I have two arrays threshold and values.
threshold=[10 22 97]
values=[99 23 77 11 8 10]
I want to output idx such that threshold(idx-1)<values(i)<=threshold(idx). That is for the above example output will be
output=[4 3 3 2 1 1]
The naive code that can produce above output will be
output=ones(1,length(values))*(length(values)+1);
for i=1:length(values)
for j=1:length(threshold)
if(values(i)>threshold(j))
output(i)=j;
end
end
end
Is there a simple way of doing it. I want to avoid loops.
You can use histc command, with a slight adjustment of threshold array
>> threshold=[-inf 10 22 97 inf];
>> values=[99 23 77 11 8 10];
>> [~, output] = histc( values, threshold+.1 )
output =
4 3 3 2 1 1
The modification of threshold is due to "less-than"/"less-than-equal" type of comparison for bin boundary decisions.
No loops often means you'll gain speed by increasing peak memory. Try this:
threshold = [10 22 97];
values = [99 23 77 11 8 10];
%// Do ALL comparisons
A = sum(bsxfun(#gt, values.', threshold));
%// Find the indices and the ones before
R = max(1, [A; A-1]);
%// The array you want
R(:).'
If you run out of memory, just use the loop, but then with a find replacing the inner loop.
Loops aren't all that bad, you know (if you have MATLAB > R2008). In theory, the solution above shouldn't even be faster than a loop with find, but oh well...profiling is key :)
Related
I have 2 vectors
A=[10 22 31 14 55 16 47 18];
B= [1 2 1 1 1 2 1 2];
I want to make a third vector C which contains values of A for values of B=1;
like
C=[10 NaN 31 14 55 NaN 47 NaN]
or
C=[10 31 14 55 47]
I did this using a for loop.
Just want to know if this is doable without using for loop as it may save a lot of computation time. (The vectors with me are really really large
for i=1:length (A);
if B(i)==1;
C(i)=A(i)
else C(i)=NaN;
end;
end;
use boolean logic for indexing. In your case, as you also suggest, you can do it with a simple
C = A(B==1);
For more complicated conditions, you can also use the function find(), as in
C = A(find(B==1));
or
C = nan(size(A));
C(find(B==1)) = A(find(B==1));
I have a matrix of 2d lets assume the values of the matrix
a =
17 24 1 8 15
23 5 7 14 16
4 6 13 20 22
10 12 19 21 3
17 24 1 8 15
11 18 25 2 9
This matrix is going to be divided into three different matrices randomly let say
b =
17 24 1 8 15
23 5 7 14 16
c =
4 6 13 20 22
11 18 25 2 9
d =
10 12 19 21 3
17 24 1 8 15
How can i know the index of the vectors in matrix d for example in the original matrix a,note that the values of the matrix can be duplicated.
for example if i want to know the index of {10 12 19 21 3} in matrix a?
or the index of {17 24 1 8 15} in matrix a,but for this one should return only on index value?
I would appreciate it so much if you can help me with this. Thank you in advance
You can use ismember with the 'rows' option. For example:
tf = ismember(a, c, 'rows')
Should produce:
tf =
0
0
1
0
0
1
To get the indices of the rows, you can apply find on the result of ismember (note that it's redundant if you're planning to use this vector for matrix indexing). Here find(tf) return the vector [3; 6].
If you want to know the number of the row in matrix a that matches a single vector, you either use the method explained and apply find, or use the second output parameter of ismember. For example:
[tf, loc] = ismember(a, [10 12 19 21 3], 'rows')
returns loc = 4 for your example. Note that here a is the second parameter, so that the output variable loc would hold a meaningful result.
Handling floating-point numbers
If your data contains floating point numbers, The ismember approach is going to fail because floating-point comparisons are inaccurate. Here's a shorter variant of Amro's solution:
x = reshape(c', size(c, 2), 1, []);
tf = any(all(abs(bsxfun(#minus, a', x)) < eps), 3)';
Essentially this is a one-liner, but I've split it into two commands for clarity:
x is the target rows to be searched, concatenated along the third dimension.
bsxfun subtracts each row in turn from all rows of a, and the magnitude of the result is compared to some small threshold value (e.g eps). If all elements in a row fall below it, mark this row as "1".
