I have a cell described as the following:
mixed_values = {'jim', 89, [5 2 1; 1 2 3]};
mixed_values{1}
mixed_values{2}
mixed_values{3}
I loop it:
for k=1:length(mixed_values)
curstate=mixed_values{k};
% Check for the [5 2 1; 1 2 3]
if ismatrix(curstate)
disp('yes');
else
disp('no')
end
end
But it founds the matrix multiple times.
yes
yes
yes
How to check it by the way?
From Matlab help:
ismatrix(M) returns logical 1 (true) if SIZE(M) returns [m n] with
nonnegative integer values m and n, and logical 0 (false) otherwise
so I checked size(curstate)
1 3 % 3 character string array
1 1 % of course you can do size of a single elements
2 3
so I modified your code
for k=1:length(mixed_values)
curstate=mixed_values{k};
% Check for the [5 2 1; 1 2 3]
if (size(curstate,1)) > 1 && (size(curstate,2)) > 1
disp('yes');
disp(size(curstate));
else
disp('no')
end
end
It really depends on what you define a matrix to be. In MathWorks case they decided that a matrix would be something with a valid size, which is certainly true. Notice that even scalars are matrices, of size 1x1. You can even have a matrix of characters. A = ['a' 'b';'c' 'd'];. I gather that in your case you want a matrix to be a numerical collection of at least 2 dimensions. I would solve it this way:
function result = TestForMatrix(m)
t1 = isnumeric(m);
t2 = ~isvector(m);
result = all([t1 t2]);
end
Use it as if it was ismatrix.
if (TestForMatrix(curstate))
disp('yes');
else
....
The way this works is the test for numerical numbers will eliminate character strings. The second test will eliminate vectors and scalars. As you find more things to include or eliminate you add those tests. For example, say you want to allow cells. t3 = iscell(m); result = all([t1 t2 t3]); The are many logical tests that can be done on Matlab objects, see Matlab is*.
Related
Let say we have the vector v=[1,2,3] and we want to build the matrix of all the combinations of the numbers contained in v, i.e.
1 2 3
1 3 2
2 1 3
2 3 1
3 1 2
3 2 1
Since I'm not good in recursion, firstly I tried to write the code to build such a matrix by using for loops
makeLoop([1,2,3])
function A = makeLoop(v)
loops=length(v);
for i = 1:loops
dummy=v;
m=factorial(loops)/loops;
A((1+m*(i-1)):m*i,1)=v(i);
v(i)=[];
loops2=length(v);
for j = 1:loops2
dummy2=v;
m2=factorial(loops2)/loops2;
A(((1+m2*(j-1))+m*(i-1)):(m2*j+m*(i-1)),2)=v(j);
v(j)=[];
loops3=length(v);
for k = 1:loops3
m3=factorial(loops3)/loops3;
A(((1+m2*(j-1))+m*(i-1)):(m2*j+m*(i-1)),3)=v(k);
end
v=dummy2;
end
v=dummy;
end
end
it seems like it work, but obviously write it all for a bigger v would be like hell. Anyway I don't understand how to properly write the recursion, I think the recursive structure will be something like this
function A = makeLoop(v)
if length(v)==1
"do the last for loop"
else
"do a regular loop and call makeLoop(v) (v shrink at each loop)"
end
but I don't get which parts should I remove from the original code, and which to keep.
You were very close! The overall structure that you proposed is sound and your loopy-code can be inserted into it with practically no changes:
function A = makeLoop(v)
% number of (remaining) elements in the vector
loops = length(v);
if loops==1 %"do the last for loop"
A = v; %Obviously, if you input only a single number, the output has to be that number
else %"do a regular loop and call makeLoop(v) (v shrink at each loop)"
%preallocate matrix to store results
A = zeros(factorial(loops),loops);
%number of results per vector element
m = factorial(loops)/loops;
for i = 1:loops
%For each element of the vector, call the function again with that element missing.
dummy = v;
dummy(i) = [];
AOut = makeLoop(dummy);
%Then add that element back to the beginning of the output and store it.
