Consider a below data set
Obs y x z
1 3 10 1
2 0 12-1
3 4 9 3
4 2 15 0
y is a dependent variable and the others are explanatory variables
I want to give total 4 observations a new coordinates based on some conditions, for example,
If y is in [0,3) give 1 to that y,
or if y is in [3,6), give 2 to that y.
Likewise,
If x is in [9,12), give 1 to that x,
or if x is in [12,16), give 2 to that x,
And do the similar for z.
As a result,
Obs y x z coordinate
1 3 10 1 (1,1,1)
2 0 12 1 (1,1,1)
3 4 9 3 (2,1,2)
4 2 15 0 (1,2,1)
I need these new coordinates as vectors for 4 observations.
I might be able to do this by 'loop' command, but it is too time consuming.
So I need to do this without 'loop' but with some commands related to vector.
Does anybody know how to do this?
While Dan's answer will work well if you only have two values for each coordinate based on a logical expression, if you have more complex logical requirements then I think that you want something similar to the following (which can easily be extended to cover more cases):
y = [ 3 0 4 2 ]';
x = [ 10 12 9 15 ]';
z = [ 1 1 3 0 ]';
coordinate = zeros(length(x), 3);
coordinate(y >= 0 & y < 3, 1) = 1;
coordinate(y >= 3 & y < 6, 1) = 2;
coordinate(x >= 9 & x < 12, 2) = 1;
coordinate(x >= 12 & x < 16, 2) = 2;
coordinate(z >= 0 & z < 3, 3) = 1;
coordinate(z >= 3 & z < 6, 3) = 2;
coordinate
results in
coordinate =
2 1 1
1 2 1
2 1 2
1 2 1
Where you can read each row off, for example coordinate(1, :) to get the first set of coordinates.
This also has the advantage that you can see where none of your rules match because the element in the coordinate matrix will be 0. You could alternatively use nan instead of zeros to create the coordinate matrix.
You can do this easily using logical indexing, in fact, this is pretty much answered here: Change elements of matrix based on condition
n=4;
coordinate = zeros(n,3);
%// y
coordinate(:,1) = (y > 3) + 1
%// x
coordinate(:,2) = (x > 12) + 1
etc...
Related
I have the following code:
x = VarName3;
y = VarName4;
x = (x/6000)/60;
plot(x, y)
Where VarName3 and VarName4 are 3000x1. I would like to apply a median filter to this in MATLAB. However, the problem I am having is that, if I use medfilt1, then I can only enter a single array of variables as the first argument. And for medfilt2, I can only enter a matrix as the first argument. But the data looks very obscured if I convert x and y into a matrix.
The x is time and y is a list of integers. I'd like to be able to filter out spikes and dips. How do I go about doing this? I was thinking of just eliminating the erroneous data points by direct manipulation of the data file. But then, I don't really get the effect of a median filter.
I found a solution using sort.
Median is the center element, so you can sort three elements, and take the middle element as median.
sort function also returns the index of the previous syntaxes.
I used the index information for restoring the matching value of X.
Here is my code sample:
%X - simulates time.
X = [1 2 3 4 5 6 7 8 9 10];
%Y - simulates data
Y = [0 1 2 0 100 1 1 1 2 3];
%Create three vectors:
Y0 = [0, Y(1:end-1)]; %Left elements [0 0 1 2 0 2 1 1 1 2]
Y1 = Y; %Center elements [0 1 2 0 2 1 1 1 2 3]
Y2 = [Y(2:end), 0]; %Right elements [1 2 0 2 1 1 1 2 3 0]
%Concatenate Y0, Y1 and Y2.
YYY = [Y0; Y1; Y2];
%Sort YYY:
%sortedYYY(2, :) equals medfilt1(Y)
%I(2, :) equals the index: value 1 for Y0, 2 for Y1 and 3 for Y2.
[sortedYYY, I] = sort(YYY);
%Median is the center of sorted 3 elements.
medY = sortedYYY(2, :);
%Corrected X index of medY
medX = X + I(2, :) - 2;
%Protect X from exceeding original boundries.
medX = min(max(medX, min(X)), max(X));
Result:
medX =
1 2 2 3 6 7 7 8 9 9
>> medY
medY =
0 1 1 2 1 1 1 1 2 2
Use a sliding window on the data vector centred at a given time. The value of your filtered output at that time is the median value of the data in the sliding window. The size of the sliding window is an odd value, not necessarily fixed to 3.
I am new to Matlab and I have a basic question.
I have this data set:
1 2 3
4 5 7
5 2 7
1 2 3
6 5 3
I am trying to calculate the relative frequencies from the dataset above
specifically calculating the relative frequency of x=1, y=2 and z=3
my code is:
data = load('datasetReduced.txt')
X = data(:, 1)
Y = data(:, 2)
Z = data(:, 3)
f = 0;
for i=1:5
if X == 1 & Y == 2 & Z == 3
s = 1;
else
s = 0;
end
f = f + s;
end
f
r = f/5
it is giving me a 0 result.
