Month: September 2024
the folder AMSimulink.ml not available
After installation of MATLAB i can use connection of MATLAB and Aspentech dynamic
after that not possible due to AMSimulink.ml not availbleAfter installation of MATLAB i can use connection of MATLAB and Aspentech dynamic
after that not possible due to AMSimulink.ml not availble After installation of MATLAB i can use connection of MATLAB and Aspentech dynamic
after that not possible due to AMSimulink.ml not availble amsimulink.ml and matlab aspentch not installed MATLAB Answers — New Questions
Pressure-flow characteristic for a 4-Way Directional Valve
I’ve to parametrize the block "4-Way Directional Valve" in Simscape Fluids by using Pressure-flow characteristic. I’ve read carefully the documentation: https://it.mathworks.com/help/physmod/hydro/ref/4waydirectionalvalve.html, but unfortunately not everything is clear. In particular the pressure differential vector is not well defined (what positive pressure or negative pressure means?) and the same for the volumetric flow. Assuming positive pressure drop from A to P and positive flow from P to A I’ve used the following parameter, but I’m note sure it’s right, someone could confirm?
x= [0,2,4,6,8,10]; %mm, spool position
P=[5,50,315]; %pressure vector bar
q5b= [0,0, 4, 14,31,58]; %liters/minute at 5 bar
q50b=[0,0, 8, 20,35,58]; %liters/minute at 50 bar
q315b=[0,0, 13, 23,33,40]; %liters/minute at 315 bar
M=[q5b’ q50b’ q315b’]; %volumetric flow rate tableI’ve to parametrize the block "4-Way Directional Valve" in Simscape Fluids by using Pressure-flow characteristic. I’ve read carefully the documentation: https://it.mathworks.com/help/physmod/hydro/ref/4waydirectionalvalve.html, but unfortunately not everything is clear. In particular the pressure differential vector is not well defined (what positive pressure or negative pressure means?) and the same for the volumetric flow. Assuming positive pressure drop from A to P and positive flow from P to A I’ve used the following parameter, but I’m note sure it’s right, someone could confirm?
x= [0,2,4,6,8,10]; %mm, spool position
P=[5,50,315]; %pressure vector bar
q5b= [0,0, 4, 14,31,58]; %liters/minute at 5 bar
q50b=[0,0, 8, 20,35,58]; %liters/minute at 50 bar
q315b=[0,0, 13, 23,33,40]; %liters/minute at 315 bar
M=[q5b’ q50b’ q315b’]; %volumetric flow rate table I’ve to parametrize the block "4-Way Directional Valve" in Simscape Fluids by using Pressure-flow characteristic. I’ve read carefully the documentation: https://it.mathworks.com/help/physmod/hydro/ref/4waydirectionalvalve.html, but unfortunately not everything is clear. In particular the pressure differential vector is not well defined (what positive pressure or negative pressure means?) and the same for the volumetric flow. Assuming positive pressure drop from A to P and positive flow from P to A I’ve used the following parameter, but I’m note sure it’s right, someone could confirm?
x= [0,2,4,6,8,10]; %mm, spool position
P=[5,50,315]; %pressure vector bar
q5b= [0,0, 4, 14,31,58]; %liters/minute at 5 bar
q50b=[0,0, 8, 20,35,58]; %liters/minute at 50 bar
q315b=[0,0, 13, 23,33,40]; %liters/minute at 315 bar
M=[q5b’ q50b’ q315b’]; %volumetric flow rate table 4-way directional valve MATLAB Answers — New Questions
how can i unblock my personal account
Hi, yesterday I created my personal account in Outlook and its going fine, not until I try to log in on Outlook App. It keeps saying Account Blocked. I can provide number but its always undergo in error “Try another verification method”
for reference see image below
Hi, yesterday I created my personal account in Outlook and its going fine, not until I try to log in on Outlook App. It keeps saying Account Blocked. I can provide number but its always undergo in error “Try another verification method” for reference see image below Read More
M365 Community Days NYC 2024: Collaboration and Innovation
The M365 Community Days NYC 2024, held on July 26th at the Microsoft Times Square Office, was a premier event for anyone looking to enhance their knowledge and skills in Microsoft 365. This conference brought together industry experts, Microsoft MVPs, and dedicated community leaders to deliver informative sessions on the latest Microsoft 365 features and technologies. Attendees had the opportunity to network with other IT professionals, engage in hands-on labs, and participate in various fun activities and social events. The event was not only educational but also a fantastic way to connect with like-minded professionals and enjoy the vibrant atmosphere of New York City. We spoke with Austrian Microsoft Azure, Cloud and Datacenter Management MVP Michael Seidl, United Stated M365 MVP Susan Hanley, and United States Azure and Security MVP Sucheta Gawade, about their experiences as speakers at this conference.
MVP Sucheta Gawade
Michael’s presentation in New York with a colleague, who was visiting the city for the first time, provided a unique opportunity for them to forge a stronger connection through their shared professional experience. Meanwhile, Susan found immense value in the community-driven nature of these events, creating the chance to reconnect with friends in an environment where the spirit of volunteerism thrived. While Sucheta was inspired by the opportunity to share practical knowledge with a dynamic audience and engage with like-minded professionals. These interactions drive her pursuit of excellence. Sucheta stated, “Speaking at an M365 event aligns well with my career, as my work focuses on centrally managing and securing devices and apps in M365 environments.”
This engagement not only highlighted Sucheta’s expertise in M365 management but also marked a significant milestone in her journey, reflecting on the transformative power of technology in fostering a connected and secure community. Sucheta discussed the importance of intriguing questions from the audience and how technical brainstorming with fellow MVPs and IT professionals at events often helps reshape her perspective. She continued to state, “During an Intune presentation demo, an attendee’s question about automating a task sparked a solution that was later applied at work. Such interactions inspire critical thinking and creative solutions, reinforcing the power of technology and community.” While Susan discussed the value and significance of feedback. After one of her sessions, an attendee expressed gratitude, stating that what they learned made the entire day worthwhile. She stated, “The feedback made the early morning flight to New York totally worth it.” Lastly, Michael spoke about how this event was a great opportunity to observe a colleague in action, proving that this colleague may be a future MVP. His colleague made significant progress and has developed a love for speaking at conferences, which Michael believes will be instrumental in spreading the word and helping the community.
