I have a data set(binary file) which i want to read only the first half of X (and corresponding Y) data which is saved to 4D matrix:
for i = 1:vols
for j = 1:cols
XY(i,:,:,j) = fread(fid,[X Y],'int16');
end
end
How do I modify the above loop so only the first e.g. 10 X data (and corresponding Y) is read in for each vols and cols?
thanks
You will need to implement reading for each vols and cols in following order:
read part of Y for the first input X, than skip rest of this line, read part of Y for the second input X, etc.
After reading of requested number of X lines, you will need to skip rest of matrix before read next (vols, cols) pair.
To skip part of matrix you can use fseek function.
Let X_count and Y_cound are dimensions of submatrix; X_total and Y_total are dimension of total matrix. You need something like following:
for i = 1:vols
for j = 1:cols
for k=1:X_count
XY(i,k,:,j) = fread(fid,Y_count,'int16');
fseek(fid,(Y_total-Y_count)*2,'cof');
end
fseek(fid,(X_total-X_count)*Y_total*2,'cof');
end
end
Related
I have a vector Cycle() that can contain several elements with a variable size.
I want to extract from this vector all the values which are in the odd columns, i.e. Cycle(1), Cycle(3), Cycle(5) ... and save them into a new vector Rcycle.
That's my code:
Rcycle = zeros(1, length(cycle)/2);
Rcycle(1) = cycle(1);
for j=3:length(cycle);
for i=2:length(Rcycle);
Rcycle(i) = cycle(j);
j = j+2;
end
end
Also I want to extract from Cycle() the even columns and save them in a vector Lcycle. My code:
Lcycle = zeros(1, length(cycle)/2);
Lcycle(1) = cycle(2);
for k=4:length(cycle);
for i=2:length(cycle);
Lcycle(i) = cycle(k);
k = k+2;
end
end
By running this for a sample Cycle() with 12 elements I get the right results for Lcycle, but the wrong ones for Rcycle. Also I get the error that my matrix have exceeded its dimension.
Has anyone any idea how to solve this in a more smooth way?
Use vector indexing!
Rcyle=cycle(1:2:end); %// Take from cycle starting from 1, each 2, until the end
Lcycle=cycle(2:2:end);%// same, but start at 2.
I am using MATLAB version R2011a, a friend of mine is using R2014b which contains the function "Flip", which flips the order of elements, this function is vital to our program that compares Matrix'es.
My problem is R2011a does not have this function, it has fliplr,flipud and flipdim. I have tried using fliplr and then flipud to try and recreate the same function but eventually it doesn't work since i'm using the function corr which requires using that it's two arguments be the same dimensions.
I need advise on how to create the flip function that is available on R2014b.
The function that is problematic:
%This function gets the DNA signiture with the relative freq of each perm at
%the refernce text, the DNA signiture with the relative freq of each perm at
%the compare text, and the MaxPerm, and return the relative editor distance
%between the 2 texts.
function [distance]=EditorDistance2 (RefDNAWithFreq,CmpDNAWithFreq,MaxPerm)
if MaxPerm>2
MaxPerm=2;
end
str='Editor Distance compare begun';
disp(str);
distance=[];
for PermLength=1:MaxPerm
freq=sum(0:PermLength);
PermInitial=freq+1;
permEnd=freq+PermLength;
%create an ordered matrix of all the perms with length "PermLength"
%in the ref text
CurRefPerms=RefDNAWithFreq(:,freq:permEnd);
OrderedRefCurPerms=sortrows(CurRefPerms);
OrderedRefCurPerms=flip(OrderedRefCurPerms);
OrderedRefCurPerms(:,1)=[];
OrderedRefCurPerms=ZeroCutter(OrderedRefCurPerms);
%create an ordered matrix of all the perms with length "PermLength"
%in the cmp text
CurcmpPerms=CmpDNAWithFreq(:,freq:permEnd);
OrderedCmpCurPerms=sortrows(CurcmpPerms);
OrderedCmpCurPerms=flip(OrderedCmpCurPerms);
OrderedCmpCurPerms(:,1)=[];
OrderedCmpCurPerms=ZeroCutter(OrderedCmpCurPerms);
len1=size(OrderedRefCurPerms,1);
len2=size(OrderedCmpCurPerms,1);
edit=1;
matrix=zeros(len2,len1);
%initiate first row of the first stirng
for i=2:len1
matrix(1,i)=matrix(1,i-1)+1;
end
%initiate first column of the second stirng
for i=2:len2
matrix(i,1)=matrix(i-1,1)+1;
end
%start algoritem
for i=2:len2
for j=2:len1
if OrderedRefCurPerms(j-1,:)==OrderedCmpCurPerms(i-1,:)
edit=0;
end
if (i>2 & j>2 & OrderedRefCurPerms(j-1,:)==OrderedCmpCurPerms(i-2,:) & RefDNAWithFreq(j-2)==CmpDNAWithFreq(i-1) )
matrix(i,j)= min([matrix(i-1,j)+1,... deletion
matrix(i,j-1)+1,... insertion
matrix(i-2,j-2)+1,... substitution
matrix(i-1,j-1)+edit... transposition
]);
else
matrix(i,j) = min([matrix(i-1,j)+1,... deletion
matrix(i,j-1)+1,... insertion
matrix(i-1,j-1)+edit... substitution
]);
end
edit=1;
end
end
%The Distance is the last elment of the matrix.
