I have two Column txt file every Column contain the speed on dc motor. I want to plot every Column with the time and compaire the two curves.
I tried this code, but not working:
fid = fopen('C:\Users\Hussam Yonis\Desktop\recive.txt','r');
KK = fscanf(fid,'%f %f',[2,50]);
t=0:0.05:0.05*length(a(:,1))-0.05;
plot(t,fid(:,1),'b',t,fid(:,2),'r')
fid is just a pointer corresponding to the opened file and does not have several dimensions, so fid(:,2) will give a matrix dimensions exceeded error. You want to plot the data that came out of the file, KK in your case. Try this:
plot(t,KK(:,1),'b',t,KK(:,2),'r')
I also suspect you might have your indexing the wrong way round, although as your code is not minimal, complete and verifiable, it is difficult to say. You might find you need the following command:
plot(t,KK(1,:),'b',t,KK(2,:),'r')
Related
I am trying to load a file in Matlab. But I am a bit confused about the best way to do it.
The file has 3 columns and looks like the screenshot below:
This file I can load very quickly by doing load('c').
However, I had to add 2 NaNs on the bottom row.
The original file actually looks like the file below:
Now if I do load('c') on the file below I get the error:
Error using load
Unable to read file 'c'. Input must be a MAT-file or an ASCII file containing numeric
data with same number of columns in each row.
Of course I can use ImportData to import this file, but it is just soooo slow to import it.
Any suggestions?
You should be able to use c = readtable('c'). This should automatically change the empty entries to "NaN" by default, but if not, there is a way to set that in the options.
If I have a file that is tricky to import (prior to readtable()...that made things a lot easier in the last few years), I will often use the Import Data tool (if its a really big file you can make a mock-up of the complicated file so it loads faster) then change all the import settings as I would want it, then where the green check says "Import Selection" use the black drop down arrow to select "Generate Function." This will give you the coded way of setting everything up to get the file in just the way you want it.
load() is better suited for reading in previously saved '.mat' files that were created in Matlab.
Here's a low-level approach, which might be faster than other methods:
filename = 'c'; % name of the file
N = 3; % number of columns
fid = fopen(filename, 'r'); % open file for reading
x = fscanf(fid, '%f'); % read all values as a column vector
fclose(fid); % close file
x = [x; NaN(N-mod(numel(x)-1,N)-1, 1)]; % include NaN's to make length a multiple of N
x = reshape(x, N, []).'; % reshape to N columns in row-major order
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 am very new to MATLAB and i am currently trying to learn how to import files in matlab and work on it. I am importing a "*.dat" file which contains a single column of floating point numbers[they are just filter coefficients I got from a c++ code] into an array in MATLAB. When I am displaying the output in command window the first line is always " 1.0e-03 * " followed by the contents of my file. I want to know what it means? When I check my workspace the array connects the correct number of inputs. My sample code and first few lines of output are below:
Code:-
clear; clc;
coeff = fopen('filterCoeff.dat');
A = fscanf(coeff, '%f');
A
fclose(coeff);
Output:-
A =
**1.0e-03 *** <===== What does this mean?
-0.170194000000000
0
0.404879000000000
0
-0.410347000000000
P.S: I found many options to read file eg. textscan, fscanf etc. Which one is the best to use?
It is a multiplier that applies to all the numbers displayed after that. It means that, for example, the last entry of A is not -0.410347 but -0.410347e-3, that is, -0.000410347.
I think it is is just Matlab's display number type. It means each of your results are scaled by that amount.
format longg
A
And see what it displays. Look at the docs for format for other options.
I have a txt file in which each row has the x, y ,z coordinates of the point. seperated by space.I want to read points from this txt file and store it as a matrix in matlab of the form [Pm_1 Pm_2 ... Pm_nmod] where each Pm_n is a point .Could someone help me with this?
I have to actually enter it into a code which accepts the model as :
"model - matrix with model points, [Pm_1 Pm_2 ... Pm_nmod]"
I use importdata heavily for this. It reads all kinds of formats ; I normally use other methods like dlmread only if importdata doesn't work.