MVP Susan Hanley
This newfound enthusiasm for public speaking is not just a personal milestone but also a catalyst for broader community engagement, setting the stage for a series of transformative experiences at the M365 Community Days. Sucheta discussed how presenting at events like this one requires preparation and staying current with the latest technology to effectively discuss innovations and engage in advanced technical collaboration. This commitment has strengthened her dedication to staying updated with the rapidly evolving Microsoft technology landscape. Additionally, Sucheta’s preference for in-person collaboration has grown, as she found the interactions invaluable. Whereas Michael emphasized that at every conference, the direct interaction with the audience and their feedback when they leave with new knowledge from his session is what makes it worthwhile. Finally, Susan stated, “Since I work from home, community days provide a great opportunity to learn from my colleagues and make connections that make me a better partner for my clients. It’s a great way to meet colleagues I can bring into my engagements.”
In conclusion, the M365 Community Days NYC 2024 event was a remarkable experience that united Microsoft FTEs, Microsoft MVPs, Regional Directors, and members of the tech community.
The feedback from the audience indicated that the event was highly informative and worthwhile to attend. This gathering fostered an environment of collaboration and innovation, providing a platform for sharing knowledge and advancing the field of technology. It aimed to strengthen Microsoft 365 skills by offering expert sessions and networking opportunities. Interactions and feedback from attendees highlighted the value of in-person collaboration and the power of technology and community. The commitment to staying updated with the latest technology and the enthusiasm generated by these events reinforced the importance of continuous learning and professional growth. Overall, the event was a testament to the vibrant and dynamic nature of the Microsoft 365 community.
MVP Michael Seidl
Microsoft Tech Community – Latest Blogs –Read More
reinforcement learning toolbox. error: Error encountered while creating actor representation: Observation names must match the names of the deep neural network’s input layers.
Error encountered while creating actor representation:
Observation names must match the names of the deep neural network’s input layers. Make sure all observation names appear in the neural network.
My code
% Clear workspace, command window, and close all figures
clear all; clc; close all;
% Define State and Action Dimensions
stateDim = 5; % State dimension
actionDim = 3; % Action dimension
% Create Observation and Action Specifications
ObservationInfo = rlNumericSpec([stateDim 1]);
ObservationInfo.Name = "state";
ActionInfo = rlNumericSpec([actionDim 1], ‘LowerLimit’, [-1; -1; -1], ‘UpperLimit’, [1; 1; 1]);
ActionInfo.Name = "action";
% Display the properties to ensure consistency
disp(ObservationInfo);
disp(ActionInfo);
% Create the environment with the step and reset functions
try
env = rlFunctionEnv(ObservationInfo, ActionInfo, @stepFunction, @resetFunction);
catch ME
disp(‘Error setting up environment:’);
disp(ME.message);
return;
end
% Create a minimal critic network
criticNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(1, ‘Name’, ‘output’)];
% Create a minimal actor network
actorNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(actionDim, ‘Name’, ‘output’)];
% Display layer names for verification
disp([‘Critic Network Input Layer Name: ‘, criticNetwork(1).Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
% Attempt to create the actor and critic representations
try
critic = rlValueFunction(layerGraph(criticNetwork), ObservationInfo);
actor = rlStochasticActorRepresentation(layerGraph(actorNetwork), ObservationInfo, ActionInfo);
catch ME
disp(‘Error encountered while creating actor representation:’);
disp(ME.message);
disp(‘Observation Info and Actor Network Input Layer Names:’);
disp([‘ObservationInfo Name: ‘, ObservationInfo.Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
return; % Stop execution if there’s a mismatch error
end
% Create the PPO agent and specify agent options
agentOptions = rlPPOAgentOptions(‘ClipFactor’, 0.2, ‘EntropyLossWeight’, 0.01, …
‘SampleTime’, 0.1, ‘MiniBatchSize’, 64, ‘ExperienceHorizon’, 128);
agent = rlPPOAgent(actor, critic, agentOptions);
% Specify training options and run training
trainOpts = rlTrainingOptions(‘MaxEpisodes’, 1000, ‘MaxStepsPerEpisode’, 500, …
‘Verbose’, true, ‘Plots’, ‘training-progress’, ‘StopTrainingCriteria’, ‘AverageReward’, …
‘StopTrainingValue’, 500);
trainingStats = train(agent, env, trainOpts);
% Custom reset function to initialize the environment
function [initialObs, loggedSignals] = resetFunction()
stateDim = 5;
initialObs = randn(stateDim, 1);
loggedSignals.State = initialObs;
end
% Custom step function to define environment behavior
function [nextObs, reward, isDone, loggedSignals] = stepFunction(action, loggedSignals)
state = loggedSignals.State;
nextObs = state + [0.1 * action; zeros(2, 1)];
reward = -sum((nextObs(1:3) – action).^2);
isDone = any(abs(nextObs(1:3)) > 10);
loggedSignals.State = nextObs;
endError encountered while creating actor representation:
Observation names must match the names of the deep neural network’s input layers. Make sure all observation names appear in the neural network.
