This question already has answers here:
Common way to generate finite geometric series in MATLAB
(2 answers)
Closed 7 years ago.
How to calculate the first N terms of the geometric sequence Un = 2^n in Matlab?
Are there any Matlab functions that I'm not aware of to facilitate this? or do I have to pick a math book to understand this and implement it in a for loop or something?
Any links to similar Matlab code would be appreciated, or if you could explain it for me that would be appreciated!
First, you set the N terms for your sequence, i.e.:
N = 10 %//set first 10
Now you want to make a vector from 1 to N, i.e.:
n= [1:N]
Un = 2.^n %//Note the dot is very important! I almost forgot
%//ans = [2,4,8,16...1024]
This would make function a vector of 1 by N where each element is the corresponding answer to your function.
for your second question (in comment)
you want to do something like:
Bflip = B' %//This flips the matrix B so that what use to be column is now rows
So Bflip would be the result you want, I tested with your example:
A = [2 2 2;4 4 4; 6 6 6];
B = [0 0 0; 1 1 1; 2 2 2];
Bflit = [ 0 1 2
0 1 2
0 1 2]
This will generate a 3 dimension matrix. To call on each of the 4 sets of results, just do something like result1 = permutation(:,:,1)
Related
So if I have a matrix s;
s = [4;5;9;12;3]
and I want to calculate the difference between an entry and it's previous entry plus add the previous difference such that I'll get
s = [ 4 0; 5 1; 9 5; 12 8; 3 -1]
I'm quite new to matlab. I understand a for loop would be required to go through the original matrix
The second column of your result seems to be essentially cumsum(diff(s)). However, that's not "the difference between an entry and its previous entry plus the previous difference"; it's the cumulative sum of differences.
So, if what you want in the second column is the cumulative sum of differences:
result = [s [0; cumsum(diff(s))]];
In matlab you have a lot of functions for working directly with matrix, the one that feeds here is diff and cumsum please visit the matlab documentation, and the functions for concatening like horzcat or vertcat int his case manually to get what you need work like this:
>> s = [4;5;9;12;3]
s =
4
5
9
12
3
Get the vector my_cum_diff which is the difference between elements in a vector
my_cum_diff = [0; cumsum(diff(s))]
my_cum_diff = [0; cumsum(diff(s))]
my_cum_diff =
0
1
5
8
-1
finally concat the two vectors
final_s=[s my_cum_diff]
final_s =
4 0
5 1
9 5
12 8
3 -1
This question already has answers here:
adding values to diagonals of matrix using element-wise addition in matlab
(3 answers)
Closed 7 years ago.
I have an (2n-1)-by-1 vector with certain values and I want to obtain an n-n matrix with the diagonals filled using the same value.
Eg. if I have
a = [1; 2; 3; 4; 5];
I want to obtain
A = [[3 4 5];[2 3 4];[1 2 3]]
= 3 4 5
2 3 4
1 2 3
My matrix dimensions are a lot bigger so I'd want this as efficient as possible. I already found following solutions:
n = 3;
A = toeplitz(a);
A = A(1:n,end-n+1:end)
and
A = a(n)*eye(n);
for j=1:n-1
A(1+j:n+1:end-j*n) = a(n-j);
A(j*n+1:n+1:end) = a(n+j);
end
I wonder if there are more efficient ways to obtain this result, keeping in mind that I am working with huge matrices and really need the speed.
ix=bsxfun(#plus,[1:n],[n-1:-1:0]'); %generate indices
A=a(ix);
or
A=hankel(a) %might be faster than toeplitz because half the matrix is zero
A(n:-1:1,1:n)
here is what hankel does internally (at least in ML R2013a), adapted to this problem:
c=[1:n];
r=[n-1:-1:0]';
idx=c(ones(n,1),:)+r(:,ones(n,1));
A=a(ix);
I guess the bsxfun solution and what thewaywewalk supposed is the fastest (it's basically the same)
Go with:
n = (numel(a)+1)/2;
A = a(bsxfun(#minus, n+1:n+n, (1:n).'));
This question already has answers here:
Element-wise array replication according to a count [duplicate]
(4 answers)
Closed 8 years ago.