if i~=1
tempdistance = matrix( floor( len2 / 3 ) , floor( len1 / 3 ) );
tempdistance=tempdistance/floor(len2/3);
else
tempdistance = matrix( len2,len1 );
tempdistance= tempdistance/len2;
end
tempdistance=1-tempdistance;
distance=[distance tempdistance];
end
end
I will further explain myself, the function which I am trying to use is A=flip(A)
The function that causes me problems is this one
%This function gets the DNA signiture with the relative freq of each perm at
%the refernce text, the DNA signiture with the relative freq of each perm at
%the compare text, and the MaxPerm, and return the corralation between the 2 texts.
function [Corvector]=CorrelationCompare(RefDNAWithFreq,CmpDNAWithFreq,MaxPerm)
str='corraltion compare begun';
disp(str);
%this vector will contain the corralation between the freqs of
%each perms vector(each length)
Corvector=[];
for PermLength=1:MaxPerm
freq=sum(0:PermLength);
PermInitial=freq+1;
permEnd=freq+PermLength;
%Cor is correlation between the 2 texts
refPerms=RefDNAWithFreq(:,freq);
cmpPerms=CmpDNAWithFreq(:,freq);
refPerms=ZeroCutter(refPerms);
cmpPerms=ZeroCutter(cmpPerms);
tempCor=corr(refPerms,cmpPerms);
Corvector =[Corvector tempCor];
% making a graph of the perms, and the relative freq of the texts.
x=ZeroCutter ( RefDNAWithFreq(:,PermInitial:permEnd) );
y1=refPerms;
y2=cmpPerms;
xchars=char(x);
Xcols=size(x,1);
o=ones(Xcols,1);
xco=mat2cell(xchars,o,PermLength);
xaxis=(1:Xcols);
figure
stem(xaxis,y1,'r');
hold
stem(xaxis,y2,'g');
set(gca,'XTick',xaxis)
set(gca,'XTickLabel',xco,'fontname','david');
xlabel('Perms');
ylabel('Perm frequency');
TitleOfGraph=sprintf('comapre between reference text to the compared, %d letters perm\n correlation=%f',PermLength,Corvector(PermLength));
legend('reference','compared');
title(TitleOfGraph);
end
end
The Error that I recieve when using a diffrent flip command is
??? Error using ==> corr at 102
X and Y must have the same number of rows.
Error in ==> CorrelationCompare at 27
tempCor=corr(refPerms,cmpPerms);
I apologize for the long codes but it's hard to explain it all since it's a big project and a lot of it was done by my partner
This should work for you -
function out = flip_hacked(A,dim)
%// Get an array of all possible dimensions
dims = 1:ndims(A);
%// Interchange first dimension and dim
dims(dim) = 1;
dims(1) = dim;
A1 = permute(A,[dims]);
%// Reshape A1 into a 2D matrix and then flip along the first dimension,
%// which would correspond to the flipping along dim and then interchange dim
%// and first dim again to keep the size of data same as input and elements
%// being flipped along dim for the desired output
A2 = reshape(A1,size(A1,1),[]);
out = permute(reshape(A2(end:-1:1,:),size(A1)),dims);
return;
It follows the same syntax as the official flip function that's stated in the official documentation as follows -
B = flip(A,dim) reverses the order of the elements in A along
dimension dim. For example, if A is a matrix, then flip(A,1) reverses
the elements in each column, and flip(A,2) reverses the elements in
each row.
