Category: News
Is MathWorks removing the concurrent license option from the Campus-Wide License offering?
MathWorks has announced their move away from MATLAB (Concurrent) to MATLAB (Individual) for shared teaching labs and computer classrooms. Does this mean that the MATLAB (Concurrent) license is being removed?MathWorks has announced their move away from MATLAB (Concurrent) to MATLAB (Individual) for shared teaching labs and computer classrooms. Does this mean that the MATLAB (Concurrent) license is being removed? MathWorks has announced their move away from MATLAB (Concurrent) to MATLAB (Individual) for shared teaching labs and computer classrooms. Does this mean that the MATLAB (Concurrent) license is being removed? MATLAB Answers — New Questions
Saving figure as .svg alters appearance
Hi,
I’m making figures in MATLAB and want to export them in .svg to work with them in other programs. So far, that has been no problem, but I’m stumbling into something odd now. I’m trying to export this figure:
As you can see, this works fine in .png. This is also what the figure looks like in MATLAB. However, when I export as .svg, the blue patch that I plotted around the line to indicate the SEM continues until 10 seconds instead of 5:
I think this might be because I’m first plotting the patch, and then alter the x axis. However, this is not visible in the matlab figure, and the red and green patches show no problem for this.
My code is as follows:
xaxeslimits = [-5 5];
f = figure(‘InvertHardcopy’,’off’,’Color’,[1 1 1]);
t = tiledlayout(size(ROIs,2)/2, 2);
x = linspace(-5, 10, 226);
tileind = 2;
for roi = 1:size(ROIs, 2)
nexttile(tileind)
title(ROInames{roi})
eval([‘yhbo = means.hbo.’ ROIs{roi} ‘;’])
eval([‘SEMhbo = sems.hbo.’ ROIs{roi} ‘;’])
eval([‘yhbr = means.hbr.’ ROIs{roi} ‘;’])
eval([‘SEMhbr = sems.hbr.’ ROIs{roi} ‘;’])
eval([‘y = means.fluo.’ ROIs{roi} ‘;’])
eval([‘SEM = sems.fluo.’ ROIs{roi} ‘;’])
y = y-1; % to get centered around 0
% HbO
yyaxis right
plot(x, yhbo, ‘Color’, ‘red’, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbo + SEMhbo fliplr(yhbo – SEMhbo)], ‘r’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
hold on
% HbR
plot(x, yhbr, ‘Color’, ‘blue’, ‘LineStyle’, ‘-‘, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbr + SEMhbr fliplr(yhbr – SEMhbr)], ‘b’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
ylim([-1.5 1.5]);
h_label = ylabel(‘Delta muM’, ‘interpreter’, ‘Tex’, ‘Rotation’, 270);
ax = gca;
ax.YColor = ‘red’;
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlim(xaxeslimits);
% Fluo
yyaxis left
plot(x,y, ‘Color’, [0.4660 0.6740 0.1880], ‘LineWidth’, 2);
patch([x, fliplr(x)], [y + SEM fliplr(y – SEM)], ‘g’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
f_label = ylabel(‘Delta F/F’);
ylim([-0.05 0.05]); % centered at 0
ax = gca;
ax.YColor = [0.4660 0.6740 0.1880];
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlabel(‘Time (sec)’)
xlim(xaxeslimits);
if tileind == size(ROIs, 2)
tileind = 1;
else
tileind = tileind+2;
end
end
leg1 = legend({‘GCaMP’, ‘SEM’, ‘HbO’,’SEM’, ‘HbR’,’SEM’}, ‘Orientation’, ‘Horizontal’);
leg1.Location = ‘southoutside’;
% f.Position = [10 10 1800 1000];
f.Position = [10 10 900 1000];
% save
pause(0.5)
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.tiff’], ‘tiff’);
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.eps’], ‘epsc’);
saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.svg’], ‘svg’);
close(f)
Does anybody know how to fix this? I’d like to be able to easily alter the x-axis and have it still work.
Best,
MarleenHi,
I’m making figures in MATLAB and want to export them in .svg to work with them in other programs. So far, that has been no problem, but I’m stumbling into something odd now. I’m trying to export this figure:
As you can see, this works fine in .png. This is also what the figure looks like in MATLAB. However, when I export as .svg, the blue patch that I plotted around the line to indicate the SEM continues until 10 seconds instead of 5:
I think this might be because I’m first plotting the patch, and then alter the x axis. However, this is not visible in the matlab figure, and the red and green patches show no problem for this.
My code is as follows:
xaxeslimits = [-5 5];
f = figure(‘InvertHardcopy’,’off’,’Color’,[1 1 1]);
t = tiledlayout(size(ROIs,2)/2, 2);
x = linspace(-5, 10, 226);
tileind = 2;
for roi = 1:size(ROIs, 2)
nexttile(tileind)
title(ROInames{roi})
eval([‘yhbo = means.hbo.’ ROIs{roi} ‘;’])
eval([‘SEMhbo = sems.hbo.’ ROIs{roi} ‘;’])
eval([‘yhbr = means.hbr.’ ROIs{roi} ‘;’])
eval([‘SEMhbr = sems.hbr.’ ROIs{roi} ‘;’])
eval([‘y = means.fluo.’ ROIs{roi} ‘;’])
eval([‘SEM = sems.fluo.’ ROIs{roi} ‘;’])
y = y-1; % to get centered around 0
% HbO
yyaxis right
plot(x, yhbo, ‘Color’, ‘red’, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbo + SEMhbo fliplr(yhbo – SEMhbo)], ‘r’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
hold on
% HbR
plot(x, yhbr, ‘Color’, ‘blue’, ‘LineStyle’, ‘-‘, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbr + SEMhbr fliplr(yhbr – SEMhbr)], ‘b’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
ylim([-1.5 1.5]);
h_label = ylabel(‘Delta muM’, ‘interpreter’, ‘Tex’, ‘Rotation’, 270);
ax = gca;
ax.YColor = ‘red’;
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlim(xaxeslimits);
% Fluo
yyaxis left
plot(x,y, ‘Color’, [0.4660 0.6740 0.1880], ‘LineWidth’, 2);
patch([x, fliplr(x)], [y + SEM fliplr(y – SEM)], ‘g’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
f_label = ylabel(‘Delta F/F’);
ylim([-0.05 0.05]); % centered at 0
ax = gca;
ax.YColor = [0.4660 0.6740 0.1880];
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlabel(‘Time (sec)’)
xlim(xaxeslimits);
if tileind == size(ROIs, 2)
tileind = 1;
else
tileind = tileind+2;
end
end
leg1 = legend({‘GCaMP’, ‘SEM’, ‘HbO’,’SEM’, ‘HbR’,’SEM’}, ‘Orientation’, ‘Horizontal’);
leg1.Location = ‘southoutside’;
% f.Position = [10 10 1800 1000];
f.Position = [10 10 900 1000];
% save
pause(0.5)
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.tiff’], ‘tiff’);
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.eps’], ‘epsc’);
saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.svg’], ‘svg’);
close(f)
Does anybody know how to fix this? I’d like to be able to easily alter the x-axis and have it still work.
