:BE9")
Core224_9_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ14:BE14")
Core224_28_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ19:BE19")
Core224_38_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ24:BE24")
Core224_156421_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ29:BE29")
KY_Fig = plot(time_X_core224_6,Core224_6_KY)
Any solutions? I want to plot graph but gives me this error. this is the code i used
time_X_core224_6= readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","A3:A4401")
time_X_core224_7= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","G3:G4401")
time_X_core224_9= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","M3:M4401")
time_X_core224_28= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","S3:S4401")
time_X_core224_38= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","Y3:Y4401")
time_X_core156421= readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AE3:AE4401")
Core224_6_KY = readmatrix("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ4:BE4")
Core224_7_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ9:BE9")
Core224_9_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ14:BE14")
Core224_28_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ19:BE19")
Core224_38_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ24:BE24")
Core224_156421_KY = readtable("Лист Microsoft Excel.xlsx","Sheet","Лист1","Range","AZ29:BE29")
KY_Fig = plot(time_X_core224_6,Core224_6_KY)
Any solutions? graph, plotting, 2d, error MATLAB Answers — New Questions
matlab command for delete bus objects
can any one help me, Matlab command for delete busobjects.can any one help me, Matlab command for delete busobjects. can any one help me, Matlab command for delete busobjects. busobjects MATLAB Answers — New Questions
For Azure Repos Individual Service Princing
I hope you’re doing well.
I’m trying to get a clear understanding of the pricing structure for Azure Repos when used as an individual service. Could someone please provide details or point me to the resources where I can find this information? Specifically, I’m interested in:
Pricing Tiers: What are the available pricing plans or tiers for Azure Repos?
Usage Costs: How is the cost determined based on usage, such as storage, number of repositories, and number of users?
Additional Fees: Are there any extra fees or costs beyond the standard pricing?
Discounts or Promotions: Are there any current discounts, offers, or promotions available for individual users?
Licensing: Any information on licensing requirements or options for individual use.
Thanks in advance for your assistance!
I hope you’re doing well. I’m trying to get a clear understanding of the pricing structure for Azure Repos when used as an individual service. Could someone please provide details or point me to the resources where I can find this information? Specifically, I’m interested in: Pricing Tiers: What are the available pricing plans or tiers for Azure Repos?Usage Costs: How is the cost determined based on usage, such as storage, number of repositories, and number of users?Additional Fees: Are there any extra fees or costs beyond the standard pricing?Discounts or Promotions: Are there any current discounts, offers, or promotions available for individual users?Licensing: Any information on licensing requirements or options for individual use. Thanks in advance for your assistance! Read More
End-to-end Stable Diffusion test on Azure NC A100/H100 MIG
You’re welcome to follow my GitHub repo and give it a star：https://github.com/xinyuwei-david/david-share.git
E2E Stable Diffusion on A100 MIG
A100/H100 are High end Training GPU, which could also work as Inference. In order to save compute power and GPU memory, We could use NVIDIA Multi-Instance GPU (MIG), then we could run Stable Diffusion on MIG.
I do the test on Azure NC A100 VM.
Config MIG
Enable MIG on the first physical GPU.
root@david1a100:~# nvidia-smi -i 0 -mig 1
After the VM reboot, MIG has been enabled.
Lists all available GPU MIG profiles:
#nvidia-smi mig -lgip
At this moment, we need to calculate how to maximise utilize the GPU resource and meet the compute power and GPU memory for SD.
I divide A100 to four parts: ID 14×3 and ID 20×1
root@david1a100:~# sudo nvidia-smi mig -cgi 14,14,14,20 -C
Successfully created GPU instance ID 5 on GPU 0 using profile MIG 2g.20gb (ID 14)
Successfully created compute instance ID 0 on GPU 0 GPU instance ID 5 using profile MIG 2g.20gb (ID 1)
Successfully created GPU instance ID 3 on GPU 0 using profile MIG 2g.20gb (ID 14)
Successfully created compute instance ID 0 on GPU 0 GPU instance ID 3 using profile MIG 2g.20gb (ID 1)
Successfully created GPU instance ID 4 on GPU 0 using profile MIG 2g.20gb (ID 14)
Successfully created compute instance ID 0 on GPU 0 GPU instance ID 4 using profile MIG 2g.20gb (ID 1)
Successfully created GPU instance ID 13 on GPU 0 using profile MIG 1g.10gb+me (ID 20)
Successfully created compute instance ID 0 on GPU 0 GPU instance ID 13 using profile MIG 1g.10gb (ID 0)
After reboot the VM, CPU MIG configuration will be lost, so I need to setup bash script.
