I have a 15 * 2 array where the first column represents the area and the second column represents the corresponding circularity to the 15 objects.
I need to select the row with maximum area while applying the following condition for the circularity to be > 0.9 and <= 1.2
Example:
Area Circularity
----- -----------
22041 1.1703
23458 2.8425
155 1.4165
37 2.1089
215 1.5692
41 1.0549
659 1.7144
64 1.0508
3 0.3092
584 1.2543
26 1.1132
396 2.9046
1 0
3 0.8488
4 0.4638
Expected Result:
22041 1.1703
You can apply your conditional to the second column to check if it is in the range (0.9 1.2] and then multiply the resulting logical array with the first column. Since false will be treated as 0 and true will be treated as 1, this will zero-out the values in the first column that don't meet the criteria for the second column. You can then use the second output of max to get the row that contains the maximum value
[~, ind] = max(data(:,1) .* (data(:,2) > 0.9 & data(:,2) <= 1.2));
result = data(ind,:)
Related
How can I randomize and generate numbers from 0-50 in matrix of 5x5 with SUM or each row printed on the right side?
+
is there any way to give weight to individual numbers before generating the numbers?
Please help
Thanks!
To generate a random matrix of integers between 0 and 50 (sampled with replacement) you could use
M = randint(5,5,[0,50])
To print the matrix with the sum of each row execute the following command
[M sum(M,2)]
To use a different distribution there are a number of techniques but one of the easiest is to use the datasample function from the Statistics and Machine Learning toolbox.
% sample from a truncated Normal distribution. No need to normalize
x = 0:50;
weights = exp(-0.5*(x-25).^2 / 5^2);
M = reshape(datasample(x,25,'Weights',weights),[5,5])
Edit:
Based on your comment you want to perform random sampling without replacement. You can perform such a random sampling without replacement if the weights are non-negative integers by simulating the classic ball-urn experiment.
First create an array containing the appropriate number of each value.
Example: If we have the values 0,1,2,3,4 with the following weights
w(0) = 2
w(1) = 3
w(2) = 5
w(3) = 4
w(4) = 1
Then we would first create the urn array
>> urn = [0 0 1 1 1 2 2 2 2 2 3 3 3 3 4];
then, we would shuffle the urn using randperm
>> urn_shuffled = urn(randperm(numel(urn)))
urn_shuffled =
2 0 4 3 0 3 2 2 3 3 1 2 1 2 1
To pick 5 elements without replacement we would simple select the first 5 elements of urn_shuffled.
Rather than typing out the entire urn array, we can construct it programatically given an array of weights for each value. For example
weight = [2 3 5 4 1];
urn = []
v = 0
for w = weight
urn = [urn repmat(v,1,w)];
v = v + 1;
end
In your case, the urn will contain many elements. Once you shuffle you would select the first 25 elements and reshape them into a matrix.
>> M = reshape(urn_shuffled(1:25),5,5)
To draw random integer uniformly distributed numbers, you can use the randi function:
>> randi(50,[5,5])
ans =
34 48 13 28 13
33 18 26 7 41
9 30 35 8 13
6 12 45 13 47
25 38 48 43 18
Printing the sum of each row can be done by using the sum function with 2 as the dimension argument:
>> sum(ans,2)
ans =
136
125
95
123
172
For weighting the various random numbers, see this question.
I am a novice at Matlab and am struggling a bit with creating a loop that will a convert a 283080 x 2 matrix - column 1 lists all stockID numbers (each repeated 60 times) and column 2 contains all lagged monthly returns (60 observations for each stock) into a 60 x 4718 matrix with a column for each stockID and its corresponding lagged returns falling in 60 rows underneath each ID number.
My aim is to then try to calculate a variance-covariance matrix of the returns.
I believe I need a loop because I will be repeating this process over 70 times as I have multiple data sets in this same current format
Thanks so much for the help!
Let data denote your matrix. Then:
aux = sortrows(data,1); %// sort rows according to value in column 1
result = reshape(aux(:,2),60,[]); %// reshape second column as desired
If you need to insert the stockID values as headings (first row of result), add this as a last line:
result = [ unique(aux(:,1)).'; result ];
A simple example, replacing 60 by 2:
>> data = [1 100
2 200
1 101
2 201
4 55
3 0
3 33
4 56];
>> aux = sortrows(data,1);
>> result = reshape(aux(:,2),2,[])
>> result = [ unique(aux(:,1)).'; result ];
result =
1 2 3 4
100 200 0 55
101 201 33 56
This question is an outgrowth of MatLab (or any other language) to convert a matrix or a csv to put 2nd column values to the same row if 1st column value is the same?