A((1+m*(i-1)):m*i,:) = [bsxfun(#times,v(i),ones(m,1)) AOut];
end
end
Explanation bsxfun() line:
First, read the bsxfun documentation, it explains how it works way better than I could. But long story short, with bsxfun() we can replicate a scalar easily by multiplying it with a column vector of ones. E.g. bsxfun(#times,5,[1;1;1]) will result in the vector [5;5;5]. Note that since Matlab 2016b, bsxfun(#times,5,[1;1;1]) can written shorter as 5.*[1;1;1]
To the task at hand, we want to add v(i) in front (as the first column) of all permutations that may occur after it. Therefore we need to replicate the v(i) into the 1. dimension to match the number of rows of AOut, which is done with bsxfun(#times,v(i),ones(m,1)). Then we just horizontally concatenate this with AOut.
You can simply use the perms function to achieve this:
v = [1 2 3];
perms(v)
ans =
3 2 1
3 1 2
2 3 1
2 1 3
1 3 2
1 2 3
If you want them sorted using the same criterion you applied in the desired output, use the following code (refer to this page for an official documentation of the sortrows functon):
v = [1 2 3];
p = perms(v);
p = sortrows(p)
p =
1 2 3
1 3 2
2 1 3
2 3 1
3 1 2
3 2 1
The specific task I'm trying to achieve is hard to describe, so here's an example: given A and x
A = [1 2;
3 0;
3 5;
4 0];
x = [1 2 3];
I want the algorithm to output
output: [1 2]
meaning that all of the nonzero elements in rows 1 and 2 in A are in x.
I have done this using cell arrays and loops; however, A and x are very large and my approach is not at all efficient. Also, I can't seem to figure out how to rework ismember to give me what I want. What is the fastest/least memory intensive method?
EDIT: Apologies, my original example was too simplistic. It is corrected now.
The first answer is good, but I would recommend to not using arrayfun. There are more eloquent ways to do what you ask. Use ismember combined with all, then index into the matrix A when you're done. Basically, your problem is to determine if a row has all of the values found in x and ignoring the zero values. In this case, we can find all of the values in the matrix A that are actually zero, then use this to augment our result.
Using A as the first input and x as the second input will return a matrix of the same size as A that tells you whether an element in A is found in x. If you want to check if all elements in the matrix A for a row can be found in x, check if all elements in a row is 1. On top of this, find all of the elements that are zero, then with the output of ismember set these to 1. This can be done with using a logical OR. After, you can use all and check each row independently by using the output of ismember as the first input into all and setting the second argument to 2. This would then return all of the rows in the matrix A where any column is found in x ignoring any values that are zero for a row in A which is what you're looking for:
A = [1 2; 3 0; 4 0];
x = [1 2 3];
mask = ismember(A, x);
ind = all(mask | A == 0, 2);
I'm also in favour of one-liners. We can consolidate this into one line of code:
ind = all(ismember(A, x) | A == 0, 2);
Even shorter is to simply invert A. All zero elements become true and false otherwise:
ind = all(ismember(A, x) | ~A, 2);
ind would thus be:
>> ind
ind =
3×1 logical array
1
1
0
Since you want the actual row indices, you can just use find on top of this:
>> find(ind)
ans =
1
2
To verify, let's use your second example in your comments:
>> A = [1 2;3 5;4 0];
>> x = [1 2 3];
>> ind = all(ismember(A, x) | ~A, 2)
ind =
3×1 logical array
1
0
0
>> find(ind)
ans =
1
I think the best way to rework ismember is to make sure there are no "no members" by just checking for the nonzero elements in A.
arrayfun can do the work in a fast way. It uses the most efficient parallel computing for your specific machine. The following line should return the correct output:
find(arrayfun(#(a) sum(~ismember(A(a,A(a,:)>0),x)),1:size(A,1))==0)
Is this what you were looking for?
However, if your problem is related to memory, then you may have to break the arrayfun operation into pieces (1:floor(size(A,1)/2), floor(size(A,1)/2):size(A,1) or smaller chunks), since MATLAB puts a bunch of workers to do the task, and may use all your available RAM memory...
