Definition of Problem
I have two arrays called weights and indices respectively:
weights = [1, 3, 2];
indices = [1, 1, 2, 3, 2, 4];
m = 4; % Number of Rows in Matrix
n = 3; % Number of Columns in Matrix
M = zeros(m, n);
The array called indices is storing the indices where I need to store a 1 in every column.
For instance for the first column at row 1 which is indicated in indices(1) I need to store a 1 and this is indicated by weights(1) which is equal to 1.
M(indices(1), 1) = 1;
For column 2, at rows 1 to 3 (indices(2:4)) I need to store a 1. The range of indices for column 2 are again indicated by weights(2).
M(indices(2:4),2) = 1;
Similarly, for column 3, at rows 2 and 4 (indices(5:6)) I need to store a 1. The range of indices for column 3 are again indicated by weights(3).
M(indices(5:6),3) = 1;
Expected Binary Matrix
The expected and resulting binary matrix is:
1 1 0
0 1 1
0 1 0
0 0 1
Solution
Is there any way I can do this in generalized manner by using both the weights and indices arrays rather than doing it in a hard coded manner to create create the binary matrix M?
You just have a weird way of describing your indices, so you just need to convert them to something standard.
columsn_idx=repelem(1:n,weights); % repeat column number as much as needed
row_idx=indices ; % just for clarity
M(sub2ind([m,n],row_idx,columsn_idx))=1;% Use linear indices
Related
I have a numerical array CentroidBins which is 3694x4. Columns 3 and 4 are arbitrary X and Y bins with a range of 1-20. My goal in the last bit of code was to go through columns 3 and 4 to count the number of times a particular pair appeared (ie. 1,1 or 1,2....etc) and place that into a 20x20 array with rows being Y bins and columns being X bins. I managed to construct something which looks like what a want, but the output is 18x17, I am assuming it is deleting rows and columns populated by "0". How can I make sure this produces 20x20?
bin20 = centroids_array / 20 %create 20 bins
imRound = round(bin20)
CentroidBins = [centroids_array , imRound]
save("CentroidBins.mat", "CentroidBins");
disp(CentroidBins)
nrow = size(CentroidBins, 1);
B = CentroidBins(:,[3 4]);
NumF = full(sparse(B(1:end-nrow),B(nrow+1:end),1))
to count the occurrence of pairs, you use hist and unique
a=[1 2; 1 2; 2 3; 8 1; 2 3];
[foo,ix,jx]=unique(a,'rows');
count=hist(jx,unique(jx)) % report the repeated counts of each unique pair
foo % lists the unique pairs
I have an array A=[a1,a2,a3, ..., aN] I would like to take a product of each 3 elements:
s1=a1+a2+a3
s2=a4+a5+a6
...
sM=a(N-2)+a(N-1)+aN
My solution:
k=size(A);
s=0;
for n=1:k
s(n)=s(n-2)+s(n-1)+s(n);
end
Error: Attempted to access s(2); index out of bounds because numel(s)=1.
Hoe to fix it?
If you want to sum in blocks, for the general case when the number of elements of A is not necessarily a multiple of the block size, you can use accumarray:
A = [3 8 5 8 2 3 4 7 9 6 4]; % 11 elements
s = 3; % block size
result = accumarray(ceil((1:numel(A))/s).', A(:));
If you want a sliding sum with a given block size, you can use conv:
A = [3 8 5 8 2 3 4 7 9 6 4]; % 11 elements
s = 3; % block size
result = conv(A(:).', ones(1,s), 'valid');
You try to calculate sby using values from s. Dont you mean s(n)=A(n-2)+A(n-1)+A(n);? Also size returns more than one dimension on its own.
