I need this section of my code to run faster, as it is called many many times. I am new to Matlab and I feel as though there MUST be a way to do this that is not so round-about. Any help you could give on how to improve the speed of what I have or other functions to look into that would help me perform this task would be appreciated.
(Task is to get only lines of "alldata" where the first column is in the set of "minuteintervals" into "alldataMinutes". "minuteintervals" is just the minimum value of "alldata" column one increasing by twenty to the maximum of alldata.
minuteintervals= min(alldata(:,1)):20:max(alldata(:,1)); %20 second intervals
alldataMinutes= zeros(30000,4);
counter=1;
for x=1:length(alldata)
if ismember(alldata(x,1), minuteintervals)
alldataMinutes(counter,:)= alldata(x,:);
counter= counter+1;
end
end
alldataMinutes(counter:length(alldataMinutes),:)= [];
This should give you what you want, and it should be substantially faster:
minuteintervals = min(alldata(:,1)):20:max(alldata(:,1)); %# Interval set
index = ismember(alldata(:,1),minuteintervals); %# Logical index showing first
%# column values in the set
alldataMinutes = alldata(index,:); %# Extract the corresponding rows
This works by passing a vector of values to the function ISMEMBER, instead of passing values one at a time. The output index is a logical vector the same size as alldata(:,1), with a value of 1 (i.e. true) for elements of alldata(:,1) that are in the set minuteintervals, and a value of 0 (i.e. false) otherwise. You can then use logical indexing to easily extract the rows corresponding to the ones in index, placing them in alldataMinutes.
Related
I have vertically concatenated files from my directory into a matrix that is about 60000 x 15 in size (verified).
d=dir('*.log');
n=length(d);
data=[];
for k=1:n
data{k}=importdata(d(k).name);
end
total=[];
for k=1:n
total=[total;data{n}];
end
I am using a the following 32-iteration loop and the 'Find" function to locate row numbers where the final column is an integer corresponding to the integer iteration of the loop:
for i=1:32
v=[];
vn=[];
[v,vn]=find(abs(fix(i)-fix(total))<eps);
g=length(v)
end
I have tried to account for the floating point accuracy by using 'fix' on values of 'i' and values from matrix 'total', in addition to taking their absolute difference and checking it to be less than a tolerance of 'eps' (floating-point relative accuracy function), up to a tolerance of .99.
The 'Find' function is not working correctly. It is only working for certain integers (although it should be locating all of them (1-32)), and for the integers it does find the values are incomplete.
What is the problem here? If 'Find' is inadequate for this purpose, what is a suitable alternative?
You are getting a lot of zeros because you are looking not just at the 15th column of data but the entire data matrix so you are going to have a lot of non-integers.
Also, you're using fix on both numbers and since floating point errors can cause the number to be slightly above and below the desired integer, this will cause the ones that are below to round down an integer lower than what you'd expect. You should use round to round to the nearest integer instead.
Rather than using find to do this, I would use simple boolean logic to determine the value of the last column
for k = 1:32
% Compare column 15 to the current index
matches = abs(total(:,end) - k) < eps;
% Do stuff with these matches
g = sum(matches); % Count the matches
end
Depending on what you want to actually do with the data, you may be able to use the last column as an input to accumarray to perform an operation on each group.
As a side note, you can replace the first chunk of code with
d = dir('*.log');
data = cellfun(#importdata, {d.name}, 'UniformOutput', false);
total = cat(1, data{:});
My goal is to create a random, 20 by 5 array of integers, sort them by increasing order from top to bottom and from left to right, and then calculate the mean in each of the resulting 20 rows. This gives me a 1 by 20 array of the means. I then have to find the column whose mean is closest to 0. Here is my code so far:
RandomArray= randi([-100 100],20,5);
NewArray=reshape(sort(RandomArray(:)),20,5);
MeanArray= mean(transpose(NewArray(:,:)))
X=min(abs(x-0))
How can I store the column number whose mean is closest to 0 into a variable? I'm only about a month into coding so this probably seems like a very simple problem. Thanks
You're almost there. All you need is a find:
RandomArray= randi([-100 100],20,5);
NewArray=reshape(sort(RandomArray(:)),20,5);
% MeanArray= mean(transpose(NewArray(:,:))) %// gives means per row, not column
ColNum = find(abs(mean(NewArray,1))==min(abs(mean(NewArray,1)))); %// gives you the column number of the minimum
MeanColumn = RandomArray(:,ColNum);
find will give you the index of the entry where abs(mean(NewArray)), i.e. the absolute values of the mean per column equals the minimum of that same array, thus the index where the mean of the column is closest to 0.