#vi /usr/local/bin/setup_mig.sh
!/bin/bash
nvidia-smi -i 0 -mig 1
sudo nvidia-smi mig -dgi
sudo nvidia-smi mig -cgi 14,14,14,20 -C
Grant execute permission:
chmod +x /usr/local/bin/setup_mig.sh
Create a system service:
vi /etc/systemd/system/setup_mig.service
[Unit]
Description=Setup NVIDIA MIG Instances
After=default.target
[Service]
Type=oneshot
ExecStart=/usr/local/bin/setup_mig.sh
[Install]
WantedBy=default.target
Enable and start setup_mig.service:
sudo systemctl daemon-reload
sudo systemctl enable setup_mig.service
sudo systemctl status setup_mig.service
Prepare MIG Container environment
Install Docker and NVIDIA Container Toolkit on VM
sudo apt-get update
sudo apt-get install -y docker.io
sudo apt-get install -y aptitude
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add –
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo aptitude install -y nvidia-docker2
sudo systemctl restart docker
sudo aptitude install -y nvidia-container-toolkit
sudo systemctl restart docker
Configure create Container script on VM
#vi createcontainer.sh
#!/bin/bash
# 容器名称数组
CONTAINER_NAMES=(“mig1_tensorrt_container” “mig2_tensorrt_container” “mig3_tensorrt_container” “mig4_tensorrt_container”)
# 删除已有的容器
for CONTAINER in “${CONTAINER_NAMES[@]}”; do
if [ “$(sudo docker ps -a -q -f name=$CONTAINER)” ]; then
echo “Stopping and removing container: $CONTAINER”
sudo docker stop $CONTAINER
sudo docker rm $CONTAINER
fi
done
# 获取MIG设备的UUID
MIG_UUIDS=$(nvidia-smi -L | grep ‘MIG’ | awk -F ‘UUID: ‘ ‘{print $2}’ | awk -F ‘)’ ‘{print $1}’)
UUID_ARRAY=($MIG_UUIDS)
# 检查是否获取到足够的MIG设备UUID
if [ ${#UUID_ARRAY[@]} -lt 4 ]; then
echo “Error: Not enough MIG devices found.”
exit 1
fi
# 启动容器
sudo docker run –gpus ‘”device=’${UUID_ARRAY[0]}'”‘ -v /mig1:/mnt/mig1 -p 8081:80 -d –name mig1_tensorrt_container nvcr.io/nvidia/pytorch:24.05-py3 tail -f /dev/null
sudo docker run –gpus ‘”device=’${UUID_ARRAY[1]}'”‘ -v /mig2:/mnt/mig2 -p 8082:80 -d –name mig2_tensorrt_container nvcr.io/nvidia/pytorch:24.05-py3 tail -f /dev/null
sudo docker run –gpus ‘”device=’${UUID_ARRAY[2]}'”‘ -v /mig3:/mnt/mig3 -p 8083:80 -d –name mig3_tensorrt_container nvcr.io/nvidia/pytorch:24.05-py3 tail -f /dev/null
sudo docker run –gpus ‘”device=’${UUID_ARRAY[3]}'”‘ -v /mig4:/mnt/mig4 -p 8084:80 -d –name mig4_tensorrt_container nvcr.io/nvidia/pytorch:24.05-py3 tail -f /dev/null
# 打印容器状态
sudo docker ps
sudo ufw allow 8081
sudo ufw allow 8082
sudo ufw allow 8083
sudo ufw allow 8084
sudo ufw reload
Check container is accessible from outside.
