Starting wish a 7x4 binary matrix I need to change a random bit in each column to simulate error. Have been trying to no avail.
A very straightforward way to do this is to use a for loop. It might not be the most efficient approach in MATLAB, but it's probably good enough considering your data set is so small.
Iterate through each of the four columns. On each iteration, randomly chose a number from 1 to 7 to represent the row in that column that you have selected to change. Finally, flip the bit at that row/column. The following code does just this. Assume that "A" is a binary matrix with 7 rows and 4 columns
for col=1:4; %// Iterate through each column
row = ceil(7*rand()); %// Randomly chose a number from 1 to 7 to represent row
A(row,col) = ~A(row,col); %// Flip the bit at the specified row/col
end
Another possibility is to create 4 random numbers in one call, and assign in a vectorized fashion:
rowNumbers = randi(4,[1 4])
A(rowNumbers,:) = ~A(rowNumbers,:);
Related
I have a 5-by-200 matrix where the i:50:200, i=1:50 are related to each other, so for example the matrix columns 1,51,101,151 are related to each other, and columns 49,99,149,199 are also related to each other.
I want to use a for-loop to create another matrix that re-sorts the previous matrix based on this relationship.
My code is
values=zeros(5,200);
for j=1:50
for m=1:4:200
a=factor_mat(:,j:50:200)
values(:,m)=a
end
end
However, the code does not work.
Here's what's happening. Let's say we're on the first iteration of the outer loop, so j == 1. This effectively gives you:
j = 1;
for m=1:4:200
a=factor_mat(:,j:50:200)
values(:,m)=a;
end
So you're creating the same submatrix for a (j doesn't change) 50 times and storing it at different places in the values matrix. This isn't really what you want to do.
To create each 4-column submatrix once and store them in 50 different places, you need to use j to tell you which of the 50 you're currently processing:
for j=1:50
a=factor_mat(:,j:50:200);
m=j*4; %// This gives us the **end** of the current range
values(:,m-3:m)=a;
end
I've used a little trick here, because the indices of Matlab arrays start at 1 rather than 0. I've calculated the index of the last column we want to insert. For the first group, this is column 4. Since j == 1, j * 4 == 4. Then I subtract 3 to find the first column index.
That will fix the problem you have with your loops. But loops aren't very Matlab-ish. They used to be very slow; now they're adequate. But they're still not the cool way to do things.
To do this without loops, you can use reshape and permute:
a=reshape(factor_mat,[],50,4);
b=permute(a,[1,3,2]);
values=reshape(b,[],200);
I'm struggling with one of my matlab assignments. I want to create 10 different models. Each of them is based on the same original array of dimensions 1x100 m_est. Then with for loop I am choosing 5 random values from the original model and want to add the same random value to each of them. The cycle repeats 10 times chosing different values each time and adding different random number. Here is a part of my code:
steps=10;
for s=1:steps
for i=1:1:5
rl(s,i)=m_est(randi(numel(m_est)));
rl_nr(s,i)=find(rl(s,i)==m_est);
a=-1;
b=1;
r(s)=(b-a)*rand(1,1)+a;
end
pert_layers(s,:)=rl(s,:)+r(s);
M=repmat(m_est',s,1);
end
for k=steps
for m=1:1:5
M_pert=M;
M_pert(1:k,rl_nr(k,1:m))=pert_layers(1:k,1:m);
end
end
In matrix M I am storing 10 initial models and want to replace the random numbers with indices from rl_nr matrix into those stored in pert_layers matrix. However, the last loop responsible for assigning values from pert_layers to rl_nr indices does not work properly.
Does anyone know how to solve this?
Best regards
Your code uses a lot of loops and in this particular circumstance, it's quite inefficient. It's better if you actually vectorize your code. As such, let me go through your problem description one point at a time and let's code up each part (if applicable):
I want to create 10 different models. Each of them is based on the same original array of dimensions 1x100 m_est.
I'm interpreting this as you having an array m_est of 100 elements, and with this array, you wish to create 10 different "models", where each model is 5 elements sampled from m_est. rl will store these values from m_est while rl_nr will store the indices / locations of where these values originated from. Also, for each model, you wish to add a random value to every element that is part of this model.
Then with for loop I am choosing 5 random values from the original model and want to add the same random value to each of them.
Instead of doing this with a for loop, generate all of your random indices in one go. Since you have 10 steps, and we wish to sample 5 points per step, you have 10*5 = 50 points in total. As such, why don't you use randperm instead? randperm is exactly what you're looking for, and we can use this to generate unique random indices so that we can ultimately use this to sample from m_est. randperm generates a vector from 1 to N but returns a random permutation of these elements. This way, you only get numbers enumerated from 1 to N exactly once and we will ensure no repeats. As such, simply use randperm to generate 50 elements, then reshape this array into a matrix of size 10 x 5, where the number of rows tells you the number of steps you want, while the number of columns is the total number of points per model. Therefore, do something like this:
num_steps = 10;
num_points_model = 5;
ind = randperm(numel(m_est));
ind = ind(1:num_steps*num_points_model);
rl_nr = reshape(ind, num_steps, num_points_model);
rl = m_est(rl_nr);
The first two lines are pretty straight forward. We are just declaring the total number of steps you want to take, as well as the total number of points per model. Next, what we will do is generate a random permutation of length 100, where elements are enumerated from 1 to 100, but they are in random order. You'll notice that this random vector uses only a value within the range of 1 to 100 exactly once. Because you only want to get 50 points in total, simply subset this vector so that we only get the first 50 random indices generated from randperm. These random indices get stored in ind.
