Category: News
MATLAB Error fitting Stable distribution to data – Help?
MATLAB returns an unknown error every time I try to fit the Stable distribution to a dataset. I haven’t encountered this error with previous datasets or MATLAB versions, but it has been 6 months since I’ve tried. This time I’ve used multiple data sets and confirmed that a Normal distribution will fit the datasets…but when I specify ‘Stable’ vice ‘Normal’, I get the following error:
"Unrecognized function or variable ‘getIpOptions’.
Error in fmincon (line 832)
options =
getIpOptions(options,sizes.nVar,mEq,flags.constr,defaultopt,10,0.01);"
This code runs:
load hospital; % get MATLAB dataset
z = hospital.Weight; % Assign data values
pd = fitdist(z,’Normal’);
However, this doesn’t and returns the above error:
pd2 = fitdist(z,’Stable’);
Is this a bug in the 2020a release?
I’m running:
>> version
ans = ‘9.8.0.1323502 (R2020a)’MATLAB returns an unknown error every time I try to fit the Stable distribution to a dataset. I haven’t encountered this error with previous datasets or MATLAB versions, but it has been 6 months since I’ve tried. This time I’ve used multiple data sets and confirmed that a Normal distribution will fit the datasets…but when I specify ‘Stable’ vice ‘Normal’, I get the following error:
"Unrecognized function or variable ‘getIpOptions’.
Error in fmincon (line 832)
options =
getIpOptions(options,sizes.nVar,mEq,flags.constr,defaultopt,10,0.01);"
This code runs:
load hospital; % get MATLAB dataset
z = hospital.Weight; % Assign data values
pd = fitdist(z,’Normal’);
However, this doesn’t and returns the above error:
pd2 = fitdist(z,’Stable’);
Is this a bug in the 2020a release?
I’m running:
>> version
ans = ‘9.8.0.1323502 (R2020a)’ MATLAB returns an unknown error every time I try to fit the Stable distribution to a dataset. I haven’t encountered this error with previous datasets or MATLAB versions, but it has been 6 months since I’ve tried. This time I’ve used multiple data sets and confirmed that a Normal distribution will fit the datasets…but when I specify ‘Stable’ vice ‘Normal’, I get the following error:
"Unrecognized function or variable ‘getIpOptions’.
Error in fmincon (line 832)
options =
getIpOptions(options,sizes.nVar,mEq,flags.constr,defaultopt,10,0.01);"
This code runs:
load hospital; % get MATLAB dataset
z = hospital.Weight; % Assign data values
pd = fitdist(z,’Normal’);
However, this doesn’t and returns the above error:
pd2 = fitdist(z,’Stable’);
Is this a bug in the 2020a release?
I’m running:
>> version
ans = ‘9.8.0.1323502 (R2020a)’ stable distribution, fitdist stable MATLAB Answers — New Questions
Derivative of state ‘1’ in block PV Array at time 0.0 is not finite error
im trying to charge a battery using a solar pv array and i keep getting the following error: An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘1’ in block ‘ChargingBatteryUsingSolarPVArray/PV Array/Diode Rsh/Transfer Fcn’ at time 0.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances)
what am i not doing correctly?im trying to charge a battery using a solar pv array and i keep getting the following error: An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘1’ in block ‘ChargingBatteryUsingSolarPVArray/PV Array/Diode Rsh/Transfer Fcn’ at time 0.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances)
what am i not doing correctly? im trying to charge a battery using a solar pv array and i keep getting the following error: An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘1’ in block ‘ChargingBatteryUsingSolarPVArray/PV Array/Diode Rsh/Transfer Fcn’ at time 0.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances)
what am i not doing correctly? simulation, simulink, simpowersystems, power_electronics_control, matlab MATLAB Answers — New Questions
How can I use the function coeffs() as the input to the function tf()?
This code works to give me the root locus of my system, but I have to manually enter the coefficients
num = [1, 117/10, 24477/400, 5584/125, -2315137/40000, 36905889/40000, -66965649/160000, -921912043/80000, 34652192177/640000, -4796713113/25600, 62141795103/160000, -223688325847/320000, 32896376299/40000, -7904756769/10000, 708588777/2000, -52514891/800];
den = [1, -4/5, -5929/400, -14969/2000, 56007543/160000, -550116261/400000, 187999365153/64000000, -1333141873017/320000000, 1759926060179/400000000, -120268082137481/32000000000, 819503408996093/320000000000, -4388359670461129/3200000000000, 338687548373223/640000000000, -1907357941873611/12800000000000, 306186935180877/10240000000000, -4892378756049/1024000000000]
sys = tf(num,den);
rlocus(sys);
However, the following code is not working. I imagine that the output of coeffs() &/or fliplr() is not technically an array despite appearing so when I print the output.
syms s
n = (s^2+10*s+50)*(s^2+8.6*s+21.73)*(s^2-0.7*s+0.1625)*(s^2-2*s+3.25)^2*(s^2+4)^2*(s-2.2);
x = expand(n);
d = (s^2+8.6*s+26.33)*(s^2+0.3*s+0.6625)*(s^2+0.09)*(s^2-0.8*s+0.25)*(s^2-0.9*s+0.5625)*(s^2-2*s+2.69)*(s^2-4*s+4.0225)*(s-2);
y = expand(d);
num = coeffs(x);
num = fliplr(num)
den = coeffs(y);
den = fliplr(den)
sys = tf(num,den); %error line
figure(1)
rlocus(sys)
If someone could help me figure out how to modify the second chunk of code so that the transfer function is created that would be much appreaciated.This code works to give me the root locus of my system, but I have to manually enter the coefficients
num = [1, 117/10, 24477/400, 5584/125, -2315137/40000, 36905889/40000, -66965649/160000, -921912043/80000, 34652192177/640000, -4796713113/25600, 62141795103/160000, -223688325847/320000, 32896376299/40000, -7904756769/10000, 708588777/2000, -52514891/800];
den = [1, -4/5, -5929/400, -14969/2000, 56007543/160000, -550116261/400000, 187999365153/64000000, -1333141873017/320000000, 1759926060179/400000000, -120268082137481/32000000000, 819503408996093/320000000000, -4388359670461129/3200000000000, 338687548373223/640000000000, -1907357941873611/12800000000000, 306186935180877/10240000000000, -4892378756049/1024000000000]
sys = tf(num,den);
rlocus(sys);
However, the following code is not working. I imagine that the output of coeffs() &/or fliplr() is not technically an array despite appearing so when I print the output.