In container, start 80 listener:
root@david1a100:~# sudo docker exec -it mig1_tensorrt_container /bin/bash
root@b6abf5bf48ae:/workspace# python3 -m http.server 80
Serving HTTP on 0.0.0.0 port 80 (http://0.0.0.0:80/) …
167.220.233.184 – – [23/Aug/2024 10:54:47] “GET / HTTP/1.1” 200 –
Curl from my laptop:
(base) PS C:Usersxinyuwei> curl http://20.5.**.**:8081
StatusCode : 200
StatusDescription : OK
Content : <!DOCTYPE HTML PUBLIC “-//W3C//DTD HTML 4.01//EN” “http://www.w3.org/TR/html4/strict.dtd“>
<html>
<head>
<meta http-equiv=”Content-Type” content=”text/html; charset=utf-8″>
<title>Directory listing fo…
RawContent : HTTP/1.0 200 OK
Content-Length: 594
Content-Type: text/html; charset=utf-8
Date: Fri, 23 Aug 2024 10:54:47 GMT
Server: SimpleHTTP/0.6 Python/3.10.12
In container, ping google.com:
root@david1a100:~#sudo docker exec -it mig1_tensorrt_container /bin/bash
root@b6abf5bf48ae:/workspace# pip install ping3
root@b6abf5bf48ae:/workspace# ping3 www.google.com
ping ‘www.google.com‘ … 2ms
ping ‘www.google.com‘ … 1ms
ping ‘www.google.com‘ … 1ms
ping ‘www.google.com‘ … 1ms
Related useful commands.
Do SD inference test in Container.
Check tensorrt version in container:
root@david1a100:/workspace# pip show tensorrt
Name: tensorrt
Version: 10.2.0
Summary: A high performance deep learning inference library
Home-page: https://developer.nvidia.com/tensorrt
Author: NVIDIA Corporation
Author-email:
License: Proprietary
Location: /usr/local/lib/python3.10/dist-packages
Requires:
Required-by:
Do SD test via github examples, in container：
git clone –branch release/10.2 –single-branch https://github.com/NVIDIA/TensorRT.git
cd TensorRT/demo/Diffusion
pip3 install -r requirements.txt
Genarate inmage 1024*1024 image from test.
python3 demo_txt2img.py “a beautiful photograph of Mt. Fuji during cherry blossom” –hf-token=$HF_TOKEN
We could check the speed of generating image in different:
In MIG1 container, which has 2 GPC and 20G memory:
In mig4 container, which has 2 GPC and 20G memory:
Check The output image is as following, copy it to VM and download it.
#cp ./output/* /mig1
Compare Int8 inference speed and quality on H100 GPU
Tested Stable Diffusion XL1.0 on a single H100 to verify the effects of int8. NVIDIA claims that on H100, INT8 is optimised over A100.
#python3 demo_txt2img_xl.py “a photo of an astronaut riding a horse on mars” –hf-token=$HF_TOKEN –version=xl-1.0
Image generation effect:
Use SDXL & INT8 AMMO quantization：
python3 demo_txt2img_xl.py “a photo of an astronaut riding a horse on mars” –version xl-1.0 –onnx-dir onnx-sdxl –engine-dir engine-sdxl –int8
After executing the above command, 8-bit quantisation of the model will be performed first.
Check generated image:
We see that the quality of the generated images is the same, and the file sizes are almost identical as well.
We observe that the inference speed of INT8 increased by 20% compared to FP16.
Microsoft Tech Community – Latest Blogs –Read More
Findings experimental values closest to the setpoint value
Hi there,
I will try to explain the issue I am having to the best of my ability (I have also attached an example excel for clarity). Essentially, in my experiment, I am trying to analyze the loads achieved at specific angles based on setpoint angles I am feeding the actuator (each case has different setpoints but in the case I am introducing here, the setpoints go from -50 to 10). There are two actuators in this example that I am testing (Compu1 and Compu2) (there are actually about 50 overall I’m testing but in this example, there are 2), each with a different achieved angle value and its equavlient load measurement. What I am trying to have Matlab do is export the load value of that actuator that best represents the neareast achieved angle based on the set point fed into it.
Reason for that, is that when I plot the loads achieved of the two actuators, my X axis (set point angle) will have ranging values for each individual actuator so I’m trying to essentially "normalize" the data based on my set "angles to plot" column in excel (increment of 0.1 degrees) and I would want matlab to just export the nearest value to that column so that each actuator can be properly plotted together against the same X range for direct comparsion.
I hope that made sense. Again, this example only includes 2 actutors but I would appreciate it if the solution can be tailored towards an X number of actuators.
Thanks so much in advance!Hi there,
I will try to explain the issue I am having to the best of my ability (I have also attached an example excel for clarity). Essentially, in my experiment, I am trying to analyze the loads achieved at specific angles based on setpoint angles I am feeding the actuator (each case has different setpoints but in the case I am introducing here, the setpoints go from -50 to 10). There are two actuators in this example that I am testing (Compu1 and Compu2) (there are actually about 50 overall I’m testing but in this example, there are 2), each with a different achieved angle value and its equavlient load measurement. What I am trying to have Matlab do is export the load value of that actuator that best represents the neareast achieved angle based on the set point fed into it.