Best,
Marleen Hi,
I’m making figures in MATLAB and want to export them in .svg to work with them in other programs. So far, that has been no problem, but I’m stumbling into something odd now. I’m trying to export this figure:
As you can see, this works fine in .png. This is also what the figure looks like in MATLAB. However, when I export as .svg, the blue patch that I plotted around the line to indicate the SEM continues until 10 seconds instead of 5:
I think this might be because I’m first plotting the patch, and then alter the x axis. However, this is not visible in the matlab figure, and the red and green patches show no problem for this.
My code is as follows:
xaxeslimits = [-5 5];
f = figure(‘InvertHardcopy’,’off’,’Color’,[1 1 1]);
t = tiledlayout(size(ROIs,2)/2, 2);
x = linspace(-5, 10, 226);
tileind = 2;
for roi = 1:size(ROIs, 2)
nexttile(tileind)
title(ROInames{roi})
eval([‘yhbo = means.hbo.’ ROIs{roi} ‘;’])
eval([‘SEMhbo = sems.hbo.’ ROIs{roi} ‘;’])
eval([‘yhbr = means.hbr.’ ROIs{roi} ‘;’])
eval([‘SEMhbr = sems.hbr.’ ROIs{roi} ‘;’])
eval([‘y = means.fluo.’ ROIs{roi} ‘;’])
eval([‘SEM = sems.fluo.’ ROIs{roi} ‘;’])
y = y-1; % to get centered around 0
% HbO
yyaxis right
plot(x, yhbo, ‘Color’, ‘red’, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbo + SEMhbo fliplr(yhbo – SEMhbo)], ‘r’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
hold on
% HbR
plot(x, yhbr, ‘Color’, ‘blue’, ‘LineStyle’, ‘-‘, ‘LineWidth’, 2)
patch([x, fliplr(x)], [yhbr + SEMhbr fliplr(yhbr – SEMhbr)], ‘b’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
ylim([-1.5 1.5]);
h_label = ylabel(‘Delta muM’, ‘interpreter’, ‘Tex’, ‘Rotation’, 270);
ax = gca;
ax.YColor = ‘red’;
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlim(xaxeslimits);
% Fluo
yyaxis left
plot(x,y, ‘Color’, [0.4660 0.6740 0.1880], ‘LineWidth’, 2);
patch([x, fliplr(x)], [y + SEM fliplr(y – SEM)], ‘g’ ,’EdgeColor’,’none’, ‘FaceAlpha’,0.25)
f_label = ylabel(‘Delta F/F’);
ylim([-0.05 0.05]); % centered at 0
ax = gca;
ax.YColor = [0.4660 0.6740 0.1880];
ax.XColor = ‘k’;
set(ax, ‘FontSize’, 15, ‘LineWidth’, 2)
xlabel(‘Time (sec)’)
xlim(xaxeslimits);
if tileind == size(ROIs, 2)
tileind = 1;
else
tileind = tileind+2;
end
end
leg1 = legend({‘GCaMP’, ‘SEM’, ‘HbO’,’SEM’, ‘HbR’,’SEM’}, ‘Orientation’, ‘Horizontal’);
leg1.Location = ‘southoutside’;
% f.Position = [10 10 1800 1000];
f.Position = [10 10 900 1000];
% save
pause(0.5)
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.tiff’], ‘tiff’);
% saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.eps’], ‘epsc’);
saveas(gcf, [SaveDir ‘/NVC/Sham_RS/’ Acq ‘_’ type ‘_’ ROIsavename ‘_AvCurves.svg’], ‘svg’);
close(f)
Does anybody know how to fix this? I’d like to be able to easily alter the x-axis and have it still work.
Best,
Marleen image export, svg, plotting, figure export MATLAB Answers — New Questions
Error using barrier Objective function is undefined at initial point. Fmincon cannot continue.
Hi, after running my code
R=readmatrix(filename1);
R=R.’;
w=readmatrix(filename2);
gamma = 2;
Aeq = ones(1,68);
beq = 1;
lb = zeros(68,1);
ub = ones(68,1);
x0=0.0147*ones(1,68);
u = @(x) 1/(1-gamma)*x.^(1-gamma);
obj = @(x)-sum(u(x*w*R));
x = fmincon(obj,x0,[],[],Aeq,beq,lb,ub);
I recived the following error
Error using barrier
Objective function is undefined at initial point. Fmincon cannot continue.
Error in fmincon (line 824)
[X,FVAL,EXITFLAG,OUTPUT,LAMBDA,GRAD,HESSIAN] =
barrier(funfcn,X,A,B,Aeq,Beq,l,u,confcn,options.HessFcn, …
I run the same code before but with a lees number of data and it works perfectly. Can you please help me what is wrong with my code ?
Thanks in advance
:::: UPDATE
after my discussion with Torsten : here
I reads my data carefully and found the problem with my dataHi, after running my code
R=readmatrix(filename1);
R=R.’;
w=readmatrix(filename2);
gamma = 2;
Aeq = ones(1,68);
beq = 1;
lb = zeros(68,1);
ub = ones(68,1);
x0=0.0147*ones(1,68);
u = @(x) 1/(1-gamma)*x.^(1-gamma);
obj = @(x)-sum(u(x*w*R));
x = fmincon(obj,x0,[],[],Aeq,beq,lb,ub);
I recived the following error
Error using barrier
Objective function is undefined at initial point. Fmincon cannot continue.
Error in fmincon (line 824)
[X,FVAL,EXITFLAG,OUTPUT,LAMBDA,GRAD,HESSIAN] =
barrier(funfcn,X,A,B,Aeq,Beq,l,u,confcn,options.HessFcn, …
I run the same code before but with a lees number of data and it works perfectly. Can you please help me what is wrong with my code ?
Thanks in advance
:::: UPDATE
after my discussion with Torsten : here
I reads my data carefully and found the problem with my data Hi, after running my code
R=readmatrix(filename1);
R=R.’;
w=readmatrix(filename2);
gamma = 2;
Aeq = ones(1,68);
beq = 1;
lb = zeros(68,1);
ub = ones(68,1);
x0=0.0147*ones(1,68);
u = @(x) 1/(1-gamma)*x.^(1-gamma);
obj = @(x)-sum(u(x*w*R));
x = fmincon(obj,x0,[],[],Aeq,beq,lb,ub);
I recived the following error
Error using barrier
Objective function is undefined at initial point. Fmincon cannot continue.
Error in fmincon (line 824)
[X,FVAL,EXITFLAG,OUTPUT,LAMBDA,GRAD,HESSIAN] =
barrier(funfcn,X,A,B,Aeq,Beq,l,u,confcn,options.HessFcn, …
I run the same code before but with a lees number of data and it works perfectly. Can you please help me what is wrong with my code ?
Thanks in advance
:::: UPDATE
after my discussion with Torsten : here
I reads my data carefully and found the problem with my data fmincon MATLAB Answers — New Questions
how extract two arrays in matlab of unequal length
I have datasets of unequal length, like data file 1 has 47 data points and data file 2 has 649 data points , now i want diffence of these two curves, but I am looking for options , how to extract them.
I am attaching image of the plots.
please guide.
Regards,
IqraI have datasets of unequal length, like data file 1 has 47 data points and data file 2 has 649 data points , now i want diffence of these two curves, but I am looking for options , how to extract them.