syms s
n = (s^2+10*s+50)*(s^2+8.6*s+21.73)*(s^2-0.7*s+0.1625)*(s^2-2*s+3.25)^2*(s^2+4)^2*(s-2.2);
x = expand(n);
d = (s^2+8.6*s+26.33)*(s^2+0.3*s+0.6625)*(s^2+0.09)*(s^2-0.8*s+0.25)*(s^2-0.9*s+0.5625)*(s^2-2*s+2.69)*(s^2-4*s+4.0225)*(s-2);
y = expand(d);
num = coeffs(x);
num = fliplr(num)
den = coeffs(y);
den = fliplr(den)
sys = tf(num,den); %error line
figure(1)
rlocus(sys)
If someone could help me figure out how to modify the second chunk of code so that the transfer function is created that would be much appreaciated. This code works to give me the root locus of my system, but I have to manually enter the coefficients
num = [1, 117/10, 24477/400, 5584/125, -2315137/40000, 36905889/40000, -66965649/160000, -921912043/80000, 34652192177/640000, -4796713113/25600, 62141795103/160000, -223688325847/320000, 32896376299/40000, -7904756769/10000, 708588777/2000, -52514891/800];
den = [1, -4/5, -5929/400, -14969/2000, 56007543/160000, -550116261/400000, 187999365153/64000000, -1333141873017/320000000, 1759926060179/400000000, -120268082137481/32000000000, 819503408996093/320000000000, -4388359670461129/3200000000000, 338687548373223/640000000000, -1907357941873611/12800000000000, 306186935180877/10240000000000, -4892378756049/1024000000000]
sys = tf(num,den);
rlocus(sys);
However, the following code is not working. I imagine that the output of coeffs() &/or fliplr() is not technically an array despite appearing so when I print the output.
syms s
n = (s^2+10*s+50)*(s^2+8.6*s+21.73)*(s^2-0.7*s+0.1625)*(s^2-2*s+3.25)^2*(s^2+4)^2*(s-2.2);
x = expand(n);
d = (s^2+8.6*s+26.33)*(s^2+0.3*s+0.6625)*(s^2+0.09)*(s^2-0.8*s+0.25)*(s^2-0.9*s+0.5625)*(s^2-2*s+2.69)*(s^2-4*s+4.0225)*(s-2);
y = expand(d);
num = coeffs(x);
num = fliplr(num)
den = coeffs(y);
den = fliplr(den)
sys = tf(num,den); %error line
figure(1)
rlocus(sys)
If someone could help me figure out how to modify the second chunk of code so that the transfer function is created that would be much appreaciated. coeff, tf, coeff(), tf() MATLAB Answers — New Questions
Why do I receive an error when running command “startworker” for the MATLAB Parallel Server?
I’ve installed MATLAB R2020b on a head node and multiple worker nodes. All run RHEL 7.8. I’ve confirmed that the MATLAB and parallel server licenses are correct and have no licensing errors. I’ve successfully started MJS service on the head and worker nodes and verified with "nodestatus" command. I successfully started a MJS job manager on the head node named "myMJS". When I start a worker via the command:
./startworker -jobmanagerhost <HEADNODE> -jobmanager <myMJS> -remotehost <WORKERNODE>
I get an error stating:
The mjs service on the host <WORKERNODE>
returned the following error:
Problem starting the MATLAB worker.
=============================================================
matlabExecutable must be of the form ‘<release string>=<path to executable>;<release string>=<path to executable>;’. Actual string:
Note, there is no "actual string" given in the error message as if no command is being passed.
What am I doing wrong or could troubleshoot the issue further?I’ve installed MATLAB R2020b on a head node and multiple worker nodes. All run RHEL 7.8. I’ve confirmed that the MATLAB and parallel server licenses are correct and have no licensing errors. I’ve successfully started MJS service on the head and worker nodes and verified with "nodestatus" command. I successfully started a MJS job manager on the head node named "myMJS". When I start a worker via the command:
./startworker -jobmanagerhost <HEADNODE> -jobmanager <myMJS> -remotehost <WORKERNODE>
I get an error stating:
The mjs service on the host <WORKERNODE>
returned the following error:
Problem starting the MATLAB worker.
=============================================================
matlabExecutable must be of the form ‘<release string>=<path to executable>;<release string>=<path to executable>;’. Actual string:
Note, there is no "actual string" given in the error message as if no command is being passed.
What am I doing wrong or could troubleshoot the issue further? I’ve installed MATLAB R2020b on a head node and multiple worker nodes. All run RHEL 7.8. I’ve confirmed that the MATLAB and parallel server licenses are correct and have no licensing errors. I’ve successfully started MJS service on the head and worker nodes and verified with "nodestatus" command. I successfully started a MJS job manager on the head node named "myMJS". When I start a worker via the command:
./startworker -jobmanagerhost <HEADNODE> -jobmanager <myMJS> -remotehost <WORKERNODE>
I get an error stating:
The mjs service on the host <WORKERNODE>
returned the following error:
Problem starting the MATLAB worker.
=============================================================
matlabExecutable must be of the form ‘<release string>=<path to executable>;<release string>=<path to executable>;’. Actual string:
Note, there is no "actual string" given in the error message as if no command is being passed.
What am I doing wrong or could troubleshoot the issue further? startworker, matlab parallel server, matlabexecutable MATLAB Answers — New Questions
set parameters read from outside a compiled simulink model at startup/initialization
Hi,
I have a Simulink Model I wish to compile into an executable which works fine except that I need to be able to set some parameters/variables at the start of the program or in the initialization phase.
So far, I have no hand-written code (.c or .h) files where I could add some lines.
What do I have to do and where would I place the code?
As of now, I’ve been using the following line to compile the simulink model:
mcc(‘-N’,’-p’,’icomm’, ‘-m’,’Reglerexe’,’-a’,[‘*’,ext],’-a’,[‘*’,ext_thunk{:}], ‘-d’, myDir)
Thanks in advance for your help!
SwantjeHi,
I have a Simulink Model I wish to compile into an executable which works fine except that I need to be able to set some parameters/variables at the start of the program or in the initialization phase.
So far, I have no hand-written code (.c or .h) files where I could add some lines.
What do I have to do and where would I place the code?
As of now, I’ve been using the following line to compile the simulink model:
mcc(‘-N’,’-p’,’icomm’, ‘-m’,’Reglerexe’,’-a’,[‘*’,ext],’-a’,[‘*’,ext_thunk{:}], ‘-d’, myDir)
Thanks in advance for your help!
Swantje Hi,
I have a Simulink Model I wish to compile into an executable which works fine except that I need to be able to set some parameters/variables at the start of the program or in the initialization phase.
So far, I have no hand-written code (.c or .h) files where I could add some lines.
What do I have to do and where would I place the code?
