I am trying to read an excel 2003 file which consist of 62 columns and 2000 rows and then draw 2d dendrogram from 2000 pattern of 2 categories of a data as my plot in matlab. When I run the script, it gives me the above error. I don't know why. Anybody has any idea why I have the above error?
My data is here:
http://rapidshare.com/files/383549074/data.xls
Please delete the 2001 column if you want to use the data for testing.
and my code is here:
% Script file: cluster_2d_data.m
d=2000; n1=22; n2=40; N=62
Data=xlsread('data.xls','A1:BJ2000');
X=Data';
R=1:2000;
C=1:2;
clustergram(X,'Pdist','euclidean','Linkage','complete','Dimension',2,...
'ROWLABELS',R,'COLUMNLABELS',C,'Dendrogram',{'color',5})
After the xlsread statement you should get a 2000x62 double matrix Data. Then you transpose it and assign to X, so X is 62x2000 matrix. In the clustergram vectors for the properties RowLabels and ColumnLabels are supposed to match the size of your Data, but you pass a 2000-length vector as RowLabels and 2-length vector as ColumnLabels. This might cause the error.
What version of MATLAB are you using? It looks like pretty old, since you have clustergram as function, but in later versions of Bioinformatic Toolbox it was redesigned as object. In R2010a your code would generate
"ROWLABELS size does not match data"
but I'm not sure what it would be in old version.
Try to remove RowLabels and ColumnLabels, as well as other properties. Do you still get the error?
Related
I created binarized images by using the Otsu methode in Matlab and cut out parts of the resulting image using a function. Now i want to take a look at these images with the VolumeViewer command. I know the x,y and z dimensions of the resulting imgages. I currently run this code doing it(excluding the volumeViewerwhich happens after the loop):
files= {'C3\C3_000mal_550_539_527.raw';...
};
for i=1:numel(files)
Image = fopen(files{i},'r');
ImageData{i} = fread(Image,Inf,'uint16=>uint16');
ImageData{i} = reshape(ImageData{i},550,539,[]);
fclose(openedCrystalImage);
end
Using this code runs into the following error using reshape:
Error using reshape
Product of known dimensions, 296450, not divisible into total number of elements, 78114575.
I did the maths and 550*539=296450 and 296450 * 527=156229150: If we divide the last number by the number of elements it equals 2 and thus is divisible into the total number of elements. In my opinion the reshape function is not able to find the size of the last dimension or defines it as 1.
Defining the size of z also results in an error suggesting using the brackets [], so the function can find it.
Error using reshape
Number of elements must not change. Use [] as one of the size inputs to automatically calculate the appropriate size
for that dimension.
Now to the weird part. This code works for another set of images, with diffrent sizes of the x,y and z ranges. So don´t know where the issue lies to be frank. So i would really appreciate and Answer to my question
I figured it out. The error lies here:
ImageData{i} = fread(Image,Inf,'uint16=>uint16');
Apparently by saving them as .raw before it converts the image to an 8 bit file rather than 16 bits it had before. Therefore, my dimension is double the size of the number of elements. With this alteration it works:
ImageData{i} = fread(Image,Inf,'uint8=>uint8');
The reason i was able to look at the other pictures was that the z range was divisble by 2.
So the reshape function was not the problem but size of the integer data while creating the array for the variable ImageData.
P.S. I just started out programming so the accuracy in the answer should be taken with a grain of salt
I need your help again :). I'm trying to plot multiple lines for a very large dataset. To start easier, I divided the dataset to get a TABLE in Matlab that contains 6 columns, with the first column representing the date that I want on my x-axis. Now I want to plot the other columns (and in the original file are a lot more than 6 columns) on the y axis, using a for loop. I tried the following, with no success:
hold on
for i=2:1:6
plot(Doldenstock(:,1), Doldenstock(:,i));
end
hold off
As I understand this, this code would do exactly what I want for columns 2,3,4,5,6. However, I always get the same error code:
Error using tabular/plot
Too many input arguments.
Error in Plotting_bogeo (line 6)
plot(Doldenstock(:,1), Doldenstock(:,i));
Now, I don't know if maybe for loops like this don't work for tabes but only for arrays?
Thanks for your help in advance!
Cheers,
Tamara
The function plot(x) expect x to be a scalar, a vector, or a matrix. But in your case the input is a table, because accessing a table with parentheses return a table, which is not supported.
If you read the doc "how to access data in a table" you will figure out that you need to use curly brace {} to extract the raw data (in your case a 1D matrix).
So use:
plot(T{:,1},T{:,2})
Unfortunately I am not too tech proficient and only have a basic MATLAB/programming background...
