In the following code, I need 1 lakh samples in the array mydata. I don't know what I am getting out of mydata. Do I have to increase the range of t to get that. And how can I use the data in mydata into another .m file for further processing.
t = [ 1 : 1 : 500]; % Time Samples
f1=10000; % Input Signal Frequency
f2=20000;
f3=30000;
f4=f2+f3;
f5=f1+f3;
f6=f4+f2;
f7=f1+f6;
f8=45000;
f9=55000;
f10=35000;
mydata=[1:100000];
Fs = 100000; % Sampling Frequency
for i=1:100000
if(i<=10000)
mydata = sin(2*pi*f1/Fs*t);
elseif((i>10000)&&(i<=20000))
mydata=sin(2*pi*f2/Fs*t);
elseif((i>20000)&&(i<=30000))
mydata=sin(2*pi*f3/Fs*t);
elseif((i>30000)&&(i<=40000))
mydata=sin(2*pi*f4/Fs*t);
elseif((i>40000)&&(i<=50000))
mydata=sin(2*pi*f5/Fs*t);
elseif((i>50000)&&(i<=60000))
mydata=sin(2*pi*f6/Fs*t);
elseif((i>60000)&&(i<=70000))
mydata=sin(2*pi*f7/Fs*t);
elseif((i>70000)&&(i<=80000))
mydata=sin(2*pi*f8/Fs*t);
elseif((i>80000)&&(i<=90000))
mydata=sin(2*pi*f9/Fs*t);
elseif((i>90000)&&(i<=100000))
mydata=sin(2*pi*f10/Fs*t);
end
end
stem(mydata)
your code doesn't do very much; you know that, right?
if we don't know/understand what you want, we can't help..
and for anyone else: 1 lakh = 100 000 (http://en.wikipedia.org/wiki/Lakh)
edit: are you trying to produce an array of 100000 samples, consisting of a fixed number of points from different sine waves? aka:
[sin(1.0*pi*[0:10]) sin(2.0*pi*[0:10] sin(1.5*pi*[0:10] (etc) ]
edit2: you repeated your earlier question (which was already answered): How can I generate a sine wave with different frequencies using matlab?
I couldnt understand what you want to do with mydata, please be more specific, because your code is wrong and I cant figure what you want to create.
Whereas for the problem on having the data to be used on other script one simple way would just write mydata into disc,
by doing on your script:
save path_for_mydata/file_name.mat mydata
And on the other script:
load path_formydata/file_name.mat
One other way, would be to create a function, and pass it as a parameter.
Finally, you could just run the first script, and then the second script on command line or on one third script that would call this both scripts, the parameters from the first script will be saved on transient memory while the second script runs.
Related
I have made a script which contains a for loop selecting columns from 533 different excel files and places them into matrices so that they can be compared, however the process is taking too long (it ran for 3 hours yesterday and wasn't even halfway through!!).
I know xlsread is naturally slow, but does anyone know how I can make my script run faster? The script is below, thanks!!
%Split the data into g's and h's
CRNum = 533; %Number of Carrington Rotation files
A(:,1) = xlsread('CR1643.xlsx','A:A'); % Set harmonic coefficient columns
A(:,2) = xlsread('CR1643.xlsx','B:B');
B(:,1) = xlsread('CR1643.xlsx','A:A');
B(:,2) = xlsread('CR1643.xlsx','B:B');
for k = 1:CRNum
textFileName = ['CR' num2str(k+1642) '.xlsx'];
A(:,k+2) = xlsread(textFileName,'C:C'); %for g
B(:,k+2) = xlsread(textFileName,'D:D'); %for h
end
Don't use xlsread if you want to go through a loop. because it opens excel and then closes excel server each time you call it, which is time consuming. instead before the loop use actxserver to open excel, do what you want and finally close actxserver after your loop. For a good example of using actxserver, search for "Read Spreadsheet Data Using Excel as Automation Server" in MATLAB help.
And also take a look at readtable which works faster than xlsread, but generates a table instead.
The most obvious improvement seems to be to load the files only partially if possible. However, if that is not an option, try whether it helps to only open each file once (read everything you need, and then assign it).
M(:,k+2) = xlsread(textFileName,'C:D');
Also check how much you are reading in each time, if you read in many rows in the first file, you may make the first dimension of A big, and then you will fill it each time you read a file?
