i searched a lot in google but didnt find an answer that did help me without reducing my performance.
I have a Matrice A and B of the same size with different values. Then i want to filter:
indices=find(A<5 & B>3)
A(indices)=
B(indices)=
Now I want to apply a function on the indices -> indices_2=find(A>=5 | b<=3) without using the find function on the whole matrices A and B again. Logic operations are not possible in this case because I need the indices and not 0 and 1.
Something like:
A(~indices)=
B(~indices)=
instead of:
indices_2=find(A>=5 | B<=3)
A(indices_2)=
B(indices_2)=
And after that I want to split these sets once again.... Just Filtering.
I used indices_2=setdiff(indices, size(A)) but it did screw my computation performance. Is there any other method to split the matrices into subsets without using find twice?
Hope you understand my problem and it fits the regulations.
I don't understand why you can't just use find again, nor why you can't use logical indexing in this case but I suppose if you are going to restrict yourself like this then you could accomplish this using setdiff:
indices_2 = setdiff(1:numel(A), indices)
however, if you are worried about performance, you should be sticking to logical indexing:
indices = A<5 & B>3
A(indices)=...
B(indices)=...
A(~indices)=...
B(~indices)=...
I think you may be looking for something like this:
%Split your data in two and keep track of which numbers you have
ranks = 1:numel(A);
indices= find(A<5 & B>3);
% Update the numbers list to contain the set of numbers you are interested in
ranks_2 = ranks(~indices)
% Operate on the set you are interested in and find the relevant ranks
indices_2= A(~indices)>=5 | B(~indices)<=3
ranks_2 = ranks_2(indices_2)
Related
I'm looking an efficient way to turn the vector:
[1,1,1,2,3,3,3,4,4,4,5,1]
into a vector of vectors such that:
[[1,2,3,12],[4],[5,6,7],[8,9,10],[11]]
In general:
newVector[i] = indexes of the initial vector that contained i
Preferably in Matlab/Octave but I'm just curious if there is an efficient way of achieving this.
I tried looking it up on google and stack but I have no idea what to call this 'operation' so nothing came up.
There is an easy way to do it using accumarray
A = [1,1,1,2,3,3,3,4,4,4,5,1]
accumarray(A',A',[],#(x){find(ismember(A,x))})
But next time, please show your own attempt in your question
Alternatively (but only if A starts from 1 and doesn't skip any numbers)
accumarray(A', (1:size(A,2))', [], #(x){sort(x)})
I am a beginner in Matlab and have not been able to find an answer to my question so far. Your help will definitely be very much appreciated.
I have 70 matrices (100x100), named SUBJ_1, SUBJ_2 etc. I would like to create a loop so that I would calculate some metrics (i.e. max and min values) for each matrix, and save the output in a 70x2 result matrix (where each row would correspond to the consecutively named SUBJ_ matrix).
I am struggling with both stages - how to use the names of individual variables in a 'for' loop and how to properly save individual outputs in a combined array.
Many thanks and all the best!
Don't use such variable names, create a big cell array named SUBJ and put each Matrix in it.
r=zeros(numel(SUBJ),2)
for idx=1:numel(SUBJ)
r(idx,1)=min(min(SUBJ{idx}))
r(idx,2)=max(max(SUBJ{idx}))
end
min and max are called twice because first call creates maximum among rows, second call among columns.
Even though this is in principle possible in Matlab, I would not recommend it: too slow and cumbersome to implement.
You could instead use a 3-D matrix (100x100x70) SUBJ which would contain all the SUBJ_1 etc. in one matrix. This would allow you to calculate min/max etc. with just one line of code. Matlab will take care of the loops internally:
OUTPUT(:,1) = min(min(SUBJ,[],1)[],2);
OUTPUT(:,2) = max(max(SUBJ,[],1)[],2);
Like this, OUTPUT(1,1) contains min(min(SUBJ(:,:,1))) and so on...
As to how to use the names of individual variables in a 'for' loop, here gives an example:
SUBJ = [];
for idx = 1:70
term = eval(['SUBJ_',num2str(idx)]);
SUBJ = [SUBJ; max(max(term)),min(min(term))];
end
My question is very similar to this one but I can't manage exactly how to apply that answer to my problem.
I am looping through a vector with a variable k and want to select the whole vector except the single value at index k.
Any idea?
for k = 1:length(vector)
newVector = vector( exluding index k); <---- what mask should I use?
% other operations to do with the newVector
end
Another alternative without setdiff() is
vector(1:end ~= k)
vector([1:k-1 k+1:end]) will do. Depending on the other operations, there may be a better way to handle this, though.
