I'm a little new to MATLAB and I am working on a class project. So I have these infinite values in my U matrix which I want to remove and replace with 0. This is part of my code:
U(Nt,y)=inv(h(Nt,y).*Atot(Nt,y))+inv(h3(y).*Ain2(y))+Rcond(y)
There are lots of inifinite values which I should remove to clear up my graphs. If you need any more information just ask. Thanks in advance!
Related
I need your help again :). I'm trying to plot multiple lines for a very large dataset. To start easier, I divided the dataset to get a TABLE in Matlab that contains 6 columns, with the first column representing the date that I want on my x-axis. Now I want to plot the other columns (and in the original file are a lot more than 6 columns) on the y axis, using a for loop. I tried the following, with no success:
hold on
for i=2:1:6
plot(Doldenstock(:,1), Doldenstock(:,i));
end
hold off
As I understand this, this code would do exactly what I want for columns 2,3,4,5,6. However, I always get the same error code:
Error using tabular/plot
Too many input arguments.
Error in Plotting_bogeo (line 6)
plot(Doldenstock(:,1), Doldenstock(:,i));
Now, I don't know if maybe for loops like this don't work for tabes but only for arrays?
Thanks for your help in advance!
Cheers,
Tamara
The function plot(x) expect x to be a scalar, a vector, or a matrix. But in your case the input is a table, because accessing a table with parentheses return a table, which is not supported.
If you read the doc "how to access data in a table" you will figure out that you need to use curly brace {} to extract the raw data (in your case a 1D matrix).
So use:
plot(T{:,1},T{:,2})
I am trying to avoid the for loops and I have been reading through all the old posts there are about it but I am not able to solve my problem. I am new in MATLAB, so apologies for my ignorance.
The thing is that I have a 300x2 cell and in each one I have a 128x128x256 matrix. Each one is an image with 128x128 pixels and 256 channels per pixel. In the first column of the 300x2 cell I have my parallel intensity values and in the second one my perpendicular intensity values.
What I want to do is to take every pixel of every image (for each component) and sum the intensity values channel by channel.
The code I have is the following:
Image_par_channels=zeros(128,128,256);
Image_per_channels=zeros(128,128,256);
Image_tot_channels=zeros(128,128,256);
for a=1:128
for b=1:128
for j=1:256
for i=1:numfiles
Image_par_channels(a,b,j)=Image_par_channels(a,b,j)+Image_cell_par_per{i,1}(a,b,j);
Image_per_channels(a,b,j)=Image_per_channels(a,b,j)+Image_cell_par_per{i,2}(a,b,j);
end
Image_tot_channels(a,b,j)=Image_par_channels(a,b,j)+2*G*Image_per_channels(a,b,j);
end
end
end
I think I could speed it up introducing (:,:,j) instead of specifying a and b. But still a for loop. I am trying to use cellfun without any success due to my lack of expertise. Could you please give me a hand?
I would really appreciate it.
Many thanks and have a nice day!
Y
I believe you could do something like
Image_par_channels=zeros(128,128,256);
Image_per_channels=zeros(128,128,256);
Image_tot_channels=zeros(128,128,256);
for i=1:numfiles
Image_par_channels = Image_par_channels + Image_cell_par_per{i,1};
Image_per_channels = Image_per_channels + Image_cell_par_per{i,2};
end
Image_tot_channels = Image_par_channels + 2*G*Image_per_channels;
I haven't work with matlab in a long time, but I seem to recall you can do something like this. g is a constant.
EDIT:
Removed the +=. Incremental assignment is not an operator available in matlab. You should also note that Image_tot_channels can be build directly in the loop, if you don't need the other two variables later.
Hello I wanted to reshape this code to make it easier.
sins=1/3*(sind(50)+sind(300)+sind(340));
coses=1/3*(cosd(50)+cosd(300)+cosd(340));
result=atand(sins/coses);
it will be more input like 50,300,340... so I wanted to like this
a=[50 300 340];
sins=1/3*(sind(a));
coses=1/3*(cosd(b));
result=atand(sins/coses);
but it doesnt work.
How can I make it ?
Thanks in advance.
In your first example, you sum all three values returned by sind, in your second code you don't sum them. Inputting a matrix, sind (like most mathematical functions in MATLAB) returns a matrix of the same size, applying the function to each element. Use sum to get the sum of a vector.
sins=1/3*(sum(sind(a)));
I have a csv file which contains data like below:[1st row is header]
Element,State,Time
Water,Solid,1
Water,Solid,2
Water,Solid,3
Water,Solid,4
Water,Solid,5
Water,Solid,2
Water,Solid,3
Water,Solid,4
Water,Solid,5
Water,Solid,6
Water,Solid,7
Water,Solid,8
Water,Solid,7
Water,Solid,6
Water,Solid,5
Water,Solid,4
Water,Solid,3
The similar pattern is repeated for State: "Solid" replaced with Liquid and Gas.
And moreover the Element "Water" can be replaced by some other element too.
Time as Integer's are in seconds (to simplify) but can be any real number.
Additionally there might by some comment line starting with # in between the file.
Problem Statement: I want to eliminate the first dip in Time values and smooth out using some quadratic or cubic or polynomial interpolation [please notice the first change from 5->2 --->8. I want to replace these numbers to intermediate values giving a gradual/smooth increase from 5--->8].
And I wish this to be done for all the combinations of Elements and States.
Is this possible through some sort of coding in Matlab etc ?
Any Pointers will be helpful !!
Thanks in advance :)
You can use the interp1 function for 1D-interpolation. The syntax is
yi = interp1(x,y,xi,method)
where x are your original coordinates, y are your original values, xi are the coordinates at which you want the values to be interpolated at and yi are the interpolated values. method can be 'spline' (cubic spline interpolation), 'pchip' (piece-wise Hermite), 'cubic' (cubic polynomial) and others (see the documentation for details).
You have alot of options here, it really depends on the nature of your data, but I would start of with a simple moving average (MA) filter (which replaces each data point with the average of the neighboring data points), and see were that takes me. It's easy to implement, and fine-tuning the MA-span a couple of times on some sample data is usually enough.
http://www.mathworks.se/help/curvefit/smoothing-data.html
I would not try to fit a polynomial to the entire data set unless I really needed to compress it, (but to do so you can use the polyfit function).
I have one big matrix of for example 3000X300. And I need to select each element and do several calculations with it. I looked into using the array fun function but because the output of my program is not one value this is not possible.
It works fine now with the loops but it has to preform much faster, so i want to remove the for loop.
Maybe i'll try to be more specific: Each value of the big matrix has to give me an answer of 4 different matrices with the size of 4X6020..
So i don't know if this is possible making this vectorized...
Maybe somebody has other suggestions to make it faster?
greetings,
You can use arrayfun and set uniformoutput to false. See here.