I'd like to write cell arrays of strings to csv files and overwrite parts of them with numerical data. I guess, for illustrative purposes we could use two matrices:
a = ones(5,5);
b = zeros(3,3);
I'd like to write a to a csv file and then overwrite specific fields of this file with b, resulting in:
1 1 1 1 1
1 1 1 1 1
1 1 0 0 0
1 1 0 0 0
1 1 0 0 0
Is there a way to do this in matlab? I tried
csvwrite('foo.csv', a);
dlmwrite('foo.csv', b, 'roffset', 2, 'coffset', 2)
but this would overwrite the entire file. I would be thankful for any suggestions.
Here's a solution based on Marcin's suggestion:
datsize = size(a);
precision = 6;
output_cell = reshape(cellstr(num2str(a(:),precision)), size(a));
for i = 3:datsize(1,1),
for j = 3:datsize(1,2),
output_textdata(i,j) = output_cell(i-2,j-2);
end
end
cell2csv('foo.csv', output_textdata);
While this produces the desired outcome three issues remain. First, the 'precision' varies from cell to cell. Second, which is not a problem for the intended limited application of this script, this code would produce an error if matrix b partially overlapped with matrix a and partially exceeded its dimensions, e.g., b had a size of 4x4 and were superimposed on a starting from a(3,3). Third, this workaround doesn't answer the more general question of whether only specific fields of a csv can be overwritten in matlab.
Related
I'm attempting the following as a hobby, not as homework. In Computer Programming with MATLAB: J. Michael Fitpatrick and Akos Ledeczi, there is a practice problem that asks this:
Write a function called alternate that takes two positive integers, n and m, as input arguments (the function does not have to check the format of the input) and returns one matrix as an output argument. Each element of the n-by-m output matrix for which the sum of its indices is even is 1.
All other elements are zero.
A previous problem was similar, and I wrote a very simple function that does what it asks:
function A = alternate(n,m)
A(1:n,1:m)=0;
A(2:2:n,2:2:m)=1;
A(1:2:n,1:2:m)=1;
end
Now my question is, is that good enough? It outputs exactly what it asks for, but it's not checking for the sum. So far we haven't discussed nested if statements or anything of that sort, we just started going over very basic functions. I feel like giving it more functionality would allow it to be recycled better for future use.
Great to see you're learning, step 1 in learning any programming language should be to ensure you always add relevant comments! This helps you, and anyone reading your code. So the first improvement would be this:
function A = alternate(n,m)
% Function to return an n*m matrix, which is 1 when the sum of the indices is even
A(1:n,1:m)=0; % Create the n*m array of zeros
A(2:2:n,2:2:m)=1; % All elements with even row and col indices: even+even=even
A(1:2:n,1:2:m)=1; % All elements with odd row and col indicies: odd+odd=even
end
You can, however, make this more concise (discounting comments), and perhaps more clearly relate to the brief:
function A = alternate(n,m)
% Function to return an n*m matrix, which is 1 when the sum of the indices is even
% Sum of row and col indices. Uses implicit expansion (R2016b+) to form
% a matrix from a row and column array
idx = (1:n).' + (1:m);
% We want 1 when x is even, 0 when odd. mod(x,2) is the opposite, so 1-mod(x,2) works:
A = 1 - mod( idx, 2 );
end
Both functions do the same thing, and it's personal preference (and performance related for large problems) which you should use.
I'd argue that, even without comments, the alternative I've written more clearly does what it says on the tin. You don't have to know the brief to understand you're looking for the even index sums, since I've done the sum and tested if even. Your code requires interpretation.
It can also be written as a one-liner, whereas the indexing approach can't be (as you've done it).
A = 1 - mod( (1:n).' + (1:m), 2 ); % 1 when row + column index is even
Your function works fine and output the desired result, let me propose you an alternative:
function A = alternate(n,m)
A = zeros( n , m ) ; % pre-allocate result (all elements at 0)
[x,y] = meshgrid(1:m,1:n) ; % define a grid of indices
A(mod(x+y,2)==0) = 1 ; % modify elements of "A" whose indices verify the condition
end
Which returns:
>> alternate(4,5)
ans =
1 0 1 0 1
0 1 0 1 0
1 0 1 0 1
0 1 0 1 0
initialisation:
The first line is the equivalent to your first line, but it is the cannonical MATLAB way of creating a new matrix.