I have several csv data files in a folder, and would like to make a histogram plot of all of them simultaneously in order to compare them. I am not sure how to go about doing this. Some digging online gave a script:
d=dir('*.csv'); % return the list of csv files
for i=1:length(d)
m{i}=csvread(d(i).name); % put into cell array
end
The problem is I cannot now simply write histogram(m(i)) command, because m(i) is a cell type not a csv file type (I'm not sure I'm using this terminology correctly, but MATLAB definitely isn't accepting the former).
I am not quite sure how to proceed. In fact, I am not sure what exactly is the nature of the elements m(i) and what I can/cannot do with them. The histogram command wants a matrix input, so presumably I would need a 'vector of matrices' and a command which plots each of the vector elements (i.e. matrices) on a separate plot. I would have about 14 altogether, which is quite a lot and would take a long time to load, but I am not sure how to proceed more efficiently.
Generalizing the question:
I will later be writing a script to reduce the noise and smooth out the data in the csv file, and binarise it (the csv files are for noisy images with vague shapes, and I want to distinguish these shapes by setting a cut off for the pixel intensity/value in the csv matrix, such as to create a binary image showing these shapes). Ideally, I would like to apply this to all of the images in my folder at once so I can shift out which images are best for analysis. So my question is, how can I run a script with all of the csv files in my folder so that I can compare them all at once? I presume whatever technique I use for the histogram plots can apply to this too, but I am not sure.
It should probably be better to write a script which:
-makes a histogram plot and/or runs the binarising script for each csv file in the folder
-and puts all of the images into a new, designated folder, so I can sift through these.
I would greatly appreciate pointers on how to do this. As I mentioned, I am quite new to programming and am getting overwhelmed when looking at suggestions, seeing various different commands used to apparently achieve the same thing- reading several files at once.
The function csvread returns natively a matrix. I am not sure but it is possible that if some elements inside the csv file are not numbers, Matlab automatically makes a cell array out of the output. Since I don't know the structure of your csv-files I will recommend you trying out some similar functions(readtable, xlsread):
M = readtable(d(i).name) % Reads table like data, most recommended
M = xlsread(d(i).name) % Excel like structures, but works also on similar data
Try them out and let me know if it worked. If not please upload a file sample.
The function csvread(filename)
always return the matrix M that is numerical matrix and will never give the cell as return.
If you have textual data inside the .csv file, it will give you an error for not having the numerical data only. The only reason I can see for using the cell array when reading the files is if the dimensions of individual matrices read from each file are different, for example first .csv file contains data organised as 3xA, and second .csv file contains data organised as 2xB, so you can place them all into a single structure.
However, it is still possible to use histogram on cell array, by extracting the element as an array instead of extracting it as cell element.
If M is a cell matrix, there are two options for extracting the data:
M(i) and M{i}. M(i) will give you the cell element, and cannot be used for histogram, however M{i} returns element in its initial form which is numerical matrix.
TL;DR use histogram(M{i}) instead of histogram(M(i)).
I simply want to import a matrix from a .csv into Matlab and find that Matlab is acting differently wrt length of a row in my csv. :
First, I read a file of 2 rows with 50000 columns and Matlab correctly shows a 2*50000 matrix in my workspace.
Now, if the file consists of 2 rows with 100000 columns, Matlab identifies it as a 200000*1 matrix.
What has gone wrong there?
What command are you using? csvread('filename.csv') ?
I would personally prefer to use
Data = importdata( 'filename.csv','\t');
I'm using GMM to fit my data to 256 Gaussians. I'm using Matlab's fitgmdist to achieve this.
gmm{i} = fitgmdist(model_feats, gaussians, 'Options',statset('MaxIter',1000), ...
'CovType','diagonal', 'SharedCov',false, 'Regularize',0.01, 'Start',cInd);
I am using RootSIFT to extract the features of each image. This produces a vector of 1x128 for each image.
Now I have 45 images maximum for each writer. So after feature extraction and everything the size of my model_feats is 45 x 128.
According to the help file for data arrangement for X is:
The rows of X correspond to observations, and columns correspond to
variables.
The problem I have is when I run the above function I am told that:
"X must have more rows than columns."
I have a total of 45 images for each writer. How will I be able to get this function to run? This is a strange limitation for such a function, I mean even if I am able to get 100 images for each writer it will not work.
I will appreciate any workaround to this.
P.S. I've tried the same with VL_Feat's vl_gmm and it works without any problems but I need this to work in Matlab not VL_FEAT.
With SIFT you usually don't compute the feature for the whole image, but literally hundreds of keypoints for each image. Then you won't have this problem anymore.
Next step then probably is a “bag of visual words” mapping of each image.