I currently have a column vectors of different lengths and I want to insert another column vector at various points of the original array. i.e. I want to add my new array to the start of the old array skip 10 places add my new array again, skip another 10 spaces and add my new array again and so on till the end of the array. I can do this by using:
OffsetSign = [1:30]';
Extra = [0;0;0;0;0];
OffsetSign =[Extra;OffsetSign(1:10);Extra;OffsetSign(11:20);Extra;OffsetSign(21:30)];
However this is not suitable for longer arrays. Any tips on an easy way to do this for longer arrays?
here's one way to do it:
a = [1:30]';
b = [0;0;0;0;0];
a=reshape(a,10,[]);
b=repmat(b,[1 size(a,2)])
r=[b ; a]
r=r(:);
the trick is to reshape a to a matrix with columns of the right size (10 elements each). Replicate b to this # of columns , concatenate both and flatten the matrix to a vector...
Related
I know mapping 2D array into 1D array has been asked many times, but I did not find a solution that would fit a where the column count varies.
So I want get a 1-dimensional index from this 2-dimensional array
Col> _0____1____2__
Row 0 |_0__|_1__|_2__|
V 1 |_3__|_4__|
2 |_5__|_6__|_7__|
3 |_8__|_9__|
4 |_10_|_11_|_12_|
5 |_13_|_14_|
The normal formula index = row * columns + column does not work, since after the 2nd row the index is out of place.
What is the correct formula here?
EDIT:
The specific issue is that I have a list of items in with the layout like in the grid, but a one dimensional array for the data. So while looping through the elements in the UI, I need to get the correct data, but can only get the row and column for that element. I need to find a way to turn a row/column value into an index for the data-array
Bad picture trying to explain it
A truly optimal answer (or even a provably correct one) will depend on the language you are using and how it lays out memory for such arrays.
However, taking your question simply at face value, you have to know what the actual length of each row is in order to calculate a 1D index.
So either the row length follows some pattern that can be inferred from the data, or you have (or can write) a rlen = rowLength( 2dTable, RowNumber) function.
Then, depending on how big the tables are and how fast you need to run, you can calculate a 1D index from the 2d table by adding all the previous row lengths until the current row length is less than the 2d column index.
or build a 1d table of the row lengths (or commulative rowlengths) so you can scan it and so only call your rowlength function for each row only once.
With a better description of your problem, you might get a better answer...
For your example which alternates between 3 and 2 columns you can construct a formula:
index = (row / 2) * (3 + 2) + (row % 2 ? 3 : 0) + column
(C-like syntax, assuming integer division)
In general though, the one and only way to implement what you're doing here, jagged arrays, is to make an array of arrays, a.k.a. an Iliffe vector. That means, use the row number as index into an array of pointers which point to the individual row arrays containing the actual data.
You can have an additional 1D array having the length of the columns say "length". Then your formula is index=sum {length(i)}+column. i runs from 0 to row.
I have an N-dimensional array of items whose last dimension is the index of the array.
For example, if the array A contained images, then A(:,:,:,1) would be the first image, A(:,:,:,2) would be the second image, and so forth.
Similarly, if the array just contained integers, then A(:,1) would be the first integer, A(:,2) would be the second integer, and so forth.
-=-=-=-
What I'm trying to do is delete the first item from A when I do not know ahead of time what dimensionality it is.
If A contains images, I want to do this:
A(:,:,:,1) = [];
If A contains integers, I want to do this:
A(:,1) = [];
The problem is since I don't know what dimensionality it is, I don't know how many colons to put, and I don't know how to denote "N-1 colons here" in Matlab.
I'm hoping there is a programmatic way to do this, but I frankly have no idea what to search for if this is possible.
You can either use cell to comma-separated list expansion:
%// Build cell: {':', ':', ..., ':', [1]}
I(1:ndims(A)-1) = {':'};
I{ndims(A)} = 1;
%// Expand cell to comma separated list and delete:
A(I{:}) = [];
Or convert to cell using num2cell and then convert back using cell2mat:
C = num2cell(A,1:ndims(A)-1);
A = cell2mat(C(2:end));
I guess that unless you really need n-dimensional arrays, doing this with a cell array of n-1 dimensional arrays instead (as is C in the above code) should be a smart move in terms of simplicity of notation.
I'm quite new to MatLab and this problem really drives me insane:
I have a huge array of 2 column and about 31,000 rows. One of the two columns depicts a spatial coordinate on a grid the other one a dependent parameter. What I want to do is the following:
I. I need to split the array into smaller parts defined by the spatial column; let's say the spatial coordinate are ranging from 0 to 500 - I now want arrays that give me the two column values for spatial coordinate 0-10, then 10-20 and so on. This would result in 50 arrays of unequal size that cover a spatial range from 0 to 500.
II. Secondly, I would need to calculate the average values of the resulting columns of every single array so that I obtain per array one 2-dimensional point.
III. Thirdly, I could plot these points and I would be super happy.
Sadly, I'm super confused since I miserably fail at step I. - Maybe there is even an easier way than to split the giant array in so many small arrays - who knows..
I would be really really happy for any suggestion.
Thank you,
Arne
First of all, since you wish a data structure of array of different size you will need to place them in a cell array so you could try something like this:
res = arrayfun(#(x)arr(arr(:,1)==x,:), unique(arr(:,1)), 'UniformOutput', 0);
The previous code return a cell array with the array splitted according its first column with #(x)arr(arr(:,1)==x,:) you are doing a function on x and arrayfun(function, ..., 'UniformOutput', 0) applies function to each element in the following arguments (taken a single value of each argument to evaluate the function) but you must notice that arr must be numeric so if not you should map your values to numeric values or use another way to select this values.
