I have an m-by-n matrix named A, with values 1s and 0s. I want to convert all 0s values to 1s if at least 5 out of 8 neighbor pixels are 1s. What I tried is to use the nlfilter function, but I'm not getting how the arg fun should be used, and I would need a help.
I created a function as handle for nlfilter as following:
function b = gap_fill(A)
b=A;
index= A([1 2 3 4 6 7 8 9]);
if sum(index)>=5
b(5)= 1
end
end
Then I tried to do this:
B= nlfilter(A,[3 3],#gap_fill)
But it gave this error:
??? Subscripted assignment dimension mismatch.
Error in ==> nlfilter at 75
b(i,j) = feval(fun,x,params{:});
Any suggestion? The main problem is I'm not used to handle functions.
= UPDATING =
I finally came up with a good result. I changed my function to output a scalar and when I use it as fun arg in nlfilter it work the way I want. This is my code, thanks for helping and I hope it could be useful for anybody:
function b = gap_fill(A)
index= A([1 2 3 4 6 7 8 9]);
if sum(index)>=5
A(5)= 1;
end
b=A(5);
end
In MATLAB:
b= nlfilter (A,[3 3],'gap_fill')
You can do it in one line with blockproc:
B = blockproc(A,[1 1],#(x)sum(x.data(:)),'BorderSize',[1 1],'TrimBorder',0)-A>=5;
For example,
A =
1 0 1 1 0
0 0 0 1 1
1 1 1 1 1
0 1 0 1 1
gives the result
B =
0 0 0 0 0
0 1 1 1 0
0 0 1 1 1
0 0 1 0 0
Note that border pixels of the image are handled correctly, thanks to using the 'BorderSize' option of blockproc.
To keep the original ones in A, apply a final "or" operation:
B = B|A;
I think it is because the documentation for nlfilter says that the user function must return a scalar and you are trying to return a matrix.
B = nlfilter(A, [m n], fun) applies the function fun to each m-by-n sliding block
of the grayscale image A. fun is a function that accepts an m-by-n matrix as input
and returns a scalar (!!!) result.
For a solution that's slightly faster than blockproc, you can use a 2D convolution:
mask = ones(3);
mask(5) = 0;
B = conv2(A,mask,'same') >= 5;
To make this even faster (you'll only notice this if the arrays become larger), you can make use of the fact that an average filter is separable:
B = conv2(conv2(A,ones(1,3),'same'),ones(3,1),'same') - A >= 5;
The fun function must return an scalar in your case it returns a matrix. from matlab
B = nlfilter(A, [m n], fun) applies the function fun to each m-by-n sliding block of the grayscale image A. fun is a function that accepts an m-by-n matrix as input and returns a scalar result.
c = fun(x)
so your code shoud be There are better ways to code it,specially with amtrix but following your sample:
function b = gap_fill(A)
index= A([1 2 3 4 6 7 8 9]);
if A(5)sum(index)>=5
b = 1;
else
b = A(5);
end
end
Sorry for the error I change b = 0 to b= A(5)
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!
New to MATLAB, and I need help with the following issue.
I want to create a function val=F(v,e) that takes in two inputs v, a 1xn vector, and a scalar e, and outputs a scalar val that counts the nonzero entries of the vector v-e, i.e. the vector v with e subtracted from all each of its entries. My code for the function is below:
function val = eff(vec, e)
val = sum( (vec - e > 0) );
end
When I evaluate the function at a single point it works as it should. but I want a plot of this function on (0,1). Plotting it gives a constant value over the entire range of e. I am using the following code on the main
figure
e = linspace(0,1);
plot(e, eff(rand(1,100),e),'o',e, e)
Also, when I use a small vector, say, rand(1,10), I get the following error message:
>Error using -
>
>Matrix dimensions must agree.
>
>Error in eff (line 3)
>
>val = sum( (vec - e > 0 ));
Is my function being too careless with matrix dimensions? Or is there an easier way to evaluate eff over a vector range?
Thanks in advance.
You have created a function which is designed to be applied only with a scalar e argument, and where passing e as an array would potentially cause errors ... but then you call it with e = linspace(0,1) which is an array.
The particular error when e is of size 10 is telling you that you cannot subtract it from a matrix of size 100.
When e happens to have the same size as vec, your function subtracts two equal-sized arrays, and returns their sum, which is a scalar. Therefore your plot is essentially doing something like plot(a_range, a_scalar), which is why it looks constant.
