i have the following three vectors and i want to insert NaNs into B where A misses the data points in An. So my Bn should be [0.1;0.2;0.3;NaN;NaN;0.6;0.7]. How can i get the Bn? Thanks.--Jackie
A=[1;2;3;6;7];
An=[1;2;3;4;5;6;7];
B=[0.1;0.2;0.3;0.6;0.7];
Okay so first off, you cant store the string 'NaN' into one cell of a matrix, it must be stored into a cell array.
The code snip below gives you your solution, if cell array is an okay output.
Please let me know any questions or concerns you might have.
Forget the italic parts, Thanks David K.
% NaN solution for Jackie
A=[1;2;3;6;7]; An=[1;2;3;4;5;6;7]; B=[0.1;0.2;0.3;0.6;0.7];
len = max(length(A),length(An))
Bn = zeros(len,1);
k = 0; % adjust the index so that you don't call B outside of its size
for i =1 :len
ind= A(An(i)==A);
if isempty(ind) ==1
Bn(i) = nan(1,1)
k = k+1;
else
Bn(i) = B(i-k)
end
end
Related
I'm writing a program that finds the indices of a matrix G where there is only a single 1 for either a column index or a row index and removes any found index if it has a 1 for both the column and row index. Then I want to take these indices and use them as indices in an array U, which is where the trouble comes. The indices do not seem to be stored as integers and I'm not sure what they are being stored as or why. I'm quite new to Matlab (but thats probably obvious) and so I don't really understand how types work for Matlab or how they're assigned. So I'm not sure why I',m getting the error message mentioned in the title and I'm not sure what to do about it. Any assistance you can provide would be greatly appreciated.
I forgot to mention this before but G is a matrix that only contains 1s or 0s and U is an array of strings (i think what would be called a cell?)
function A = ISClinks(U, G)
B = [];
[rownum,colnum] = size(G);
j = 1;
for i=1:colnum
s = sum(G(:,i));
if s == 1
B(j,:) = i;
j = j + 1;
end
end
for i=1:rownum
s = sum(G(i,:));
if s == 1
if ismember(i, B)
B(B == i) = [];
else
B(j,:) = i;
j = j+1;
end
end
end
A = [];
for i=1:size(B,1)
s = B(i,:);
A(i,:) = U(s,:);
end
end
This is the problem code, but I'm not sure what's wrong with it.
A = [];
for i=1:size(B,1)
s = B(i,:);
A(i,:) = U(s,:);
end
Your program seems to be structured as though it had been written in a language like C. In MATLAB, you can usually substitute specialized functions (e.g. any() ) for low-level loops in many cases. Your function could be written more efficiently as:
function A = ISClinks(U, G)
% Find columns and rows that are set in the input
active_columns=any(G,1);
active_rows=any(G,2).';
% (Optional) Prevent columns and rows with same index from being simultaneously set
%exclusive_active_columns = active_columns & ~active_rows; %not needed; this line is only for illustrative purposes
%exclusive_active_rows = active_rows & ~active_columns; %same as above
% Merge column state vector and row state vector by XORing them
active_indices=xor(active_columns,active_rows);
% Select appropriate rows of matrix U
A=U(active_indices,:);
end
This function does not cause errors with the example input matrices I tested. If U is a cell array (e.g. U={'Lorem','ipsum'; 'dolor','sit'; 'amet','consectetur'}), then return value A will also be a cell array.
I wrote this matlab code in order to concatenate the results of the integration of all the columns of a matrix extracted form a multi matrix array.
"datimf" is a matrix composed by 100 matrices, each of 224*640, vertically concatenated.
In the first loop i select every single matrix.
In the second loop i integrate every single column of the selected matrix
obtaining a row of 640 elements.
The third loop must concatenate vertically all the lines previously calculated.