How can the code be corrected??
thanks,
Shosho
Your issue is likely that you are comparing floating point numbers using the == operator which is likely to fail due to floating point errors.
A faster way to do this would be to use ismember with the 'rows' option which will result in a logical array that you can then sum to get the total number of rows that matched and divide by the total number of rows.
tf = ismember(data, [1 2 3], 'rows');
relFreq = sum(tf) / numel(tf);
I think you want to count frequency of each instance, So try this
data = [1 2 3
4 5 7
5 2 7
1 2 3
6 5 3];
[counts,centers] = hist(data , unique(data))
Where centers is your unique instances and counts is count of each of them. The result should be as follow:
counts =
2 0 0
0 3 0
0 0 3
1 0 0
1 2 0
1 0 0
0 0 2
centers =
1 2 3 4 5 6 7
That it means you have 7 unique instances, from 1 to 7 and there is two 1s in first column and there is not any 1s in second and third and etc.
I'm currently bringing some GAUSS code over to Matlab and I'm stuck trying to use the GAUSS "rotater" function.
The command reference entry for rotater says:
Purpose Rotates the rows of a matrix
Format y = rotater(x,r)
Input x: N x K matrix to be rotated. r: N x 1 or 1 x 1 matrix specifying the amount of rotation.
Output y: N x K rotated matrix.
Remarks The rotation is performed horizontally within each row of the matrix. A positive rotation value will cause the elements to move
to the right. A negative rotation will cause the elements to move to
the left. In either case, the elements that are pushed off the end of
the row will wrap around to the opposite end of the same row. If the rotation value is greater than or equal to the number of columns in x, then the rotation value will be calculated using (r % cols(x)).
Example 1
(I'm following Matlab's notation here, with straight brackets for matrices and a semicolon for a new ro)
If x = [1 2 3; 4 5 6], and r = [1; -1],then y = [3 1 2; 5 6 4]
Example 1
If x = [1 2 3; 4 5 6; 7 8 9; 10, 11, 12], and r = [0; 1; 2; 3], then y = [1 2 3; 6 4 5; 8 9 7; 10 11 12]
Maybe someone has found a function like that somewhere or can give me advice how to write it?
This can be done using bsxfun twice:
Compute rotated row indices by subtracting r with bsxfun and using mod. As usual, mod needs indices starting at 0, not 1. The rotated row indices are left as 0-based, because that's more convenient for step 2.
Get a linear index from columns and rotated rows, again using bsxfun. This linear index applied to x gives y:
Code:
[s1 s2] = size(x);
rows = mod(bsxfun(#plus, 1:s2, -r(:))-1, s2); % // step 1
y = x(bsxfun(#plus, rows*s1, (1:s1).')); %'// step 2
circshift is pretty close to what you're looking for except that 1) it works on columns rather than rows, and 2) it shifts the entire matrix by the same offset.
The first one is easy to fix, we just transpose. For the second one I haven't been able to find a vectorized approach, but in the meantime, here's a version with a for loop:
x = [1 2 3; 4 5 6; 7 8 9; 10 11 12]
r = [0 1 2 3]
B = x'
C = zeros(size(B));
for ii = 1:size(B,2)
C(:,ii) = circshift(B(:,ii),r(ii));
end
y = C'
The output is:
x =
1 2 3
4 5 6
7 8 9
10 11 12
r =
0 1 2 3
B =
1 4 7 10
2 5 8 11
3 6 9 12
y =
1 2 3
6 4 5
8 9 7
10 11 12
This can be done using a simple for loop to iterate over each row, and a function called 'circshift' from matlab.
I created a function the goes through each row and applies the appropriate shift to it. There may be more efficient ways to implement this, but this way works with your examples. I created a function
function rotated_arr = GaussRotate(input_array, rotation_vector)
[N,K] = size(input_array)
%creates array for return values
rotated_arr = zeros(N,K);
%if the rotation vector is a scalar
if (length(rotation_vector) == 1)
%replicate the value once for each row
rotation_vector = repmat(rotation_vector, [1,N]);
end
%if the rotation vector doesn't have as many entries as there are rows
%in the input array
if (length(rotation_vector) ~= N)
disp('ERROR GaussRotate: rotation_vector is the wrong size')
disp('if input_Array is NxK, rotation_vector must be Nx1 or 1x1')
return
end
%for each row
for idx=1:size(input_array,1)
%shift the row by the appropriate number of columns
%we use [0,shift] because we want to shift the columns, the row
%stays where it is (even though this is a 1xN at this point we
%still specify rows vs columns)
rotated_arr(idx,:) = circshift(input_array(idx,:),[0,rotation_vector(idx)]);
end
end
then simply called it with your examples
x = [1 2 3; 4 5 6];
r = [1; -1];
y = GaussRotate(x,r)
%produces [3 1 2; 5 6 4]
%I also made it support the 1x1 case
r = [-1]
%this will shift all elements one column to the left
y = GaussRotate(x,r)
%produces [2 3 1; 5 6 4]
x = [1 2 3; 4 5 6; 7 8 9; 10, 11, 12]
r = [0; 1; 2; 3]
y = GaussRotate(x,r)
%produces [1 2 3; 6 4 5; 8 9 7; 10 11 12]
I want to create a matrix of the following form
Y = [1 x x.^2 x.^3 x.^4 x.^5 ... x.^100]
Let x be a column vector.
or even some more variants such as
Y = [1 x1 x2 x3 (x1).^2 (x2).^2 (x3).^2 (x1.x2) (x2.x3) (x3.x1)]
Let x1,x2 and x3 be column vectors
Let us consider the first one. I tried using something like
Y = [1 : x : x.^100]
But this also didn't work because it means take Y = [1 x 2.*x 3.*x ... x.^100] ?