It uses the function zeros(n,m).
Note that MATLAB has similar functions to create and preallocate matrices for different types, for examples:
ones(n,m) Create
a matrix of double, size [n,m] with all elements set to 1
nan(n,m) Create a
matrix of double, size [n,m] with all elements set to NaN
false(n,m) Create a
matrix of boolean size [n,m] with all elements set to false
There are several other matrix construction predefined function, some more specialised (like eye), so before trying hard to generate your initial matrix, you can look in the documentation if a specialised function exist for your case.
indices
The second line generate 2 matrices x and y which will be the indices of A. It uses the function meshgrid. For example in the case shown above, x and y look like:
| x = | y = |
| 1 2 3 4 5 | 1 1 1 1 1 |
| 1 2 3 4 5 | 2 2 2 2 2 |
| 1 2 3 4 5 | 3 3 3 3 3 |
| 1 2 3 4 5 | 4 4 4 4 4 |
odd/even indices
To calculate the sum of the indices, it is now trivial in MATLAB, as easy as:
>> x+y
ans =
2 3 4 5 6
3 4 5 6 7
4 5 6 7 8
5 6 7 8 9
Now we just need to know which ones are even. For this we'll use the modulo operator (mod) on this summed matrix:
>> mod(x+y,2)==0
ans =
1 0 1 0 1
0 1 0 1 0
1 0 1 0 1
0 1 0 1 0
This result logical matrix is the same size as A and contain 1 where the sum of the indices is even, and 0 otherwise. We can use this logical matrix to modify only the elements of A which satisfied the condition:
>> A(mod(x+y,2)==0) = 1
A =
1 0 1 0 1
0 1 0 1 0
1 0 1 0 1
0 1 0 1 0
Note that in this case the logical matrix found in the previous step would have been ok since the value to assign to the special indices is 1, which is the same as the numeric representation of true for MATLAB. In case you wanted to assign a different value, but the same indices condition, simply replace the last assignment:
A(mod(x+y,2)==0) = your_target_value ;
I don't like spoiling the learning. So let me just give you some hints.
Matlab is very efficient if you do operations on vectors, not on individual elements. So, why not creating two matrices (e.g. N, M) that holds all the indices? Have a look at the meshgrid() function.
Than you might be able find all positions with an even sum of indices in one line.
Second hint is that the outputs of a logic operation, e.g. B = A==4, yields a logic matrix. You can convert this to a matrix of zeros by using B = double(B).
Have fun!
I have searched the forum and have not found enough info to help me solve this problem.
Consider the set (cell of vectors)
A = {[1],[1 2],[2],[1 2 3],[1 2 3 4],[1 3]}
I want to construct a matrix B that looks like
B = [1 1 0 1 1 1
0 1 0 1 1 0
0 1 1 1 1 0
0 0 0 1 1 0
0 0 0 0 1 0
0 0 0 1 1 1]
The matrix B specifies membership of vectors with respect to each other. That is, the first row looks at the first element in A, [1], and checks if it is a member of the other vectors, placing a 1 if it is a member and a 0 otherwise.
I can do this using two for loops: one over the elements of A, and another nested, for each element of A, that checks membership with respect to every other member of A.
I want to avoid using for loops. Is there a vectorized solution for obtaining B from A?
With cell arrays it's hard to avoid loops, or their cousin cellfun. This is how I would do it:
[ii, jj] = ndgrid(1:numel(A)); % indices of all possible pairs
result = cellfun(#(x,y) all(ismember(x,y)), A(ii), A(jj)); % see if all elements in the
% first are present in the second
Well you asked for it, so here's an almost* vectorized solution using bsxfun and permute -
lens = cellfun('length',A)
vals = [A{:}]
mask = bsxfun(#ge,lens,[1:max(vals)]')
a = nan(size(mask))
a(mask) = vals
matches = bsxfun(#eq,a,permute(a,[3,4,1,2]));
out = bsxfun(#eq,squeeze(sum(any(matches,3),1)),lens(:))
*: Almost because of the use of cellfun at the start with cellfun('length',A), but since its just getting the length of the cells there, so computationally would be negligible .