As an extra: a small but simple improvment can be found at the start. Don't use 4 load statements, but use 1 and then assign variables based on the result.
As mentioned in this post, the easiest thing to change would be to set 'Basic' to true. This disables things like formulas and macros in Excel and allows you to read a simple table more quickly. For example, you can use:
xlsread('CR1643.xlsx','A:A', 'Basic', true)
This resulted in a decrease in load time from about 22 seconds to about 1 second for me when I tested it on a 11,000 by 7 Excel sheet.
I have 100 data files in a folder called "Experiment1", and I need to take all of the data from them and put them into a single matrix. Each data file contains 15 columns and 40 rows of data.
The order in which the files are in the folder is arbitrary. It doesn't matter in what order they get put into the combined matrix.
I've written some code using dlmread that will do the job:
for i = 1:100
%% Read in the relevant file.
filename = ['File_' int2str(i) '.dat']
Data = dlmread(fullfile(pwd, 'Experiment1',filename));
%% Put all the data I need in a separate matrix
NeededData(1+((i-1)*40):i+((i-1)*40)-i+40,1:15) = Data(:,1:15);
end
However, there are two things I don't like about my code.
The files have random names at present, and I'd need to manually change all their names to "File_1.dat", "File_2.dat", etc.
The code is cumbersome and hard to read.
How could I do things better?
Since you've fixed the problem of defining the name of the files to be read with dir, you can improve the way you add the read data (Data) to the output matrix (NeededData).
You can sumultaneously read the input files and add the data to the output matrix by inserting the call to dlmread directly in the assignment statement:
files=dir('*.dat');
n_files=length(files)
% Initialize the output matrix as empty
NeededData_0=[]
for i=1:n_files
% Simultaneously read input file and assign data to the output matrinx
NeededData_0=[NeededData_0;dlmread(files(i).name)]
end
In case you prefer working with the inides (as in your origina approach), since you know in advance that all the files have the same (40) number of rows) you can simplify the notation as follows:
files=dir('*.dat');
n_files=length(files)
% Define the number of rows in each inout file
n_rows=40;
% Define the number of colums in each inout file
n_col=15;
NeededData_2=nan(n_rows*n_files,n_col)
% Define the sequence of rows
r_list=1:n_rows:n_rows*n_files
for i=1:3
Data=dlmread(files(i).name)
NeededData_2(r_list(i):r_list(i)+n_rows-1,:)=Data
end
Hope this helps.
Using the suggestion to use dir present in the answers I have made the following code, which is clearly an improvement on my earlier effort. I would welcome further improvements, or suggestions for alternative approaches.
files = dir('*.dat');
for i = 1:length({files.name})
%% Read in the relevant file.
Data = dlmread(files(i).name);
%% Put all the data I need in a separate matrix
NeededData(1+((i-1)*40):i+((i-1)*40)-i+40,1:15) = Data(:,1:15);
end
I'm trying to split an audio file into 30 millisecond disjoint intervals using Matlab. I have the following code at the moment:
clear all
close all
% load the audio file and get its sampling rate
[y, fs] = audioread('JFK_ES156.wav');
for m = 1 : 6000
[t(m), fs] = audioread('JFK_ES156.wav', [(m*(0.03)*fs) ((m+1)*(0.03)*fs)]);
end
But the problem is that I get the following error:
In an assignment A(I) = B, the number of elements in B and I
must be the same.
Error in splitting (line 12)
[t(m), fs] = audioread('JFK_ES156.wav', [(m*(0.03)*fs)
((m+1)*(0.03)*fs)]);
I don't see why there's a mismatch in the number of elements in B and I and how to solve this. How can I get past this error? Or is there just an easier way to split the audio file (maybe another function I don't know about or something)?
I think the easiest way to split audio is to just load it and use the vec2mat function. so you would have something like this;
[X,Fs] = audioread('JFK_ES156.wav');
%Calculate how many samples you need to capture 30ms of audio
matSize = Fs*0.3;
%Pay attention to that apostrophe. Makes sure samples are stored in columns
%rather than rows.
output = vec2mat(x,matSize)';
%You can now have your audio split up into the different columns of your matrix.
%You can call them by using the column calling command for matrices.
