I have a 1xN cell, call it X, whose components X{i} (for i in {1, 2, ..., N}) are either Mx1 cells of strings or Mx1 numeric vectors.
NOTE: the fact that X contains both text cells and numeric vectors precludes using cell2mat here:
>> tmp = cell2mat(X);
Error using cell2mat (line 46)
All contents of the input cell array must be of the same data type.
My question is:
What's MATLAB's "idiomatic" way to transpose this data into an array of M 1xN cells?
EDIT: To be clear, the data structure I want to arrive at, let's call it Y, is an M-long array of 1xN cells (each consisting of a mixture of numbers and strings). E.g., if N=2, and if X{1} is an Mx1 cell of strings, and X{2} is an Mx1 vector of doubles, then the desired data structure Y is such that, for any 1 ≤ i ≤ M, Y(i,:) is a 1x2 cell whose first element is the i-th string in X{1} and whose second element is the i-th double in X{2}. I.e. Y(i,:) would be the same as the 1x2 cell Yi defined as follows
xi1 = X(i, 1);
xi2 = X(i, 2);
Yi = {xi1{1} xi2{1}};
(Sorry for the awkwardness! I just can't find a MATLAB expression for Yi directly in terms X and i, without having to create intermediate variables xi1 and xi2.)
First of all, to my knowledge there is no 'idiomatic' way of doing that i Matlab. Remember, we're talking about a complex data structure with nested cells and differing types.
I tried to cook up a solution based on cellfun. It quickly got complicated and I didn't even succeed. So instead I would recommend doing a simple double for loop and a if like this:
for a=1:size(X,2),
for b=1:size(X{a},1),
if iscell(X{a}),
Y{a,b} = X{a}{b};
else
Y{a,b} = X{a}(b);
end
end
end
If X = {{'s1';'s2'} [3; 4]} then this solution will give Y = {'s1' 3 ;'s2' 4}.
As you see I have flattened the cell to one depth. To get your 1xN vectors, do Y{1,:}
Hope it helps
If each cell in X contains a vector of the same size convert it to a matrix, transpose that matrix and then convert it back to a cell array?
tmp = cell2mat(X);
Y = mat2cell(tmp', ...);
Here is the function:
feval(#(y) feval(#(x) cellfun(#(varargin)[varargin],x{:},'un',0), cellfun(#(x) feval(#(varargin) varargin{3-varargin{1}}(), iscell(x),x,num2cell(x)),y,'un',0)), {{'1','2','3'},[4 5 6],{7,8,9}})
Or stored as a function name:
transpose_nest = #(cell_nest) feval(#(y) feval(#(x) cellfun(#(varargin)[varargin],x{:},'un',0), cellfun(#(x) feval(#(varargin) varargin{3-varargin{1}}(),iscell(x),x,num2cell(x)),y,'un',0)), cell_nest);
transpose_nest({{'1','2','3'},[4 5 6],{7,8,9}})
{{'1',4,7},{'2',5,8},{'3',6,9}}
It is based on a Matlab equivalent of Scheme's (apply map list '(("1" "2" "3") (4 5 6) (7 8 9))) that only works on sub cells:
feval(#(x) cellfun(#(varargin)[varargin],x{:},'un',0), {{'1','2','3'},{4,5,6},{7,8,9}})
{{'1',4,7},{'2',5,8},{'3',6,9}}
The extra part:
#(x) feval(#(varargin) varargin{3-varargin{1}}(), iscell(x), x, num2cell(x))
is an if statement within an anonymous function that calls num2cell if any sub element is a vector
Related
The sort() function sorts the elements row/column wise but how to sort the elements absolutely? The result should be another matrix with smallest element in (1,1) , second smallest in (1,2) and so on.
Take some random input
input = rand(5,10);
If you want the output to be a row vector, simply use
sortedRow = sort(input(:)).';
If you want the result to be the same shape as the input, then use
sortedOriginalShape = reshape(sort(input(:)), size(input,2), size(input,1)).';
Note that when maintaining the shape, we must use the reversed size dimensions and then transpose. This is because otherwise the result is column-wise i.e. smallest element in (1,1), next in (2,1) etc, which is the opposite of what you requested.
You can use the column operator (:) to vectorize all elements of 'nxm' matrix as a vector of 'nxm' elements and sort this vector. Then you can use direct assignement or 'reshape' function to store elements as matricial form.
All you need to know is that matlab use column-major-ordering to vectorize/iterate elements:
A = rand(3, 5);
A(:) = sort(A(:);
Will preserve colum-major-ordering, or as you said you prefer row-major ordering:
A = rand(3, 5);
A = reshape(sort(A(:)), fliplr(size(A)).';
Note the fliplr to store columnwise with reversed dimension and then the .' operator to transpose again the result.