Also, please note that this approach would use a lot of memory resources, so might not be beneficial, but just respecting the requirements of a vectorized solution as much as possible!
Given a vector of zeros and ones in MATLAB, where the zeros represent an event in time, I would like to add additional ones before and after the existing ones in order to capture additional variation.
Example: I would like to turn [0;0;1;0;0] into [0;1*;1;1*;0] where 1* are newly added ones.
Assuming A to be the input column vector -
%// Find all neighbouring indices with a window of [-1 1]
%// around the positions/indices of the existing ones
neigh_idx = bsxfun(#plus,find(A),[-1 1])
%// Select the valid indices and set them in A to be ones as well
A(neigh_idx(neigh_idx>=1 & neigh_idx<=numel(A))) = 1
Or use imdilate from Image Processing Toolbox with a vector kernel of ones of length 3 -
A = imdilate(A,[1;1;1])
You can do it convolving with [1 1 1], and setting to 1 all values greater than 0. This works for column or row vactors.
x = [0;0;1;0;0];
y = double(conv(x, [1 1 1],'same')>0)
Purely by logical indexing:
>> A = [0 1 1 0 0];
>> A([A(2:end) 0] == 1 | [0 A(1:end-1)] == 1) = 1;
>> disp(A);
A =
1 1 1 1 0
This probably merits an explanation. The fact that it's a 3 element local neighbourhood makes this easy. Essentially, take two portions of the input array:
Portion #1: A starting from the second element to the last element
Portion #2: A starting from the first element to the second-last element
We place the first portion into a new array and add 0 at the end of this array, and check to see which locations are equal to 1 in this new array. This essentially shifts the array A over to the left by 1. Whichever locations in this first portion are equal to 1, we set the corresponding locations in A to be 1. The same thing for the second portion where we are effectively shifting the array A over to the right by 1. To shift to the right by 1, we prepend a 0 at the beginning, then extract out the second portion of the array. Whichever locations in this second portion are equal to 1 are also set to 1.
At the end of this operation, you would essentially shift A to the left by 1 and save this as a separate array. Also, you would shift to the right by 1 and save this as another array. With these two, you simply overlap on top of the original to obtain the final result.
The benefit of this method over its predecessors in this post is that this doesn't require computations of any kind (bsxfun, conv, imdilate etc.) and purely relies on indexing into arrays and using logical operators1. This also handles boundary conditions and can work on either row or column vectors.
Some more examples with boundary cases
>> A = [0 0 1 1 0];
>> A([A(2:end) 0] == 1 | [0 A(1:end-1)] == 1) = 1
A =
0 1 1 1 1
>> A = [0 0 0 0 1];
>> A([A(2:end) 0] == 1 | [0 A(1:end-1)] == 1) = 1
A =
0 0 0 1 1
>> A = [1 0 1 0 1];
>> A([A(2:end) 0] == 1 | [0 A(1:end-1)] == 1) = 1
A =
1 1 1 1 1
1: This post is dedicated to Troy Haskin, one who believes that almost any question (including this one) can be answered by logical indexing.
I'm reading some MATLAB trying to pick it up. The line below is probably rather simple but I do not understand it.
I understand length will give me the length of a vector, in this case a vector which is part of a struct, index_struct.data_incl.