I am attaching image of the plots.
please guide.
Regards,
Iqra I have datasets of unequal length, like data file 1 has 47 data points and data file 2 has 649 data points , now i want diffence of these two curves, but I am looking for options , how to extract them.
I am attaching image of the plots.
please guide.
Regards,
Iqra arrays, different length, matlab MATLAB Answers — New Questions
how to remove noise from curves and take their derivates
Hello,
I have some curves which are not smooth, I have to take their derivative. therefore first requirement is remove the noise and take the derivative.
I am doing this work through curve fitting using rat35, poly9 etc. and then taking the derivative. but everytime i run the script, result changes slighty.
i am attaching the curve , their zoom version and then warnings which appeared in workspace, would you please guide me how i should handle this issue.
Regards,
KiranHello,
I have some curves which are not smooth, I have to take their derivative. therefore first requirement is remove the noise and take the derivative.
I am doing this work through curve fitting using rat35, poly9 etc. and then taking the derivative. but everytime i run the script, result changes slighty.
i am attaching the curve , their zoom version and then warnings which appeared in workspace, would you please guide me how i should handle this issue.
Regards,
Kiran Hello,
I have some curves which are not smooth, I have to take their derivative. therefore first requirement is remove the noise and take the derivative.
I am doing this work through curve fitting using rat35, poly9 etc. and then taking the derivative. but everytime i run the script, result changes slighty.
i am attaching the curve , their zoom version and then warnings which appeared in workspace, would you please guide me how i should handle this issue.
Regards,
Kiran curve fitting, noise, smooth curve, derivative, denoising, fitnlm, sgolayfilt MATLAB Answers — New Questions
Write a function called corners that takes a matrix as an input argument and returns four outputs: the elements at its four corners in this order: top_left, top_right, bottom_left and bottom_right. (Note that loops and if-statements are neither neces
This question is soft-locked: new answers that are equivalent to already posted answers may be deleted without prior notice.
Can’t find a solution to this problem im a noob, please help, example
>> [a, b, c, d] = corners([1 2; 3 4])
a =
1
b =
2
c =
3
d =
4This question is soft-locked: new answers that are equivalent to already posted answers may be deleted without prior notice.
Can’t find a solution to this problem im a noob, please help, example
>> [a, b, c, d] = corners([1 2; 3 4])
a =
1
b =
2
c =
3
d =
4 This question is soft-locked: new answers that are equivalent to already posted answers may be deleted without prior notice.
Can’t find a solution to this problem im a noob, please help, example
>> [a, b, c, d] = corners([1 2; 3 4])
a =
1
b =
2
c =
3
d =
4 functions, homework, soft-lock, corners of matrix MATLAB Answers — New Questions
Maximize my GUI window
How can i maximize my GUI window keeping the ratio of all my labels and buttons maximized with the windowHow can i maximize my GUI window keeping the ratio of all my labels and buttons maximized with the window How can i maximize my GUI window keeping the ratio of all my labels and buttons maximized with the window matlab gui, guide, app designer, appdesigner, resize, gui MATLAB Answers — New Questions
Enhanced Collaboration in Custom Environment
Does anyone know if the enhanced collaboration is available in a custom environment?
Does anyone know if the enhanced collaboration is available in a custom environment? Read More
Future of Project Accelerator
I recently deployed Project Accelerator and have been using it in production. I am concerned over the future of the platform. Does anyone have any insight on the future of this platform?
I recently deployed Project Accelerator and have been using it in production. I am concerned over the future of the platform. Does anyone have any insight on the future of this platform? Read More
Copilot for Microsoft 365 limitations with document size
Hey,
I’m trying to understand what the limitations with files size within Copilot for M365 are.
For example, when I ask to summarize a very large file, I’m not sure what is the size limit in terms of number of words or MB.
Another example, when I create a Word document or a PPT document from a Word file or a PDF file, I’m not sure what the size limit is for the referred document.
Any clue, any links, any data?
Hey,I’m trying to understand what the limitations with files size within Copilot for M365 are.For example, when I ask to summarize a very large file, I’m not sure what is the size limit in terms of number of words or MB.Another example, when I create a Word document or a PPT document from a Word file or a PDF file, I’m not sure what the size limit is for the referred document.Any clue, any links, any data? Read More
Calculate Year’s Past
Hello All – I’m looking to convert many rows within a table to a Year’s left equation instead of doing it all by hand. The result should be,
Year New – 2020
5 Years before Expiration
Years remaining – 1
Year New 2018
5 Years before Expiration
Years Remaining – (-1)
I have all my years of expiration in a separate box but trying to come up with a simple formula that calculates the years remaining but putting it simply as a 5 years left or -1 years left. Any advice would be appreciated, thank you
Hello All – I’m looking to convert many rows within a table to a Year’s left equation instead of doing it all by hand. The result should be, Year New – 2020 5 Years before Expiration Years remaining – 1 Year New 2018 5 Years before ExpirationYears Remaining – (-1) I have all my years of expiration in a separate box but trying to come up with a simple formula that calculates the years remaining but putting it simply as a 5 years left or -1 years left. Any advice would be appreciated, thank you Read More
Uusi Bit.get-suosituskoodi: qp29 (uusi rekisteröinti 2024)
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Kun sinua pyydetään antamaan viittauskoodi, kirjoita qp29.
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Lisätulot: Jaa koodisi ja ansaitse 50 % provisio.
Hyödynnä tämä tilaisuus ja varmista etusi nykyisellä B I T GE T -viitekoodilla qp29! Saat jopa 5005 USDT ja hyödynnä pysyviä alennuksia kaupankäyntikuluistasi.
Paras B I T GE T -viitekoodi vuodelle 2024 on “qp29”. Käytä tätä koodia saadaksesi 30% alennuksen kaupoista. Lisäksi uudet käyttäjät, jotka rekisteröityvät B I T GE T -palveluun käyttämällä tarjouskoodia “qp29”, voivat saada eksklusiivisen palkinnon, joka on jopa 5005 USDT.B I T GE T -viitekoodin qp29 edutB I T GE T -viitekoodi qp29 tarjoaa loistavan tavan säästää kaupankäyntikuluissa ja ansaita samalla houkuttelevia palkintoja. Syöttämällä tämän koodin saat pysyvän 30 % alennuksen kaupankäyntikuluistasi. Lisäksi, jos jaat henkilökohtaisen viittauskoodisi ystäviesi kanssa, voit saada 50 % bonuksen heidän kaupankäyntikuluistaan. Hyödynnä tämä tilaisuus kasvattaaksesi tulojasi ja tuomalla uusia käyttäjiä alustalle.Paras B I T GE T -viitekoodi vuodelle 2024Suositeltu B I T GE T -viitekoodi vuodelle 2024 on qp29. Kun rekisteröidyt tällä koodilla, voit saada jopa 5005 USDT bonuksena. Jaa tämä koodi ystävillesi ansaitaksesi 50 % provisiota, mikä auttaa sinua varmistamaan enintään 5005 USDT:n rekisteröintibonuksen. Tämä on loistava tapa parantaa kaupankäyntikokemustasi lisäetuilla ja kannustaa muita osallistumaan.Kuinka käyttää B I T GE T -viitekoodiaB I T GE T -viitekoodi on tarkoitettu erityisesti uusille käyttäjille, jotka eivät ole vielä rekisteröityneet alustalle. Käytä koodia seuraavasti:Vieraile B I T GE T -sivustolla ja napsauta “Kirjaudu sisään”.Anna käyttäjätietosi ja käy läpi KYC- ja AML-menettelyt.Kun sinua pyydetään antamaan viittauskoodi, kirjoita qp29.Suorita rekisteröintiprosessi ja suorita tarvittavat vahvistukset.Kun kaikki ehdot täyttyvät, saat heti tervetuliaisbonuksesi.Miksi käyttää B I T GE T -viitekoodia?Pysyvä alennus: Koodilla qp29 saat automaattisesti 30 % alennuksen kaikista kaupankäyntipalkkioista.Runsas tervetuliaisbonus: Uudet käyttäjät voivat saada jopa 5005 USDT.Lisätulot: Jaa koodisi ja ansaitse 50 % provisio.Hyödynnä tämä tilaisuus ja varmista etusi nykyisellä B I T GE T -viitekoodilla qp29! Saat jopa 5005 USDT ja hyödynnä pysyviä alennuksia kaupankäyntikuluistasi. Read More
Deleted Users
Hi all,
We have E5 Compliance licenses. I’ve been asked to set a retention policy of five years just for current employees. If I use a Static scope of all users for the retention policy, what happens when a user leaves.