As of now, I’ve been using the following line to compile the simulink model:
mcc(‘-N’,’-p’,’icomm’, ‘-m’,’Reglerexe’,’-a’,[‘*’,ext],’-a’,[‘*’,ext_thunk{:}], ‘-d’, myDir)
Thanks in advance for your help!
Swantje reading parameters into an executable at startup MATLAB Answers — New Questions
Exchange Online Restricts the Number of Dynamic Distribution Groups
New 3,000 Threshold for Dynamic Distribution Groups in April 2025
Fresh from its decision to impose a tenant-wide external recipient run rate (now delayed until May 2025), Microsoft announced another restriction for Exchange Online on March 5, 2025 by limiting the number of dynamic distribution groups (DDGs) in a tenant to 3000 (message center notification MC1024399). Once the limit is reached, no further dynamic distribution groups can be created until some have been removed. Microsoft plans to introduce the restriction in early April 2025.
To discover how many dynamic distribution groups are in a tenant, run this PowerShell command:
(Get-DynamicDistributionGroup).count
A Surprising Move
It’s a surprising move. Dynamic distribution groups require service resources to resolve recipient filters to individual recipients when messages pass through the transport pipeline. Microsoft announced “modern” DDGs in December 2021 (rolled out in mid-2022) to save resources and reduce the time required to process list expansion by calculating list membership on a scheduled basis in the background rather than on-demand.
Dynamic distribution groups support both precanned and custom recipient filters, and expansion of some complex custom filters is likely quite demanding. Recently, Microsoft fixed a bug in wildcard support in DDGs that affected custom filter resolution for many customers. No hint was given then or earlier that tenants might be using too many DDGs. I suspect that very few tenants surpass the new 3,000 limit.
Entra ID supports a much higher 15,000 limit shared between dynamic Microsoft 365 groups and dynamic administrative units. Both the dynamic Entra ID object types require Entra P1 licenses whereas dynamic distribution groups are covered in the standard Exchange Online license. Dynamic distribution groups are not Entra ID objects and do not synchronize from Exchange Online to Entra ID. Nevertheless, it seems odd that Exchange Online should choose a much lower limit than pertains for dynamic Microsoft 365 groups. Conspiracy theorists will no doubt conclude that the new limit is yet another not-so-subtle hint from Microsoft that they’d prefer if customers use Microsoft 365 groups instead of distribution groups.
The actual answer might be that this is a simple check to stop people abusing dynamic distribution lists. Many components that consume service resources are limited in one way or another. This could just be another example of Microsoft introducing a threshold to impose an upper limit on the resources DDGs can consume.
Checking for Inactive Dynamic Distribution Groups
If your tenant is near the new limit, you might want to check for inactive Dynamic distribution groups. The easiest way to do this is using the report available in the Reports section of the Exchange admin center (Figure 1). As you can see, all 27 of the DDGs in my tenant are unused, probably because so much of my recent work has focused on Microsoft 365 Groups and Teams.
The report supports filtering for 7, 30, and 90 days and a custom start date (within the last 80 days). The information shown in the report comes from message tracing data (which goes back a maximum of 90 days). If you want more control over the reported data, you can use the technique explained in this article to run historical message trace reports and analyze that data with PowerShell (the article explains how to do this for normal distribution groups, be sure to change the reference to the Get-DistributionGroup cmdlet to Get-DynamicDistributionGroup).
Time to Trim Dynamic Distribution Groups
I don’t have knowledge about any abuse that might have driven Microsoft to clamp down on dynamic distribution groups, Given that it is very easy to build a recipient filter that addresses everyone in the tenant, it’s understandable that abuse could occur in the form of a significant increase in email volume generated when such a DDG is used. In the past, this might have caused an email storm, but Microsoft built checks for email storms into Exchange Online several years ago.
In any case, the limit will come into effect in early April 2025. Before then, it’s time to check the set of dynamic distribution groups with the aim of trimming unused DDGs. And if you can’t get the number of DDGs under the limit, consider converting them to dynamic Microsoft 365 groups.
Support the work of the Office 365 for IT Pros team by subscribing to the Office 365 for IT Pros eBook. Your support pays for the time we need to track, analyze, and document the changing world of Microsoft 365 and Office 365.
addon installer says i dont own the addon still after changing accounts
Hi, i was using personal account with trial and then i changed to my schools academic license on matlab but i still can’t download stuff from addon installer and i have the addons on my license. It seems addon installer is not updated on my account because it is still showing me that i have 27 days of trial left. It is true for my personal account but not for my academic account.
update: a new installation fixed this problem.Hi, i was using personal account with trial and then i changed to my schools academic license on matlab but i still can’t download stuff from addon installer and i have the addons on my license. It seems addon installer is not updated on my account because it is still showing me that i have 27 days of trial left. It is true for my personal account but not for my academic account.
update: a new installation fixed this problem. Hi, i was using personal account with trial and then i changed to my schools academic license on matlab but i still can’t download stuff from addon installer and i have the addons on my license. It seems addon installer is not updated on my account because it is still showing me that i have 27 days of trial left. It is true for my personal account but not for my academic account.
update: a new installation fixed this problem. addons, account, license MATLAB Answers — New Questions
How to get values of pre-filled holes in dotx template
Hi,
I would like to import a template.dotx that contains holes, some being already pre-filled beforehand.
For instance: Imagine that a holeID "ahole1" that contains in the dotx a predefined value x, written when creating the dotx.
In the script, I would like to read the value of "ahole1" prior deciding what to write in a second hole "ahole2".
Pratical example:
dotx is created with "ahole1" value = 10 and "ahole2" is empty.
dotx is imported into matlab
If the value of "ahole1"> 12, a second hole "ahole2" will have appended into it "5"
I am using matlab 2024b and the report generator to import the dotx, but i cannot find the means to get the content of a Hole unless from the script level i append a value to it.Hi,
I would like to import a template.dotx that contains holes, some being already pre-filled beforehand.
For instance: Imagine that a holeID "ahole1" that contains in the dotx a predefined value x, written when creating the dotx.
In the script, I would like to read the value of "ahole1" prior deciding what to write in a second hole "ahole2".
Pratical example:
dotx is created with "ahole1" value = 10 and "ahole2" is empty.
dotx is imported into matlab
If the value of "ahole1"> 12, a second hole "ahole2" will have appended into it "5"
I am using matlab 2024b and the report generator to import the dotx, but i cannot find the means to get the content of a Hole unless from the script level i append a value to it. Hi,
I would like to import a template.dotx that contains holes, some being already pre-filled beforehand.
For instance: Imagine that a holeID "ahole1" that contains in the dotx a predefined value x, written when creating the dotx.
In the script, I would like to read the value of "ahole1" prior deciding what to write in a second hole "ahole2".
