how to delete nan values from array columns without losing data from other columns

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dareen 2024-5-11

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2117691-how-to-delete-nan-values-from-array-columns-without-losing-data-from-other-columns

评论： Mathieu NOE 2024-5-14

采纳的回答： Mathieu NOE

i have a huge file from a lab expremient

every run gives me 4 columns and every 2 out of the 4 start with nan then 2 nan vars and end with nan and 3 nan vars i want to delet the nan values without losing any data so that when i try to make graphs from it every graph will have enough inputs and neither of them get lost

i am espisally troubled by the second 2 columns of every 4 and how to deal with them

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dareen 2024-5-13

编辑：dareen 2024-5-13

i think i have a much more fundemental problem i am not sure what to do to plot my goal , my goal is to get something as x(t)=a(t) sin(w*t+phi)

i have x(t) and (at) i have t and v(t) i know that i can get the rest using cftool but in regards to how to so do not really ,i tried to deal with the problem by starting to take values from 3 entery from row i to row j in a certain column , and so on for the 4 first columns and i remove nan values from the buttom and take the bottom -4 so that i would not have diffrent lengths for the function ,

emp=rmmissing(data2{:,1:4}); % Remove NaN from col 1,2,3 4

t=data2(3:end-4,1) x=data2(3:end-4,2) v=data2(3:end-4,3) a=data2(3:end-4,4)

but now stuck with the implementing

here when i tried to turn this into a function

[num_rows, num_columns] = size(data2);

function rebuildtable (data2,num_rows,num_columns)

emp=rmmissing(data2{:,1:4:end}); % Remove NaN from col 1,2,3 4

t=data2(3:end-4,1:4:end) x=data2(3:end-4,2:4:end) v=data2(3:end-4,3:4:end) a=data2(3:end-4,4:4:end)

end

but now stuck with the implementing

of the funciton above in order to get w and phi using cftool

this did not really work so i backed down and reached a new way

Mathieu NOE 2024-5-14

glad I could help a bit , but this was just a starter

ok, let's focus on the selected runs (for both files I presume ?)

these 2 lines are indeed just to extract a block of 4 contiguous columns , and we simply shift by a factor 4 when we change to the next run :

ind_cols = (1:4)+(ck-1)*4;

data_this_run = data(:,ind_cols);

and yes this line is not anymore of any use (I used it for another purpose that I removed afterwards) : [m,n] = size(data_this_run);

I'll come back soon with a new code

dareen 2024-5-14

编辑：dareen 2024-5-14

i appreciate your time and help ,sorry that the question is lengthy and not written in the most clear form, yeah for both files ,i tried to seprate them since each should yield some intersting observations ,= i was not sure if i should also keep the accelration and velocity since i am not sure implementation wise what to do , if any of the data before is needed in the later sections then we can work on the original file and i will try to learn and implement it in the the tided up versions and add whats needed , as for what i am trying to reach i firstly had another file of data from excel that helped find the spring constant and i ploted angular velocity intialy as a function of mass and now the new angular velocity when the system is osillating and slowing down as a function of mass here what i did for now i tried to copperate cftool since i thougth maybe there i can the sin and cos values yet failed mesriably not sure how to get the data from normal plots either

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Answer 1

Mathieu NOE 2024-5-14

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2117691-how-to-delete-nan-values-from-array-columns-without-losing-data-from-other-columns#answer_1457146

在 MATLAB Online 中打开

expr2lab.csv

ok, so this is now the main dishes....

have first tried this code on the first data file , will adapt to your new files as soon as possible

have fun !

data= readmatrix('expr2lab.csv'); % or readtable or whatever

runs = [12 , 16 ,17,20,22,24,29,30,31,34,33,11]; % selection of best runs

%% main loop

for ck = 1:numel(runs)

k = runs(ck);

ind_cols = (1:4)+(k-1)*4; % Time (s) Position (m) Velocity (m/s) Acceleration (m/s²)

data_this_run = data(:,ind_cols);

[m,n] = size(data_this_run);

Time = data_this_run(:,1);

Position = data_this_run(:,2);

Velocity = data_this_run(:,3);

Acceleration = data_this_run(:,4);

%% fit on acceleration data

% remove all NaN's first

ind = isnan(Time) | isnan(Acceleration);

Time(ind) = [];

Position(ind) = [];

Velocity(ind) = [];

Acceleration(ind) = [];

% select valid data between first max peak and end of data

[v,indm] = max(Acceleration); % search for the first positive max peak

nn = numel(Time);

[b,yf] = exp_decay_sinus_fit(Time(indm:nn),Acceleration(indm:nn));

% b array contains 5 coefficients according to this equation (model)

% y = b(1).*exp(b(2).*x).*(sin(2*pi*b(3)*x + b(4))) + b(5)

eq_str = [ ' y = ' num2str(b(1),'%.2f'),'* exp(-' num2str(-b(2),'%.2f') ' t * sin(2*pi*' num2str(b(3),'%.2f') ' t + ' num2str(b(4),'%.2f') ' ) + (' num2str(b(5),'%.2f') ')'];

figure(ck)

subplot(3,1,1),plot(Time,Position)

title(['Run # : ' num2str(k)]);

ylabel('Position');

subplot(3,1,2),plot(Time,Velocity)

ylabel('Velocity');

subplot(3,1,3),plot(Time,Acceleration,Time(indm:nn),yf);

ylabel('Acceleration');

legend('data',eq_str);

end

%%%%%%%%%%%%%%% functions %%%%%%%%%%%%%%%%%%%%%%

function [B,yf] = exp_decay_sinus_fit(t,y)

[yu,indm] = max(y);

yl = min(y);

yr = (yu-yl); % Range of y

yz = y-yu+(yr/2);

% zero crossing are performed on first 1/3 of data (better signal to

% noise ratio)

n = round(numel(y)/3);

yz = yz(indm:n); % extract from first major peak to end of 30% of data

zt = t(yz(:) .* circshift(yz(:),[1 0]) <= 0); % Find zero-crossings

per = 2*mean(diff(zt)); % Estimate period

freq = 1/per; % Estimate frequency

% initial phase estimate

tmax = t(indm);

phase_init = mod(-2*pi*freq*tmax + pi/2,2*pi); % initial phase estimate

ym = mean(y); % Estimate DC value (offset)

fit = @(b,x) b(1).*exp(b(2).*x).*(sin(2*pi*b(3)*x + b(4))) + b(5); % Objective Function to fit

fcn = @(b) norm(fit(b,t) - y); % Least-Squares cost function

B = fminsearch(fcn, [yr; -0.1; freq; phase_init; ym]); % Minimise Least-Squares

if B(4)<0 % complement negative phase with 2pi

B(4) = B(4) + 2*pi;

end

yf = fit(B,t);

end

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dareen 2024-5-14

and once again thank you for your time and effort i am learning a lot

Mathieu NOE 2024-5-14

as always, my pleasure !

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how to delete nan values from array columns without losing data from other columns

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how to delete nan values from array columns without losing data from other columns

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