So after the deleted user is soft deleted then hard deleted, are their associated retained emails also deleted. I know we can use inactive mailboxes and legal holds if we want to keep the email, but just wondering about what happens if we don’t.
Hi all, We have E5 Compliance licenses. I’ve been asked to set a retention policy of five years just for current employees. If I use a Static scope of all users for the retention policy, what happens when a user leaves. So after the deleted user is soft deleted then hard deleted, are their associated retained emails also deleted. I know we can use inactive mailboxes and legal holds if we want to keep the email, but just wondering about what happens if we don’t. Read More
Új Bit.get ajánlási kód: qp29 (új regisztráció 2024)
A legjobb B I T GE T ajánlókód 2024-re a „qp29”. Használja ezt a kódot, hogy 30% kedvezményt kapjon a kereskedésekből. Ezenkívül az új felhasználók, akik a „qp29” promóciós kóddal regisztrálnak a B I T GE T-re, akár 5005 USDT exkluzív jutalomban is részesülhetnek.
A B I T GE T ajánlókód qp29 előnyei
A B I T GE T qp29 ajánlókód nagyszerű lehetőséget kínál a kereskedési díjak megtakarítására, miközben vonzó jutalmakat keres. A kód megadásával állandó 30% kedvezményt kap a kereskedési díjaiból. Ezenkívül, ha megosztja személyes ajánlókódját barátaival, 50% bónuszt kaphat a kereskedési díjakra. Használja ki ezt a lehetőséget, hogy növelje bevételeit, miközben új felhasználókat hozzon a platformra.
A legjobb B I T GE T ajánlókód 2024-re
Az ajánlott B I T GE T ajánlókód 2024-re a qp29. Ha ezzel a kóddal regisztrál, akár 5005 USDT-t is kaphat bónuszként. Oszd meg ezt a kódot barátaiddal, hogy 50%-os jutalékot kapj, így biztosíthatod a maximum 5005 USDT értékű regisztrációs bónuszt. Ez egy nagyszerű módja annak, hogy további előnyökkel javítsa kereskedési élményét, miközben másokat is a részvételre ösztönöz.
A B I T GE T ajánlókód használata
A B I T GE T ajánlókód kifejezetten azoknak az új felhasználóknak szól, akik még nem regisztráltak a platformon. A kód használatához kövesse az alábbi lépéseket:
Látogassa meg a B I T GE T webhelyet, és kattintson a „Bejelentkezés” gombra.
Adja meg felhasználói adatait, és végezze el a KYC és AML eljárásokat.
Amikor a rendszer kéri az ajánlókódot, írja be a qp29 kódot.
Végezze el a regisztrációs folyamatot, és végezze el a szükséges ellenőrzéseket.
Ha minden feltétel teljesül, azonnal megkapja az üdvözlő bónuszt.
Miért használja a B I T GE T ajánlókódot?
Állandó kedvezmény: A qp29 kóddal automatikusan 30% kedvezményt kap minden kereskedési jutalékból.
Nagyvonalú üdvözlő bónusz: Az új felhasználók akár 5005 USDT-t is kaphatnak.
További bevétel: Ossza meg kódját, és szerezzen 50% jutalékot.
Használja ki ezt a lehetőséget, és biztosítsa előnyeit a jelenlegi B I T GE T qp29 ajánlókóddal! Kapjon akár 5005 USDT-t, és részesüljön állandó kedvezményekben kereskedési díjaiból.
A legjobb B I T GE T ajánlókód 2024-re a „qp29”. Használja ezt a kódot, hogy 30% kedvezményt kapjon a kereskedésekből. Ezenkívül az új felhasználók, akik a „qp29” promóciós kóddal regisztrálnak a B I T GE T-re, akár 5005 USDT exkluzív jutalomban is részesülhetnek.A B I T GE T ajánlókód qp29 előnyeiA B I T GE T qp29 ajánlókód nagyszerű lehetőséget kínál a kereskedési díjak megtakarítására, miközben vonzó jutalmakat keres. A kód megadásával állandó 30% kedvezményt kap a kereskedési díjaiból. Ezenkívül, ha megosztja személyes ajánlókódját barátaival, 50% bónuszt kaphat a kereskedési díjakra. Használja ki ezt a lehetőséget, hogy növelje bevételeit, miközben új felhasználókat hozzon a platformra.A legjobb B I T GE T ajánlókód 2024-reAz ajánlott B I T GE T ajánlókód 2024-re a qp29. Ha ezzel a kóddal regisztrál, akár 5005 USDT-t is kaphat bónuszként. Oszd meg ezt a kódot barátaiddal, hogy 50%-os jutalékot kapj, így biztosíthatod a maximum 5005 USDT értékű regisztrációs bónuszt. Ez egy nagyszerű módja annak, hogy további előnyökkel javítsa kereskedési élményét, miközben másokat is a részvételre ösztönöz.A B I T GE T ajánlókód használataA B I T GE T ajánlókód kifejezetten azoknak az új felhasználóknak szól, akik még nem regisztráltak a platformon. A kód használatához kövesse az alábbi lépéseket:Látogassa meg a B I T GE T webhelyet, és kattintson a „Bejelentkezés” gombra.Adja meg felhasználói adatait, és végezze el a KYC és AML eljárásokat.Amikor a rendszer kéri az ajánlókódot, írja be a qp29 kódot.Végezze el a regisztrációs folyamatot, és végezze el a szükséges ellenőrzéseket.Ha minden feltétel teljesül, azonnal megkapja az üdvözlő bónuszt.Miért használja a B I T GE T ajánlókódot?Állandó kedvezmény: A qp29 kóddal automatikusan 30% kedvezményt kap minden kereskedési jutalékból.Nagyvonalú üdvözlő bónusz: Az új felhasználók akár 5005 USDT-t is kaphatnak.További bevétel: Ossza meg kódját, és szerezzen 50% jutalékot.Használja ki ezt a lehetőséget, és biztosítsa előnyeit a jelenlegi B I T GE T qp29 ajánlókóddal! Kapjon akár 5005 USDT-t, és részesüljön állandó kedvezményekben kereskedési díjaiból. Read More
Announcing new Windows Autopilot onboarding experience for government and commercial customers
Organizations are increasingly adopting a hybrid workplace and Windows Autopilot provides flexibility to deliver devices to users anywhere with internet connectivity. With more and more adoption of Windows Autopilot, Microsoft Intune is enhancing this solution to support a greater variety of scenarios and use cases.