Pratical example:
dotx is created with "ahole1" value = 10 and "ahole2" is empty.
dotx is imported into matlab
If the value of "ahole1"> 12, a second hole "ahole2" will have appended into it "5"
I am using matlab 2024b and the report generator to import the dotx, but i cannot find the means to get the content of a Hole unless from the script level i append a value to it. dotx, pre-filled holes, hole value, dotx reporter generator MATLAB Answers — New Questions
I need help for drawing a constraint in Matlab in 2D
Dear All,
I’m trying to draw a set of constraints but I got a wrong line for the constraint 2×1<=3 !!!! I need a vertical line !! I approciate any help from you !!!
Many Thanks,
Nadia
clear;clc;close;
%max 5×1+7×2;
%3×1+8×2<=12;
%x1+x2<=2;
%2×1<=3;
%x2<=4;
%x1,x2>=0;
%% plot the feasible region %Generate data
[x1,x2] = meshgrid(0:0.1:10);% i changed 0.1 to 0.01 to plot the fourth constraint
NB=5*x1+7*x2;
% Get True where condition applies, false where not.
cond1=3*x1+8*x2<=12; cond2=x1+x2<=2; cond3=2*x1<=3; cond4=x2<=2;
% Get boundaries of the condition
p1=(12-3*x1(1,:))/8;
p2=2-x1(1,:);
p3=3/2-x1(1,:);
p4=2-x2(1,:);
%Delete Areas whereCondition does not apply;
NB(~cond1)=NaN; NB(~cond2)=NaN; NB(~cond3)=NaN; NB(~cond4)=NaN;
%% Plot
[x2,h]=contourf(x1,x2,NB,0); % command contourf for filling the area between the contour levels
hold on
plot(x1(1,:),p1,’r’,’LineWidth’,2); text(x1(1,20),p1(20), ‘leftarrow Cond1’); %arbitrary location
plot(x1(1,:),p2,’k’,’LineWidth’,2); text(x1(1,15),p2(15), ‘leftarrow Cond2’); %arbitrary location
plot(x1(1,:),p3,’b’,’LineWidth’,2); text(x1(1,20),p3(20), ‘leftarrow Cond3’); %arbitrary location
plot(x1(1,:),p4,’b’,’LineWidth’,2); text(x1(1,20),p4(20), ‘leftarrow Cond3’); %arbitrary location
axis([0 5 0 5])
xlabel(‘x1’)
ylabel(‘x2’)Dear All,
I’m trying to draw a set of constraints but I got a wrong line for the constraint 2×1<=3 !!!! I need a vertical line !! I approciate any help from you !!!
Many Thanks,
Nadia
clear;clc;close;
%max 5×1+7×2;
%3×1+8×2<=12;
%x1+x2<=2;
%2×1<=3;
%x2<=4;
%x1,x2>=0;
%% plot the feasible region %Generate data
[x1,x2] = meshgrid(0:0.1:10);% i changed 0.1 to 0.01 to plot the fourth constraint
NB=5*x1+7*x2;
% Get True where condition applies, false where not.
cond1=3*x1+8*x2<=12; cond2=x1+x2<=2; cond3=2*x1<=3; cond4=x2<=2;
% Get boundaries of the condition
p1=(12-3*x1(1,:))/8;
p2=2-x1(1,:);
p3=3/2-x1(1,:);
p4=2-x2(1,:);
%Delete Areas whereCondition does not apply;
NB(~cond1)=NaN; NB(~cond2)=NaN; NB(~cond3)=NaN; NB(~cond4)=NaN;
%% Plot
[x2,h]=contourf(x1,x2,NB,0); % command contourf for filling the area between the contour levels
hold on
plot(x1(1,:),p1,’r’,’LineWidth’,2); text(x1(1,20),p1(20), ‘leftarrow Cond1’); %arbitrary location
plot(x1(1,:),p2,’k’,’LineWidth’,2); text(x1(1,15),p2(15), ‘leftarrow Cond2’); %arbitrary location
plot(x1(1,:),p3,’b’,’LineWidth’,2); text(x1(1,20),p3(20), ‘leftarrow Cond3’); %arbitrary location
plot(x1(1,:),p4,’b’,’LineWidth’,2); text(x1(1,20),p4(20), ‘leftarrow Cond3’); %arbitrary location
axis([0 5 0 5])
xlabel(‘x1’)
ylabel(‘x2’) Dear All,
I’m trying to draw a set of constraints but I got a wrong line for the constraint 2×1<=3 !!!! I need a vertical line !! I approciate any help from you !!!
Many Thanks,
Nadia
clear;clc;close;
%max 5×1+7×2;
%3×1+8×2<=12;
%x1+x2<=2;
%2×1<=3;
%x2<=4;
%x1,x2>=0;
%% plot the feasible region %Generate data
[x1,x2] = meshgrid(0:0.1:10);% i changed 0.1 to 0.01 to plot the fourth constraint
NB=5*x1+7*x2;
% Get True where condition applies, false where not.
cond1=3*x1+8*x2<=12; cond2=x1+x2<=2; cond3=2*x1<=3; cond4=x2<=2;
% Get boundaries of the condition
p1=(12-3*x1(1,:))/8;
p2=2-x1(1,:);
p3=3/2-x1(1,:);
p4=2-x2(1,:);
%Delete Areas whereCondition does not apply;
NB(~cond1)=NaN; NB(~cond2)=NaN; NB(~cond3)=NaN; NB(~cond4)=NaN;
%% Plot
[x2,h]=contourf(x1,x2,NB,0); % command contourf for filling the area between the contour levels
hold on
plot(x1(1,:),p1,’r’,’LineWidth’,2); text(x1(1,20),p1(20), ‘leftarrow Cond1’); %arbitrary location
plot(x1(1,:),p2,’k’,’LineWidth’,2); text(x1(1,15),p2(15), ‘leftarrow Cond2’); %arbitrary location
plot(x1(1,:),p3,’b’,’LineWidth’,2); text(x1(1,20),p3(20), ‘leftarrow Cond3’); %arbitrary location
plot(x1(1,:),p4,’b’,’LineWidth’,2); text(x1(1,20),p4(20), ‘leftarrow Cond3’); %arbitrary location
axis([0 5 0 5])
xlabel(‘x1’)
ylabel(‘x2’) drawing a constraint, vertical line, matlab MATLAB Answers — New Questions
How can I calculate the probability of false detection?
Hello everyone!
I need to justify for my dissertation the problems of false detection of a signal by a normal distribution (Gaussian) and build a graph where I should get a decreasing exponent in the interval for P from 10^-8 to 10^-1, and for alpha squared (alpha^2) from 10 to 100. The sigma dispersion = from 10 to 100. The threshold value of the signal n2 = 1.5, from which the normal value is integrated to infinity to calculate the probability of P.