The actual value of index_stuct.data_incl at run time is simply 1. What is confusing me is what is inside the brackets i.e. (index_struct.data_incl == 1)? I can't work out what this line is trying to do as simple as it may be!
int_var = length(index_struct.data_incl(index_struct.data_incl == 1));
try this (but think of x as your index_struct.data_incl:):
x = [1 4 5 13 1 1]
length(x(x==1))
ans =
3
It's just counting the number of elements of your x vector that are equal to 1
because x==1 evaluates to [1 0 0 0 1 1] and then using logical indexing x(x==1) evaluates to [1 1 1] whose length is 3;
It could have been written more simply as sum(index_struct.data_incl == 1)
If I dont see the code I can only guess..., but I guess that index_struc.data_incl should be a vector, with length n meaning that you have the option to read until n files, and all the values of the array should be 0 at the begining, and when you read a file you change the corresponding position in the vector index_struc.data_incl from 0 to 1. After some time you can see how many of these files you have read using
int_var = length(index_struct.data_incl(index_struct.data_incl == 1));
because it will give to you the number of 1 in the vector index_struct.data_incl.
I have a 50x50 matrix named nghlist(i,j) containing 0 and 1 values. 1 means there is a relation between (i,j).
There is another 5x50 matrix named chlist.
I need to check the nghlist matrix and if there is any connection between i and j (nghlist(i,j)==1) then I need to go to the chlist matrix and compare the values on column i and column j. For example compare columns (1,3,8,21,52) and get how many similar values they share together. i.e. I find all those columns have 3 similar values.
I tried using following code. But the problem is I need to compare the unknown number of columns (depend on the node connection (nghlist) for example 4 or 5 columns) together.
for i=1:1:n
for j=1:1:n
if (i~=j & nghlist(i,j)==1)
sum(ismember(chlist(:,i),chlist(:,j)));
end
end
end
Any help is highly appreciated.
++++ simplified example ++++++
take a look at the example http://i.imgur.com/mQjDqzz.jpg
nghlist matrix:
1 1 1 0 0
1 1 1 0 0
1 1 1 1 1
0 0 1 1 1
0 0 1 1 1
chlist matrix:
3 1 4 5 4
4 3 5 6 5
5 4 6 7 6
In this example since node 1 is connected to nodes 2 and 3, I need to compare column 1,2 and 3 from chlist. The output would be 1 (because they only share value '4').
And this value for node 5 would be 2 (because columns 3,4 and 5 only share value '5' and '6'). I hope now it is clear.
If the result of your simplified example is [1,2,0,3,2] then the following code worked for me.
(Matrix a stands for nghlist and matrix b for chlist, result is stored in s )
for i = 1:size(a,1)
s(i)=0;
row = a(i,:);
idx = find(row==1);
idx = idx(idx~=i);
tempb = b(:,idx);
for j=1:size(tempb,1)
if sum(sum(tempb==tempb(j,1)))==size(tempb,2)
s(i)=s(i)+1;
end
end
end
For every node you find all the ones in its row, then discard the one referring to the node itself. Pick the appropriate columns of chlist (line 6) and create a new matrix. For every element of the 1st column of this matrix check if it exists in all other columns.If it does, update the s value
Let's say, the indices of the columns that are to be compared is called idxList:
idxList = [1,3,8,21,50];
You may compare all with the first one and use "AND" to find the minimum number of shared values:
shared = ones(size(chlist(:,i)))
for ii = 2:length(idxList)
shared = (shared == (chlist(:,idxList(1)) == chlist(:,idxList(ii))))
end
Finally, sum as before
sum(shared)
I haven't checked the exact code, but the concept should become clear.
I manage to solve it this way. I compare the first and second column of tempb and put the result in tem. then compare tem with third column of tempb and so on. Anyway thank you finmor and also pyStarter, your codes has inspired me. However I knew its not the best way, but at least it works.
for i=1:size(nghlist,1)
s(i)=0;
j=2;
row=nghlist(i,:);
idx=find(row==1);
tempb=chlist(:,idx);
if (size(tempb,2)>1)
tem=intersect(tempb(:,1),tempb(:,2));
if (size(tempb,2)<=2)
s(i)=size(tem,1);
end
while (size(tempb,2)>j & size(tem)~=0)
j=j+1;
tem= intersect(tem(:,1),tempb(:,j));
s(i)=size(tem,1);
end
end
end