Today, Intune is releasing a new Autopilot profile experience, Windows Autopilot device preparation, which enables IT admins to deploy configurations efficiently and consistently and removes the complexity of troubleshooting for both commercial and government (Government Community Cloud (GCC) High, and U.S. Department of Defense (DoD)) organizations and agencies.
What is Windows Autopilot device preparation and why was it created?
While the existing Windows Autopilot experience supports multiple scenarios and device types, we’re extending this value across additional cloud instances and improving consistency and troubleshooting capabilities based on customer feedback. We’re introducing Autopilot device preparation in a way that won’t interrupt current deployments or experience and provides a more consistent and efficient experience.
Among some of the benefits of Autopilot device preparation are:
Availability in government clouds (GCC High and DoD) which will allow government customers to deploy at scale using Autopilot.
Providing more consistency in user experience during deployments by locking in IT admins intentions for onboarding.
Creating more error resiliency in the experience to allow users to recover without needing to call a help desk.
Sharing more insight into the Autopilot process with new reporting details.
A single Autopilot device preparation profile to configure deployment and OOBE settings
The Autopilot device preparation admin experience simplifies admin configuration by having a single profile to provision all policies in one location, including deployment settings and out-of-box (OOBE) settings. It also improves the consistency of the experience for users and gets them to the desktop faster by allowing you to select which apps (line-of-business (LOB), Win32, or Store apps) and PowerShell scripts must be delivered during OOBE.
Grouping at enrollment time
An improved grouping experience places devices in a group at the time of enrollment. Simply assign all configurations to a device security group and include the group as part of the device preparation profile. The configuration will be saved and then delivered on the device as soon as the user authenticates during OOBE.
New user experience in OOBE
A simplified OOBE view shows the progress of the deployment in percentage % so that users know how far along in the process they are. When the device preparation configuration has been delivered to the device, the user will be informed that critical setup is complete, and they can continue to the desktop.
The Autopilot device preparation deployment report
The new Autopilot device preparation deployment report captures the status of each deployment in near real-time and provides detailed information to help with troubleshooting. Here are some highlights of what to expect:
Easily track which devices went through Autopilot
Track status and deployment phase in near-real-time
Expand more details for each deployment:
Device details
Profile name and version
Deployment status details
Apps applied with status
Scripts applied with status
Coming soon: Corporate identifiers for Windows
While we don’t have a tenant association feature ready in this initial release, we understand the importance of only allowing known devices to enroll to your tenant. So, we’ll soon expand enrollment restrictions to include Windows corporate identifiers. Autopilot device preparation will support the new corporate identifier enrollment feature <link to doc>. This added functionality will allow you to pre-upload device identifiers and ensure only trusted devices go through Autopilot device preparation. Stay tuned to What’s new in Intune for the release!
Frequently Asked Questions
How is this new Autopilot profile different from the current Autopilot profile?
The new Autopilot profile is a re-architecture of the current Autopilot profile so while the experience to OEMs, IT admins and users may look the same, the underlying architecture is very different. The updated architecture in the new Autopilot profiles gives the admin new capabilities that improve the deployment experience.
New orchestration agent allows the experience to fail fast and provide more error details.
Targeting is more precise and avoids dynamic changes when dynamic grouping is used.
Reporting infrastructure provides more details on the deployment experience.
Who does the new Autopilot profile benefit?
The new profile will benefit government customers who can now use Windows Autopilot device preparation to streamline their deployments at scale. It’ll also benefit new customers onboarding Windows Autopilot by reducing the complexity of setting up the deployment.
Is the new profile available in all sovereign clouds?
The new profile is available for Government Community Cloud (GCC) High and U.S. Department of Defense (DoD). It’s expected to be available for Intune operated by 21Vianet in China later this year.
What about the other Autopilot scenarios like pre-provisioning and self-deploying mode?
These functionalities will be supported in the future but aren’t part of the initial release.
Why is there a limit on the number of apps I can select to be delivered during OOBE?
We limited the number of applications that can be applied during OOBE to increase stability and achieve a higher success rate. Looking at our telemetry, almost 90% of all Autopilot deployments are deployed with 10 or fewer apps. This limit is intended to improve the overall user experience so that users can become more productive quickly. We understand that there are outliers and companies that want to target more during setup, but for the user-driven approach, we want to leverage the desktop experience for non-essential applications.
What is the order of installation for the device preparation profile?
The process is described in detail in: Overview for Windows Autopilot device preparation user-driven Microsoft Entra join in Intune.
Can we now mix app types such as LOB and Win32 apps with the device preparation profile?
While we always recommend Win32 apps, in current Autopilot deployments, mixing apps may result in errors. With the device preparation profile, we’ve streamlined the providers so different app types should not impact each other.
What is the guidance on user- vs device-based targeting?
Only device-based configurations will be delivered during OOBE. Assign security policy to devices, ensure all selected apps in the device preparation profile are set to install in system context, and are targeted to the device security group specified in the profile.
How will users know when the setup is complete?
Many users aren’t sure when the provisioning process is complete. To help mitigate confusion and calls to the help desk, we’re adding a completion page in OOBE. Admins can configure the pageto require a user to manually select to continue or set the page to auto-continue. This message will let the user know that OOBE setup is complete but there may be additional installations happening that they can monitor in the Intune Company Portal.
Can the new profile be used by other MDMs?
Windows Autopilot device preparation will support 3rd party MDMs. In this initial release, configuration is only possible via Intune.
Will this be available on Windows 10 devices?
Currently, device preparation profiles are only available on:
Windows 11, version 23H2 with KB5035942 or later.
Windows 11, version 22H2 with KB5035942 or later.
How can I move my existing devices to the new device preparation profile?
If you’d like to have an existing device join your tenant through the device preparation profile, the device would first need to be de-registered from Autopilot, then retargeted to a security group within your device preparation profile.
Do I need to migrate my existing profiles from Autopilot-to-Autopilot device preparation?
There’s no need to migrate from existing Autopilot to the new Autopilot profile. We expect both environments to exist in parallel for a while as we work to improve the experience and add more functionality.
Does this mean we are no longer investing in Autopilot?
Not at all! We’re continuing to work on Autopilot in parallel with developing Autopilot device preparation. The first release of Autopilot device preparation won’t have all the scenarios of Autopilot, specifically pre-provisioning and self-deploying modes, so we’ll continue to invest in those areas. Additionally, where possible, we plan to add any high value features from Autopilot device preparation to Autopilot to improve the experience for all customers.