Instead, you should probably collect an array V for each value of e in a for loop, or using arrayfun, e.g.
e = linspace(0,1);
V = arrayfun(#eff, e);
and then plot e against V
Alternatively, you could rewrite your function such that it expects e to be an array, and your return value is an array of the same size as e, filled with the appropriate values.
without using arrayfun, your task can also be accomplished using broadcasting. I noticed you had this question tagged Octave as well as Matlab. Octave uses automatic broadcasting when you attempt elementwise operations with vectors in different dimensions. Matlab can do broadcasting with the bsxfun function. (if you want code that will run in either program, Octave also can use bsxfun.) Also, according to the release notes I believe Matlab 2016b will now include automatic broadcasting, although I cannot confirm yet that it will behave the same as Octave does.
Because your vectors vec and e are both row vectors, when you try to subtract them Matlab/Octave will subtract each element if they have the same size, or give a size mismatch error if they do not.
If you instead create one of the vectors as a column vector, broadcasting can take over. a simple example:
>> a = [1:4]
a =
1 2 3 4
>> b = [1:4]'
b =
1
2
3
4
>> a-b //Error in Matlab versions before 2016b
ans =
0 1 2 3
-1 0 1 2
-2 -1 0 1
-3 -2 -1 0
>> bsxfun(#minus,a,b) //works under Octave or Matlab
ans =
0 1 2 3
-1 0 1 2
-2 -1 0 1
-3 -2 -1 0
So, if you are running Octave, your code will run correctly if you just rewrite your function so the vectors use different dimensions. There are a number of ways to do this, but since both Matlab and Octave default to column ordering, you can use the : operator to force them to work the way you want. E.g.:
>> a = [1:4]
a =
1 2 3 4
>> a(:)
ans =
1
2
3
4
>> a(:)'
ans =
1 2 3 4
>> b = [1:4]'
b =
1
2
3
4
>> b(:)
ans =
1
2
3
4
>> b(:)'
ans =
1 2 3 4
So, after all that, you can rewrite your function:
function val = eff(vec, e)
vec = vec(:);
e = e(:)';
val = sum ( (vec-e ) > 0 );
end
If you're running matlab, or you want code that could run in both Octave and Matlab, you can just replace the last line of the function with:
sum ( bsxfun(#minus,vec,e) > 0 )
Finally, if you want, you can add some 'isvector' error checking at the beginning of the function in case you accidentally pass it an array. And note that had I chosen to make 'vec' a row vector and 'e' a column vector I would have had to tell the sum function which dimension to sum over. (it defaults to summing each column and returning a row vector, which matches the choices I made above.)
you function works fine as long as e is a scaler and not an array or matrix. You can then you looping or arrayfun (as already answered) to get a final answer
figure
e = rand(1,10); % create 10 random e numbers
vec = rand(1,100);
for inc = 1:length(e)
v(inc) = eff(vec,e(inc));
end
scatter(e,v);
I am trying to compare two vectors of different size. For instance when I run the code below:
A = [1 4 3 7 9];
B = [1 2 3 4 5 6 7 8 9];
myPadded = [A zeros(1,4)];
C = ismember(myPadded,B)
I get the following output:
C = 1 1 1 1 1 0 0 0 0
However, I want an output that will reflect the positions of the compared values, hence, I would like an output that is displayed as follows:
C = 1 0 1 1 0 0 1 0 1
Please, I need some help :)
There are 2 points. First, you are writing the inputs of ismember in the wrong order. Additionally, you do not need to grow your matrix. Simply try ismember(B, A) and you will get what you expect.
The function ismember(myPadded, B) returns a vector the same size of myPadded, indicating if the i-th element of myPadded is present in B.
To get what you want, just invert parameter order: ismember(B, myPadded).
A quick way of doing this is to use logical indexing. This will only work if the last digit of B is included in A.
A = [1 4 3 7 9];
c(A) = 1; % or true.
An assumption here is that you want to subindex a vector 1:N, so that B always is B = 1:N. In case the last digit is not one this is easy to fix. Just remember to return all to its previous state after you are done. It will be 2 rows extra though.
This solution is meant as a special case working on a very common problem.
I believe most functions in MATLAB should be able to receive matrix input and return the output in the form of matrix.
For example sqrt([1 4 9]) would return [1 2 3].
However, when I tried this recurring factorial function:
function k = fact(z)
if z ~= 0
k = z * fact(z-1);
else
k = 1;
end
end
It works perfectly when a number is input into fact. However, when a matrix is input into fact, it returns the matrix itself, without performing the factorial function.
E.g.
fact(3) returns 6
fact([1 2 3]) returns [1 2 3] instead of [1 2 6].
Any help is appreciated. Thank you very much!
