I have a large structure array.
I would like to perform a sensitivity analysis on a function that processes this array.
So, say my structure array has name 's', 10,000 elements, and field names 'x' and 'y'.
I'd like to do the following:
xs = [s(:).x];
xs = xs + 5*randn(size(xs));
s(:).x = xs;
Sadly, the last step is not valid matlab. Any thoughts? Was hoping to avoid a loop.
From this answer and after playing around with deal. I think I have what you are looking for but it requires converting xs into a cell array using num2cell:
xs_cell = num2cell(xs); % convert matrix to cell array.
[S(:).X]=xs_cell{:}; % update the values in the field X
Related
I have two numpy arrays that are shaped (8760,1) that I want to combine into a single array that is (8760,2) and then from that, filter out any values of zero that might be in first index column, or gauge in the "data" so that I can do statistical manipulation with the temp array. I have tried np.stack and then attempted to filter out any zero values that way, but ended up with my temp array being 3D rather than still 2D.
data=np.stack((mb, gauge), axis=-1)
dta = data[:,data!=0]
idx = np.where(data[:,1]>0)
temp = data[idx,:]
I know I could filter out the zeros from gauge first, but I want to preserve the index values that go along with the mb array
np.stack joins along a newly created axis. Thus your arrays become 3D.
To join along an existing axis, you could use np.concatenate:
a1 = np.empty((100, 1))
a2 = np.empty((100, 1))
a3 = np.concatenate((a1, a2), axis=1) # will give a (100, 2) array
I am trying to carry out the intersection of two arrays in Matlab but I cannot find the way.
The arrays that I want to intersect are:
and
I have tried:[dur, itimes, inewtimes ] = intersect(array2,char(array1));
but no luck.
However, if I try to intersect array1 with array3 (see array3 below), [dur, itimes, inewtimes ] = intersect(array3,char(array1));the intersection is performed without any error.
Why I cannot intersect array1 with array2?, how could I do it?. Thank you.
Just for ease of reading, your formats for Arrays are different, and you want to make them the same. There are many options for you, like #Visser suggested, you could convert the date/time into a long int which allows faster computation, or you can keep them as strings, or even convert them into characters (like what you have done with char(Array2)).
This is my example:
A = {'00:00:00';'00:01:01'} %//Type is Cell String
Z = ['00:00:00';'00:01:01'] %//Type is Cell Char
Q = {{'00:00:00'};{'00:01:01'}} %//Type is a Cell of Cells
A = cellstr(A) %//Convert CellStr to CellStr is essentially doing nothing
Z = cellstr(Z) %//Convert CellChar to CellStr
Q = vertcat(Q{:,:}) %// Convert Cell of Cells to Cell of Strings
I = intersect (A,Z)
>>'00:00:00'
'00:01:01'
II = intersect (A,Q)
>>'00:00:00'
'00:01:01'
This keeps your dates in the format of Strings in case you want to export them back into a txt/csv file.
Your first array would look something like this:
array1 = linspace(0,1,86400); % creates 86400 seconds in 1 day
Your second array should be converted using datenum, then use cell2mat to make it a matrix. Lastly, use ismember to find the intersection:
InterSect = ismember(array2,array1);
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.