I wrote the following code:
% Given parameters
sigma2_values = linspace (0.1, 0.01, 100); % dispersion values from 0.01 to 1000
n2 = 1.5; % threshold value
P_loznoe = zeros(length(sigma2_values), 1); % Initialize array for P_false
% Calculate P_false for each value of sigma^2 for fixed n2
for j = 1: length(sigma2_values)
sigma2 = sigma2_values(j); % use current value of sigma^2
alpha2 = 1/sigma2; % Calculate alpha^2
% Calculate integral of P(x) from n2 to infinity
integrand = @(x) (1 / (sqrt(2 * pi * sigma2))) .* exp(-((x.^2) / (2 * sigma2)));
P_loznoe(j) = integral(integrand, n2, Inf); % Calculate the integral
end
% Calculate alpha^2 for each sigma^2
alpha2_values = 1 ./sigma2_values; % alpha^2 = 1/sigma^2
% Plot P_false vs. alpha^2
figure;
semilogy(alpha2_values, P_loznoe, ‘r’, ‘LineWidth’, 2); % Logarithmic scale on the Y axis
title(‘False discovery rate vs. alpha^2’);
xlabel(‘alpha^2’);
ylabel(‘P_{false}’);
xlim([10 100]); % Set limits on the X axis
ylim([10^(-8) 10^(-1)]); % Set limits on the Y axis to expand the grid
grid on; % Grid on
But for some reason my graph is not in the specified interval and not in the form of a decreasing exponent, but in the form of a linear decrease.
How can this be fixed?
Thanks in advance!Hello everyone!
I need to justify for my dissertation the problems of false detection of a signal by a normal distribution (Gaussian) and build a graph where I should get a decreasing exponent in the interval for P from 10^-8 to 10^-1, and for alpha squared (alpha^2) from 10 to 100. The sigma dispersion = from 10 to 100. The threshold value of the signal n2 = 1.5, from which the normal value is integrated to infinity to calculate the probability of P.
I wrote the following code:
% Given parameters
sigma2_values = linspace (0.1, 0.01, 100); % dispersion values from 0.01 to 1000
n2 = 1.5; % threshold value
P_loznoe = zeros(length(sigma2_values), 1); % Initialize array for P_false
% Calculate P_false for each value of sigma^2 for fixed n2
for j = 1: length(sigma2_values)
sigma2 = sigma2_values(j); % use current value of sigma^2
alpha2 = 1/sigma2; % Calculate alpha^2
% Calculate integral of P(x) from n2 to infinity
integrand = @(x) (1 / (sqrt(2 * pi * sigma2))) .* exp(-((x.^2) / (2 * sigma2)));
P_loznoe(j) = integral(integrand, n2, Inf); % Calculate the integral
end
% Calculate alpha^2 for each sigma^2
alpha2_values = 1 ./sigma2_values; % alpha^2 = 1/sigma^2
% Plot P_false vs. alpha^2
figure;
semilogy(alpha2_values, P_loznoe, ‘r’, ‘LineWidth’, 2); % Logarithmic scale on the Y axis
title(‘False discovery rate vs. alpha^2’);
xlabel(‘alpha^2’);
ylabel(‘P_{false}’);
xlim([10 100]); % Set limits on the X axis
ylim([10^(-8) 10^(-1)]); % Set limits on the Y axis to expand the grid
grid on; % Grid on
But for some reason my graph is not in the specified interval and not in the form of a decreasing exponent, but in the form of a linear decrease.
How can this be fixed?
Thanks in advance! Hello everyone!
I need to justify for my dissertation the problems of false detection of a signal by a normal distribution (Gaussian) and build a graph where I should get a decreasing exponent in the interval for P from 10^-8 to 10^-1, and for alpha squared (alpha^2) from 10 to 100. The sigma dispersion = from 10 to 100. The threshold value of the signal n2 = 1.5, from which the normal value is integrated to infinity to calculate the probability of P.
I wrote the following code:
% Given parameters
sigma2_values = linspace (0.1, 0.01, 100); % dispersion values from 0.01 to 1000
n2 = 1.5; % threshold value
P_loznoe = zeros(length(sigma2_values), 1); % Initialize array for P_false
% Calculate P_false for each value of sigma^2 for fixed n2
for j = 1: length(sigma2_values)
sigma2 = sigma2_values(j); % use current value of sigma^2
alpha2 = 1/sigma2; % Calculate alpha^2
% Calculate integral of P(x) from n2 to infinity
integrand = @(x) (1 / (sqrt(2 * pi * sigma2))) .* exp(-((x.^2) / (2 * sigma2)));
P_loznoe(j) = integral(integrand, n2, Inf); % Calculate the integral
end
% Calculate alpha^2 for each sigma^2
alpha2_values = 1 ./sigma2_values; % alpha^2 = 1/sigma^2
% Plot P_false vs. alpha^2
figure;
semilogy(alpha2_values, P_loznoe, ‘r’, ‘LineWidth’, 2); % Logarithmic scale on the Y axis
title(‘False discovery rate vs. alpha^2’);
xlabel(‘alpha^2’);
ylabel(‘P_{false}’);
xlim([10 100]); % Set limits on the X axis
ylim([10^(-8) 10^(-1)]); % Set limits on the Y axis to expand the grid
grid on; % Grid on
But for some reason my graph is not in the specified interval and not in the form of a decreasing exponent, but in the form of a linear decrease.
How can this be fixed?
Thanks in advance! gauss MATLAB Answers — New Questions
liver tumor image segmentation
hi, I have a CT image 2D and the mask for it. I need to do a MATLAB code for U-NET that I can train for this images and also test images. Can you help me with some ideas? Thank you.hi, I have a CT image 2D and the mask for it. I need to do a MATLAB code for U-NET that I can train for this images and also test images. Can you help me with some ideas? Thank you. hi, I have a CT image 2D and the mask for it. I need to do a MATLAB code for U-NET that I can train for this images and also test images. Can you help me with some ideas? Thank you. image segmentation, deep learning MATLAB Answers — New Questions
unrecognized table variable name minLS in Bayesian optimization of TreeBagger
Hello,
I tried to do the hyperparameter tuning using bayesian optimization for the randomforest model I made using Treebagger. This is the code I used. I didnot use ensemble bagged trees in regression learner directly because eachtime i check the optimization the minimum mse output is like 498 learners and 1 minimum leaf size for 9 number of predictors.