In addition to the generic solution provided by Divakar you could simply use:
flip = #(A) A(end:-1:1, :);
A = flip(A);
To reverse the elements in each column of a matrix A. Even simpler:
A = A(end:-1:1, :);
I am searching for any matlab code that reads the skeleton text files from the dataset (MSR Daily Activity 3D). I can't figure how to understand how the files are written and what they represent ? Also, don't know how to parse them to extract the features.
this is the matlab code which read the depth sequences.
in each loop of 'for ei = 1:2',it read all the depth data to depth(a 3D matrix) from a bin file.
clear;close all;clc;
binPath = 'MSR Daily Activity 3D dataset\Depth';
for ai = 1:16
for si = 1:10
for ei = 1:2
%%%%%%%%%%%%%
%%%%%%%%%%%%%
[acsr,susr,exsr]=getsr(ai,si,ei);
%%%%%% getsr(ai,si,ei) convert ai,si,ei to double bits
%%%%%% for example, if ai=3, acsr is 03
%%%%%%%%%%%
binfile = [binPath,'\a',acsr,'_s',susr,'_e',exsr,'_depth.bin'];
if ~exist(binfile,'file');
disp('error');
continue;
end;
disp(binfile);
fileread = fopen(binfile);
if fileread<0
disp('no such file.');
return;
end
header = fread(fileread,3,'uint=>uint');
nnof = header(1); ncols = header(2); nrows = header(3);
depths = zeros(ncols, nrows, nnof);
for f = 1:nnof
frame = zeros( ncols, nrows);
for row = 1:nrows
tempRow = fread(fileread, ncols, 'uint=>uint');
tempRowID = fread(fileread, ncols, 'uint8');%%%%%
frame(:,row) = tempRow;
end
depth(:,:,f) = frame;
clear tempRow tempRowID;
end
fclose(fileread);
end
end
end
The site http://research.microsoft.com/en-us/um/people/zliu/ActionRecoRsrc/ tells you exactly how they're organised. They also provide some C++ example loaders.
"The format of the skeleton file is as follows. The first integer is the number of frames. The second integer is the number of joints which is always 20. For each frame, the first integer is the number of rows. This integer is 40 when there is exactly one skeleton being detected in this frame. It is zero when no skeleton is detected. It is 80 when two skeletons are detected (in that case which is rare, we simply use the first skeleton in our experiments). For most of the frames, the number of rows is 40. Each joint corresponds to two rows. The first row is its real world coordinates (x,y,z) and the second row is its screen coordinates plus depth (u, v, depth) where u and v are normalized to be within [0,1]. For each row, the integer at the end is supposed to be the confidence value, but it is not useful."
Hope this helps.
I'm trying to write an octave program that will convert a .mat file to a .csv file. The .mat file has a matrix X and a column vector y. X is populated with 0s and 1s and y is populated with labels from 1 to 10. I want to take y and put it in front of X and write it as a .csv file.
Here is a code snippet of my first approach:
load(filename, "X", "y");
z = [y X];
basename = split{1};
csvname = strcat(basename, ".csv");
csvwrite(csvname, z);
The resulting file contains lots of really small decimal numbers, e.g. 8.560596795891285e-06,1.940359477121703e-06, etc...
My second approach was to loop through and manually write the values out to the .csv file:
load(filename, "X", "y");
z = [y X];
basename = split{1};
csvname = strcat(basename, ".csv");
csvfile = fopen(csvname, "w");
numrows = size(z, 1);
numcols = size(z, 2);
for i = 1:numrows
for j = 1:numcols
fprintf(csvfile, "%d", z(i, j));
if j == numcols
fprintf(csvfile, "\n");
else
fprintf(csvfile, ",");
end
end
end
fclose(csvfile);
That gave me a correct result, but took a really long time.
Can someone tell me either how to use csvwrite in a way that will write the correct values, or how to more efficiently manually create the .csv file.
Thanks!
The problem is that if y is of type char, your X vector gets converted to char, too. Since your labels are nothing else but numbers, you can simply convert them to numbers and save the data using csvwrite:
csvwrite('data.txt', [str2num(y) X]);
Edit Also, in the loop you save the numbers using integer conversion %d, while csvwrite writes doubles if your data is of type double. If the zeros are not exactly zeros, csvwrite will write them with scientific notation, while your loop will round them. Hence the different behavior.
