# MATLAB one-liners

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Andrew Newell on 3 Mar 2011
One of the joys of using MATLAB is that it has a stock of matrix functions like diff, sort, all, and so on, that can be combined in all sorts of interesting ways. For example, in a recent question, the challenge was to find a compact code to determine which columns of a matrix A have all elements equal. Matt Tearle came up with this nifty answer:
all(~diff(A))
What are your favorite one-line MATLAB expressions?

Walter Roberson on 3 Mar 2011
cell2mat(arrayfun(@(K) accumarray(C, F(:,K), [], @mean), 1:size(F,2), 'Uniform', 0))
In response to a cssm question:
I have a feature matrix, F(m, n) and a cluster vector, C(m, 1).
Now I want to get the mean of feature in F according to C. Make
it simple as below:
F = [2 5; 3 7; 8 4]
C = [2; 1; 2]
output should be [3 7; (2+8)/2 (5+4)/2]
=[3 7; 5 4.5]
##### 2 CommentsShowHide 1 older comment
Andrew Newell on 28 Mar 2011
Even though BSXFUN is missing, I decided to accept this one. Very clever, @Walter!

Matt Tearle on 3 Mar 2011
I'm a huge fan of logical indexing. Expressions like
mean(frogs(wombats > 42))
rock my world.
Andrew Newell on 3 Mar 2011
I like it!

Sean de Wolski on 3 Mar 2011
Here's another from a thread today:
Given a connected components analysis (bwconncomp) and some criteria for objects to meet: remove objects that don't meet that criteria from your binary image:
I(cell2mat(CC.PixelIdxList(~idx)')) = false;
Sean de Wolski on 3 Mar 2011
idx can usually be a one line expression from cellfun making this a super-awesome-long-one-liner.

Matt Fig on 3 Mar 2011
Here is a good one. After already writing a solution to this Question, I stumbled upon this:
groups = mat2cell(A,diff([0;find(diff(A) ~= 1);length(A)]),1);
Pretty Slick.
Walter Roberson on 3 Mar 2011
Ah, I found my copy, and it was _not_ a 1 liner. I had used
b=diff(a); %find differences
idx = find([b 2]>1); %find their indexes
cel = mat2cell(a, 1, [idx(1) diff(idx)]); %break up the matrix

Matt Tearle on 3 Mar 2011
Inspired by something I'm working on right now & your comment to my previous answer...
If you have an n-by-1 structure array people with a field suck (which contains a scalar for each struct element), and you want to find the average:
mean([people.suck])
Extract multiple elements, concatenate, apply function. All in one line.
Andrew Newell on 3 Mar 2011
I like compact expressions with social commentary.

Andrew Newell on 3 Mar 2011
Turn a structure array S into a cell array with the names of the fields in the first column:
C = horzcat(fieldnames(S), squeeze(struct2cell(S)))

Andrew Newell on 6 Mar 2011
Here is a real beauty from a comment by Tim Davis on a guest blog for Loren Shure. Suppose you have three 2D vectors p1, p2 and p3, and you want to know if they are collinear. The shortest solution also happens to be numerically the most reliable:
rank ([p2-p1 ; p3-p1]) < 2
It is also easily generalized to more dimensions!

Oleg Komarov on 3 Mar 2011
eval('fliplr(['''' 33 33 33 33 33 76 105 118 69 32 109 39 73 ''''])')
MuAhahauHAh!!!
the cyclist on 28 Mar 2011
I used to be an admin on a chess server where "qu" could be used as a shorthand to quit out of the interface. A common prank was to tell newbies that "qu" could be used to display the "quote of the day".

Andrew Newell on 4 Mar 2011
Here is an interesting way of calculating n rows of Pascal's triangle:
round(expm(diag(1:n-1,-1)))
Now if we could just remove the zeros and center it on the same line!
Andrew Newell on 29 Mar 2011
Wow! Three nested cellfuns! This deserves a separate answer.

Drew Weymouth on 4 Mar 2011
Read in an image and convert it to a grayscale, double matrix of data range 0..1
Walter Roberson on 4 Mar 2011
Your code would fail for images that happened to be already double or happened to be uint16.

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