264 inputTable=readtable(‘dataall_trainingregression.csv’);
265 predictorNames = {‘temp_diff’, ‘temp_median’, ‘NDVI’, ‘Clay’, ‘elevation’, ‘slope’, ‘TWI’, ‘sand’, ‘DOY’};
266 predictors = inputTable(:, predictorNames);
267 response = inputTable.daily_meanSM;
268 n=length(inputTable.daily_meanSM);
269 cvp = cvpartition(n,’KFold’,5);
271 maxMinLS = 20;
272 minLS = optimizableVariable(‘minLS’,[1,maxMinLS],’Type’,’integer’);
273 numPTS = optimizableVariable(‘numPTS’,[1,size(predictors,2)],’Type’,’integer’);
274 hyperparametersRF = [minLS; numPTS];
275 fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
277 results = bayesopt(fun,hyperparametersRF,…
‘AcquisitionFunctionName’,’expected-improvement-plus’,’Verbose’,0);
280 function yfit = myfunction(params,predictors,response,test)
281 Mdl1 = TreeBagger(30,predictors,response,…
282 ‘Method’,"regression",’Surrogate’,"on",…
283 ‘PredictorSelection’,"curvature",…
284 ‘OOBPredictorImportance’,"on",’MinLeafSize’,params.minLS,…
285 ‘NumPredictorsToSample’,params.numPTS);
286 yfit = predict(Mdl1,test);
288 end
for this code i receive an error message of :
Error using crossval>evalFun
The function ‘myfunction’ generated the following error:
Unrecognized table variable name ‘minLS’.
Error in crossval>getLossVal (line 529)
funResult = evalFun(funorStr,arg(1:end-1));
Error in crossval (line 428)
[funResult,outarg] = getLossVal(i, nData, cvp, data, predfun);
Error in model_hyperparameter_tuning>@(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp) (line 275)
fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
Error in BayesianOptimization/callObjNormally (line 13)
Objective = this.ObjectiveFcn(conditionalizeX(this, X));
Error in BayesianOptimization/callObjFcn (line 25)
= callObjNormally(this, X);
Error in BayesianOptimization/runSerial (line 24)
ObjectiveFcnObjectiveEvaluationTime, ObjectiveNargout] = callObjFcn(this, this.XNext);
Error in BayesianOptimization/run (line 9)
this = runSerial(this);
Error in BayesianOptimization (line 184)
this = run(this);
Error in bayesopt (line 323)
Results = BayesianOptimization(Options);
Error in model_hyperparameter_tuning (line 277)
results = bayesopt(fun,hyperparametersRF,…
can anyone please help me to solve this problem. ThanksHello,
I tried to do the hyperparameter tuning using bayesian optimization for the randomforest model I made using Treebagger. This is the code I used. I didnot use ensemble bagged trees in regression learner directly because eachtime i check the optimization the minimum mse output is like 498 learners and 1 minimum leaf size for 9 number of predictors.
264 inputTable=readtable(‘dataall_trainingregression.csv’);
265 predictorNames = {‘temp_diff’, ‘temp_median’, ‘NDVI’, ‘Clay’, ‘elevation’, ‘slope’, ‘TWI’, ‘sand’, ‘DOY’};
266 predictors = inputTable(:, predictorNames);
267 response = inputTable.daily_meanSM;
268 n=length(inputTable.daily_meanSM);
269 cvp = cvpartition(n,’KFold’,5);
271 maxMinLS = 20;
272 minLS = optimizableVariable(‘minLS’,[1,maxMinLS],’Type’,’integer’);
273 numPTS = optimizableVariable(‘numPTS’,[1,size(predictors,2)],’Type’,’integer’);
274 hyperparametersRF = [minLS; numPTS];
275 fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
277 results = bayesopt(fun,hyperparametersRF,…
‘AcquisitionFunctionName’,’expected-improvement-plus’,’Verbose’,0);
280 function yfit = myfunction(params,predictors,response,test)
281 Mdl1 = TreeBagger(30,predictors,response,…
282 ‘Method’,"regression",’Surrogate’,"on",…
283 ‘PredictorSelection’,"curvature",…
284 ‘OOBPredictorImportance’,"on",’MinLeafSize’,params.minLS,…
285 ‘NumPredictorsToSample’,params.numPTS);
286 yfit = predict(Mdl1,test);
288 end
for this code i receive an error message of :
Error using crossval>evalFun
The function ‘myfunction’ generated the following error:
Unrecognized table variable name ‘minLS’.
Error in crossval>getLossVal (line 529)
funResult = evalFun(funorStr,arg(1:end-1));
Error in crossval (line 428)
[funResult,outarg] = getLossVal(i, nData, cvp, data, predfun);
Error in model_hyperparameter_tuning>@(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp) (line 275)
fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
Error in BayesianOptimization/callObjNormally (line 13)
Objective = this.ObjectiveFcn(conditionalizeX(this, X));
Error in BayesianOptimization/callObjFcn (line 25)
= callObjNormally(this, X);
Error in BayesianOptimization/runSerial (line 24)
ObjectiveFcnObjectiveEvaluationTime, ObjectiveNargout] = callObjFcn(this, this.XNext);
Error in BayesianOptimization/run (line 9)
this = runSerial(this);
Error in BayesianOptimization (line 184)
this = run(this);
Error in bayesopt (line 323)
Results = BayesianOptimization(Options);
Error in model_hyperparameter_tuning (line 277)
results = bayesopt(fun,hyperparametersRF,…
can anyone please help me to solve this problem. Thanks Hello,
I tried to do the hyperparameter tuning using bayesian optimization for the randomforest model I made using Treebagger. This is the code I used. I didnot use ensemble bagged trees in regression learner directly because eachtime i check the optimization the minimum mse output is like 498 learners and 1 minimum leaf size for 9 number of predictors.
264 inputTable=readtable(‘dataall_trainingregression.csv’);
265 predictorNames = {‘temp_diff’, ‘temp_median’, ‘NDVI’, ‘Clay’, ‘elevation’, ‘slope’, ‘TWI’, ‘sand’, ‘DOY’};
266 predictors = inputTable(:, predictorNames);
267 response = inputTable.daily_meanSM;
268 n=length(inputTable.daily_meanSM);
269 cvp = cvpartition(n,’KFold’,5);
271 maxMinLS = 20;
272 minLS = optimizableVariable(‘minLS’,[1,maxMinLS],’Type’,’integer’);
273 numPTS = optimizableVariable(‘numPTS’,[1,size(predictors,2)],’Type’,’integer’);
274 hyperparametersRF = [minLS; numPTS];
275 fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
277 results = bayesopt(fun,hyperparametersRF,…
‘AcquisitionFunctionName’,’expected-improvement-plus’,’Verbose’,0);
280 function yfit = myfunction(params,predictors,response,test)
281 Mdl1 = TreeBagger(30,predictors,response,…
282 ‘Method’,"regression",’Surrogate’,"on",…
283 ‘PredictorSelection’,"curvature",…
284 ‘OOBPredictorImportance’,"on",’MinLeafSize’,params.minLS,…
285 ‘NumPredictorsToSample’,params.numPTS);
286 yfit = predict(Mdl1,test);
288 end
for this code i receive an error message of :
Error using crossval>evalFun
The function ‘myfunction’ generated the following error:
Unrecognized table variable name ‘minLS’.