That being said, getting the 2 privous values n-2 and n-1 doenst work for n=1;2 (because you must have positive indices). You have to explain how the first two values should be handeled. I assume either 0 for elements not yet exisiting
k=size(A,2); %only the second dimension when A 1xn, or length(A)
s=zeros(1,k); %get empty values instead of appending each value for better performance
s(1)=A(1);
s(2)=A(2)+A(1);
for n=3:k %start at 3
s(n)=A(n-2)+A(n-1)+A(n);
end
or sshoult be 2 values shorter than A.
k=size(A,2);
s=zeros(1,k-2);
for n=1:k-2
s(n)=A(n)+A(n+1)+A(n+2);
end
You initialise s as a scalar with s = 0. Then you try and index it like an array, but it only has a single element.
Your current logic (if fixed) will calculate this:
s(1) = a(1)+a(2)+a(3)
s(2) = a(2)+a(3)+a(4)
...
% 's' will be 2 elements shorter than 'a'
So we need to be a bit wiser with the indexing to get what you describe, which is
s(1) = a(1)+a(2)+a(3)
s(2) = a(4)+a(5)+a(6)
...
% 's' will be a third as big as 'a'
You should pre-allocate s to the right size, like so:
k = numel(A); % Number of elements in 'A'
s = zeros( 1, k/3 ); % Output array, assuming 'k' is divisible by 3
for n = 0:3:k-3
s(n/3+1) = a(n+1) + a(n+2) + a(n+3);
end
You could do this in one line by reshaping the array to have 3 rows, then summing down each column, this assumes that the number of elements in a is divisible by 3, and that a is a row vector...
s = sum( reshape( a, 3, [] ) );
Let's say I have two (large) vectors a=[0 0 0 0 0] and b=[1 2 3 4 5] of the same size and one index vector ind=[1 5 2 1] with values in {1,...,length(a)}. I would like to compute
for k = 1:length(ind)
a(ind(k)) = a(ind(k)) + b(ind(k));
end
% a = [2 2 0 0 5]
That is, I want to add those entries of b declared in ind to a including multiplicity.
a(ind)=a(ind)+b(ind);
% a = [1 2 0 0 5]
is much faster, of course, but ignores indices which appear multiple times.
How can I speed up the above code?
We can use unique to identify the unique index values and use the third output to determine which elements of ind share the same index. We can then use accumarray to sum all the elements of b which share the same index. We then add these to the original value of a at these locations.
[uniqueinds, ~, inds] = unique(ind);
a(uniqueinds) = a(uniqueinds) + accumarray(inds, b(ind)).';
If max(inds) == numel(a) then this could be simplified to the following since accumarray will simply return 0 for any missing entry in ind.
a(:) = a(:) + accumarray(ind(:), b(ind));
Another approach based on accumarray:
a(:) = a(:) + accumarray(ind(:), b(ind(:)), [numel(a) 1]);
How it works
accumarray with two column vectors as inputs aggregates the values of the second input corresponding to the same index in the first. The third input is used here to force the result to be the same size as a, padding with zeros if needed.
Let's say, I have an array like this:
1 2 3 4 5
And given pair is (2,3), then number of possible subarrays that don't have (2,3) present in them will be,,
1. 1
2. 2
3. 3
4. 4
5. 5
6. 1 2
7. 3 4
8. 4 5
9. 3 4 5
So, the answer will be 9.
Obviously, there can be more of such pairs.
Now, one method that I thought of is of O(n^2) which involves finding all such elements of maximum length n. Can I do better? Thanks!
Let's see, this adhoc pseudocode should be O(n):
array = [1 2 3 4 5]
pair = [2 3]
length = array.length
n = 0
start = 0
while (start < length)
{
# Find next pair
pair_pos = start
while (pair_pos < length) and (array[pair_pos,pair_pos+1] != pair) # (**1)
{
pair_pos++
}
# Count subarrays
n += calc_number_of_subarrays(pair_pos-start) # (**2)
# Continue after the pair
start = pair_pos+2
}
print n
Note **1: This seems to involve a loop inside the outer loop. Since every element of the array is visited exactly once, both loops together are O(n). In fact, it is probably easy to refactor this to use only one while loop.