It depends on how you build those divided matrices. For example:
a = magic(5);
d = a([2 1 2 3],:);
then the matching rows are obviously: 2 1 2 3
EDIT:
Let me expand on the idea of using ismember shown by #EitanT to handle floating-point comparisons:
tf = any(cell2mat(arrayfun(#(i) all(abs(bsxfun(#minus, a, d(i,:)))<1e-9,2), ...
1:size(d,1), 'UniformOutput',false)), 2)
not pretty but works :) This would be necessary for comparisons such as: 0.1*3 == 0.3
(basically it compares each row of d against all rows of a using an absolute difference)
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'm trying to monitor the average temperature in a fabrication every hour to ensure quality control. How can I write a script that looks at the temperature inside the plant as a function of time, and outputs the times when the temperature drops below 10 degrees Celsius and when the temperature is above 80 degrees Celsius. My script should say when the temperature is out of the boundary and what the temperature is. I wanna Use the following data:
Temperature = [-15 -5 5 15 24 33 42 51 59 66 73 79 85 90 78]
The first measurement is made at 5am, the last measurement is made at 7pm. I wanna display the time in a 24 hour system instead of a 12 hour system.
It looks like you'll need to loop through the elements of the Temperature vector and find which ones are either below 10 degrees OR above 80 degrees. In a traditional programming language you would use a FOR loop to go through the elements of an array or vector, but generally in MATLAB you want to avoid FOR loops if you can and instead take advantage of MATLAB's vectorization, because it's much faster.
You'll want to look into the FIND function (type 'help find' into the console for more information). But, for example if I had a vector:
A = [0 1 2 1 2 1 1 0];
And used
find(A==0)
The output would be a vector of the indices of A where the element is equal to 0:
[1 8]
I could similarly do:
find(A==1 & A==0)
And I would get
[1 2 4 6 7 8]
This is useful because while traditionally you access the elements of a vector with an index, you can access the elements of a vector in MATLAB with another vector. For example:
>> A = [-10 4 -2 3];
>> ind = [2 3];
>> A(ind)
ans =
4 -2
MATLAB also makes the syntax a bit easier, because you can use the following shortcut instead of explicitly using the FIND function:
>> A = [-10 4 -2 3];
>> A( A<-5 | A>3)
ans =
-10 4
Which would be the same as using the FIND function:
>> A(find(A<-5 | A>3))
ans =
-10 4
I hope this helps. Sorry for the long post. It takes some time to get used to MATLAB's vectorized way of writing code, but once you do get used to it, you'll find it's very useful for computation.
You could crate a 'time' vector like this:
time = 5:1:19;
I want to get a vector of elements of a Matlab matrix at predefined locations. For example, I have the following
>> i = [1,2,3];
>> j = [1,3,4];
>> A = [1,2,3,4; 5,6,7,8; 9,10,11,12; 13,14,15,16]
A =
1 2 3 4
5 6 7 8
9 10 11 12
13 14 15 16
I want a vector that will give me the values of A at the locations correspongin to i,j. I tried
A(i,j)
ans =
1 3 4
5 7 8
9 11 12
but this is not what I wanted. I want to get the following
>> [A(i(1),j(1)); A(i(2),j(2));A(i(3),j(3))]
ans =
1
7
12
What is the matlab syntax for that? Please, avoid suggesting for loops or anything that is not in a vectorized form, as I need this to be done fast. Hopefully there will be some built-in function.
to get it in the fastest way, use linear indexing:
A((j-1)*size(A,1)+i)
remember that MATLAB uses a column-major order.
A(sub2ind(size(A),i,j))
If you really crave speed, you might try making your own copy of sub2ind.m that strips out all the input-checking that that function does.
To understand how to do this, it is best to understand how matlab stores its arrays. In the matrix:
i = [1,2,3];
j = [1,3,4];
A = [1,2,3,4; 5,6,7,8; 9,10,11,12; 13,14,15,16]
matlab stores the elements going DOWN the columns. So they actually reside in memory in the order:
{1 5 9 13 2 6 10 14 3 7 11 15 4 8 12 16}
You can actually index a 2-d array using a SINGLE index. This is why the sub2ind trick works. Since the elements that you want to get are the 1st, 10th and 15th elements, as stored in a column-wise ordering,
singleIndex = [1 10 15];
A(singleIndex)
ans =
1 7 12
To confirm that sub2ind gave that index list, try it...
ind = sub2ind([4 4],i,j)
ind =
1 10 15
For now I'm using this:
>> diag(A(i,j))
ans =
1
7
12