Next, we simply reshape ind into a 10 x 5 matrix to get rl_nr. rl_nr will contain those indices that will be used to select those entries from m_est which is of size 10 x 5. Finally, rl will be a matrix of the same size as rl_nr, but it will contain the actual random values sampled from m_est. These random values correspond to those indices generated from rl_nr.
Now, the final step would be to add the same random number to each model. You can certainly use repmat to replicate a random column vector of 10 elements long, and duplicate them 5 times so that we have 5 columns then add this matrix together with rl.... so something like:
a = -1;
b = 1;
r = (b-a)*rand(num_steps, 1) + a;
r = repmat(r, 1, num_points_model);
M_pert = rl + r;
Now M_pert is the final result you want, where we take each model that is stored in rl and add the same random value to each corresponding model in the matrix. However, if I can suggest something more efficient, I would suggest you use bsxfun instead, which does this replication under the hood. Essentially, the above code would be replaced with:
a = -1;
b = 1;
r = (b-a)*rand(num_steps, 1) + a;
M_pert = bsxfun(#plus, rl, r);
Much easier to read, and less code. M_pert will contain your models in each row, with the same random value added to each particular model.
The cycle repeats 10 times chosing different values each time and adding different random number.
Already done in the above steps.
I hope you didn't find it an imposition to completely rewrite your code so that it's more vectorized, but I think this was a great opportunity to show you some of the more advanced functions that MATLAB has to offer, as well as more efficient ways to generate your random values, rather than looping and generating the values one at a time.
Hopefully this will get you started. Good luck!
X =
4 3
8 3
I want to extract the element in each row of X and do some operation on each of them separably (4,3) and (8,3). however the size of may be different based on some parameters in my code, so I want general formula to do such thing,
How I can use the for loop for solving this issue ?
This link shows how to extract specific lines (or columns) from a matrix http://www.mathworks.com/company/newsletters/articles/matrix-indexing-in-matlab.html
All you have to do is write a loop on an index ii to go through every line.
for ii=1:size(X,1)
a=myfun(X(ii,:));
end
I'm working with matrices in Matlab which have five columns and several million rows. I'm interested in picking particular groups of this data. Currently I'm doing this using plot3() and the brush/select data tool.
I plot the first three columns of the matrix as X,Y, Z and highlight the matrix region I'm interested in. I then use the brush/select tool's "Create variable" tool to export that region as a new matrix.
The problem is that when I do that, the remaining two columns of the original, bigger matrix are dropped. I understand why- they weren't plotted and hence the figure tool doesn't know about them. I need all five columns of that subregion though in order to continue the processing pipeline.
I'm adding the appropriate 4th and 5th column values to the exported matrix using a horrible nested if loop approach- if columns 1, 2 and 3 match in both the original and exported matrix, attach columns 4/5 of the original matrix to the exported one. It's bad design and agonizingly slow. I know there has to be a Matlab function/trick for this- can anyone help?
Thanks!
This might help:
1. I start with matrix 1 with columns X,Y,Z,A,B
2. Using the brush/select tool, I create a new (subregion) matrix 2 with columns X,Y,Z
3. I then loop through all members of matrix 2 against all members of matrix 1. If X,Y,Z match for a pair of rows, I append A and B
from that row in matrix 1 to the appropriate row in matrix 2.
4. I become very sad as this takes forever and shows my ignorance of Matlab.
If I understand your situation correctly here is a simple way to do it:
Assuming you have a matrix like so: M = [A B C D E] where each letter is a Nx1 vector.
You select a range, this part is not really clear to me, but suppose you can create the following:
idxA,idxB and idxC, that are 1 if they are in the region and 0 otherwise.
Then you can simply use:
M(idxA&idxB&idxC,:)
and you will get the additional two columns as well.
i am trying this code since last night but i cant understand what this code is doing. actually i am beginner in matlab programming
load('79.mat')
trainingData=d79;
colormap(gray);
colormap(grey);
x=reshape(d79(1234,:),28,28);
y = x(:,28:-1:1);
pcolor(y');
Kindly help me in understanding this code. :/
This is pretty simple. Here is a line-by-line explanation:
Loads data from a data file
Puts the loaded data into a variable named trainingData
Sets the colormap for plotting
Take the 1234th row of the loaded matrix, convert it into a 28-by-28 matrix, and store it in the variable x. So for example, on a smaller scale, [5 6 7 8] is converted to the matrix [5 7; 6 8] if you want to reshape that matrix to 2-by-2.
Reverse the column order of x and put that in y. So the last column becomes the first, second-last becomes second, etc.
This is a checkerboard plot of the values contained in y.
Edited to include more detail on lines 5 and 6:
The reshape line assumes that there is a row with number 1234, and that there are 784 (28*28) elements in that row. It takes that row, and makes a 28x28 matrix out of it, by taking the first 28 elements, making them into the first column of the new matrix, then taking the next 28 elements, making them the second column, and so on 26 more times. The final matrix is names x.
For the y line, like I said, it just reverses the columns of x, it puts the last column first, the second-last column second, and so on until the first column of the x is put as the last column of y.