Since MATLAB is not known to be good with recursive functions, how about a vectorized approach? Try this for a vector input -
mat1 = repmat([1:max(z)],[numel(z) 1])
mat1(bsxfun(#gt,1:max(z),z'))=1
output1 = prod(mat1,2)
Sample run -
z =
1 2 7
output1 =
1
2
5040
For the sake of answering your original question, here's the annoying loopy code for a vector or 2D matrix as input -
function k1 = fact1(z1)
k1 = zeros(size(z1));
for ii = 1:size(z1,1)
for jj = 1:size(z1,2)
z = z1(ii,jj);
if z ~= 0
k1(ii,jj) = z .* fact1(z-1);
else
k1(ii,jj) = 1;
end
end
end
return
Sample run -
>> fact1([1 2 7;3 2 1])
ans =
1 2 5040
6 2 1
You can use the gamma function to compute the factorial without recursion:
function k = fact(z)
k = gamma(z+1);
Example:
>> fact([1 2 3 4])
ans =
1 2 6 24
Not sure if all of you know, but there is an actual factorial function defined in MATLAB that can take in arrays / matrices of any size, and computes the factorial element-wise. For example:
k = factorial([1 2 3 4; 5 6 7 8])
k =
1 2 6 24
120 720 5040 40320
Even though this post is looking for a recursive implementation, and Divakar has provided a solution, I'd still like to put my two cents in and suggest an alternative. Also, let's say that we don't have access to factorial, and we want to compute this from first principles. What I would personally do is create a cell array that's the same size as the input matrix, but each element in this cell array would be a linear index array from 1 up to the number defined for each location in the original matrix. You would then apply prod to each cell element to compute the factorial. A precondition is that no number is less than 1, and that all elements are integers. As such:
z1 = ... ; %// Define input matrix here
z1_matr = arrayfun(#(x) 1:x, z1, 'uni', 0);
out = cellfun(#prod, z1_matr);
If z1 = [1 2 3 4; 5 6 7 8];, from my previous example, we get the same output with the above code:
out =
1 2 6 24
120 720 5040 40320
This will obviously be slower as there is an arrayfun then cellfun call immediately after, but I figured I'd add another method for the sake of just adding in another method :) Not sure how constructive this is, but I figured I'd add my own method and join Divakar and Luis Mendo :)
new_img is ==>
new_img = zeros(height, width, 3);
curMean is like this: [double, double, double]
new_img(rows,cols,:) = curMean;
so what is wrong here?
The line:
new_img(rows,cols,:) = curMean;
will only work if rows and cols are scalar values. If they are vectors, there are a few options you have to perform the assignment correctly depending on exactly what sort of assignment you are doing. As Jonas mentions in his answer, you can either assign values for every pairwise combination of indices in rows and cols, or you can assign values for each pair [rows(i),cols(i)]. For the case where you are assigning values for every pairwise combination, here are a couple of the ways you can do it:
Break up the assignment into 3 steps, one for each plane in the third dimension:
new_img(rows,cols,1) = curMean(1); %# Assignment for the first plane
new_img(rows,cols,2) = curMean(2); %# Assignment for the second plane
new_img(rows,cols,3) = curMean(3); %# Assignment for the third plane
You could also do this in a for loop as Jonas suggested, but for such a small number of iterations I kinda like to use an "unrolled" version like above.
Use the functions RESHAPE and REPMAT on curMean to reshape and replicate the vector so that it matches the dimensions of the sub-indexed section of new_img:
nRows = numel(rows); %# The number of indices in rows
nCols = numel(cols); %# The number of indices in cols
new_img(rows,cols,:) = repmat(reshape(curMean,[1 1 3]),[nRows nCols]);
For an example of how the above works, let's say I have the following:
new_img = zeros(3,3,3);
rows = [1 2];
cols = [1 2];
curMean = [1 2 3];
Either of the above solutions will give you this result:
>> new_img
new_img(:,:,1) =
1 1 0
1 1 0
0 0 0
new_img(:,:,2) =
2 2 0
2 2 0
0 0 0
new_img(:,:,3) =
3 3 0
3 3 0
0 0 0
Be careful with such assignments!
a=zeros(3);
a([1 3],[1 3]) = 1
a =
1 0 1
0 0 0
1 0 1
In other words, you assign all combinations of row and column indices. If that's what you want, writing
for z = 1:3
newImg(rows,cols,z) = curMean(z);
end
should get what you want (as #gnovice suggested).
However, if rows and cols are matched pairs (i.e. you'd only want to assign 1 to elements (1,1) and (3,3) in the above example), you may be better off writing
for i=1:length(rows)
newImg(rows(i),cols(i),:) = curMean;
end