My code
% Clear workspace, command window, and close all figures
clear all; clc; close all;
% Define State and Action Dimensions
stateDim = 5; % State dimension
actionDim = 3; % Action dimension
% Create Observation and Action Specifications
ObservationInfo = rlNumericSpec([stateDim 1]);
ObservationInfo.Name = "state";
ActionInfo = rlNumericSpec([actionDim 1], ‘LowerLimit’, [-1; -1; -1], ‘UpperLimit’, [1; 1; 1]);
ActionInfo.Name = "action";
% Display the properties to ensure consistency
disp(ObservationInfo);
disp(ActionInfo);
% Create the environment with the step and reset functions
try
env = rlFunctionEnv(ObservationInfo, ActionInfo, @stepFunction, @resetFunction);
catch ME
disp(‘Error setting up environment:’);
disp(ME.message);
return;
end
% Create a minimal critic network
criticNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(1, ‘Name’, ‘output’)];
% Create a minimal actor network
actorNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(actionDim, ‘Name’, ‘output’)];
% Display layer names for verification
disp([‘Critic Network Input Layer Name: ‘, criticNetwork(1).Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
% Attempt to create the actor and critic representations
try
critic = rlValueFunction(layerGraph(criticNetwork), ObservationInfo);
actor = rlStochasticActorRepresentation(layerGraph(actorNetwork), ObservationInfo, ActionInfo);
catch ME
disp(‘Error encountered while creating actor representation:’);
disp(ME.message);
disp(‘Observation Info and Actor Network Input Layer Names:’);
disp([‘ObservationInfo Name: ‘, ObservationInfo.Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
return; % Stop execution if there’s a mismatch error
end
% Create the PPO agent and specify agent options
agentOptions = rlPPOAgentOptions(‘ClipFactor’, 0.2, ‘EntropyLossWeight’, 0.01, …
‘SampleTime’, 0.1, ‘MiniBatchSize’, 64, ‘ExperienceHorizon’, 128);
agent = rlPPOAgent(actor, critic, agentOptions);
% Specify training options and run training
trainOpts = rlTrainingOptions(‘MaxEpisodes’, 1000, ‘MaxStepsPerEpisode’, 500, …
‘Verbose’, true, ‘Plots’, ‘training-progress’, ‘StopTrainingCriteria’, ‘AverageReward’, …
‘StopTrainingValue’, 500);
trainingStats = train(agent, env, trainOpts);
% Custom reset function to initialize the environment
function [initialObs, loggedSignals] = resetFunction()
stateDim = 5;
initialObs = randn(stateDim, 1);
loggedSignals.State = initialObs;
end
% Custom step function to define environment behavior
function [nextObs, reward, isDone, loggedSignals] = stepFunction(action, loggedSignals)
state = loggedSignals.State;
nextObs = state + [0.1 * action; zeros(2, 1)];
reward = -sum((nextObs(1:3) – action).^2);
isDone = any(abs(nextObs(1:3)) > 10);
loggedSignals.State = nextObs;
end Error encountered while creating actor representation:
Observation names must match the names of the deep neural network’s input layers. Make sure all observation names appear in the neural network.
My code
% Clear workspace, command window, and close all figures
clear all; clc; close all;
% Define State and Action Dimensions
stateDim = 5; % State dimension
actionDim = 3; % Action dimension
% Create Observation and Action Specifications
ObservationInfo = rlNumericSpec([stateDim 1]);
ObservationInfo.Name = "state";
ActionInfo = rlNumericSpec([actionDim 1], ‘LowerLimit’, [-1; -1; -1], ‘UpperLimit’, [1; 1; 1]);
ActionInfo.Name = "action";
% Display the properties to ensure consistency
disp(ObservationInfo);
disp(ActionInfo);
% Create the environment with the step and reset functions
try
env = rlFunctionEnv(ObservationInfo, ActionInfo, @stepFunction, @resetFunction);
catch ME
disp(‘Error setting up environment:’);
disp(ME.message);
return;
end
% Create a minimal critic network
criticNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(1, ‘Name’, ‘output’)];
% Create a minimal actor network
actorNetwork = [
featureInputLayer(stateDim, ‘Normalization’, ‘none’, ‘Name’, ‘state’)
fullyConnectedLayer(actionDim, ‘Name’, ‘output’)];
% Display layer names for verification
disp([‘Critic Network Input Layer Name: ‘, criticNetwork(1).Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
% Attempt to create the actor and critic representations
try
critic = rlValueFunction(layerGraph(criticNetwork), ObservationInfo);
actor = rlStochasticActorRepresentation(layerGraph(actorNetwork), ObservationInfo, ActionInfo);
catch ME
disp(‘Error encountered while creating actor representation:’);
disp(ME.message);
disp(‘Observation Info and Actor Network Input Layer Names:’);
disp([‘ObservationInfo Name: ‘, ObservationInfo.Name]);
disp([‘Actor Network Input Layer Name: ‘, actorNetwork(1).Name]);
return; % Stop execution if there’s a mismatch error
end
% Create the PPO agent and specify agent options
agentOptions = rlPPOAgentOptions(‘ClipFactor’, 0.2, ‘EntropyLossWeight’, 0.01, …
‘SampleTime’, 0.1, ‘MiniBatchSize’, 64, ‘ExperienceHorizon’, 128);
agent = rlPPOAgent(actor, critic, agentOptions);
% Specify training options and run training
trainOpts = rlTrainingOptions(‘MaxEpisodes’, 1000, ‘MaxStepsPerEpisode’, 500, …
‘Verbose’, true, ‘Plots’, ‘training-progress’, ‘StopTrainingCriteria’, ‘AverageReward’, …
‘StopTrainingValue’, 500);
trainingStats = train(agent, env, trainOpts);
% Custom reset function to initialize the environment
function [initialObs, loggedSignals] = resetFunction()
stateDim = 5;
initialObs = randn(stateDim, 1);
loggedSignals.State = initialObs;
end
% Custom step function to define environment behavior
function [nextObs, reward, isDone, loggedSignals] = stepFunction(action, loggedSignals)
state = loggedSignals.State;
nextObs = state + [0.1 * action; zeros(2, 1)];
reward = -sum((nextObs(1:3) – action).^2);
isDone = any(abs(nextObs(1:3)) > 10);
loggedSignals.State = nextObs;
end reinforced learning, observation names, deep neural network’s input layers. MATLAB Answers — New Questions
What types of components should be connected to the interfaces of the fault(three-phase) module?
What components should be connected to the external trigger of the faulty (three-phase) module? I think it should be input control signals, such as step modules, PWM modules, or signal generators. But the interface of the faulty module is triangular, and none of the above matches and cannot be connected. Should I choose other modules? How do I still need to convert it? Another interface is the three-phase composite interface, which directly includes the ABC three-phase, which makes it impossible for me to connect this faulty module to my three-phase circuit. Even if I tried to combine the three phases with mux, I couldn’t connect to the symbol interface. Can this interface only connect components such as programmable voltage sources that are also three-phase composite interfaces?What components should be connected to the external trigger of the faulty (three-phase) module? I think it should be input control signals, such as step modules, PWM modules, or signal generators. But the interface of the faulty module is triangular, and none of the above matches and cannot be connected. Should I choose other modules? How do I still need to convert it? Another interface is the three-phase composite interface, which directly includes the ABC three-phase, which makes it impossible for me to connect this faulty module to my three-phase circuit. Even if I tried to combine the three phases with mux, I couldn’t connect to the symbol interface. Can this interface only connect components such as programmable voltage sources that are also three-phase composite interfaces? What components should be connected to the external trigger of the faulty (three-phase) module? I think it should be input control signals, such as step modules, PWM modules, or signal generators. But the interface of the faulty module is triangular, and none of the above matches and cannot be connected. Should I choose other modules? How do I still need to convert it? Another interface is the three-phase composite interface, which directly includes the ABC three-phase, which makes it impossible for me to connect this faulty module to my three-phase circuit. Even if I tried to combine the three phases with mux, I couldn’t connect to the symbol interface. Can this interface only connect components such as programmable voltage sources that are also three-phase composite interfaces? simulink, signal MATLAB Answers — New Questions
Multiply two probability plots (CDF/PDF)
I have two probability plots, one generated as a CDF, and one as a pdf. The exact mathematics is not important for my purpose, I only want to extract the qualitative idea.