%Plot first 30ms of audio
plot(output(:,1));
%You can join the audio back together using this command.
output = output(:);
Hope that helps. Another good thing about this method is that it keeps all your data in one place!
Edit : One thing I thought of, you may get a problem with this depending on your vector size. But I think vec2mat actually zeroPads your vector. Not a big thing, but if you're moving back and forth between the two, then it might be a good idea to have another variable that stores the original length of your signal.
You should just use the variable y and reshape it to form your split audio. For example,
chunk_size = fs*0.03;
y_chunks = reshape(y, chunk_size, 6000);
That will give you a matrix with each column a 30 ms chunk. This code will also be faster than reading small segments from file in a loop.
As hiandbaii suggested you could also use cell array. Make sure you clear your existing variables before that. Not clearing the array t is probably the reason you got the error "Cell contents assignment to a non-cell array object."
Your original error is because you cannot assign a vector with scalar indexing. That is, 'm' is a scalar, but your audioread call is returning a vector. This is what the error says about mismatch in size of I and B. You could also fix that by making t a 2-D array and use an assignment like
[t(m,:), fs] =
It appears that each 30 ms segment is not equal to one sample. That would be the only case where your code works. i.e. 0.03*fs != 1.
You could try using cells instead.. i.e. replace t(m) with t{m}
I have 50 matrices contained in one folder, all of dimension 181 x 360. How do I cycle through that folder and take an average of each corresponding data points across all 50 matrices?
If the matrices are contained within Matlab variables stored using save('filename','VariableName') then they can be opened using load('filename.mat').
As such, you can use the result of filesInDirectory = dir; to get a list of all your files, using a search pattern if appropriate, like files = dir('*.mat');
Next you can use your load command, and then whos to see which variables were loaded. You should consider storing these for ease clearing after each iteration of your loop.
Once you have your matrix loaded (one at a time), you can take averages as you need, probably summing a value across multiple loop iterations, then dividing by a total counter you've been measuring (using perhaps count = count + size(MatrixVar, dimension);).
If you need all of the matrices loaded at once, then you can modify the above idea, to load using a loop, then average outside of the loop. In this case, you may need to take care - but 50*181*360 isn't too bad I suspect.
A brief introduction to the load command can be found at this link. It talks mainly about opening one matrix, then plotting the values, but there are some comments about dealing with headers, if needed, and different ways in which you can open data, if load is insufficient. It doesn't talk about binary files, though.
Note on binary files, based on comment to OP's question:
If the file can be opened using
FID = fopen('filename.dat');
fread(FID, 'float');
then you can replace the steps referring to load above, and instead use a loop to find filenames using dir, open the matrices using fopen and fread, then average as needed, finally closing the files and clearing the matrices.
In this case, probably your file identifier is the only part you're likely to need to change during the loop (although your total will increase, if that's how you want to average your data)
Reshaping the matrix, or inverting it, might make the code clearer (which is good!), but might not be necessary depending on what you're trying to average - it may be that selecting only a subsection of the matrix is sufficient.
Possible example code?
Assuming that all of the files in the current directory are to be opened, and that no files are elsewhere, you could try something like:
listOfFiles = dir('*.dat');
for f = 1:size(listOfFiles,1)
FID = fopen(listOfFiles(f).name);
Data = fread(FID, 'float');
% Reshape if needed?
Total = Total + sum(Data(start:end,:)); % This might vary, depending on what you want to average etc.
Counter = Counter + (size(Data,1) * size(Data,2)); % This product will be the 181*360 you had in the matrix, in this case
end
Av = Total/Counter;
I created a MATLAB function that runs bootstrap regression based on your data and the sample size desired. The only inputs required are the Y data, X data and 'n' the bootstrap sample size required, e.g. boot(Y,X,10).
How can I create an input that will loop for numerous sample sizes? I.e. something like boot(Y,X,[10,30,100]).
This is important as bootstrap can take quite a while to run, so it is ideal if you can just enter the desired sample sizes and leave the computer while running instead of entering the same command three times.
This can be done easily as follows:
bootstrapSampleSize = [10 30 100];
for i=1:length(bootstrapSampleSize)
yourResult{i}=boot(Y,X,bootstrapSampleSize(i)); %stores the results in a cell array
end
This can be made completely interactive with the use of input command but I will leave that upto you.