Anyway i got always a problem with the third loop. Where is the error?
singleframe = zeros(224,640);
int_frame_all = zeros(1,640);
conc = zeros(100,640);
for i=0:224:(22400-224)
for j = 1:640
for k = 1:100
singleframe(:,:) = datimf([i+1:(i+223)+1],:);
int_frame_all(:,j) = trapz(singleframe(:,j));
conc(:,k) = vertcat(int_frame_all);
end
end
end
An alternate way to do this without using any explicit loops (edited in response to rayryeng's comment below. It's also worth noting that using cellfun may not be more efficient than explicitly looping.):
nmats = 100;
nrows = 224;
ncols = 640;
datimf = rand(nmats*nrows, ncols);
% convert to an nmats x 1 cell array containing each matrix
cellOfMats = mat2cell(datimf, ones(1, nmats)*nrows, ncols);
% Apply trapz to the contents of each cell
cellOfIntegrals = cellfun(#trapz, cellOfMats, 'UniformOutput', false);
% concatenate the results
conc = cat(1, cellOfIntegrals{:});
Taking inspiration from user2305193's answer, here's an even better "loop-free" solution, based on reshaping the matrix and applying trapz along the appropriate dimension:
datReshaped = reshape(datimf, nrows, nmats, ncols);
solution = squeeze(trapz(datReshaped, 1));
% verify solutions are equivalent:
all(solution(:) == conc(:)) % ans = true
I think I understand what you want. The third loop is unnecessary as both the inner and outer loops are 100 elements long. Also the way you have it you are assigning singleframe lots more times than necessary since it does not depend on the inner loops j or k. You were also trying to add int_frame_all to conc before int_frame_all was finished being populated.
On top of that the j loop isn't required either since trapz can operate on the entire matrix at once anyway.
I think this is closer to what you intended:
datimf = rand(224*100,640);
singleframe = zeros(224,640);
int_frame_all = zeros(1,640);
conc = zeros(100,640);
for i=1:100
idx = (i-1)*224+1;
singleframe(:,:) = datimf(idx:idx+223,:);
% for j = 1:640
% int_frame_all(:,j) = trapz(singleframe(:,j));
% end
% The loop is uncessary as trapz can operate on the entire matrix at once.
int_frame_all = trapz(singleframe,1);
%I think this is what you really want...
conc(i,:) = int_frame_all;
end
It looks like you're processing frames in a video.
The most efficent approach in my experience would be to reshape datimf to be 3-dimensional. This can easily be achieved with the reshape command.
something along the line of vid=reshape(datimf,224,640,[]); should get you far in this regard, where the 3rd dimension is time. vid(:,:,1) then would display the first frame of the video.
I have the following function that works perfectly, but I would like to apply vectorization to it...
for i = 1:size(centroids,1)
centroids(i, :) = mean(X(idx == i, :));
end
It checks if idx matches the current index and if it does, it calculates the mean value for all the X values that correspond to that index.
This is my attempt at vectorization, my solution does not work and I know why...
centroids = mean(X(idx == [1:size(centroids,1)], :));
The following idx == [1:size(centroids,1)] breaks the code. I have no idea how to check if idx equals to either of the numbers from 1 to size(centroids,1).
tl:dr
Get rid of the for loop through vectorization
One option is to use arrayfun;
nIdx = size(centroids,1);
centroids = arrayfun(#(ii) mean(X(idx==ii,:)),1:nIdx, 'UniformOutput', false);
centroids = vertcat(centroids{:})
Since the output of a single function call is not necessarily a scalar, the UniformOutput option has to be set to false. Thus, arrayfun returns a cell array and you need to vertcat it to get the desired double array.
you can split the matrix into cells and take the mean from each cell using cellfun (which applies a loop in its inner operation):
generate data:
dim = 10;
N = 400;
nc = 20;
idx = randi(nc,[N 1]);
X = rand(N,dim);
centroids = zeros(nc,dim);
mean using loop (the question's method)
for i = 1:size(centroids,1)
centroids(i, :) = mean(X(idx == i, :));
end
vectorizing:
% split X into cells by idx
A = accumarray(idx, (1:N)', [nc,1], #(i) {X(i,:)});
% mean of each cell
C = cell2mat(cellfun(#(x) mean(x,1),A,'UniformOutput',0));
maximum absolute error between the methods:
max(abs(C(:) - centroids(:))) % about 1e-16
Hi for my code I would like to know how to best save my variable column. column is 733x1. Ideally I would like to have
column1(y)=column, but I obtain the error:
Conversion to cell from logical is not possible.
in the inner loop. I find it difficult to access these stored values in overlap.
for i = 1:7
for y = 1:ydim % ydim = 436
%execute code %code produces different 'column' on each iteration
column1{y} = column; %'column' size 733x1 %altogether 436 sets of 'column'
end
overlap{i} = column1; %iterates 7 times.
end
Ideally I want overlap to store 7 variables saved that are (733x436).