This is the code I used:
figure()
ax1 = subplot(1,1,1);
cdfplot(temp);
% plot(DE,y)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
figure();
pd_HOLT = fitdist(total_HOLT,’Normal’);
DE_HOLT = bingroups_HOLT;
y_HOLT = pdf(pd_HOLT,DE_HOLT);
ax1 = subplot(1,1,1);
plot(DE_HOLT,y_HOLT)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
The x-axis is the same. How can I multiply these plots to convey a (qualitative) idea? Thanks.I have two probability plots, one generated as a CDF, and one as a pdf. The exact mathematics is not important for my purpose, I only want to extract the qualitative idea.
This is the code I used:
figure()
ax1 = subplot(1,1,1);
cdfplot(temp);
% plot(DE,y)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
figure();
pd_HOLT = fitdist(total_HOLT,’Normal’);
DE_HOLT = bingroups_HOLT;
y_HOLT = pdf(pd_HOLT,DE_HOLT);
ax1 = subplot(1,1,1);
plot(DE_HOLT,y_HOLT)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
The x-axis is the same. How can I multiply these plots to convey a (qualitative) idea? Thanks. I have two probability plots, one generated as a CDF, and one as a pdf. The exact mathematics is not important for my purpose, I only want to extract the qualitative idea.
This is the code I used:
figure()
ax1 = subplot(1,1,1);
cdfplot(temp);
% plot(DE,y)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
figure();
pd_HOLT = fitdist(total_HOLT,’Normal’);
DE_HOLT = bingroups_HOLT;
y_HOLT = pdf(pd_HOLT,DE_HOLT);
ax1 = subplot(1,1,1);
plot(DE_HOLT,y_HOLT)
ax1.XDir = ‘reverse’;
set(gca, ‘YScale’, ‘log’)
The x-axis is the same. How can I multiply these plots to convey a (qualitative) idea? Thanks. probability, distribution, multiply MATLAB Answers — New Questions
Outlook displaying only some images
I have two problems that may or may not be related. In Outlook 365 sometimes emails will not display in the preview pane. Click on another email and click back and it often displays. Not a big issue, mainly a small annoyance.
I mention it because it may be related to the second. An email with multiple images will display some, but not others. Typically it does not display smaller images. For example a product sale newsletter will display the full page width specials, but not the smaller line items which may be quarter width.
I checked trust center and also Control Panel –> Internet Options –> Advanced Tab –> “Do not save encrypted pages to disk” is unchecked.
Below is an example.
I have two problems that may or may not be related. In Outlook 365 sometimes emails will not display in the preview pane. Click on another email and click back and it often displays. Not a big issue, mainly a small annoyance. I mention it because it may be related to the second. An email with multiple images will display some, but not others. Typically it does not display smaller images. For example a product sale newsletter will display the full page width specials, but not the smaller line items which may be quarter width.I checked trust center and also Control Panel –> Internet Options –> Advanced Tab –> “Do not save encrypted pages to disk” is unchecked. Below is an example. Read More
appData has randomly disappeared and crashing app
Very weird issue. We store local cache for EF model in
Environment.GetFolderPath(Environment.SpecialFolder.ApplicationData)
Been doing this for years. We restarted the app this afternoon, and it suddenly crashed just on restart without any code changes. In debugging I found that this code is now returning an empty string, so the path to save is invalid.
Why did this path suddenly cease to exist, and why on a restart without any actual code deployment? Is there some documented change to Azure App Services that would explain how to properly retrieve AppData path?
Very weird issue. We store local cache for EF model in Environment.GetFolderPath(Environment.SpecialFolder.ApplicationData) Been doing this for years. We restarted the app this afternoon, and it suddenly crashed just on restart without any code changes. In debugging I found that this code is now returning an empty string, so the path to save is invalid. Why did this path suddenly cease to exist, and why on a restart without any actual code deployment? Is there some documented change to Azure App Services that would explain how to properly retrieve AppData path? Read More
One Drive Frozen
I bought more storage and still one drive is frozen. I can’t get into it at all.
I bought more storage and still one drive is frozen. I can’t get into it at all. Read More
How do I solve “pyrunfile is not suppoted” error in MATLAB Function ?
I got these errors in MATLAB Function. I tried everything but I couldn’t figure out how to solve. I’m not sure.
Could you give me any advice? I’d be happy if you could tell me why this happens and where I’m missing.
Also, I’m now executing this model on MATLAB Online.
Error1
The function ‘pyrunfile’ is not supported in code generation.
Function ‘MATLAB Function’ (#24.95.220), line 2, column 13:.
“pyrunfile(“scikit_learn_model.py”, “output_vars”,in1=input1,in2=input2,in3=input3")
Error2
Terminal width or dimension error.
‘Output terminal 1’ in ‘MATLAB Function/input7’ is a 1-dimensional vector with 1 element
Here is my .slx model.
Also, Here is my MATLAB Function code.
function [trq,brake] = RunPython(input1,input2,input3,input4,input5,input6,input7)
outputs=pyrunfile("scikit_learn_model.py","output_vars",in1=input1,in2=input2,in3=input3,in4=input4,in5=input5,in6=input6,in7=input7);
trq=outputs(1);
brake=outputs(2);
end
scikit_learn_model.py
import pickle
with open(‘surrogate_model.pkl’, ‘rb’) as f:
model = pickle.load(f)
inputs = [in1,in2,in3,in4,in5,in6,in7]
output1, output2 = model.predict(inputs)
output_vars=[output1,output2]I got these errors in MATLAB Function. I tried everything but I couldn’t figure out how to solve. I’m not sure.