Note that you don't need your MeanArray, as it transposes (which can be done by NewArray.', and then gives the mean per column, i.e. your old rows. I chucked everything in the find statement.
As suggested in the comment by Matthias W. it's faster to use the second output of min directly instead of a find:
RandomArray= randi([-100 100],20,5);
NewArray=reshape(sort(RandomArray(:)),20,5);
% MeanArray= mean(transpose(NewArray(:,:))) %// gives means per row, not column
[~,ColNum] = min(abs(mean(NewArray,1)));
MeanColumn = RandomArray(:,ColNum);
I have a 161*32 matrix (labelled "indpic") in MATLAB and I'm trying to find the frequency of a given number appearing in a row. So I think that I need to analyse each row separately for each value, but I'm incredibly unsure about how to go about this (I'm only new to MATLAB). This also means I'm incredibly useless with loops and whatnot as well.
Any help would be greatly appreciated!
If you want to count the number of times a specific number appears in each row, you can do this:
sum(indpic == val, 2)
where indpic is your matrix (e.g image) and val is the desired value to be counted.
Explanation: checking equality of each element with the value produces a boolean matrix with "1"s at the locations of the counted value. Summing each row (i.e summing along the 2nd dimension results in the desired column vector, where each element being equal to the number of times val is repeated in the corresponding row).
If you want to count how many times each value is repeated in your image, this is called a histogram, and you can use the histc command to achieve that. For example:
histc(indpic, 1:256)
counts how many times each value from 1 to 256 appears in image indpic.
Like this,
sum(indpic(rownum,:) == 7)
obviously change 7 to whatever.
You can just write
length(find(indpic(row_num,:)==some_value))
and it will give you the number of elements equal to "some_value" in the "row_num"th row in matrix "indpic"
I'm trying to assign ~1 Million values to a 100x100 logical matrix like this:
CC(Labels,LabelsXplusOne) = true;
where CC is 100x100 logical and Labels, LabelsXplusOne are 1024x768 int32.
The problem now is the above statement takes about as long as 5 minutes to complete on a modern CPU.
Obviously it is badly implemented in MATLAB, so how can we make the above run faster without resorting to loops?
In case you are wondering, i need this statement to compute blobs in a integer (not binary) image.
And also:
max(max(Labels)) = 100
max(max(LabelsXplusOne)) = 100
EDIT:
Ok i got it. Maybe this will help others in the future:
tic; CC(sub2ind(size(CC),Labels,LabelsXplusOne)) = true; toc;
Elapsed time is 0.026414 seconds.
Much better now.
There are a couple of issues that jump out at me...
I have the feeling you are doing the matrix indexing wrong. As it stands now, what will happen is every value in Labels will be paired with every value in LabelsXplusOne, producing (1024*768)^2 total index pairs for your rows and columns of CC. That's likely what's taking so long.
What you probably want is to only use each pair of values as indices, like Labels(1,1),LabelsXplusOne(1,1), Labels(1,2),LabelsXplusOne(1,2), etc. To do this, you should convert your indices into linear indices using the function SUB2IND.
Additionally, your matrix CC only contains 10,000 entries, yet your index matrices each contain 786,432 integer values. This means you will end up assigning the value true to the same entry in CC many times over. You should first remove redundant sets of indices using the function UNIQUE, then use them to assign values to CC.
This is what I think you want:
CC(unique(sub2ind(size(CC), Labels, LabelsXplusOne))) = true;
I have created a vector containing zeros and 1's using the following command in a for loop.
G(:,i)=rand(K,1)<rand;
Since this is part of a larger problem at a particular stage I need to count the number of 1's that are present in each column.
I have tried to find the count using a for loop which is very messy and takes too long.
I found that histc can be used for this but I get an error
histc(G(:,1),1)
First input must be non-sparse numeric array.
Is there a better way to do this or am I missing something here ?
If you have a matrix G containing zeroes and ones, and you want to know how many ones are in each column, all you need is SUM:
nZeroes = sum(G);
This will give you a vector containing a total for each column in G.