Usage is as simple as M = importdata('data.txt');
Just use
load -ascii data.txt
That creates a matrix called `data' in your workspace whose rows contain the coordinates.
You can find all the details of the conversion in the documentation for the load command.
I've written a script that saves its output to a CSV file for later reference, but the second script for importing the data takes an ungainly amount of time to read it back in.
The data is in the following format:
Item1,val1,val2,val3
Item2,val4,val5,val6,val7
Item3,val8,val9
where the headers are on the left-most column, and the data values take up the remainder of the row. One major difficulty is that the arrays of data values can be different lengths for each test item. I'd save it as a structure, but I need to be able to edit it outside the MATLAB environment, since sometimes I have to delete rows of bad data on a computer that doesn't have MATLAB installed. So really, part one of my question is: Should I save the data in a different format?
Second part of the question:
I've tried importdata, csvread, and dlmread, but I'm not sure which is best, or if there's a better solution. Right now I'm using my own script using a loop and fgetl, which is horribly slow for large files. Any suggestions?
function [data,headers]=csvreader(filename); %V1_1
fid=fopen(filename,'r');
data={};
headers={};
count=1;
while 1
textline=fgetl(fid);
if ~ischar(textline), break, end
nextchar=textline(1);
idx=1;
while nextchar~=','
headers{count}(idx)=textline(1);
idx=idx+1;
textline(1)=[];
nextchar=textline(1);
end
textline(1)=[];
data{count}=str2num(textline);
count=count+1;
end
fclose(fid);
(I know this is probably terribly written code - I'm an engineer, not a programmer, please don't yell at me - any suggestions for improvement would be welcome, though.)
It would probably make the data easier to read if you could pad the file with NaN values when your first script creates it:
Item1,1,2,3,NaN
Item2,4,5,6,7
Item3,8,9,NaN,NaN
or you could even just print empty fields:
Item1,1,2,3,
Item2,4,5,6,7
Item3,8,9,,
Of course, in order to pad properly you would need to know what the maximum number of values across all the items is before hand. With either format above, you could then use one of the standard file reading functions, like TEXTSCAN for example:
>> fid = fopen('uneven_data.txt','rt');
>> C = textscan(fid,'%s %f %f %f %f','Delimiter',',','CollectOutput',1);
>> fclose(fid);
>> C{1}
ans =
'Item1'
'Item2'
'Item3'
>> C{2}
ans =
1 2 3 NaN %# TEXTSCAN sets empty fields to NaN anyway
4 5 6 7
8 9 NaN NaN
Instead of parsing the string textline one character at a time. You could use strtok to break the string up for example
stringParts = {};
tline = fgetl(fid);
if ~ischar(tline), break, end
i=1;
while 1
[stringParts{i},r]=strtok(tline,',');
tline=r;
i=i+1;
if isempty(r), break; end
end
% store the header
headers{count} = stringParts{1};
% convert the data into numbers
for j=2:length(stringParts)
data{count}(j-1) = str2double(stringParts{j});
end
count=count+1;
I've had the same problem with reading csv data in Matlab, and I was surprised by how little support there is for this, but then I just found the import data tool. I'm in r2015b.
On the top bar in the "Home" tab, click on "Import Data" and choose the file you'd like to read. An app window will come up like this:
Import Data tool screenshot
Under "Import Selection" you have the option to "generate function", which gives you quite a bit of customization options, including how to fill empty cells, and what you'd like the output data structure to be. Plus it's written by MathWorks, so it's probably utilizing the fastest available method to read csv files. It was almost instantaneous on my file.
Q1) If you know the max number of columns you can fill empty entries with NaN
Also, if all values are numerical, do you really need "Item#" column? If yes, you can use only "#", so all data is numerical.
Q2) The fastest way to read num. data from a file without mex-files is csvread.
I try to avoid using strings in csv files, but if I have to, I use my csv2cell function:
http://www.mathworks.com/matlabcentral/fileexchange/20135-csv2cell