If
A = [2 3 234 ; 2 44 33; 2 12 22; 3 123 99; 3 1232 45; 5 224 57]
1st column | 2nd column | 3rd column
2 3 234
2 44 33
2 12 22
3 123 99
3 1232 45
5 224 57
then running
[U ix iu] = unique(A(:,1) );
r= accumarray( iu, A(:,2:3), [], #(x) {x'} )
will show me the error
Error using accumarray
Second input VAL must be a vector with one element for each row in SUBS, or a
scalar.
I want to make
1st col | 2nd col | 3rd col | 4th col | 5th col | 6th col| 7th col
2 3 234 44 33 12 22
3 123 99 1232 45
5 224 57
I know how to do it using for and if, but that spends too much time for big data.
How can I do this?
Thank you in advance!
You're misusing accumarray in the solution provided to your previous question. The first parameter iu is the vector of indices and the second parameter should be a vector of values, of the same length. What you did here is specify a matrix as the second parameter, which in fact has twice more values than indices in iu.
What you need to do in order to make it work is create a vector of indices both for the second column and for the third column (they are the same indices, not coincidentally!) and specify a matching column vector of values, like so:
[U, ix, iu] = unique(A(:,1));
vals = reshape(A(:, 2:end).', [], 1); %'// Columnize values
subs = reshape(iu(:, ones(size(A, 2) - 1, 1)).', [], 1); %'// Replicate indices
r = accumarray(subs, vals, [], #(x){x'});
This solution is generalized for any number of columns that you want to pass to accumarray.
I want to calculate the sum of the elements surrounding a given element in a matrix. So far, I have written these lines of code:
for i=1:m,
rij(1:n)=0
for j=1:n,
alive = tijdelijk(i-1,j)+tijdelijk(i+1,j)+tijdelijk(i-1,j-1)+tijdelijk(i+1,j-1)+tijdelijk(i,j+1)+tijdelijk(i,j-1)+tijdelijk(i-1,j+1)+tijdelijk(i+1,j+1)
This results in an error because, for example, i-1 becomes zero for i=1. Anyone got an idea how to do this without getting this error?
You can sum the elements via filtering. conv2 can be used for this manner.
Let me give an example. I create a sample matrix
>> A = reshape(1:20, 4, 5)
A =
1 5 9 13 17
2 6 10 14 18
3 7 11 15 19
4 8 12 16 20
Then, I create a filter. The filter is like a mask where you put the center on the current cell and the locations corresponding to the 1's on the filter are summed. For eight-connected neighbor case, the filter should be as follows:
>> B = [1 1 1; 1 0 1; 1 1 1]
B =
1 1 1
1 0 1
1 1 1
Then, you simply convolve the matrix with this small matrix.
>> conv2(A, B, 'same')
ans =
13 28 48 68 45
22 48 80 112 78
27 56 88 120 83
18 37 57 77 50
If you want four-connected neighbors, you can make the corners of your filter 0. Similarly, you can design any filter for your purpose, such as for averaging all neighbors instead of summing them.
For details, please see the convolution article in Wikipedia.
Two possibilities : change the limits of the loops to i=k:(m-k) and j=k:(n-k) or use blkproc
ex :
compute the 2-D DCT of each 8-by-8 block
I = imread('cameraman.tif');
fun = #dct2;
J = blkproc(I,[8 8],fun);
imagesc(J), colormap(hot)
There are lots of things you can do at the edges. Which you do depends very specifically on your problem and is different from usage case to usage case. Typical things to do:
If (i-1) or (i+1) is out of range, then just ignore that element. This is equivalent to zero padding the matrix with zeros around the outside and adjusting the loop limits accordingly
Wrap around the edges. In other words, for an MxN matrix, if (i-1) takes you to 0 then instead of taking element (i-1, j) = (0, j) you take element (M, j).
Since your code mentions "your teacher" I'd guess that you can ask what should happen at the edges (or working it out in a sensible manner may well be part of the task!!).
I have a challenge to order my matrix. The provided functions like sortrows work in the opposite way...
Take this 2D matrix
M =
40 45 68
50 65 58
60 55 48
57 67 44
,
The objective is to find matrix O that indicates the sorting index (rank) per row, i.e.:
O =
1 2 3
1 3 2
3 2 1
2 3 1
.
So for the second row 50 is the smallest element (1), 65 the largest (3), and 58 is the second largest (2), therefore row vector [1 3 2].
[~,sorted_inds] = sort(M,2);
will do.
I think you're looking for the second output of the regular sort function:
[~,I] = sort(M,2)
This syntax supresses the actual sorted matrix Msorted, and returns the indices I such that
for j = 1:n, Msorted(j,:) = M(I(j,:),j); end
Type doc sort for more information.