Reason for that, is that when I plot the loads achieved of the two actuators, my X axis (set point angle) will have ranging values for each individual actuator so I’m trying to essentially "normalize" the data based on my set "angles to plot" column in excel (increment of 0.1 degrees) and I would want matlab to just export the nearest value to that column so that each actuator can be properly plotted together against the same X range for direct comparsion.
I hope that made sense. Again, this example only includes 2 actutors but I would appreciate it if the solution can be tailored towards an X number of actuators.
Thanks so much in advance! Hi there,
I will try to explain the issue I am having to the best of my ability (I have also attached an example excel for clarity). Essentially, in my experiment, I am trying to analyze the loads achieved at specific angles based on setpoint angles I am feeding the actuator (each case has different setpoints but in the case I am introducing here, the setpoints go from -50 to 10). There are two actuators in this example that I am testing (Compu1 and Compu2) (there are actually about 50 overall I’m testing but in this example, there are 2), each with a different achieved angle value and its equavlient load measurement. What I am trying to have Matlab do is export the load value of that actuator that best represents the neareast achieved angle based on the set point fed into it.
Reason for that, is that when I plot the loads achieved of the two actuators, my X axis (set point angle) will have ranging values for each individual actuator so I’m trying to essentially "normalize" the data based on my set "angles to plot" column in excel (increment of 0.1 degrees) and I would want matlab to just export the nearest value to that column so that each actuator can be properly plotted together against the same X range for direct comparsion.
I hope that made sense. Again, this example only includes 2 actutors but I would appreciate it if the solution can be tailored towards an X number of actuators.
Thanks so much in advance! matlab, optimization, plot MATLAB Answers — New Questions
I’m trying to plot matrix data from an Excel file, but the plot I obtained (named “2”) doesn’t match my expected result (named “1”); here’s my code—can anyone assist?
I am trying to plot my matrix data from an excel file. However, what I obtained is the same as what I desired. The expected plot is name 1, while what I have obtained is named 2. Here is my code:
% Load the matrix from the Excel sheet
matrix1 = readmatrix(‘Sample_Axes.xlsx’, ‘Sheet’, ‘one’);
% Create a figure with subplots
figure;
% Plot matrix1 using contour
subplot(1, 3, 1);
contourf(matrix1, 20, ‘LineColor’, ‘none’); % 20 contour levels, ‘LineColor’, ‘none’ for no contour lines
cb1 = colorbar;
colormap jet;
title(‘Matrix 1’);
Can someone help me out?I am trying to plot my matrix data from an excel file. However, what I obtained is the same as what I desired. The expected plot is name 1, while what I have obtained is named 2. Here is my code:
% Load the matrix from the Excel sheet
matrix1 = readmatrix(‘Sample_Axes.xlsx’, ‘Sheet’, ‘one’);
% Create a figure with subplots
figure;
% Plot matrix1 using contour
subplot(1, 3, 1);
contourf(matrix1, 20, ‘LineColor’, ‘none’); % 20 contour levels, ‘LineColor’, ‘none’ for no contour lines
cb1 = colorbar;
colormap jet;
title(‘Matrix 1’);
Can someone help me out? I am trying to plot my matrix data from an excel file. However, what I obtained is the same as what I desired. The expected plot is name 1, while what I have obtained is named 2. Here is my code:
% Load the matrix from the Excel sheet
matrix1 = readmatrix(‘Sample_Axes.xlsx’, ‘Sheet’, ‘one’);
% Create a figure with subplots
figure;
% Plot matrix1 using contour
subplot(1, 3, 1);
contourf(matrix1, 20, ‘LineColor’, ‘none’); % 20 contour levels, ‘LineColor’, ‘none’ for no contour lines
cb1 = colorbar;
colormap jet;
title(‘Matrix 1’);
Can someone help me out? matrix, importing excel data, contour MATLAB Answers — New Questions
Prevant Offboarding Devices get ip from DHCP Server
Hi,
There is a way to prevent offboarding device or non-compliance device to get ip from dhcp server?
Even add the mac address to deny list when there is a non-compilance device (on the computer is not installed microsoft defender for endpoint)
I would love a solution!