Error in crossval>getLossVal (line 529)
funResult = evalFun(funorStr,arg(1:end-1));
Error in crossval (line 428)
[funResult,outarg] = getLossVal(i, nData, cvp, data, predfun);
Error in model_hyperparameter_tuning>@(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp) (line 275)
fun = @(params)crossval(‘mse’,predictors,response,’Predfun’,@myfunction,’Partition’,cvp);
Error in BayesianOptimization/callObjNormally (line 13)
Objective = this.ObjectiveFcn(conditionalizeX(this, X));
Error in BayesianOptimization/callObjFcn (line 25)
= callObjNormally(this, X);
Error in BayesianOptimization/runSerial (line 24)
ObjectiveFcnObjectiveEvaluationTime, ObjectiveNargout] = callObjFcn(this, this.XNext);
Error in BayesianOptimization/run (line 9)
this = runSerial(this);
Error in BayesianOptimization (line 184)
this = run(this);
Error in bayesopt (line 323)
Results = BayesianOptimization(Options);
Error in model_hyperparameter_tuning (line 277)
results = bayesopt(fun,hyperparametersRF,…
can anyone please help me to solve this problem. Thanks treebagger, bayesian optimization MATLAB Answers — New Questions
How to add newer CCSTUDIO version (12.8.0) in Matlab 2024a/b
Hello,
How do I add newer CCSTUDIO IDE version (v12.8.0) from TI in Matlab 2024a/b ?
Thanks for the guidance.
Regards,
JohnnyHello,
How do I add newer CCSTUDIO IDE version (v12.8.0) from TI in Matlab 2024a/b ?
Thanks for the guidance.
Regards,
Johnny Hello,
How do I add newer CCSTUDIO IDE version (v12.8.0) from TI in Matlab 2024a/b ?
Thanks for the guidance.
Regards,
Johnny c2000 microcontroller MATLAB Answers — New Questions
Identify an unrecognized function or variable
clear all; close all;
syms T U t w
a=0.3; M=1; h0=1; h1=1; k0=1; k1=1; p=0.5; d=0.5; Z=10;
%t=0:1:10; %w=0.75;
H=@(s) (p*Z-d-exp(-s))*k1;
K=@(r,g) p*Z*k1-(d+exp(-r))*k1-2*exp(a*r).*g;
for n=1:10
y=int(H(U),0,10);
yy= h0 + ((1-a)./M)*H(t).*h1 + (a./M)*y;
h1=yy;
end
for n=1:10
z=int(K(U,T),0,10);
zz= k0 + ((1-w)./M).*K(t,yy).*k1 + (w./M)*z;
k1=zz;
end
zzfcn = matlabFunction(zz)
t=0:0.1:10;
w = 0.1:0.1:0.75;
[T,W] = ndgrid(t,w);
figure
surf(T, W, zzfcn(T,W))
xlabel(‘t’)
ylabel(‘omega’)
zlabel(‘k(t)’)
set(gca, ‘ZScale’,’log’)
colormap(turbo)
colorbarclear all; close all;
syms T U t w
a=0.3; M=1; h0=1; h1=1; k0=1; k1=1; p=0.5; d=0.5; Z=10;
%t=0:1:10; %w=0.75;
H=@(s) (p*Z-d-exp(-s))*k1;
K=@(r,g) p*Z*k1-(d+exp(-r))*k1-2*exp(a*r).*g;
for n=1:10
y=int(H(U),0,10);
yy= h0 + ((1-a)./M)*H(t).*h1 + (a./M)*y;
h1=yy;
end
for n=1:10
z=int(K(U,T),0,10);
zz= k0 + ((1-w)./M).*K(t,yy).*k1 + (w./M)*z;
k1=zz;
end
zzfcn = matlabFunction(zz)
t=0:0.1:10;
w = 0.1:0.1:0.75;
[T,W] = ndgrid(t,w);
figure
surf(T, W, zzfcn(T,W))
xlabel(‘t’)
ylabel(‘omega’)
zlabel(‘k(t)’)
set(gca, ‘ZScale’,’log’)
colormap(turbo)
colorbar clear all; close all;
syms T U t w
a=0.3; M=1; h0=1; h1=1; k0=1; k1=1; p=0.5; d=0.5; Z=10;
%t=0:1:10; %w=0.75;
H=@(s) (p*Z-d-exp(-s))*k1;
K=@(r,g) p*Z*k1-(d+exp(-r))*k1-2*exp(a*r).*g;
for n=1:10
y=int(H(U),0,10);
yy= h0 + ((1-a)./M)*H(t).*h1 + (a./M)*y;
h1=yy;
end
for n=1:10
z=int(K(U,T),0,10);
zz= k0 + ((1-w)./M).*K(t,yy).*k1 + (w./M)*z;
k1=zz;
end
zzfcn = matlabFunction(zz)
t=0:0.1:10;
w = 0.1:0.1:0.75;
[T,W] = ndgrid(t,w);
figure
surf(T, W, zzfcn(T,W))
xlabel(‘t’)
ylabel(‘omega’)
zlabel(‘k(t)’)
set(gca, ‘ZScale’,’log’)
colormap(turbo)
colorbar function MATLAB Answers — New Questions
Request for MATLAB Code of Elephant Search Algorithm (ESA)
Hi everyone,
I’m looking for a MATLAB implementation of the Elephant Search Algorithm (ESA) for optimization problems. I couldn’t find an existing code online, and I’d appreciate it if someone could share a working implementation or guide me on how to code it based on its original paper.
If anyone has experience implementing ESA in MATLAB or can point me to a useful resource, I’d be very grateful.
Thanks in advance!Hi everyone,
I’m looking for a MATLAB implementation of the Elephant Search Algorithm (ESA) for optimization problems. I couldn’t find an existing code online, and I’d appreciate it if someone could share a working implementation or guide me on how to code it based on its original paper.
If anyone has experience implementing ESA in MATLAB or can point me to a useful resource, I’d be very grateful.
Thanks in advance! Hi everyone,
I’m looking for a MATLAB implementation of the Elephant Search Algorithm (ESA) for optimization problems. I couldn’t find an existing code online, and I’d appreciate it if someone could share a working implementation or guide me on how to code it based on its original paper.