Just a heads up your code isn't optimized for Matab / octave. Switch the for i and for j lines around.
Octave is in column major order so its not cache efficient to do what your doing. It will speed up the overall loop by making the change to probably an acceptable time
In Matlab, I want to make a seqlogo plot of an amino acid sequence profile. But instead of scaling the heights of the plot columns by entropy, I want all the columns to be the same height.
I'm in the process of modifying the code from the answers to this question, but I wonder if there is a parameter to seqlogo or some other function that I have missed that will make the column heights uniform.
Alternatively, is there a statistical transformation I can apply to the sequence profile to hack the desired output? (column heights uniform, height of each letter linearly proportion to
its probability in the seqprofile)
Probably the easiest way around this problem is to directly modify the code for the Bioinformatics Toolbox function SEQLOGO (if possible). In R2010b, you can do:
edit seqlogo
And the code for the function will be shown in the editor. Next, find the following lines (lines 267-284) and either comment them out or remove them entirely:
S_before = log2(nSymbols);
freqM(freqM == 0) = 1; % log2(1) = 0
% The uncertainty after the input at each position
S_after = -sum(log2(freqM).*freqM, 1);
if corrError
% The number of sequences correction factor
e_corr = (nSymbols -1)/(2* log(2) * numSeq);
R = S_before - (S_after + e_corr);
else
R = S_before - S_after;
end
nPos = (endPos - startPos) + 1;
for i =1:nPos
wtM(:, i) = wtM(:, i) * R(i);
end
Then put this line in their place:
wtM = bsxfun(#times,wtM,log2(nSymbols)./sum(wtM));
You will probably want to save the file under a new name, like seqlogo_norm.m, so you can still use the original unmodified SEQLOGO function. Now you can create sequence profile plots with all the columns normalized to the same height. For example:
S = {'LSGGQRQRVAIARALAL',... %# Sample amino acid sequence
'LSGGEKQRVAIARALMN',...
'LSGGQIQRVLLARALAA',...
'LSGGERRRLEIACVLAL',...
'FSGGEKKKNELWQMLAL',...
'LSGGERRRLEIACVLAL'};
seqlogo_norm(S,'alphabet','aa'); %# Use the modified SEQLOGO function
OLD ANSWER:
I'm not sure how to transform the sequence profile information to get the desired output from the Bioinformatics Toolbox function SEQLOGO, but I can show you how to modify the alternative seqlogo_new.m that I wrote for my answer to the related question you linked to. If you change the line that initializes bitValues from this:
bitValues = W{2};
to this:
bitValues = bsxfun(#rdivide,W{2},sum(W{2}));
Then you should get each column scaled to a height of 1. For example:
S = {'ATTATAGCAAACTA',... %# Sample sequence
'AACATGCCAAAGTA',...
'ATCATGCAAAAGGA'};
seqlogo_new(S); %# After applying the above modification
For now, my workaround is to generate a bunch of fake sequences that match the sequence profile, then feed those sequences to http://weblogo.berkeley.edu/logo.cgi . Here is the code to make the fake sequences:
function flatFakeSeqsFromPwm(pwm, letterOrder, nSeqsToGen, outFilename)
%translates a pwm into a bunch of fake seqs with the same probabilities
%for use with http://weblogo.berkeley.edu/
%pwm should be a 4xn or a 20xn position weight matrix. Each col must sum to 1
%letterOrder = e.g. 'ARNDCQEGHILKMFPSTWYV' for my data
%nSeqsToGen should be >= the # of pixels tall you plan to make your chart
[height windowWidth] = size(pwm);
assert(height == length(letterOrder));
assert(isequal(abs(1-sum(pwm)) < 1.0e-10, ones(1, windowWidth))); %assert all cols of pwm sum to 1.0
fd = fopen(outFilename, 'w');
for i = 0:nSeqsToGen-1
for seqPos = 1:windowWidth
acc = 0; %accumulator
idx = 0;
while i/nSeqsToGen >= acc
idx = idx + 1;
acc = acc + pwm(idx, seqPos);
end
fprintf(fd, '%s', letterOrder(idx));
end
fprintf(fd, '\n');
end
fclose(fd);
end