I am having matrix with approx 3000 rows(changing) and 3 columns.
I have count of both rows and columns.
I am trying to plot the graph:
x=1:3000;
plot(matrix(x,1))
is there any way that I can include all rows in the plot instruction itself so that I can remove 'x=1:3000' ?
Also, I want to divide, 1st column of matrix which have 3000 rows into another matrix of 3 columns each with 1000 rows. Any specific instruction for this ?
I have made for loop for this and then i am placing individually the elements in the new array. But its taking long time.
As to the plotting issue, using the colon operator will plot all rows for your desired column:
plot(matrix(:,1));
EDIT: You mentioned you were a beginner. In case you haven't seen the colon operator used like this before, a colon operator all by itself when indexing into a matrix essentially means "all __", either "all rows" if in the first position or "all columns" if in the second position.
As for the second question, of splitting one column into a new matrix with multiple columns, you can use the reshape() function, which takes the input matrix to be reshaped and a number of output rows and columns. For example, to split the first column of matrix into 3 columns and put them into newMatrix, use the following:
newMatrix = reshape(matrix(:,1),[],3);
Note that the above code uses [] in the second argument (the number of rows argument) to mean "automatically determine number of rows".This is automatically determined based on the number of columns, which is defined in the third argument here as 3. The reshape function requires that the number of output rows * output columns be equal to input rows * input columns. So in the above case this will only work if the starting matrix has a number of rows which is divisible by 3.
Related
I have a matrix and I am interested in changing values that satisfy a certain condition inside that matrix differently, depending on where they are. Say I have a matrix smallPic. How do I obtain a matrix smallPicB with the same dimensions that changed all values that are above 50 in the first two columns to a 255, while those that are in the third and fourth column are changed to a 180?
I have this code which works, but it is pretty ugly and requires splitting the matrix and concatenating it again:
smallPic1=smallPic(:,1:2);smallPic1(smalllPic1>50)=255;
smallPic2=smallPic(:,3:4);smallPic2(smalllPic2>50)=180;
smallPicB = [smalllPic1 smalllPic2];
How would you combine the logical index with the scalar index in one command?
What doesn't work is this:
smallPic(:,smallPic(:,3:4)>50) = 180
Here, the second mention of smallPic inside the brackets does not allow indexing into the correct position of smallPic because it doesn't have the same dimensions as smallPic. So this command actually replaces values in the first two columns of smallPic that are in the same row as those values that are above 50 in the third and fourth column, instead of replacing the values in the third and fourth column themselves.
Any other suggestions?
It probably is not what you're looking for, but it can help if you have lots of assignments like that:
J = repmat(1:size(smallPic, 2), size(smallPic, 1), 1)
smallPic((J<3)&(smallPic>50))=255
smallPic((J>2)&(J<5)&(smallPic>50))=180
You can also call ismember function if column indices are not consecutive:
smallPic(ismember(J, [[1:2 5:6]])&(smallPic>50))=255
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);
Kindly somebody help me in this.
I have two arrays of equal size 8x8.
And I need covariance of Column 1 of array 1 with the column 1 of second one.
After that I want to find Column 1 with the column 2 of second array.
After that I want to find Column 1 with the column 3 of second array.
After that I want to find Column 1 with the column 4 of second array.
After that I want to find Column 2 with the column 1 of second array.
And so on
I am assuming you want a measure as to how a column of first array varies with a column of second array. If yes, then that will be a scalar, otherwise, if you calculate the covariance matrix of two vectors, it is going to be a... matrix, obviously.
The following solution is based on the fact that covariance of two vectors is their correlation times the product of their standard deviations. More succinctly, for two random variables X and Y,
cov(X,Y)=corr(X,Y)*(sd(X)*sd*Y))
Thus, the solution to your question is:
pairCovariance=corr(X,Y).*(std(X).'*std(Y))
I have to write a script using MATLAB which will classify my data.
My data consists of 1051 web pages (rows) and 11000+ words (columns). I am holding the word occurences in the matrix for each page. The first 230 rows are about computer science course (to be labeled with +1) and remaining 821 are not (to be labeled with -1). I am going to label few part of these rows (say 30 rows) by myself. Then SVM will label the remaining unlabeled rows.
I have found that I could solve my problem using MATLAB's svmtrain() and svmclassify() methods. First I need to create SVMStruct.
SVMStruct = svmtrain(Training,Group)
Then I need to use
Group = svmclassify(SVMStruct,Sample)
But the point that I do not know what Training and Group are. For Group Mathworks says:
Grouping variable, which can be a categorical, numeric, or logical
vector, a cell vector of strings, or a character matrix with each row
representing a class label. Each element of Group specifies the group
of the corresponding row of Training. Group should divide Training
into two groups. Group has the same number of elements as there are
rows in Training. svmtrain treats each NaN, empty string, or
'undefined' in Group as a missing value, and ignores the corresponding
row of Training.
And for Training it is said that:
Matrix of training data, where each row corresponds to an observation
or replicate, and each column corresponds to a feature or variable.
svmtrain treats NaNs or empty strings in Training as missing values
and ignores the corresponding rows of Group.
I want to know how I can adopt my data to Training and Group? I need (at least) a little code sample.
EDIT
What I did not understand is that in order to have SVMStruct I have to run
SVMStruct = svmtrain(Training, Group);
and in order to have Group I have to run
Group = svmclassify(SVMStruct,Sample);
Also I still did not get what Sample should be like?
I am confused.
Training would be a matrix with 1051 rows (the webpages/training instances) and 11000 columns (the features/words). I'm assuming you want to test for the existence of each word on a webpage? In this case you could make the entry of the matrix a 1 if the word exists for a given webpage and a 0 if not.
You could initialize the matrix with Training = zeros(1051,11000); but filling the entries would be up to you, presumably done with some other code you've written.
Group is a 1-D column vector with one entry for every training instance (webpage) than tells you which of two classes the webpage belongs to. In your case you would make the first 230 entries a "+1" for computer science and the remaining 821 entries a "-1" for not.
Group = zeros(1051,1); % gives you a matrix of zeros with 1051 rows and 1 column
Group(1:230) = 1; % set first 230 entries to +1
Group(231:end) = -1; % set the rest to -1
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"