I would like to vectorize the creation of the following vector:
For example-
Let A be a vector [5 3 2 1]
And let B be a vector [1 2 3 4]
I would like C to be the vector [1 1 1 1 1 2 2 2 3 3 4]
Meaning- each element i in B is duplicated A(i) times in C.
I haven't found a way to vectorize the creation of this, any ideas?
Thanks in advance!
Ronen
Approach #1
Here's one approach if B doesn't have any zeros -
C = nonzeros(bsxfun(#times,bsxfun(#le,[1:max(A)]',A),B))
Approach #2
A general case solution -
mask = bsxfun(#le,[1:max(A)]',A) %//'
B_ext = bsxfun(#times,mask,B)
C = B_ext(mask)
Approach #3
cumsum based approach and must be pretty efficient one -
idx = [1 cumsum(A(1:end-1))+1] %// indices where each new B values start
C = zeros(sum(A),1) %// storage for output
C(idx) = diff([0 B]) %// put those values, but offseted
C = cumsum(C) %// finally get the output
This question already has answers here:
Vector norm of an array of vectors in MATLAB
(4 answers)
Closed 5 years ago.
I have an input matrix that has 3 rows and 1000 columns. Each column represents and x, y, z variable. I want to find the magnitude of each column and store that in an output matrix that has 1 row and 1000 columns.
This is my current attempt but it doesn't seem to be working:
output(1,:) = norm(input(3,:));
my input matrix looks like:
x1, x2,...,x1000
y1, y2,...,y1000
z1, z2,...,z1000
I want my output matrix to look like:
[magnitude(x1,y1,z1), magnitude(x2,y2,z2),...,magnitude(x1000,y1000,z1000)]
Any help would be greatly appreciated.
norm(input(3,:)) will give you the norm of the 1000 elements of the third row.
Easy solution is to just run a for loop.
output = zeros(1,1000); %Preallocate space
for i = 1:length(output)
output(i) = norm(input(:, i));
end
MATLAB's norm function only works for single vectors. Let A be the name of the matrix which columns you want to find the norm to. Then this command does the job:
norm_A = sqrt(sum(A.*A));
Here is an example:
>> A = [1:5; 1:5; 1:5]
A =
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
>> norm_A = sqrt(sum(A.*A))
norm_A =
1.7321 3.4641 5.1962 6.9282 8.6603
This question already has answers here:
Get the indices of the n largest elements in a matrix
(4 answers)
Closed 8 years ago.
If I have a matrix like this:
sample = [1 0.21852382 0.090085552 0.219984954 0.446286385;
0.21852382 1 0.104580323 0.138429617 0.169216538;
0.090085552 0.104580323 1 0.237582739 0.105637177;
0.219984954 0.138429617 0.237582739 1 0.192753169;
0.446286385 0.169216538 0.105637177 0.192753169 1 ]
I want to find the top 3 max values in every rows in Matlab.
what i do in Matlab?
and is it true? i want to find top-N method in select neighbors.
I would recommend rewording your question. You say you want the top ten max values in every row, but the matrix you gave has only five columns :/
I think that what you are looking for is something like this.
sample = [1 0.21852382 0.090085552 0.219984954 0.446286385;
0.21852382 1 0.104580323 0.138429617 0.169216538;
0.090085552 0.104580323 1 0.237582739 0.105637177;
0.219984954 0.138429617 0.237582739 1 0.192753169;
0.446286385 0.169216538 0.105637177 0.192753169 1 ]
B = sort(sample,2,'descend') % will sort the rows of the array in descending order
C = B(:,1:N) % Select the top N values.
Hope this answers your question.
If that isn't what you want, try [Y,I] = max(matrix,[],desired_dimension) where Y and an array of the is the actual max values (e.g. [1 1 1 1 1]) and I is the index of the max values, (e.g [1 2 3 4 5])
EDIT
If desired_output = [1 1 1 1 1]', (a column vector, note transpose), then the command to do that is max(matrix,[],2) to operate along the second dimension. This behavior is defined in help max.