How to generate all numbers randomly in the limit [m,n]. To generate all numbers from 6 to 12.. ie., the sequence must be like [7 12 11 9 8 10 6].
r = randi([6 12],1,7);
But this gives the result:
[12 11 12 7 9 10 12]
Here the numbers are repeated and the sequence does not contain all numbers from 6 to 12.
You can use randperm to make a list of random numbers between 1 and n (where n is the length of your vector), and use that to permute the vector.
v=6:12;
n=length(v);
I=randperm(n);
v(I)
Assuming you are sampling using a uniform distribution.
r = datasample(6:12,7,'Replace',false)
In a nutshell this does a random sampling without replacement, hence you get all the values from your original population in a random order.
I am reading in images with imread which results in 768x1024x3 matrix with R,G,B values of each pixel.
I have a function that takes in an image and returns matrix of segment labels for each pixel so this matrix is 768x1024. the labels are just numbers 1,2,3,4 depending on how many different segments the function finds.
Now I want to calculate the average Red, Green and Blue value in each segment of the image. So I want to use the indices from the segment label matrix to find group all R,G,B values into separate arrays and then be able to calculate the mean.
Is there any smart way to do this? use the indices of each 1 value in the segment matrix to get the values from the imread matrix and group the segments into different arrays? I though of using for loops and brute force through this but is there a better way to do this?
Here's a code that you will get you everything without looping.
Code
%// img is your input RGB image (NxMx3)
%// L is your label matrix (NxM)
t1 = bsxfun(#eq,L,permute(unique(L),[3 2 1]));
t2 = bsxfun(#times,permute(img,[ 1 2 4 3]),t1);
t2(t2==0)=nan;
out = squeeze(nanmean(nanmean(t2)))
%// out is the desired output matrix that is (NLx3),
%// where NL is the number of labels. Thus, the mean of labels is
%// along the rows and the corresponding values for R, G and B are in the three
%// columns of it.
Explanation
Let's test out with some random values for img -
img = randi(9,3,4,3)
Giving us -
img(:,:,1) =
9 7 5 3
7 7 2 4
1 6 7 9
img(:,:,2) =
8 6 6 4
4 9 3 9
3 9 8 1
img(:,:,3) =
5 4 4 5
7 2 5 3
2 3 1 3
Some assumed values for L that goes from 1 to 8
L = [1 3 3 4;
4 5 8 8;
5 6 7 2]
The code output is -
out =
9 8 5
9 1 3
6 6 4
5 4 6
4 6 2
6 9 3
7 8 1
3 6 4
Let's see how to make sense of the output.
Looking at the input, let's choose the label 8, which is at locations (2nd row,3rd col) and (2nd row,4th col). The corresponding R values at these locations in img are [2 4], and thus the R mean/average value must be 3. Similarly for G it must be from [3 9], that is 6 and again for B would be from [5 3], that is 4.
Let's look at the 8th row of out that represents the label-8, we have [3 6 4], which are the mean values as calculated earlier. Similarly other mean values could be interpreted from out.
Edited to handle all channels at once.
Let img be your RGB image and labels the labels array.
You can mask the RGB image with the labels like this:
% create a 3-channels mask:
labelsRGB=repmat(labels, 1, 1, 3);
Segment1=img.*(labelsRGB==1);
The average values in the segment labeled as 1 is then:
avg=mean(mean(Segment1, 1), 2);
Get the average for re in avg(1), the average for green in avg(2), etc.
Idem for the other segments.
Here goes a general alternative.
In this case you do not need to loop over the different segments to get the average of each.
%simulated image and label
img=rand(10,12,3);
labeled=[ones(10,3),ones(10,3)*2,ones(10,3)*3,ones(10,3)*4];
% actual code for the mean
red_mean = regionprops(labeled, img(:,:,1), 'MeanIntensity')
I'm doing a curve fitting problem in Matlab and so far I've set up some orthonormal polynomials along a specified range of x-values with x = (0:0.0001:40);
The polynomials themselves are each a manipulation of that x vector and are stored as a row in a matrix. I also have some have data entries in the form of two vectors - one for the data x-coords and one for the actual values. I need a way to use the x-coords of my data points to find the same values in my continuous x-vector and then take the corresponding columns from my polynomial matrix and add them to a new matrix.
EDIT: To be more clear. I have, for example:
x = [0 1 2 3 4 5]
Polynomial =
1 1 1 1 1 1
0 1 2 3 4 5
0 1 4 9 16 25
% Data values:
x-coord = [1 3 4]
values = [5 3 8]
I want to check the x-coord values against 'x' to find the corresponding columns and then pull out those columns from the polynomial matrix to get:
Polynomial =
1 1 1
1 3 4
1 9 16
If your x, Polynomial, and xcoord are the same length you could use logical indexing which is elegant; something along the lines of Polynomial(x==xcoord). But since this doesn't seem to be the case, there's a less fancy solution with a for-loop and find(xcoord(i)==x)
I have a vector of values which represent an index of a row to be removed in some matrix M (an image). There's only one row value per column in this vector (i.e. if the image is 128 x 500, my vector contains 500 values).
I'm pretty new to MATLAB so I'm unsure if there's a more efficient way of removing a single pixel (row,col value) from a matrix so I've come here to ask that.
I was thinking of making a new matrix with one less row, looping through each column up until I find the row whose value I wish to remove, and "shift" the column up by one and then move onto the next column to do the same.
Is there a better way?
Thanks
Yes, there is a solution which avoids loops and is thus faster to write and to execute. It makes use of linear indexing, and exploits the fact that you can remove a matrix entry by assigning it an empty value ([]):
% Example data matrix:
M = [1 5 9 13 17
2 6 10 14 18
3 7 11 15 19
4 8 12 16 20];
% Example vector of rows to be removed for each column:
vector = [2 3 4 1 3];
[r c] = size(M);
ind = sub2ind([r c],vector,1:c);
M(ind) = [];
M = reshape(M,r-1,c);
This gives the result:
>> M =
1 5 9 14 17
3 6 10 15 18
4 8 11 16 20
I would like to ask a question about Matlab program.
I have vector a
a = [1 2 3 4 5 6 7 8 9 10 11 12];
I would like to convert vector a to 2D array. Normally, I use this code to convert it.
m =1;
for i=1:4
for j=1:3
b(i,j) = a(m);
m=m+1;
end
end
Then b is a 2D matrix.
b =
1 2 3
4 5 6
7 8 9
10 11 12
Anybody, have an idea to convert 1D to 2D without using loop.
Thanks,
Check out the reshape function and help page.
In particular,
B = reshape(A,m,n)
returns the m-by-n matrix B whose elements are taken column-wise from A. An error results if A does not have m*n elements.
Note that it is column-wise, so I suggest you make a matrix with 3 rows and 4 columns and then tip it on its side (A.' will take the transpose of a matrix).