Could you give me any advice? I’d be happy if you could tell me why this happens and where I’m missing.
Also, I’m now executing this model on MATLAB Online.
Error1
The function ‘pyrunfile’ is not supported in code generation.
Function ‘MATLAB Function’ (#24.95.220), line 2, column 13:.
“pyrunfile(“scikit_learn_model.py”, “output_vars”,in1=input1,in2=input2,in3=input3")
Error2
Terminal width or dimension error.
‘Output terminal 1’ in ‘MATLAB Function/input7’ is a 1-dimensional vector with 1 element
Here is my .slx model.
Also, Here is my MATLAB Function code.
function [trq,brake] = RunPython(input1,input2,input3,input4,input5,input6,input7)
outputs=pyrunfile("scikit_learn_model.py","output_vars",in1=input1,in2=input2,in3=input3,in4=input4,in5=input5,in6=input6,in7=input7);
trq=outputs(1);
brake=outputs(2);
end
scikit_learn_model.py
import pickle
with open(‘surrogate_model.pkl’, ‘rb’) as f:
model = pickle.load(f)
inputs = [in1,in2,in3,in4,in5,in6,in7]
output1, output2 = model.predict(inputs)
output_vars=[output1,output2] I got these errors in MATLAB Function. I tried everything but I couldn’t figure out how to solve. I’m not sure.
Could you give me any advice? I’d be happy if you could tell me why this happens and where I’m missing.
Also, I’m now executing this model on MATLAB Online.
Error1
The function ‘pyrunfile’ is not supported in code generation.
Function ‘MATLAB Function’ (#24.95.220), line 2, column 13:.
“pyrunfile(“scikit_learn_model.py”, “output_vars”,in1=input1,in2=input2,in3=input3")
Error2
Terminal width or dimension error.
‘Output terminal 1’ in ‘MATLAB Function/input7’ is a 1-dimensional vector with 1 element
Here is my .slx model.
Also, Here is my MATLAB Function code.
function [trq,brake] = RunPython(input1,input2,input3,input4,input5,input6,input7)
outputs=pyrunfile("scikit_learn_model.py","output_vars",in1=input1,in2=input2,in3=input3,in4=input4,in5=input5,in6=input6,in7=input7);
trq=outputs(1);
brake=outputs(2);
end
scikit_learn_model.py
import pickle
with open(‘surrogate_model.pkl’, ‘rb’) as f:
model = pickle.load(f)
inputs = [in1,in2,in3,in4,in5,in6,in7]
output1, output2 = model.predict(inputs)
output_vars=[output1,output2] python, matlab function MATLAB Answers — New Questions
Is it possible to make Machine Learning model to predict multiple outputs with Statistics and Machine Learning Toolbox?
I’d like to create a model to predict two output signals based on the following seven input signals, by using Statistics and Machine Learning Toolbox.
This csv is a the data (about 4,200 rows) used as training data.
This data is a time series every 0.025 seconds.
I think the model type is Regressin model if you create a model from this data.
(Data type of each Signal is double type.)
Input Signals：
V_TGT_Vehicle
P_DCDC_PNT_W
P_HVAC_PNT_W
SOC_BT_Hi_PNT_per
open_accel_Driver_per
open_break_Driver_per
w_MG_PNT_radps
Output Signals：
trq_MG2_tgtCalc1
trq_MG2_tgtCalc2
I’ve been going through Statistics and Machine Learning Toolbox documentation, I’m not sure if it’s possible to create a machine learning model like above.
I’d like to export the model as Simulink block.
Do you have any ideas?
How do I make this with Statistics and Machine Learning Toolbox?I’d like to create a model to predict two output signals based on the following seven input signals, by using Statistics and Machine Learning Toolbox.
This csv is a the data (about 4,200 rows) used as training data.
This data is a time series every 0.025 seconds.
I think the model type is Regressin model if you create a model from this data.
(Data type of each Signal is double type.)
Input Signals：
V_TGT_Vehicle
P_DCDC_PNT_W
P_HVAC_PNT_W
SOC_BT_Hi_PNT_per
open_accel_Driver_per
open_break_Driver_per
w_MG_PNT_radps
Output Signals：
trq_MG2_tgtCalc1
trq_MG2_tgtCalc2
I’ve been going through Statistics and Machine Learning Toolbox documentation, I’m not sure if it’s possible to create a machine learning model like above.
I’d like to export the model as Simulink block.
Do you have any ideas?
How do I make this with Statistics and Machine Learning Toolbox? I’d like to create a model to predict two output signals based on the following seven input signals, by using Statistics and Machine Learning Toolbox.
This csv is a the data (about 4,200 rows) used as training data.
This data is a time series every 0.025 seconds.
I think the model type is Regressin model if you create a model from this data.
(Data type of each Signal is double type.)
Input Signals：
V_TGT_Vehicle
P_DCDC_PNT_W
P_HVAC_PNT_W
SOC_BT_Hi_PNT_per
open_accel_Driver_per
open_break_Driver_per
w_MG_PNT_radps
Output Signals：
trq_MG2_tgtCalc1
trq_MG2_tgtCalc2
I’ve been going through Statistics and Machine Learning Toolbox documentation, I’m not sure if it’s possible to create a machine learning model like above.
I’d like to export the model as Simulink block.
Do you have any ideas?
How do I make this with Statistics and Machine Learning Toolbox? machine learning MATLAB Answers — New Questions
Excel VLOOKUP Help!
Hello!
I ran a VLOOKUP to return a customer ID. That works but how do I now only keep the results that were not returned for a mailing? When just filtering for the #N/A, it messes up the results / rows and mixes and matches the cells with wrong addresses etc. What do I do? I tried removing by duplicates but it is not working.