In the same way you could do
uo = 'UniformOutput';
res = arrayfun(#(x){arr(arr(:,1)==x,:), mean(arr(arr(:,1)==x,2))), unique(arr(:,1)), uo, 0);
You will probably want to flat the returning value, check the function cat, you could do:
res = cat(1,res{:})
Plot your data depends on their format, so I can't help if i don't know how the data are, but you could try to plot inside a loop over your 'res' variable or something similar.
Step I indeed comes with some difficulties. Once these are solved, I guess steps II and III can easily be solved. Let me make some suggestions for step I:
You first define the maximum value (maxValue = 500;) and the step size (stepSize = 10;). Now it is possible to iterate through all steps and create your new vectors.
for k=1:maxValue/stepSize
...
end
As every resulting array will have different dimensions, I suggest you save the vectors in a cell array:
Y = cell(maxValue/stepSize,1);
Use the find function to find the rows of the entries for each matrix. At each step k, the range of values of interest will be (k-1)*stepSize to k*stepSize.
row = find( (k-1)*stepSize <= X(:,1) & X(:,1) < k*stepSize );
You can now create the matrix for a stepk by
Y{k,1} = X(row,:);
Putting everything together you should be able to create the cell array Y containing your matrices and continue with the other tasks. You could also save the average of each value range in a second column of the cell array Y:
Y{k,2} = mean( Y{k,1}(:,2) );
I hope this helps you with your task. Note that these are only suggestions and there may be different (maybe more appropriate) ways to handle this.
I have a two arrays within a <1x2 cell>. I want to permute those arrays. Of course, I could use a loop to permute each one, but is there any way to do that task at once, without using loops?
Example:
>> whos('M')
Name Size Bytes Class Attributes
M 1x2 9624 cell
>> permute(M,p_matrix)
This does not permute the contents of the two arrays within M.
I could use something like:
>> for k=1:size(M,2), M{k} = permute(M{k},p_matrix); end
but I'd prefer not to use loops.
Thanks.
This seems to work -
num_cells = numel(M) %// Number of cells in input cell array
size_cell = size(M{1}) %// Get sizes
%// Get size of the numeric array that will hold all of the data from the
%// input cell array with the second dimension representing the index of
%// each cell from the input cell array
size_num_arr = [size_cell(1) num_cells size_cell(2:end)]
%// Dimensions array for permuting with the numeric array holding all data
perm_dim = [1 3:numel(size_cell)+1 2]
%// Store data from input M into a vertically concatenated numeric array
num_array = vertcat(M{:})
%// Reshape and permute the numeric array such that the index to be used
%// for indexing data from different cells ends up as the final dimension
num_array = permute(reshape(num_array,size_num_arr),perm_dim)
num_array = permute(num_array,[p_matrix numel(size_cell)+1])
%// Save the numeric array as a cell array with each block from
%// thus obtained numeric array from its first to the second last dimension
%// forming each cell
size_num_arr2 = size(num_array)
size_num_arr2c = num2cell(size_num_arr2(1:end-1))
M = squeeze(mat2cell(num_array,size_num_arr2c{:},ones(1,num_cells)))
Some quick tests show that mat2cell would prove to be the bottleneck, so if you don't mind indexing into the intermediate numeric array variable num_array and use it's last dimension for an equivalent indexing into M, then this approach could be useful.
Now, another approach if you would like to preserve the cell format would be with arrayfun, assuming each cell of M to be a 4D numeric array -
M = arrayfun(#(x) num_array(:,:,:,:,x),1:N,'Uniform',0)
This seems to perform much better than with mat2cell in terms of performance.
Please note that arrayfun isn't a vectorized solution as most certainly it uses loops behind-the-scenes and seems like mat2cell is using for loops inside its source code, so please do keep all these issues in mind.
I need to create a 1-D array of 2-D arrays, so that a program can read each 2-D array separately.
I have a large array with 5 columns, with the second column storing 'marker' data. Depending on the marker value, I need to take the corresponding data from the remaining 4 columns and put them into a new array on its own.
I was thinking of having two for loops running, one to take the target data and write it to a cell in the 1-D array, and one to read the initial array line-by-line, looking for the markers.
I feel like this is a fairly simple issue, I'm just having trouble figuring out how to essentially cut and paste certain parts of an array and write them to a new one.
Thanks in advance.
No for loops needed, use your marker with logical indexing. For example, if your large array is A :
B=A(A(:,2)==marker,[1 3:5])
will select all rows where the marker was present, without the 2nd col. Then you can use reshape or the (:) operator to make it 1D, for example
B=B(:)
or, if you want a one-liner:
B=reshape(A(A(:,2)==marker,[1 3:5]),1,[]);
I am just answering my own question to show any potential future users the solution I came up with eventually.
%=======SPECIFY CSV INPUT FILE HERE========
MARKER_DATA=csvread('ESphnB2.csv'); % load data from csv file
%===================================
A=MARKER_DATA(:,2); % create 1D array for markers
A=A'; % make column into row
for i=1:length(A) % for every marker
if A(i) ~= 231 % if it is not 231 then
A(i)=0; % set value to zero
end
end
edgeArray = diff([0; (A(:) ~= 0); 0]); % set non-zero values to 1
ind = [find(edgeArray > 0) find(edgeArray < 0)-1]; % find indices of 1 and save to array with beginning and end
t=1; % initialize counter for trials
for j=1:size(ind,1) % for every marked index
B{t}=MARKER_DATA(ind(j,1):ind(j,2),[3:6]); % create an array with the rows from the data according to indicies
t=t+1; % create a new trial
end
gazeVectors=B'; % reorient and rename array of trials for saccade analysis
%======SPECIFY MAT OUTPUT FILE HERE===
save('Trial_Data_2.mat','gazeVectors'); % save array to mat file
%=====================================