If you have any questions, leave a comment below or reach out to us on X @IntuneSuppTeam. Stay tuned to What’s new in Intune and What’s new in Autopilot as we continue developing this new deployment experience.
Microsoft Tech Community – Latest Blogs –Read More
Announcing: Public Preview of Resubmit from an Action in Logic Apps Consumption Workflows
Announcing: Public Preview of Resubmit from an Action in Logic Apps Consumption Workflows
Introduction
We are happy to introduce Resubmit Action in the Consumption SKU. This is a feature that customers have been asking for a long time, and we are glad to finally deliver it to Consumption SKU. Resubmit action has been part of Standard SKU for a while, and we have gotten positive feedback from customers. Standard SKU announcement.
Background
Resubmit from trigger has been a feature available for many years, however customers are looking for more flexibility around being able to resubmit from any action within the workflow. This will give customers more control over where they resume their workflow from and will allow customers to avoid data duplication in action calls that previously were successful.
How it works
Once you select the action to be resubmitted, all actions before the selected action including the trigger are replayed from the original workflow run. This means we will reuse the inputs and outputs of those actions and not actually execute them. Once the workflow execution reaches the resubmitted action, we will process that action and all following actions as normal.
How to use it
We have improved the visibility of this operation since its first Standard SKU release. We listened to the input from our partners and customers and realized that the feature was too obscure and not easy to find. Therefore, we have expanded the number of locations where users can start the Resubmit operation.
Go to your workflow’s Run History page and select the run you want to resubmit.
Find the action you want to resubmit. Note: Failed and Successful actions can be resubmitted. There are two ways to resubmit from an action:
Option A
Right-click on the action and click the Submit from this action button.
Option B
Click on the action to bring up the run details. Near the top of the newly opened pane find and click on the Submit from this action button.
The page will refresh, putting you into the context of the new run. Note: Actions occurring before the resubmitted action will have a dim-green icon indicating their inputs and outputs were reused from the parent run.
Limitations
The resubmit actions feature is not available to all actions and workflow configurations. Below are the limitations to keep in mind when using this feature:
The workflow must be a Stateful workflow
The resubmitted run will execute the same flow version as the original run. This is true even if the workflow definition has been updated.
The workflow must have 40 or fewer actions to be eligible for action resubmit.
The workflow must be in a completed state e.g. Failed, Successful, Cancelled
Only actions of sequential workflows are eligible to be resubmitted. Workflows with parallel paths are currently not supported.
Actions inside of a Foreach or Until operations are not eligible to be resubmitted. Additionally, the Foreach and Until operations themselves are not eligible.
Actions that occur after Foreach and Until operations are not eligible to be resubmitted.
This feature is currently not available in VS Code or the Azure CLI.
What’s next
Give it a try! This is a highly requested feature from customers as there currently is no way to resubmit from an action inside of a Consumption workflow. This feature alleviates the need to re-run an entire workflow because of an external service failure or misconfiguration. Please give it a try and let us know your thoughts!
Microsoft Tech Community – Latest Blogs –Read More
Build Your Dream With Autogen
The motivation – Is it possible to solve multi step tasks?
The short answer is Yes.
While large language models (LLMs) demonstrate remarkable capabilities in a variety of applications, such as language generation, understanding, and reasoning, they struggle to provide accurate answers when faced with complicated tasks.
According to this research (More agents is all you need), the performance of large language models (LLMs) scales with the number of agents instantiated. This method is orthogonal to existing complicated methods to further enhance LLMs, while the degree of enhancement is correlated to the task difficulty.
The Application
Now that we understand the motivation, and the business value of solving complicated, let’s build our dream team.
AutoGen provides a general conversation pattern called group chat, which involves more than two agents. The core idea of group chat is that all agents contribute to a single conversation thread and share the same context. This is useful for tasks that require collaboration among multiple agents.
Priya is the VP engineering of “Great Company”, the company leadership would like to build a solution for the legal domain based on LLMs, before writing a single line of code, Priya would like to research what are the available open sources on GitHub:
“What are the 5 leading GitHub repositories on llm for the legal domain?”
Executing it on Google, Bing or another search engine will not provide a structured and accurate result.
Let’s Build
We’ll build a system of agents using the Autogen library. The agents include a human admin, developer, planner, code executor, and a quality assurance agent. Each agent is configured with a name, a role, and specific behaviors or responsibilities.
Here’s the final output:
Install
(AutoGen requires Python>=3.8)
Set your API Endpoint
The config_list_from_json function loads a list of configurations from an environment variable or a json file.
from autogen.agentchat import ConversableAgent,UserProxyAgent,AssistantAgent,GroupChat,GroupChatManager
from autogen.oai.openai_utils import config_list_from_json
import os
from dotenv import load_dotenv
import warnings
warnings.filterwarnings(‘ignore’)
load_dotenv()
config_list_gpt4 = config_list_from_json(
“OAI_CONFIG_LIST”,
filter_dict={
“model”: [“gpt4o”],# in this example we used gpt4 omni
},
)
It first looks for environment variable “OAI_CONFIG_LIST” which needs to be a valid json string. If that variable is not found, it then looks for a json file named “OAI_CONFIG_LIST”. It filters the configs by models (you can filter by other keys as well).
You can set the value of config_list in any way you prefer.
Construct Agents
“cache_seed”: 42, # change the cache_seed for different trials
“temperature”: 0,
“config_list”: config_list_gpt4,
“timeout”: 120,
}
Let’s build our team, this code is setting up the agents:
user_proxy = UserProxyAgent(
name=”Admin”,
human_input_mode=”ALWAYS”,
system_message=”1. A human admin. 2. Interact with the team. 3. Plan execution needs to be approved by this Admin.”,
code_execution_config=False,
llm_config=gpt4_config,
description=”””Call this Agent if:
You need guidance.
The program is not working as expected.
You need api key
DO NOT CALL THIS AGENT IF:
You need to execute the code.”””,
)
# Assistant Agent – Developer
developer = AssistantAgent(
name=”Developer”,
llm_config=gpt4_config,
system_message=”””You are an AI developer. You follow an approved plan, follow these guidelines:
1. You write python/shell code to solve tasks.
2. Wrap the code in a code block that specifies the script type.
3. The user can’t modify your code. So do not suggest incomplete code which requires others to modify.
4. You should print the specific code you would like the executor to run.
5. Don’t include multiple code blocks in one response.
6. If you need to import libraries, use “`bash pip install module_name“`, please send a code block that installs these libraries and then send the script with the full implementation code
7. Check the execution result returned by the executor, If the result indicates there is an error, fix the error and output the code again
8. Do not show appreciation in your responses, say only what is necessary.
9. If the error can’t be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.
“””,
description=”””Call this Agent if:
You need to write code.
DO NOT CALL THIS AGENT IF:
You need to execute the code.”””,
)
# Assistant Agent – Planner
planner = AssistantAgent(
name=”Planner”, #2. The research should be executed with code
system_message=”””You are an AI Planner, follow these guidelines:
1. Your plan should include 5 steps, you should provide a detailed plan to solve the task.
2. Post project review isn’t needed.
3. Revise the plan based on feedback from admin and quality_assurance.
4. The plan should include the various team members, explain which step is performed by whom, for instance: the Developer should write code, the Executor should execute code, important do not include the admin in the tasks e.g ask the admin to research.