For completeness, if you want to remove one element, you do not need to go the vector = vector([1:k-1 k+1:end]) route, you can use vector(k)=[];
Just for fun, here's an interesting way with setdiff:
vector(setdiff(1:end,k))
What's interesting about this, besides the use of setdiff, you ask? Look at the placement of end. MATLAB's end keyword translates to the last index of vector in this context, even as an argument to a function call rather than directly used with paren (vector's () operator). No need to use numel(vector). Put another way,
>> vector=1:10;
>> k=6;
>> vector(setdiff(1:end,k))
ans =
1 2 3 4 5 7 8 9 10
>> setdiff(1:end,k)
Error using setdiff (line 81)
Not enough input arguments.
That is not completely obvious IMO, but it can come in handy in many situations, so I thought I would point this out.
Very easy:
newVector = vector([1:k-1 k+1:end]);
This works even if k is the first or last element.
%create a logic vector of same size:
l=ones(size(vector))==1;
l(k)=false;
vector(l);
Another way you can do this which allows you to exclude multiple indices at once (or a single index... basically it's robust to allow either) is:
newVector = oldVector(~ismember(1:end,k))
Works just like setdiff really, but builds a logical mask instead of a list of explicit indices.
I have two lists of timestamps and I'm trying to create a map between them that uses the imu_ts as the true time and tries to find the nearest vicon_ts value to it. The output is a 3xd matrix where the first row is the imu_ts index, the third row is the unix time at that index, and the second row is the index of the closest vicon_ts value above the timestamp in the same column.
Here's my code so far and it works, but it's really slow. I'm not sure how to vectorize it.
function tmap = sync_times(imu_ts, vicon_ts)
tstart = max(vicon_ts(1), imu_ts(1));
tstop = min(vicon_ts(end), imu_ts(end));
%trim imu data to
tmap(1,:) = find(imu_ts >= tstart & imu_ts <= tstop);
tmap(3,:) = imu_ts(tmap(1,:));%Use imu_ts as ground truth
%Find nearest indecies in vicon data and map
vic_t = 1;
for i = 1:size(tmap,2)
%
while(vicon_ts(vic_t) < tmap(3,i))
vic_t = vic_t + 1;
end
tmap(2,i) = vic_t;
end
The timestamps are already sorted in ascending order, so this is essentially an O(n) operation but because it's looped it runs slowly. Any vectorized ways to do the same thing?
Edit
It appears to be running faster than I expected or first measured, so this is no longer a critical issue. But I would be interested to see if there are any good solutions to this problem.
Have a look at knnsearch in MATLAB. Use cityblock distance and also put an additional constraint that the data point in vicon_ts should be less than its neighbour in imu_ts. If it is not then take the next index. This is required because cityblock takes absolute distance. Another option (and preferred) is to write your custom distance function.
I believe that your current method is sound, and I would not try and vectorize any further. Vectorization can actually be harmful when you are trying to optimize some inner loops, especially when you know more about the context of your data (e.g. it is sorted) than the Mathworks engineers can know.
Things that I typically look for when I need to optimize some piece of code liek this are:
All arrays are pre-allocated (this is the biggest driver of performance)
Fast inner loops use simple code (Matlab does pretty effective JIT on basic commands, but must interpret others.)
Take advantage of any special data features that you have, e.g. use sort appropriate algorithms and early exit conditions from some loops.
You're already doing all this. I recommend no change.
A good start might be to get rid of the while, try something like:
for i = 1:size(tmap,2)
C = max(0,tmap(3,:)-vicon_ts(i));
tmap(2,i) = find(C==min(C));
end
To begin, this problem is easily solvable with a for-loop. However, I'm trying to force/teach myself to think vector-wise to take advantage of what Matlab does best.
Simplified, here is the problem explanation:
I have a vector with data in it.
I have a 2xN array of start/stop indices that represent ranges of interesting data in the vector.
I want to perform calculations on each of those ranges, resulting in a number (N results, corresponding to each start/stop range.)
In code, here's a pseudoexample of what I'd like to have at the end:
A = 1:10000;
startIndicies = [5 100 1000];
stopIndicies = [10 200 5000];
...
calculatedResults = [func(A(5:10)) func(A(100:200)) func(A(1000:5000))]
The length of A, and of the start/stop index array is variable.
Like I said, I can easily solve this with a for loop. However since could be used with a large data set, I'd like to know if there's a good solution without a for loop.
Here is one possible solution, although, I won't call it a fully vectorized solution, rather a one liner one.
out = cellfun(#(i,j) fun(A(i:j)), num2cell(startIndicies), num2cell(stopIndicies) );
or, if you plan to have homogeneous outputs,
out = arrayfun(#(i,j) fun(A(i:j)), startIndicies, stopIndicies);