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)));
Related
I need to (repeatedly) build a vector of length 200 from a vector of length 2500. I can describe this operation using multiplication by a matrix which is extremely sparse: it is 200x2500 and has only one entry in each row. But I have very little control over where this entry is. My actual problem is that I need to apply this matrix not to the vector that I currently have, but rather to some componentwise function of this vector. Since I have all this sparsity, it is wasteful to apply this componentwise function to all 2500 components of my vector. Instead I would rather apply it only to the 200 components that actually contribute.
A program (with randomly chosen numbers replacing of my actual numbers) which would have a similar problem would be something like this:
ind=randi(2500,200,1);
coefficients=randn(200,1);
A=sparse(1:200,ind,coefficients,200,2500);
x=randn(2500,1);
y=A*subplus(x);
What I don't like here is applying subplus to all of x; I would rather only have to apply it to x(ind), since only that contributes to the matrix product.
Right now the only way I can see to work around this is to replace my sparse matrix with a 200-component vector of coefficients and a 200-component vector of indices. Working this way, the code above would become:
ind=randi(2500,200,1);
coefficients=randn(200,1);
x=randn(2500,1);
y=coefficients.*subplus(x(ind))
Is there a better way to do this, preferably one that would work when A contains a few elements per row instead of just one?
The code in your question throws an exception, I think it should be:
n=2500;
m=200;
ind=randi(n,m,1);
coefficients=randn(m,1);
A=sparse(1:m,ind,coefficients,m,n);
x=randn(n,1);
Your idea using x(ind) was basically right, but ind would reorder x which is not intended. Instead you could use sort(unique(ind)). I opted to use the sparse logical index any(A~=0) because I expect it to be faster, but you could compare both versions.
%original code
y=A*subplus(x);
.
%multiplication using sparse logical indexing:
relevant=any(A~=0);
y=A(:,relevant)*subplus(x(relevant));
.
%fixed version of your code
relevant=sort(unique(ind));
y=A(:,relevant)*subplus(x(relevant));
I have the results from an iterative process, where the results from each iteration is placed beside eachother, like this:
res =
43.7826 38.8460 38.6889 38.6912 38.6915
107.0735 98.5577 98.1212 98.1170 98.1175
-134.6218 -131.6938 -131.5378 -131.5352 -131.5352
-105.9498 -103.1403 -102.9195 -102.9139 -102.9139
What I want to do is create one matrix that shows the difference between each column, and one matrix that shows the percentage change from one column to the next.
This is obviously simple to do using loops, but is there a clever way to do this without loops (maybe using some built-in Matlab functions)?
Thanks.
The command diff(...) performes the difference:
diff_res = diff(res,1,2)
in this case the difference of the first order in the second dimension (columns).
After you can compute the percentage:
per_res = diff_res(:,1:4)./res(:,1:4).*100
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).
What is the difference between hist and imhist functions in Matlab? I have a matrix of color levels values loaded from image with imread and need to count entropy value of the image using histogram.
When using imhist the resulting matrix contains zeros in all places except the last one (lower-right) which contains some high value number (few thousands or so).
Because that output seems to be wrong, I have tried to use hist instead of imhist and the resulting values are much better, the matrix is fulfilled with correct-looking values instead of zeros.
However, according to the docs, imhist should be better in this case and hist should give weird results..
Unfortunately I am not good at Matlab, so I can not provide you with better problem description. I can add some other information in the future, though.
So I will try to better explain my problem..I have an image, for which I should count entropy and few other values (how much bytes it will take to save that image,..). I wrote this function and it works pretty well
function [entropy, bytes_image, bytes_coding] = entropy_single_pixels(im)
im = double(im);
histg = hist(im);
histg(histg==0) = [];
nzhist = histg ./ numel(im);
entropy = -sum(nzhist.*log2(nzhist));
bytes_image = (entropy*(numel(im))/8);
bytes_coding = 2*numel(unique(im));
fprintf('ENTROPY_VALUE:%s\n',num2str(entropy));
fprintf('BYTES_IMAGE:%s\n',num2str(bytes_image));
fprintf('BYTES_CODING:%s\n',num2str(bytes_coding));
end
Then I have to count the same, but I have to make "pairs" from pixels which are below each other. So I have only half the rows and the same count of columns. I need to express every unique pixel pair as a different number, so I multiplied the first one by 1000 and added the second one to it... Subsequently I need to actually apply the same function as in the first example, but that is the time, when I am getting weird numbers from the imhist function. When using hist, it seems to be OK, but I really don't think that behavior is correct, so that must be my error somewhere. I actually understand pretty good, to what I want to do, or at least I hope so, but unfortunately Matlab makes all that kind of hard for me :)
hist- compute histogram(count number of occurance of each pixel) in color image.........
imhist- compute histogram in two dimensional image.
Use im2double instead of double if you want to use imhist. The imhist function expects double or single-precision data to be in the [0,1] data range, which is why you see everything in the last bin of the histogram.
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.