5. Do not show appreciation in your responses, say only what is necessary.
6. The final message should include an accurate answer to the user request
“””,
llm_config=gpt4_config,
description=”””Call this Agent if:
You need to build a plan.
DO NOT CALL THIS AGENT IF:
You need to execute the code.”””,
)
# User Proxy Agent – Executor
executor = UserProxyAgent(
name=”Executor”,
system_message=”1. You are the code executer. 2. Execute the code written by the developer and report the result.3. you should read the developer request and execute the required code”,
human_input_mode=”NEVER”,
code_execution_config={
“last_n_messages”: 20,
“work_dir”: “dream”,
“use_docker”: True,
},
description=”””Call this Agent if:
You need to execute the code written by the developer.
You need to execute the last script.
You have an import issue.
DO NOT CALL THIS AGENT IF:
You need to modify code”””,
)
quality_assurance = AssistantAgent(
name=”Quality_assurance”,
system_message=”””You are an AI Quality Assurance. Follow these instructions:
1. Double check the plan,
2. if there’s a bug or error suggest a resolution
3. If the task is not solved, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach.”””,
llm_config=gpt4_config,
)
Group chat is a powerful conversation pattern, but it can be hard to control if the number of participating agents is large. AutoGen provides a way to constrain the selection of the next speaker by using the allowed_or_disallowed_speaker_transitions argument of the GroupChat class.
allowed_transitions = {
user_proxy: [ planner,quality_assurance],
planner: [ user_proxy, developer, quality_assurance],
developer: [executor,quality_assurance, user_proxy],
executor: [developer],
quality_assurance: [planner,developer,executor,user_proxy],
}
groupchat = GroupChat(
agents=[user_proxy, developer, planner, executor, quality_assurance],allowed_or_disallowed_speaker_transitions=allowed_transitions,
speaker_transitions_type=”allowed”, messages=[], max_round=30,send_introductions=True
)
manager = GroupChatManager(groupchat=groupchat, llm_config=gpt4_config, system_message=system_message_manager)
Sometimes it’s a bit complicated to understand the relationship between the entities, here we print a graph representation of the code:
import matplotlib.pyplot as plt
G = nx.DiGraph()
# Add nodes
G.add_nodes_from([agent.name for agent in groupchat.agents])
# Add edges
for key, value in allowed_transitions.items():
for agent in value:
G.add_edge(key.name, agent.name)
# Set the figure size
plt.figure(figsize=(12, 8))
# Visualize
pos = nx.spring_layout(G) # For consistent positioning
# Draw nodes and edges
nx.draw_networkx_nodes(G, pos)
nx.draw_networkx_edges(G, pos)
# Draw labels below the nodes
label_pos = {k: [v[0], v[1] – 0.1] for k, v in pos.items()} # Shift labels below the nodes
nx.draw_networkx_labels(G, label_pos, verticalalignment=’top’, font_color=”darkgreen”)
# Adding margins
ax = plt.gca()
ax.margins(0.1) # Increase the margin value if needed
# Adding a dynamic title
total_transitions = sum(len(v) for v in allowed_transitions.values())
title = f’Agent Interactions: {len(groupchat.agents)} Agents, {total_transitions} Potential Transitions’
plt.title(title)
plt.show()
chat_result=user_proxy.initiate_chat(
manager,
message=task1
, clear_history=True
)
what are the 5 leading GitHub repositories on llm for the legal domain?
——————————————————————————–
Planner (to chat_manager):
To identify the 5 leading GitHub repositories on large language models (LLM) for the legal domain, we will follow a structured plan. Here is the detailed plan:
### Step 1: Define Search Criteria
**Team Member:** Planner
– Define the criteria for what constitutes a “leading” GitHub repository. This could include factors such as the number of stars, forks, recent activity, and relevance to the legal domain.
### Step 2: Conduct Initial Search
**Team Member:** Developer
– Use GitHub’s search functionality to find repositories related to LLMs in the legal domain.
– Apply filters based on the criteria defined in Step 1.
### Step 3: Compile and Analyze Data
**Team Member:** Developer
– Compile a list of the top 10 repositories based on the initial search.
– Analyze these repositories to ensure they meet the criteria and are relevant to the legal domain.
### Step 4: Narrow Down to Top 5
**Team Member:** Developer
– Narrow down the list from 10 to the top 5 repositories based on further analysis and comparison.
### Step 5: Verify and Finalize
**Team Member:** Quality Assurance
– Double-check the final list of 5 repositories to ensure they meet all the criteria and are indeed leading repositories in the legal domain.
– Provide a brief description of each repository and why it was selected.
### Final List of 5 Leading GitHub Repositories on LLM for the Legal Domain
1. **Repository Name:** [Link to Repository]
– **Description:** Brief description of the repository and its relevance to the legal domain.
2. **Repository Name:** [Link to Repository]
– **Description:** Brief description of the repository and its relevance to the legal domain.
3. **Repository Name:** [Link to Repository]
– **Description:** Brief description of the repository and its relevance to the legal domain.
4. **Repository Name:** [Link to Repository]
– **Description:** Brief description of the repository and its relevance to the legal domain.
5. **Repository Name:** [Link to Repository]
– **Description:** Brief description of the repository and its relevance to the legal domain.
This plan will ensure that we identify and verify the top 5 leading GitHub repositories on LLM for the legal domain.
*****************
You can find the full output in the GitHub repo
——————————————————————————–
Quality_assurance (to chat_manager):
### Final List of 5 Leading GitHub Repositories on LLM for the Legal Domain
1. **Repository Name:** [lexpredict-lexnlp](https://github.com/LexPredict/lexpredict-lexnlp)
– **Description:** LexNLP by LexPredict
– **Stars:** 676
– **Forks:** 174
2. **Repository Name:** [Blackstone](https://github.com/ICLRandD/Blackstone)
– **Description:** A spaCy pipeline and model for NLP on unstructured legal text.
– **Stars:** 632
– **Forks:** 100
3. **Repository Name:** [Legal-Text-Analytics](https://github.com/Liquid-Legal-Institute/Legal-Text-Analytics)
– **Description:** A list of selected resources, methods, and tools dedicated to Legal Text Analytics.
– **Stars:** 563
– **Forks:** 113
4. **Repository Name:** [2019Legal-AI-Challenge-Legal-Case-Element-Recognition-solution](https://github.com/wangxupeng/2019Legal-AI-Challenge-Legal-Case-Element-Recognition-solution)
– **Description:** Completed this competition in collaboration with Jiang Yan and Guan Shuicheng.
– **Stars:** 501
– **Forks:** 33
5. **Repository Name:** [DISC-LawLLM](https://github.com/FudanDISC/DISC-LawLLM)
– **Description:** DISC-LawLLM, an intelligent legal system utilizing large language models (LLMs) to provide a wide range of legal services.
– **Stars:** 445
– **Forks:** 45
### Verification and Finalization
**Quality Assurance Task:**
– **Double-check the final list:** Ensure that the repositories meet all the criteria and are indeed leading repositories in the legal domain.
– **Provide a brief description:** Each repository has been described briefly, highlighting its relevance to the legal domain.