EDIT
Even if matlab uses column-major-ordering for storing elements in memory, here below are two generic routines to work with row-major-order whatever the number of dimension of your array (i.e. no limited to 2D):
function [vector] = VectorizeWithRowMajorOrdering(array)
%[
axisCount = length(size(array)); % Squeezed size of original array
permutation = fliplr(1:(axisCount + 2)); % +2 ==> Trick to vectorize data in correct order
vector = permute(array, permutation);
vector = vector(:);
%]
end
function [array] = ReshapeFromRowMajorOrdering(vector, siz)
%[
siz = [siz( : ).' 1]; % Fix size if only one dim
array = NaN(siz); % Init
axisCount = length(size(array)); % Squeezed size!
permutation = fliplr(1:(axisCount + 2)); % +2 ==> Trick to vectorize data in correct order
array = reshape(vector, [1 1 fliplr(size(array))]);
array = ipermute(array, permutation);
%]
end
This can be useful when working with data coming from C/C++ (these languages use row-major-ordering). In your case this can be used this way:
A = rand(3, 5);
A = ReshapeFromRowMajorOrdering(sort(A(:)), size(A));
I have two column matrices:
size(X) = 50 x 1
size(Y) = 50 x 1
which I got from ind2sub
I want to create a structure str such that
str(i).XYZ returns [X(i), Y(i)] for i in [1,50]
I am trying to use
str = struct('XYZ', num2cell([X,Y]));
However, I believe for this to work properly, I need to modify [X,Y] to a matrix of row vectors, each row vector being [X(i), Y(i)]. Not sure if there is a better approach
You are basically on the right way, but num2cell([X,Y]) creates a 2x50 cell, which results in a 2x50 struct. You want to split your input matrix [X,Y] only among the second dimensions so each cell is a 2x1, use num2cell([X,Y],2)
str = struct('XYZ', num2cell([X,Y],2));
Concatenate the two vectors, convert from matrix to cell, and then from cell to struct array:
str = cell2struct(mat2cell([X Y], ones(1,size(X,1)), size(X,2)+size(Y,2) ).', 'XYZ');
Say I have a nxm matrix and want to treat each row as vectors in a function. So, if I have a function that adds vectors, finds the Cartesian product of vectors or for some reason takes the input of several vectors, I want that function to treat each row in a matrix as a vector.
This sounds like a very operation in Matlab. You can access the ith row of a matrix A using A(i, :). For example, to add rows i and j, you would do A(i, :) + A(j, :).
Given an nxm matrix A:
If you want to edit a single column/row you could use the following syntax: A(:, i) for the ith-column and A(i, :) for ith-row.
If you want to edit from a column/row i to a column/row j, you could use that syntax: A(:, i:j) or A(i:j, :)
If you want to edit (i.e.) from the penultimate column/row to the last one, you could you: A(:, end-1:end) or A(end-1:end, :)
EDIT:
I can't add a comment above because I don't have 50 points, but you should post the function setprod. I think you should be able to do what you want to do, by iterating the matrix you're passing as an argument, with a for-next statement.
I think you're going to have to loop:
Input
M = [1 2;
3 4;
5 6];
Step 1: Generate a list of all possible row pairs (row index numbers)
n = size(M,1);
row_ind = nchoosek(1:n,2)
Step 2: Loop through these indices and generate the product set:
S{n,n} = []; //% Preallocation of cell matrix
for pair = 1:size(row_ind,1)
p1 = row_ind(pair,1);
p2 = row_ind(pair,2);
S{p1,p2} = setprod(M(p1,:), M(p2,:))
end
Transform the matrix into a list of row vectors using these two steps:
Convert the matrix into a cell array of the matrix rows, using mat2cell.
Generate a comma-separated list from the cell array, using linear indexing of the cell contents.
Example: let
v1 = [1 2];
v2 = [10 20];
v3 = [11 12];
M = [v1; v2; v3];
and let fun be a function that accepts an arbitrary number of vectors as its input. Then
C = mat2cell(M, ones(1,size(M,1)));
result = fun(C{:});
is the same as result = fun(v1, v2, v3).
i have matrix C01 <0>, matrix C02 <50x1800 double>, matrix C3 <50x34 double> and i need to transform it to one thing C(i), for using expression like this C(1) = C01, C(2) = C02.
You need to use cell array and refer individual elements as C{1} = C01, C{2} = C02, etc.
You can also create the cell array as C = {C01, C02, C03};
Notice that you still can use C(1) syntax for cell array, but this statement will return not the original numeric matrix, but the matrix encapsulated into a cell array with one element.
Say I have a cell array of (n X 1) vectors, A, and a cell array of vectors containing indices into A, called B. I wish to extract a cell array, C, such that C{i} = [A{B{i}}].
In other words, I have a cell array of arrays of indices, and I want to pull out the matrices corresponding to the concatenations of the vectors in A indexed by each of those arrays of indices.
for i = 1:length(B)
%# B{i} is an array of indices, C{i} is a matrix
C{i} = [ A{ B{i} } ];
end
The loop is equivalent to:
C = cellfun(#(x)[A{x}],B,'UniformOutput',false); %# implicit for loop w/ closure
Can I do that using an indexing expression alone? Or at least without the loop?
I think deal() might have to be involved but can't figure it out.
Here are two alternative solutions:
Collect all the indices of B together with the function cell2mat, index the contents of A to make one large matrix, then divide that matrix up using the function mat2cell and the sizes of the index arrays in B:
N = size(A{1}); % Size of an array in A
M = cellfun('prodofsize', B); % Array of sizes of elements in B
C = mat2cell([A{cell2mat(B)}], N, M);
Here's a more compact version of your cellfun-based solution:
C = cellfun(#(x) {[A{x}]}, B);
Ultimately, I would decide what solution to use based on speed and readability, which may actually turn out to be your for-loop-based solution.
Try the following expression:
C = A(cell2mat(B))
You may have a look at Loren's blog post about Cell Arrays and Their Contents