Hi I have the following matrix:
A= 1 2 3;
0 4 0;
1 0 9
I want matrix A to be:
A= 1 2 3;
1 4 9
PS - semicolon represents the end of each column and new column starts.
How can I do that in Matlab 2014a? Any help?
Thanks
The problem you run into with your problem statement is the fact that you don't know the shape of the "squeezed" matrix ahead of time - and in particular, you cannot know whether the number of nonzero elements is a multiple of either the rows or columns of the original matrix.
As was pointed out, there is a simple function, nonzeros, that returns the nonzero elements of the input, ordered by columns. In your case,
A = [1 2 3;
0 4 0;
1 0 9];
B = nonzeros(A)
produces
1
1
2
4
3
9
What you wanted was
1 2 3
1 4 9
which happens to be what you get when you "squeeze out" the zeros by column. This would be obtained (when the number of zeros in each column is the same) with
reshape(B, 2, 3);
I think it would be better to assume that the number of elements may not be the same in each column - then you need to create a sparse array. That is actually very easy:
S = sparse(A);
The resulting object S is a sparse array - that is, it contains only the non-zero elements. It is very efficient (both for storage and computation) when lots of elements are zero: once more than 1/3 of the elements are nonzero it quickly becomes slower / bigger. But it has the advantage of maintaining the shape of your matrix regardless of the distribution of zeros.
A more robust solution would have to check the number of nonzero elements in each column and decide what the shape of the final matrix will be:
cc = sum(A~=0);
will count the number of nonzero elements in each column of the matrix.
nmin = min(cc);
nmax = max(cc);
finds the smallest and largest number of nonzero elements in any column
[i j s] = find(A); % the i, j coordinates and value of nonzero elements of A
nc = size(A, 2); % number of columns
B = zeros(nmax, nc);
for k = 1:nc
B(1:cc(k), k) = s(j == k);
end
Now B has all the nonzero elements: for columns with fewer nonzero elements, there will be zero padding at the end. Finally you can decide if / how much you want to trim your matrix B - if you want to have no zeros at all, you will need to trim some values from the longer columns. For example:
B = B(1:nmin, :);
Simple solution:
A = [1 2 3;0 4 0;1 0 9]
A =
1 2 3
0 4 0
1 0 9
A(A==0) = [];
A =
1 1 2 4 3 9
reshape(A,2,3)
ans =
1 2 3
1 4 9
It's very simple though and might be slow. Do you need to perform this operation on very large/many matrices?
From your question it's not clear what you want (how to arrange the non-zero values, specially if the number of zeros in each column is not the same). Maybe this:
A = reshape(nonzeros(A),[],size(A,2));
Matlab's logical indexing is extremely powerful. The best way to do this is create a logical array:
>> lZeros = A==0
then use this logical array to index into A and delete these zeros
>> A(lZeros) = []
Finally, reshape the array to your desired size using the built in reshape command
>> A = reshape(A, 2, 3)
I have a (row)vector of some size, containing the values 1,2 and 3. They are in there in no 'specific' order, so a sample of the array would be [1,1,1,1,2,2,2,1,1,2,2,3,3]. What I want to do is find the consecutive number of identical elements, but with some restrictions.
What I want is to make new arrays of which the elements denote:
The number of consecutive 1's before it changes into a 2
The number of consecutive 2's before it changes into a 1
The number of consecutive 2's before it changes into a 3
The number of consecutive 3's before it changes into a 2
So for the example I have given, the arrays would be
[4,2]
[3]
[2]
[]
I'm not sure how to tackle this. I can use the diff function to find where it changes sign, but then it'll be a little tough to figure out exactly what change has occured, right?
The method does not have to be super fast, as I only have to do this a few times for around 10^5 datapoints.