If anyone has experience implementing ESA in MATLAB or can point me to a useful resource, I’d be very grateful.
Thanks in advance! esa, elephant search algorithm, code MATLAB Answers — New Questions
how to fuse image
Dear all,
this is my code to view CT image by slice
P = zeros(256, 256, 72);
for K = 1 : 72
petname = sprintf(‘I4%03d.dcm’, K);
P(:,:,K) = dicomread(petname);
end
imshow3D(P)
then, this is my code for view SPECT image by slice,
Noted: all my 512 slice SPECT image stored in one file.
[spect map]=dicomread(‘128×128’);
info = dicominfo(‘128×128’);
gp=info.SliceThickness;
spect=(squeeze(spect));%smooth3
aa=size(spect);aa=aa(3);
imshow3D(spect);
Anybody can help me to fuse both SPECT and CT images?Dear all,
this is my code to view CT image by slice
P = zeros(256, 256, 72);
for K = 1 : 72
petname = sprintf(‘I4%03d.dcm’, K);
P(:,:,K) = dicomread(petname);
end
imshow3D(P)
then, this is my code for view SPECT image by slice,
Noted: all my 512 slice SPECT image stored in one file.
[spect map]=dicomread(‘128×128’);
info = dicominfo(‘128×128’);
gp=info.SliceThickness;
spect=(squeeze(spect));%smooth3
aa=size(spect);aa=aa(3);
imshow3D(spect);
Anybody can help me to fuse both SPECT and CT images? Dear all,
this is my code to view CT image by slice
P = zeros(256, 256, 72);
for K = 1 : 72
petname = sprintf(‘I4%03d.dcm’, K);
P(:,:,K) = dicomread(petname);
end
imshow3D(P)
then, this is my code for view SPECT image by slice,
Noted: all my 512 slice SPECT image stored in one file.
[spect map]=dicomread(‘128×128’);
info = dicominfo(‘128×128’);
gp=info.SliceThickness;
spect=(squeeze(spect));%smooth3
aa=size(spect);aa=aa(3);
imshow3D(spect);
Anybody can help me to fuse both SPECT and CT images? image processing, image analysis, image segmentation MATLAB Answers — New Questions
Is the pny GeForce rtx 3090 supported by the deep learning toolbox?
Is the pny GeForce rtx 3090 supported by the deep learning toolbox?Is the pny GeForce rtx 3090 supported by the deep learning toolbox? Is the pny GeForce rtx 3090 supported by the deep learning toolbox? pny geforce MATLAB Answers — New Questions
make “plot” visualization more visible
I have 5 plots in a figure. One plot has a lot more points (gray color in the figure with about 4000 points) and hence while other a few hundred. I put the color for the larger set curve to gray in order to make the other 4 plots (shown in green, orange, and purple) more visible (following script). I also made the ‘Linewidth’ for gray curve to 0.5. Are the any suggestions to make the other 4 curves (shown as orange, green, red, and purple) more visible?
newcolors = [0.83 0.14 0.14
1.00 0.54 0.00
0.47 0.25 0.80
0.25 0.80 0.54
0.7 0.7 0.7];
colororder(newcolors)I have 5 plots in a figure. One plot has a lot more points (gray color in the figure with about 4000 points) and hence while other a few hundred. I put the color for the larger set curve to gray in order to make the other 4 plots (shown in green, orange, and purple) more visible (following script). I also made the ‘Linewidth’ for gray curve to 0.5. Are the any suggestions to make the other 4 curves (shown as orange, green, red, and purple) more visible?
newcolors = [0.83 0.14 0.14
1.00 0.54 0.00
0.47 0.25 0.80
0.25 0.80 0.54
0.7 0.7 0.7];
colororder(newcolors) I have 5 plots in a figure. One plot has a lot more points (gray color in the figure with about 4000 points) and hence while other a few hundred. I put the color for the larger set curve to gray in order to make the other 4 plots (shown in green, orange, and purple) more visible (following script). I also made the ‘Linewidth’ for gray curve to 0.5. Are the any suggestions to make the other 4 curves (shown as orange, green, red, and purple) more visible?
newcolors = [0.83 0.14 0.14
1.00 0.54 0.00
0.47 0.25 0.80
0.25 0.80 0.54
0.7 0.7 0.7];
colororder(newcolors) plot, visualization MATLAB Answers — New Questions
2022 or later version giving error when compiling model for nucleo board
using nucleo h743zi2 board working fine with matlaab version 2020 but when compling in later version gives error when using some analog pins on the boardusing nucleo h743zi2 board working fine with matlaab version 2020 but when compling in later version gives error when using some analog pins on the board using nucleo h743zi2 board working fine with matlaab version 2020 but when compling in later version gives error when using some analog pins on the board stm, nucleo MATLAB Answers — New Questions
why I cant use velodyneFileReader
hello here,
I am new to this velodyne toolbox, and I am try using velodyneFileReader to read my recorded PCAP file (around 9GB).
the code is as follows
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
but it gives me
vision.internal.VelodyneFileReader/open
Error reading packet from PCAP file bogus savefile header.
velodyneFileReader (line 269)
tmpReturnStruct = open(this.VelodyneFileReaderObj, this.FileName,…
rosbagtest (line 4)
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
I have tried this command with my other PCAP files (up to 1GB), they were all fine, so I am wondering if there is a size limit with this command or some other issues, thanks.hello here,
I am new to this velodyne toolbox, and I am try using velodyneFileReader to read my recorded PCAP file (around 9GB).
the code is as follows
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
but it gives me
vision.internal.VelodyneFileReader/open
Error reading packet from PCAP file bogus savefile header.
velodyneFileReader (line 269)
tmpReturnStruct = open(this.VelodyneFileReaderObj, this.FileName,…
rosbagtest (line 4)
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
I have tried this command with my other PCAP files (up to 1GB), they were all fine, so I am wondering if there is a size limit with this command or some other issues, thanks. hello here,
I am new to this velodyne toolbox, and I am try using velodyneFileReader to read my recorded PCAP file (around 9GB).
the code is as follows
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
but it gives me
vision.internal.VelodyneFileReader/open
Error reading packet from PCAP file bogus savefile header.
velodyneFileReader (line 269)
tmpReturnStruct = open(this.VelodyneFileReaderObj, this.FileName,…
rosbagtest (line 4)
veloReader = velodyneFileReader(‘velodyne.pcap’,’VLP16′)
I have tried this command with my other PCAP files (up to 1GB), they were all fine, so I am wondering if there is a size limit with this command or some other issues, thanks. velodyne, lidar MATLAB Answers — New Questions