Hello! I ran a VLOOKUP to return a customer ID. That works but how do I now only keep the results that were not returned for a mailing? When just filtering for the #N/A, it messes up the results / rows and mixes and matches the cells with wrong addresses etc. What do I do? I tried removing by duplicates but it is not working. Read More
can’t add default access role to enterprise application
I have added a user for my Enterprise Manager, but I noticed the role assigned is not the ‘Default Access’ role. It’s a different role (‘Tester’). When I initialy created this user, there was no option for the ‘Default Access’ role. It only had ‘Tester’. I want to change the role of this user to ‘Default Access’, but I couldn’t find where to change it. I was wondering if you know where to change the role? Read More
The Marketplace Summit in the UK, maximizing marketplace success
The Marketplace Summit is happening today, in the United Kingdom. Over 350 Microsoft partners are joining us to discuss live the opportunity to build their relationship with Microsoft and accelerate growth through the marketplace. London was a perfect setting for the event as multiparty private offers are now available to customers in the United Kingdom (as well as Canada and the United States, more geographies to be added soon).
Sessions are being recorded—we will update this blog post when the on-demand sessions are published (we expect by mid-October). The event consists of five sessions, hosted by Microsoft team members from product marketing, members from the United Kingdom partner team, esteemed partners, and a guest appearance by Andy Whyte, Chief Executive Officer of MEDDICC, giving an overview of the MEDDICC sales qualification framework.
Keynote: Maximizing marketplace success
Jason Rook, Senior Director, Microsoft
Joined by guest partner speakers: Andy Whyte, CEO, MEDDICC; Nick Ross, UK&I Channel Leader, Wiz; and Amit Sinha, President and Co-Founder, WorkSpan
AI is reimagining technology, creating opportunities to accelerate innovation and sales through the Microsoft commercial marketplace. Learn how the marketplace simplifies sales and unlocks growth opportunities through multiparty private offers, which empower software development companies and channel partners to collaborate on custom deals to enhance sales opportunities.
The marketplace multiplier: Co-sell and enterprise sales
Lee Corbett, UK ISV & SaaS Recruit Lead, Microsoft
Discover the fundamentals of marketplace and gain insights into co-selling and enterprise sales, including how to leverage the marketplace to sell alongside Microsoft sellers and close bigger deals faster. This session outlines eight actionable steps to accelerate your marketplace business with Microsoft sellers and build a robust cloud go-to-market strategy.
Accelerate your growth: Cloud marketplaces for customers and GTM tools
Kristyn Maddox, Director of product marketing for the marketplace
While there has never been a better time to be a software development company, it’s a crowded market. Learn how the marketplace helps you go-to-market faster, so you can sell more. This session offers practical guidance on how to accelerate cloud marketplace sales and provides a deep dive into the marketing support Microsoft offers.
Manage your listings—from start to finish
Chris Whitehead, Senior Program Manager, Microsoft
Learn how to manage your marketplace listings from start to finish. Gain insights into creating and managing private offers, including multiparty private offers, and understanding the billing and payout processes. This session also covers tips and tricks for using Partner Center effectively to support customer success.
Activating the channel: Empowering partners to sell together
Darren Sharpe, Senior Partner Development Manager, Microsoft
Learn about the opportunities for partners to scale by selling together through the Microsoft commercial marketplace. Gain best practices for building marketplace channel practices, and the importance of accelerating marketplace channel adoption. This session provides an adoption framework that details four steps you can take to build a successful cloud marketplace resell practice to scale your business.
While the event supports holistic opportunities for the marketplace, there is a special focus on multiparty private offers. Multiparty private offers empower our Microsoft partner ecosystem of over 500K organizations to collaborate and sell together. For software development companies, this helps you find new ways to scale. For channel partners, you can extend customer relationships to the marketplace to access pre-committed cloud budget while creating a simplified procurement process for both yourself, and your customer.
Canalys recently estimated the cloud marketplace TAM at US$85B by 2028—with 50% of sales relying on channel partners—previously estimated at 30% by 20271. Multiparty private offers create a tremendous opportunity for partners to sell together, while leaning on the marketplace to alleviate sales overhead, like collecting payment or currency conversion and taxes.
Whether you joined us onsite in London or not, get the PDF below for all the latest resources to help guide your marketplace success. For companies building software, get support as you build and launch your solutions with ISV Success—the programmatic offering purpose-built for companies looking to grow through the marketplace. And if you have questions, the marketplace community is your go-to option to connect with Microsoft experts to get your question(s) answered.
1Hyperscale cloud marketplace sales to hit US$85 billion by 2028, Canalys, August 15, 2024
Microsoft Tech Community – Latest Blogs –Read More
Formula to check if date range falls within another date range
I am trying to determine if a date range falls within another date range for a specific ID.
Example:
Table1
IDStart DateEnd Date110/9/202211/19/202222/12/20233/11/2023
Table2
IDStart DateEnd DateValue110/10/202211/10/2022Leave25/5/20245/21/2024Leave
Expected Result
IDResult1Leave2(blank)
I am trying to determine if a date range falls within another date range for a specific ID. Example: Table1IDStart DateEnd Date110/9/202211/19/202222/12/20233/11/2023Table2IDStart DateEnd DateValue110/10/202211/10/2022Leave25/5/20245/21/2024LeaveExpected ResultIDResult1Leave2(blank) Read More
AVD and Bicep
Hello,
I’m trying to deploy AVD as ADD joined using bicep but it failed. The session host is created but not correctly assigned to the host pool. There is always an error with the DomainTrustCheck and DomainJoinedCheck
My code:
resource joinAzuredomain ‘Microsoft.Compute/virtualMachines/extensions@2024-07-01’ = {
name: ‘${vmPrefix}/joinAzuredomain’
location: location
properties: {
publisher: ‘Microsoft.Azure.ActiveDirectory’
type: ‘AADLoginForWindows’
typeHandlerVersion: ‘1.0’
autoUpgradeMinorVersion: true
}
dependsOn: [
vm
]
}
resource dscextension ‘Microsoft.Compute/virtualMachines/extensions@2024-07-01’ = {
name: ‘${vmPrefix}/dscextension’
location: location
properties: {
publisher: ‘Microsoft.Powershell’
type: ‘DSC’
typeHandlerVersion: ‘2.73’
autoUpgradeMinorVersion: true
settings: {
modulesUrl: ‘https://wvdportalstorageblob.blob.core.windows.net/galleryartifacts/Configuration_1.0.02627.270.zip’
configurationFunction: ‘Configuration.ps1\AddSessionHost’
properties: {
HostPoolName: hostPoolName
registrationInfoToken: HostPoolToken
aadJoin: AADJoin
}
}
}
dependsOn: [
joinAzuredomain
]
}
I follow steps found on the following links to make most of my deployment.