Thanks.
I'm assuming column is calculated using a procedure where each column is dependent on the latter. If not, then there are very likely improvements that can be made to this:
column = zeros(733, 1); % Might not need this. Depends on you code.
all_columns = zeros(xdim, ydim); % Pre-allocate memory (always do this)
% Note that the first dimension is usually called x,
% and the second called y in MATLAB
overlap = cell(7, 1);
overlap(:) = {zeros(xdim, ydim)}; % Pre-allocate memory
for ii = 1:numel(overlap) % numel is better than length
for jj = 1:ydim % ii and jj are better than i and j
% several_lines_of_code_to_calculate_column
column = something;
all_columns(:, jj) = column;
end
overlap{ii} = all_columns;
end
You can access the variables in overlap like this: overlap{1}(1,1);. This will get the first element in the first cell. overlap{2} will get the entire matrix in the second cell.
You specified that you wanted 7 variables. Your code implies that you know that cells are better than assigning it to different variables (var1, var2 ...). Good! The solution with different variables is bad bad bad.
Instead of using a cell array, you could instead use a 3D-array. This might make processing later on faster, if you can vectorize stuff for instance.
This will be:
column = zeros(733, 1); % Might not need this. Depends on you code.
overlap = zeros(xdim, ydim, 7) % Pre-allocate memory for 3D-matrix
for ii = 1:7
for jj = 1:ydim
% several_lines_of_code_to_calculate_column
column = something;
all_column(:, jj, ii) = column;
end
end
I am refering to an example like this
I have a function to analize the elements of a vector, 'input'. If these elements have a special property I store their values in a vector, 'output'.
The problem is that at the begging I don´t know the number of elements it will need to store in 'output'so I don´t know its size.
I have a loop, inside I go around the vector, 'input' through an index. When I consider special some element of this vector capture the values of 'input' and It be stored in a vector 'ouput' through a sentence like this:
For i=1:N %Where N denotes the number of elements of 'input'
...
output(j) = input(i);
...
end
The problem is that I get an Error if I don´t previously "declare" 'output'. I don´t like to "declare" 'output' before reach the loop as output = input, because it store values from input in which I am not interested and I should think some way to remove all values I stored it that don´t are relevant to me.
Does anyone illuminate me about this issue?
Thank you.
How complicated is the logic in the for loop?
If it's simple, something like this would work:
output = input ( logic==true )
Alternatively, if the logic is complicated and you're dealing with big vectors, I would preallocate a vector that stores whether to save an element or not. Here is some example code:
N = length(input); %Where N denotes the number of elements of 'input'
saveInput = zeros(1,N); % create a vector of 0s
for i=1:N
...
if (input meets criteria)
saveInput(i) = 1;
end
end
output = input( saveInput==1 ); %only save elements worth saving
The trivial solution is:
% if input(i) meets your conditions
output = [output; input(i)]
Though I don't know if this has good performance or not
If N is not too big so that it would cause you memory problems, you can pre-assign output to a vector of the same size as input, and remove all useless elements at the end of the loop.
output = NaN(N,1);
for i=1:N
...
output(i) = input(i);
...
end
output(isnan(output)) = [];
There are two alternatives
If output would be too big if it was assigned the size of N, or if you didn't know the upper limit of the size of output, you can do the following
lengthOutput = 100;
output = NaN(lengthOutput,1);
counter = 1;
for i=1:N
...
output(counter) = input(i);
counter = counter + 1;
if counter > lengthOutput
%# append output if necessary by doubling its size
output = [output;NaN(lengthOutput,1)];
lengthOutput = length(output);
end
end
%# remove unused entries
output(counter:end) = [];
Finally, if N is small, it is perfectly fine to call
output = [];
for i=1:N
...
output = [output;input(i)];
...
end
Note that performance degrades dramatically if N becomes large (say >1000).