The task is now complete, and the final list of leading GitHub repositories on LLM for the legal domain has been verified and finalized.
We have shown how to build a complex multi agent solution, this enhancement ensures that complex multi steps tasks can be solved with Autogen.
Now we can deploy this group to solve various business use cases like customer support, IT, finance and more.
Microsoft Tech Community – Latest Blogs –Read More
how to model a fire alarm system on simulink
KIndly advise as to how I can model and simulate a fire alarm system on simulink. So if you can suggest any crediable and reliable learning resources that would be best.KIndly advise as to how I can model and simulate a fire alarm system on simulink. So if you can suggest any crediable and reliable learning resources that would be best. KIndly advise as to how I can model and simulate a fire alarm system on simulink. So if you can suggest any crediable and reliable learning resources that would be best. fire alarms, simulink MATLAB Answers — New Questions
Sensor Fusion and Tracking Toolbox
I have installed Sensor Fusion and Tracking toolbox for my MATLAB R2019a but when i try to open example using this command:
openExample(‘shared_fusion_arduinoio/EstimateOrientationUsingInertialSensorFusionAndMPU9250Example’)
I get this message:
Error using exampleUtils.componentExamplesDir (line 13)
Invalid argument "shared_fusion_arduinoio".
Error in findExample (line 18)
componentExamplesDir =
exampleUtils.componentExamplesDir(component);
Error in openExample (line 24)
metadata = findExample(id);
Actualy I want to use HelperOrientationViewer command to view the 3D pose of my IMU sensor which is possible via this example because when i try to do that it just gives error:
Undefined function or variable ‘HelperOrientationViewer’.
Error in matlab_mpu9250 (line 72)
viewer = HelperOrientationViewer(‘Title’,{‘AHRS Filter’});
Please do help me i really need Viewer for proper visualization of my robot’s orientation.I have installed Sensor Fusion and Tracking toolbox for my MATLAB R2019a but when i try to open example using this command:
openExample(‘shared_fusion_arduinoio/EstimateOrientationUsingInertialSensorFusionAndMPU9250Example’)
I get this message:
Error using exampleUtils.componentExamplesDir (line 13)
Invalid argument "shared_fusion_arduinoio".
Error in findExample (line 18)
componentExamplesDir =
exampleUtils.componentExamplesDir(component);
Error in openExample (line 24)
metadata = findExample(id);
Actualy I want to use HelperOrientationViewer command to view the 3D pose of my IMU sensor which is possible via this example because when i try to do that it just gives error:
Undefined function or variable ‘HelperOrientationViewer’.
Error in matlab_mpu9250 (line 72)
viewer = HelperOrientationViewer(‘Title’,{‘AHRS Filter’});
Please do help me i really need Viewer for proper visualization of my robot’s orientation. I have installed Sensor Fusion and Tracking toolbox for my MATLAB R2019a but when i try to open example using this command:
openExample(‘shared_fusion_arduinoio/EstimateOrientationUsingInertialSensorFusionAndMPU9250Example’)
I get this message:
Error using exampleUtils.componentExamplesDir (line 13)
Invalid argument "shared_fusion_arduinoio".
Error in findExample (line 18)
componentExamplesDir =
exampleUtils.componentExamplesDir(component);
Error in openExample (line 24)
metadata = findExample(id);
Actualy I want to use HelperOrientationViewer command to view the 3D pose of my IMU sensor which is possible via this example because when i try to do that it just gives error:
Undefined function or variable ‘HelperOrientationViewer’.
Error in matlab_mpu9250 (line 72)
viewer = HelperOrientationViewer(‘Title’,{‘AHRS Filter’});
Please do help me i really need Viewer for proper visualization of my robot’s orientation. mpu9250, sensor fusion, toolbox, error opening example, helper orientation viewer, matlab2019a, imu MATLAB Answers — New Questions
How to read shape file in matlab?
I am using following matlab code to read shape file. I am attaching the shape file also as zip file.
% pickup the shape files
d = uigetdir(pwd, ‘Select a folder’);
shapefiles = dir(fullfile(d, ‘*.shp’));
for n = 1:length(shapefiles)
shapefile = shapefiles(n);
disp(shapefile.name);
S = shaperead(shapefile.name);
polygon = polyshape([S.X], [S.Y]);
% Create a logical mask
logical_mask = inpolygon(lon, lat, polygon.Vertices(:, 1), polygon.Vertices(:, 2));
end
This is giving the following errors;
>> testrnAchi Khurd.shp
Error using openShapeFiles>checkSHP (line 82)
Unable to open file ‘Achi Khurd.shp’. Check the path and filename or file permissions.
Error in openShapeFiles (line 19)
[basename, ext] = checkSHP(basename,shapeExtensionProvided);
Error in shaperead (line 212)
= openShapeFiles(filename,’shaperead’);
Error
in test (line 9)
S = shaperead(shapefile.name);
>>
Please suggest me how to fix it? I would be highly obliged for kind help.
DaveI am using following matlab code to read shape file. I am attaching the shape file also as zip file.
% pickup the shape files
d = uigetdir(pwd, ‘Select a folder’);
shapefiles = dir(fullfile(d, ‘*.shp’));
for n = 1:length(shapefiles)
shapefile = shapefiles(n);
disp(shapefile.name);
S = shaperead(shapefile.name);
polygon = polyshape([S.X], [S.Y]);
% Create a logical mask
logical_mask = inpolygon(lon, lat, polygon.Vertices(:, 1), polygon.Vertices(:, 2));
end
This is giving the following errors;
>> testrnAchi Khurd.shp
Error using openShapeFiles>checkSHP (line 82)
Unable to open file ‘Achi Khurd.shp’. Check the path and filename or file permissions.
Error in openShapeFiles (line 19)
[basename, ext] = checkSHP(basename,shapeExtensionProvided);
Error in shaperead (line 212)
= openShapeFiles(filename,’shaperead’);
Error
in test (line 9)
S = shaperead(shapefile.name);
>>
Please suggest me how to fix it? I would be highly obliged for kind help.
Dave I am using following matlab code to read shape file. I am attaching the shape file also as zip file.
% pickup the shape files
d = uigetdir(pwd, ‘Select a folder’);
shapefiles = dir(fullfile(d, ‘*.shp’));
for n = 1:length(shapefiles)
shapefile = shapefiles(n);
disp(shapefile.name);
S = shaperead(shapefile.name);
polygon = polyshape([S.X], [S.Y]);
% Create a logical mask
logical_mask = inpolygon(lon, lat, polygon.Vertices(:, 1), polygon.Vertices(:, 2));
end
This is giving the following errors;
>> testrnAchi Khurd.shp
Error using openShapeFiles>checkSHP (line 82)
Unable to open file ‘Achi Khurd.shp’. Check the path and filename or file permissions.
Error in openShapeFiles (line 19)
[basename, ext] = checkSHP(basename,shapeExtensionProvided);
Error in shaperead (line 212)
= openShapeFiles(filename,’shaperead’);
Error
in test (line 9)
S = shaperead(shapefile.name);
>>
Please suggest me how to fix it? I would be highly obliged for kind help.
Dave how to read shape file in matlab? MATLAB Answers — New Questions