Rodriguez_591
Hi,There is a way to prevent offboarding device or non-compliance device to get ip from dhcp server?Even add the mac address to deny list when there is a non-compilance device (on the computer is not installed microsoft defender for endpoint)I would love a solution! Rodriguez_591 Read More
Plotting a Simulink reinforcement learning environment
Hello there,
I have declared an environment starting from a simulink model:
env = rlSimulinkEnv("main","main/RL Agent",obsInfo,actInfo);
Then i have properly defined the training options and i have executed the training.
Now, I would like to plot the environment during the training process. In the help center i have found the possibility to use create a plot function exploiting a callback on environment update.
Are there any ways to do something similar also for the rlSimulinkEnv command without defining a custom environment with all the dynamic equations?
Thank you in advance.Hello there,
I have declared an environment starting from a simulink model:
env = rlSimulinkEnv("main","main/RL Agent",obsInfo,actInfo);
Then i have properly defined the training options and i have executed the training.
Now, I would like to plot the environment during the training process. In the help center i have found the possibility to use create a plot function exploiting a callback on environment update.
Are there any ways to do something similar also for the rlSimulinkEnv command without defining a custom environment with all the dynamic equations?
Thank you in advance. Hello there,
I have declared an environment starting from a simulink model:
env = rlSimulinkEnv("main","main/RL Agent",obsInfo,actInfo);
Then i have properly defined the training options and i have executed the training.
Now, I would like to plot the environment during the training process. In the help center i have found the possibility to use create a plot function exploiting a callback on environment update.
Are there any ways to do something similar also for the rlSimulinkEnv command without defining a custom environment with all the dynamic equations?
Thank you in advance. rl, simulink, enviroment, plot MATLAB Answers — New Questions
Issue on running PV array/VSC concurrently with Synchronous Machine
Hello,
I am having some trouble in simulating on Simulink this two blocks together:
PV array / Universal Bridge (VSC average model) – I don’t know which is responsible for the errors….
Synchronous Machine
I am able to run these blocks separately (by commenting one, then running the simulation and later commenting the other and running again) so I know it isn’t a problem with parameters and neither a singularity in the synchronous machine, which is one of the errors message that I receive when I try to simulate them together.
Also I know that, probably, it isn’t caused by the dynamics of the system because, as you can see in my model, I put a breaker on the PV array, and tried to run with it open, so that it doesn’t affect the dynamics of the system/synchronous machine, and even so the simulation goes wrong.
Does anybody knows what may be happening? Did this occur with you too? How can I solve it?
Please, try to run the cases I just said and see for yourself.*
The error happens at t = 0.0566 when both PV and SM are connected and non-commented.
*First, run "init_var.m" for setting the system parameters and variables.Hello,
I am having some trouble in simulating on Simulink this two blocks together:
PV array / Universal Bridge (VSC average model) – I don’t know which is responsible for the errors….
Synchronous Machine
I am able to run these blocks separately (by commenting one, then running the simulation and later commenting the other and running again) so I know it isn’t a problem with parameters and neither a singularity in the synchronous machine, which is one of the errors message that I receive when I try to simulate them together.
Also I know that, probably, it isn’t caused by the dynamics of the system because, as you can see in my model, I put a breaker on the PV array, and tried to run with it open, so that it doesn’t affect the dynamics of the system/synchronous machine, and even so the simulation goes wrong.
Does anybody knows what may be happening? Did this occur with you too? How can I solve it?
Please, try to run the cases I just said and see for yourself.*
The error happens at t = 0.0566 when both PV and SM are connected and non-commented.
*First, run "init_var.m" for setting the system parameters and variables. Hello,
I am having some trouble in simulating on Simulink this two blocks together:
PV array / Universal Bridge (VSC average model) – I don’t know which is responsible for the errors….
Synchronous Machine
I am able to run these blocks separately (by commenting one, then running the simulation and later commenting the other and running again) so I know it isn’t a problem with parameters and neither a singularity in the synchronous machine, which is one of the errors message that I receive when I try to simulate them together.
Also I know that, probably, it isn’t caused by the dynamics of the system because, as you can see in my model, I put a breaker on the PV array, and tried to run with it open, so that it doesn’t affect the dynamics of the system/synchronous machine, and even so the simulation goes wrong.
Does anybody knows what may be happening? Did this occur with you too? How can I solve it?
Please, try to run the cases I just said and see for yourself.*
The error happens at t = 0.0566 when both PV and SM are connected and non-commented.
*First, run "init_var.m" for setting the system parameters and variables. pv array, simulink, synchronous machine, universal bridge, vsc MATLAB Answers — New Questions
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