This approach will group things the way you specified in the question:
a=[1,1,1,1,2,2,2,1,1,2,2,3,3]
b = diff(a)
c = find(b)
d = diff([0,c]);
type1 = d(b(c) == 1 & a(c) == 1);
type2 = d(b(c) == -1 & a(c) == 2);
type3 = d(b(c) == 1 & a(c) == 2);
type4 = d(b(c) == -1 & a(c) == 3);
type1 =
4 2
type2 =
3
type3 =
2
type4 =
Empty matrix: 1-by-0
Use the standard procedure with diff to detect changes and run lengths, and then apply accumarray to group run lengths according to each pair of values before and after the change:
x = [1,1,1,1,2,2,2,1,1,2,2,3,3];
x = x.'; %'// easier to work with a column vector
ind = find(diff(x))+1; %// index of positions where x changes
%// To detect what change has ocurred, we'll use x(ind-1) and x(ind)
len = diff([1; ind]); %// length of each run
result = accumarray([x(ind-1) x(ind)], len, [], #(v) {v}); %// group lengths
Note the order within each result vector may be altered, as per accumarray.
In your example, this gives
>> result
result =
[] [2x1 double] []
[3] [] [2]
>> result{1,2}
ans =
2
4
>> result{2,1}
ans =
3
>> result{2,3}
ans =
2
I believe this will do the trick (although it's not very pretty)
a=[1,1,1,1,1,2,2,2,2,1,1,1,2,2,3,3,3];
d=diff(a);
deltas=(d~=0);
d12=[];d23=[];d32=[];d21=[];
last=0;
for i=1:length(a)-1
if deltas(i)
if a(i)==1&&a(i+1)==2
d12=[d12,i-last];
last=i;
elseif a(i)==2&&a(i+1)==3
d23=[d23,i-last];
last=i;
elseif a(i)==3&&a(i+1)==2
d32=[d32,i-last];
last=i;
elseif a(i)==2&&a(i+1)==1
d21=[d21,i-last];
last=i;
end
end
end
I have two vectors with the same elements but their order is not same. For eg
A
10
9
8
B
8
9
10
I want to find the mapping between the two
B2A
3
2
1
How can I do this in matlab efficiently?
I think the Matlab sort is efficient. So:
[~,I]=sort(A); %sort A; we want the indices, not the values
[~,J]=sort(B); %same with B
%I(1) and J(1) both point to the smallest value, and a similar statement is true
%for other pairs, even with repeated values.
%Now, find the index vector that sorts I
[~,K]=sort(I);
%if K(1) is k, then A(k) is the kth smallest entry in A, and the kth smallest
%entry in B is J(k)
%so B2A(1)=J(k)=J(K(1)), where BSA is the desired permutation vector
% A similar statement holds for the other entries
%so finally
B2A=J(K);
if the above were in script "findB2A" the following should be a check for it
N=1e4;
M=100;
A=floor(M*rand(1,N));
[~,I]=sort(rand(1,N));
B=A(I);
findB2A;
all(A==B(B2A))
There are a couple of ways of doing this. The most efficient in terms of lines of code is probably using ismember(). The return values are [Lia,Locb] = ismember(A,B), where Locb are the indices in B which correspond to the elements of A. You can do [~, B2A] = ismember(A, B) to get the result you want. If your version of MATLAB does not allow ~, supply a throwaway argument for the first output.
You must ensure that there is a 1-to-1 mapping to get meaningful results, otherwise the index will always point to the first matching element.
Here a solution :
arrayfun(#(x)find(x == B), A)
I tried with bigger arrays :
A = [ 7 5 2 9 1];
B = [ 1 9 7 5 2];
It gives the following result :
ans =
3 4 5 2 1
Edit
Because arrayfun is usually slower than the equivalent loop, here a solution with a loop:
T = length(A);
B2A = zeros(1, length(A));
for tt = 1:T
B2A(1, tt) = find(A(tt) == B);
end
I would go for Joe Serrano's answer using three chained sort's.
Another approach is to test all combinations for equality with bsxfun:
[~, B2A] = max(bsxfun(#eq, B(:), A(:).'));
This gives B2A such that B(B2A) equals A. If you want it the other way around (not clear from your example), simply reverse A and B within bsxfun.