Ref : https://rozemuller.com/avd-automation-cocktail-avd-with-bicep-and-azure-cli/
Ref: https://tighetec.co.uk/2021/07/07/deploy-azure-virtual-desktop-with-project-bicep/
Hello, I’m trying to deploy AVD as ADD joined using bicep but it failed. The session host is created but not correctly assigned to the host pool. There is always an error with the DomainTrustCheck and DomainJoinedCheck My code:resource joinAzuredomain ‘Microsoft.Compute/virtualMachines/extensions@2024-07-01’ = {
name: ‘${vmPrefix}/joinAzuredomain’
location: location
properties: {
publisher: ‘Microsoft.Azure.ActiveDirectory’
type: ‘AADLoginForWindows’
typeHandlerVersion: ‘1.0’
autoUpgradeMinorVersion: true
}
dependsOn: [
vm
]
}
resource dscextension ‘Microsoft.Compute/virtualMachines/extensions@2024-07-01’ = {
name: ‘${vmPrefix}/dscextension’
location: location
properties: {
publisher: ‘Microsoft.Powershell’
type: ‘DSC’
typeHandlerVersion: ‘2.73’
autoUpgradeMinorVersion: true
settings: {
modulesUrl: ‘https://wvdportalstorageblob.blob.core.windows.net/galleryartifacts/Configuration_1.0.02627.270.zip’
configurationFunction: ‘Configuration.ps1\AddSessionHost’
properties: {
HostPoolName: hostPoolName
registrationInfoToken: HostPoolToken
aadJoin: AADJoin
}
}
}
dependsOn: [
joinAzuredomain
]
}I follow steps found on the following links to make most of my deployment.Ref : https://rozemuller.com/avd-automation-cocktail-avd-with-bicep-and-azure-cli/Ref: https://tighetec.co.uk/2021/07/07/deploy-azure-virtual-desktop-with-project-bicep/ Read More
BDG Game Invite Code 2024: 163786198385 (Claim Bonus)
BDG Game Invite Code is 163786198385. Apply this code at the time of signup and receive an exclusive bonus of Rs 1500 in your BDG Game account instantly. If you are a corporate employee and working 9 to 5, five to six days a week but still cannot become rich and worry about your future salary all the time.
Then this way of earning huge money is for you and that also just by playing games you can make money. Hurry up and sign up on BDG Game using our invite code and receive an exclusive bonus of Rs 1500 in your BDG Game new account.
BDG Game Invite Code
App Name
BDG Game
BDG Game Invite Code
163786198385
Signup Bonus
Rs 1500
BDG Game Invitation Code
163786198385
Big Daddy Game Invitation Code
163786198385 is your Big Daddy Game Invitation Code, apply this code and get a sign up bonus of Rs 1500 instantly. If you are a school or college student and want to earn money but don’t have that many skills to get a job now. So this platform is for you, you will not only earn for your daily expenses but also you can be your parent’s proud son by giving them their dream life they want to live ever.
And you must be getting shocked by hearing that you can earn huge money just by playing games online on BDG Game. Yes, I am talking about the Colour Prediction Games. You can simply earn by playing games here and if you want to know how to play these games then read this article till the end.
BDG Game Gift Code
If you are searching for BDG Game Gift Code but could now find anywhere and got upset then don’t worry we are here with the latest gift code of BDG Game. Apply this code “163786198385 ” at the time of signup and you will receive a gift bonus of Rs 1500 by BDG Game. This is the exclusive bonus offered to you by any online gaming platform. Get yourself registered now on BDG Game and claim this BDG Game Gift code now.
BDG Game Invite Code is 163786198385. Apply this code at the time of signup and receive an exclusive bonus of Rs 1500 in your BDG Game account instantly. If you are a corporate employee and working 9 to 5, five to six days a week but still cannot become rich and worry about your future salary all the time. Then this way of earning huge money is for you and that also just by playing games you can make money. Hurry up and sign up on BDG Game using our invite code and receive an exclusive bonus of Rs 1500 in your BDG Game new account.BDG Game Invite CodeApp NameBDG GameBDG Game Invite Code163786198385Signup BonusRs 1500BDG Game Invitation Code163786198385 Big Daddy Game Invitation Code163786198385 is your Big Daddy Game Invitation Code, apply this code and get a sign up bonus of Rs 1500 instantly. If you are a school or college student and want to earn money but don’t have that many skills to get a job now. So this platform is for you, you will not only earn for your daily expenses but also you can be your parent’s proud son by giving them their dream life they want to live ever. And you must be getting shocked by hearing that you can earn huge money just by playing games online on BDG Game. Yes, I am talking about the Colour Prediction Games. You can simply earn by playing games here and if you want to know how to play these games then read this article till the end.BDG Game Gift CodeIf you are searching for BDG Game Gift Code but could now find anywhere and got upset then don’t worry we are here with the latest gift code of BDG Game. Apply this code “163786198385 ” at the time of signup and you will receive a gift bonus of Rs 1500 by BDG Game. This is the exclusive bonus offered to you by any online gaming platform. Get yourself registered now on BDG Game and claim this BDG Game Gift code now. Read More
Reza stitches together global Fabric communities
Barcelona Power BI User Group
Reza Rad, a Microsoft MVP and Regional Director, has journeyed across the globe, visiting myriad cities and interacting with over 800 community members as he teaches them about Microsoft Fabric and Power BI. His story is one of vision and passion and his relentless schedule speaks volumes about his dedication to spreading knowledge and fostering global community spirit.
Reza’s travels have taken him to 15 cities this year alone, with more planned in his busy world tour schedule. “This year I think I have been in 15 cities so far, and there are at least 10 more for the rest of the year to come. I did not have a course in each city though, some were courses, some were user group presentations, some conferences,” he shares.
Reza Rad visiting community in the USA
Reza’s journey is not just about imparting technical knowledge and helping people upskill in Microsoft Fabric and Power BI; it’s about building global bridges amongst leaders and their community and creating lasting personal connections. “I like to thank the community leaders and MVPs in each of the cities. They are the people who host the user group sessions, Data Saturdays, and conferences and building the community over there, they are doing the most important job,” he acknowledges. These leaders and MVPs are the community champions who work tirelessly behind the scenes to make these interactions possible, and Reza’s gratitude towards them is evident.