(ie all values between 1 to x.^100 with difference x)
So, this also cannot be used to generate such a matrix.
Please consider x = [1; 2; 3; 4];
and suggest a way to generate this matrix
Y = [1 1 1 1 1;
1 2 4 8 16;
1 3 9 27 81;
1 4 16 64 256];
without manually having to write
Y = [ones(size(x,1)) x x.^2 x.^3 x.^4]
Use this bsxfun technique -
N = 5; %// Number of columns needed in output
x = [1; 2; 3; 4]; %// or [1:4]'
Y = bsxfun(#power,x,[0:N-1])
Output -
Y =
1 1 1 1 1
1 2 4 8 16
1 3 9 27 81
1 4 16 64 256
If you have x = [1 2; 3 4; 5 6] and you want Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36] i.e. Y = [ 1 x1 x1.^2 x2 x2.^2 ] for column vectors x1, x2 ..., you can use this one-liner -
[ones(size(x,1),1) reshape(bsxfun(#power,permute(x,[1 3 2]),1:2),size(x,1),[])]
Using an adapted Version of the code found in Matlabs vander()-Function (which is also to be found in the polyfit-function) one can get a significant speedup compared to Divakars nice and short solution if you use something like this:
N = 5;
x = [1:4]';
V(:,n+1) = ones(length(x),1);
for j = n:-1:1
V(:,j) = x.*V(:,j+1);
end
V = V(:,end:-1:1);
It is about twice as fast for the example given and it gets about 20 times as fast if i set N=50 and x = [1:40]'. Although I state that is not easy to compare the times, just as an option if speed is an issue, you might have a look at this solution.
in octave, broadcasting allows to write
N=5;
x = [1; 2; 3; 4];
y = x.^(0:N-1)
output -
y =
1 1 1 1 1
1 2 4 8 16
1 3 9 27 81
1 4 16 64 256
How can I avoid using a double for loop in order to build a matrix pos like this code does:
pos=[0 0];
for i=1:m;
for j=1:n;
pos=[pos; i j];
end
end
m and n are numbers such as 500 and 900.
I have to find a better solution in order improve computation time.
Thank you so much.
You can easily do this by meshgrid.
[X,Y] = meshgrid(1:m, 1:n);
pos = [0 0; X(:) Y(:)];
How the above code works is the following. meshgrid (in this case) creates a 2D grid of (X,Y) co-ordinates. X progresses horizontally while Y progresses vertically. As we can see in your for loops, m defines the horizontal boundaries while n denotes the vertical boundaries. By calling meshgrid(1:m, 1:n), I am creating a n x m grid for both X and Y, where each row of X progresses from 1 to m, while each column of Y progresses from 1 to n. Therefore, these will both be n x m matrices. Calling the above with m = 4 and n = 5 computes:
m = 4;
n = 5;
[X,Y] = meshgrid(1:m, 1:n)
X =
1 2 3 4
1 2 3 4
1 2 3 4
1 2 3 4
1 2 3 4
Y =
1 1 1 1
2 2 2 2
3 3 3 3
4 4 4 4
5 5 5 5
This almost follows the format you wish. You'll notice that by looking at the columns individually, this achieves what you want, but you want to stack all of the X and Y to be in a (n x m) + 1 x 2 matrix (1 to account for [0 0]). All we have to do now is take every column of X and Y and stack them on top of each other to create a single column for both. We can stack all of these together by doing X(:) and Y(:). X(:) will take every column of X and create a single column that stacks all of the columns together. The same is done for Y(:). As such, we first create pos by attaching [0 0] as the first row, and we then attach X(:) and Y(:) as columns to pos after, thus completing the construction of pos.
Let's do an example as a proof-of-concept. Suppose that we use the same values like we did before:
m = 4;
n = 5;
Using your for loop, we get:
pos =
0 0
1 1
1 2
1 3
1 4
1 5
2 1
2 2
2 3
2 4
2 5
3 1
3 2
3 3
3 4
3 5
4 1
4 2
4 3
4 4
4 5
Using the code I have written, we also get:
pos =
0 0
1 1
1 2
1 3
1 4
1 5
2 1
2 2
2 3
2 4
2 5
3 1
3 2
3 3
3 4
3 5
4 1
4 2
4 3
4 4
4 5
Minor Note
As you stated that m and n are going to be relatively large, I would recommend you clear X and Y from your workspace before you proceed. X and Y were only created to help you create pos. As you don't need them anymore, after you calculate pos, do:
clear X;
clear Y;