Note **2: Given an array of length l, there are l+(l-1)+(l-2)+...+1 subarrays (including the array itself). Which is easy to calculate in O(1), there is no loop involved. c/f Euler. :)
You don't need to find which subarrays are in an array to know how many of them there are. Finding where the pair is in the array is at most 2(n-1) array operations. Then you only need to do a simple calculation with the two lengths you extract from that. The amount of subarrays in an array of length 3 is, for example, 3 + 2 + 1 = 6 = (n(n+1))/2.
The solution uses that in a given array [a, ..., p1, p2, ..., b], the amount of subarrays without the pair is the amount of subarrays for [a, ..., p1] + the amount of subarrays for [p2, ..., b]. If multiple of such pairs exist, we repeat the same trick on [p2, ..., b] as if it was the whole array.
function amount_of_subarrays ::
index := 1
amount := 0
lastmatch := 0
while length( array ) > index do
if array[index] == pair[1] then
if array[index+1] == pair[2] then
length2 := index - lastmatch
amount := amount + ((length2 * (length2 + 1)) / 2)
lastmatch := index
fi
fi
index := index + 1
od
//index is now equal to the length
length2 := index - lastmatch
amount := amount + ((length2 * (length2 + 1)) / 2)
return amount
For an array [1, 2, 3, 4, 5] with pair [2, 3], index will be 2 when the two if-statements are true. amount will be updated to 3 and lastmatch will be updated to 2. No more matches will be found, so lastmatch is 2 and index is 5. amount will be 3 + 6 = 9.
I have a matrix of growing length for example a 4-by-x matrix A where x is increasing in a loop. I want to find the smallest column c where all columns before that, each, carry one single number. The matrix A can look like:
A = [1 2 3 4;
1 2 3 5;
1 2 3 1;
1 2 3 0];
where c=3, and x=4.
At each iteration of the loop where A grows in length, the value of index c grows as well. Therefore, at each iteration, I want to update the value of c. How efficiently can I code this in Matlab?
Let's say you had the matrix A and you wanted to check a particular column iito see if all its elements are the same. The code would be:
all(A(:, ii)==A(1, ii)) % checks if all elements in column are same as first element
Also, keep in mind that once the condition is broken, x cannot be updated anymore. Therefore, your code should be:
x = 0;
while true
%% expand A by one column
if ~all(A(:, x)==A(1, x)) % true if all elements in column are not the same as first element
break;
end
x = x+1;
end
You could use this:
c = find(arrayfun(#(ind)all(A(1, ind)==A(:, ind)), 1:x), 1, 'first');
This finds the first column where not all values are the same. If you run this in a loop, you can detect when entries in a column start to differ:
for x = 1:maxX
% grow A
c = find(arrayfun(#(ind)~all(A(1, ind)==A(:, ind)), 1:x), 1, 'first');
% If c is empty, all columns have values equal to first row.
% Otherwise, we have to subtract 1 to get the number of columns with equal values
if isempty(c)
c = x;
else
c = c - 1;
end
end
Let me give a try as well:
% Find the columns which's elements are same and sum the logical array up
c = sum(A(1,:) == power(prod(A,1), 1/size(A,1)))
d=size(A,2)
To find the last column such that each column up to that one consists of equal values:
c = find(any(diff(A,1,1),1),1)-1;
or
c = find(any(bsxfun(#ne, A, A(1,:)),1),1)-1;
For example:
>> A = [1 2 3 4 5 6;
1 2 3 5 5 7;
1 2 3 1 5 0;
1 2 3 0 5 8];
>> c = find(any(diff(A,1,1),1),1)-1
c =
3
You can try this (easy and fast):
Equal_test = A(1,:)==A(2,:)& A(2,:)==A(3,:)&A(3,:)==A(4,:);
c=find(Equal_test==false,1,'first')-1;
You can also check the result of find if you want.