One constant companion on Reza’s travels, although in spirit, is his wife, and inspirational MVP Leila Etaati. “I also like to mention Leila as she is the most missed person in all these travels, I know she would have enjoyed being with the community in every city,” Reza reflects. Leila, a prominent figure in the tech community, is forever remembered by her fearless leadership in Data and AI and vision for building strong community.
Hamburg PASS Data Platform User Group
Despite the busy schedule and the demands of his role as CEO of RADACAD, Reza finds a way to integrate work, community leadership, and personal wellbeing, allowing him to recharge and bring his best self to each community interaction. “That is hard to balance. I am probably spending more time in my day doing work and community activity than personal wellbeing. However, I am also trying to have a day before or after my courses or conferences just to explore the city a bit too, so giving a bit more space to pleasure part this way,” he admits.
The second half of 2024 promises to be equally exciting for Reza. “A lot of things are happening such as PASS Data Community Summit, Microsoft Ignite, I have still four more cities in the tour, and Difinity Conference dates are also approaching towards end of the year. There are still a lot to look forward to,” he says with anticipation. These events are not just milestones in his calendar; they are opportunities to continue his mission to help people to get upskilled and learn how to use the tools and services in their data analytics projects.
Reza takes the stage at the Microsoft Power BI & Fabric User Group at the Microsoft Reactor, Sydney
As Reza travels from city to city, his journey is not just about the destinations; it’s about the people he meets along the way, the communities he helps build, and the connections he fosters. “I love to see others succeed in their projects and career and I play my small part in it,” he says.
To connect with Reza and the data community, check out the upcoming events Reza has mentioned in his schedule. These include:
PASS Data Community Summit: November 4-8, 2024, in person in Seattle, US.
Microsoft Ignite: November 19–22, 2024, hybrid.
Difinity Conference: November 28, 2024, in Auckland, New Zealand.
Microsoft Tech Community – Latest Blogs –Read More
Colormap generated using the information of different arrays
Hello everyone
I am trying to plot the data in five different matrices in the same graphic. Interestingly, the elements of these matrices are not equal to NaN just in the spatial domain where, each of them, should exists. In principle, if the matrix element (i,j) of one of these matrices is different from NaN, it would not be again non-NaN in the other data arrays at (i,j). The five different matrices can be found here.
I would like to make the NaN elements to be completely transparent. As you can see, I am attaching a colormap, "Colors.txt", which is not white at the middle. I do not know if that makes any difference.
I am plotting the system as follows:
p1=uimagesc(Space_a,Space_b,mz_Tetra_1_Data);
set(p1,’alphadata’,~isnan(mz_Tetra_1_Data));
hold on
p2=uimagesc(Space_a,Space_b,mz_Tetra_2_Data);
set(p2,’alphadata’,~isnan(mz_Tetra_2_Data));
p3=uimagesc(Space_a,Space_b,mz_Penta_1_Data);
set(p3,’alphadata’,~isnan(mz_Penta_1_Data));
p4=uimagesc(Space_a,Space_b,mz_Penta_2_Data);
set(p4,’alphadata’,~isnan(mz_Penta_2_Data));
p5=uimagesc(Space_a,Space_b,mz_Hexa_Data);
set(p5,’alphadata’,~isnan(mz_Hexa_Data));
colormap(Colors);
clim([-1 1]);
Is the code above correct for my purpose?Hello everyone
I am trying to plot the data in five different matrices in the same graphic. Interestingly, the elements of these matrices are not equal to NaN just in the spatial domain where, each of them, should exists. In principle, if the matrix element (i,j) of one of these matrices is different from NaN, it would not be again non-NaN in the other data arrays at (i,j). The five different matrices can be found here.
I would like to make the NaN elements to be completely transparent. As you can see, I am attaching a colormap, "Colors.txt", which is not white at the middle. I do not know if that makes any difference.
I am plotting the system as follows:
p1=uimagesc(Space_a,Space_b,mz_Tetra_1_Data);
set(p1,’alphadata’,~isnan(mz_Tetra_1_Data));
hold on
p2=uimagesc(Space_a,Space_b,mz_Tetra_2_Data);
set(p2,’alphadata’,~isnan(mz_Tetra_2_Data));
p3=uimagesc(Space_a,Space_b,mz_Penta_1_Data);
set(p3,’alphadata’,~isnan(mz_Penta_1_Data));
p4=uimagesc(Space_a,Space_b,mz_Penta_2_Data);
set(p4,’alphadata’,~isnan(mz_Penta_2_Data));
p5=uimagesc(Space_a,Space_b,mz_Hexa_Data);
set(p5,’alphadata’,~isnan(mz_Hexa_Data));
colormap(Colors);
clim([-1 1]);
Is the code above correct for my purpose? Hello everyone
I am trying to plot the data in five different matrices in the same graphic. Interestingly, the elements of these matrices are not equal to NaN just in the spatial domain where, each of them, should exists. In principle, if the matrix element (i,j) of one of these matrices is different from NaN, it would not be again non-NaN in the other data arrays at (i,j). The five different matrices can be found here.
I would like to make the NaN elements to be completely transparent. As you can see, I am attaching a colormap, "Colors.txt", which is not white at the middle. I do not know if that makes any difference.
I am plotting the system as follows:
p1=uimagesc(Space_a,Space_b,mz_Tetra_1_Data);
set(p1,’alphadata’,~isnan(mz_Tetra_1_Data));
hold on
p2=uimagesc(Space_a,Space_b,mz_Tetra_2_Data);
set(p2,’alphadata’,~isnan(mz_Tetra_2_Data));
p3=uimagesc(Space_a,Space_b,mz_Penta_1_Data);
set(p3,’alphadata’,~isnan(mz_Penta_1_Data));
p4=uimagesc(Space_a,Space_b,mz_Penta_2_Data);
set(p4,’alphadata’,~isnan(mz_Penta_2_Data));
p5=uimagesc(Space_a,Space_b,mz_Hexa_Data);
set(p5,’alphadata’,~isnan(mz_Hexa_Data));
colormap(Colors);
clim([-1 1]);
Is the code above correct for my purpose? imagesc with nan elements being transparent MATLAB Answers — New Questions
