I have a .mtx file which contains a vector which I am suppose to use for matrix vector multiplication. I tried to open the file using
fopen('filename') but this does not work, it returns a single number. I have also tried using readmtx but this gives me the following error: File size does not match inputs. Expected a file size of 232316 bytes. Instead the file size is
365 bytes. Could you please advise how I can open and work with this type of file in MATLAB.
fopen('filename') outputs only the fileID, which is typically an integer >3. This fileID can be used with e.g. fscanf(fileID) to get the content of the file.
For the .mtx format, where each line contains [row-number column-number matrix-entry], you could also do something like:
%% file
filename = 'my_matrix.mtx';
%% read Matrix
Mat = read_mtx(filename);
%% function
function Mat = read_mtx(filename)
% open file
fID = fopen(filename,'r');
M = fscanf(fID, '%f');
% reshape M vector into Nx3 matrix
M = reshape(M, [3, length(M)/3])';
% assemble final matrix
Mat = zeros(M(end,1),M(end,1));
for ii = 1:size(M,1)
Mat(M(ii,1),M(ii,2)) = M(ii,3);
end
end
Related
I am trying to edit 100 .mat files in a folder with no pattern in their names. Each file contains a matrix of size 100-by-10, and I want to convert them to 10-by-10-by-10. How do I go about this?
Provided you have a single matrix in each file, and want to overwrite the original matrix:
listing = dir('*.mat'); % finds all .mat files in your pwd
for ii = 1:numel(listing)
tmp = listing(ii).name;
s = load(tmp); % load a file
Fname = fieldnames(s); % get matrix name
out = reshape(s.(Fname{1}),[10 10 10]); % reshape
save(tmp,'out') % Save, overwriting original
end
I'm trying to use a .dat file's data to create an RBF neural network and train it. But I don't know how to use it's columns as input and target data in the network.
This is an image of the file in matlab:
train.dat
I tried this:
fid = fopen('train.dat','r');
A = fscanf(fid, '%f');
C1 = textscan(fid,'%s%f%s%f'); %read the first line
nb_col = C1{4}; %get the number of columns (could be set by user too)
%read the remaining of the file
C2 = textscan(fid, repmat('%f',1,nb_col), 'CollectOutput',1);
fclose(fid); %close the connection
My question is what code should I write at the beginning to open the train.dat file and put it's first column into a vector (patterns) and it's third column in another vector (target)?
I'm not sure if this will work but you can try:
load train.dat
patterns = train(:,1); % If just first column
patterns = train(:,[1:2]); % If column 1 & 2 are the vector patterns
target = train(:,3);
Consider a matrix A in Matlab of dimension mxn and suppose I want to save it as a binary file test.dat using
File_id = fopen('test.dat', 'w');
fwrite(File_id, A, 'float32');
fclose(File_id);
Now suppose that A is created within a loop for h=1:100: how can I assign to the binary files the names test1.dat, test2.dat,...,test100.dat? In other words this is what I want to do and my question is related to step 2):
%for h=1:H
%1)do something that creates A
%2) Save A using
%File_id = fopen('test'h'.dat', 'w'); %clearly wrong
%fwrite(File_id, A, 'float32');
%fclose(File_id);
%end
In the code you posted, the line:
%File_id = fopen('test'h'.dat', 'w'); %clearly wrong
should read:
File_id = fopen(strcat('test',num2str(h),'.dat'),'w');
and that should do the trick nicely.
I am having difficulty in reading data from a .txt file using Matlab.
I have to create a 200x128 dimension array in Matlab, using the data from the .txt file. This is a repetitive task, and needs automation.
Each row of the .txt file is a complex number of form a+ib, which is of form a[space]b. A sample of my text file :
Link to text file : Click Here
(0)
1.2 2.32222
2.12 3.113
.
.
.
3.2 2.22
(1)
4.4 3.4444
2.33 2.11
2.3 33.3
.
.
.
(2)
.
.
(3)
.
.
(199)
.
.
I have numbers of rows (X), inside the .txt file surrounded by brackets. My final matrix should be of size 200x128. After each (X), there are exactly 128 complex numbers.
Here is what I would do. First thing, delete the "(0)" types of lines from your text file (could even use a simple shells script for that). This I put into the file called post2.txt.
# First, load the text file into Matlab:
A = load('post2.txt');
# Create the imaginary numbers based on the two columns of data:
vals = A(:,1) + i*A(:,2);
# Then reshape the column of complex numbers into a matrix
mat = reshape(vals, [200,128]);
The mat will be a matrix of 200x128 complex data. Obviously at this point you can put a loop around this to do this multiple times.
Hope that helps.
You can read the data in using the following function:
function data = readData(aFilename, m,n)
% if no parameters were passed, use these as defaults:
if ~exist('aFilename', 'var')
m = 128;
n = 200;
aFilename = 'post.txt';
end
% init some stuff:
data= nan(n, m);
formatStr = [repmat('%f', 1, 2*m)];
% Read in the Data:
fid = fopen(aFilename);
for ind = 1:n
lineID = fgetl(fid);
dataLine = fscanf(fid, formatStr);
dataLineComplex = dataLine(1:2:end) + dataLine(2:2:end)*1i;
data(ind, :) = dataLineComplex;
end
fclose(fid);
(edit) This function can be improved by including the (1) parts in the format string and throwing them out:
function data = readData(aFilename, m,n)
% if no parameters were passed, use these as defaults:
if ~exist('aFilename', 'var')
m = 128;
n = 200;
aFilename = 'post.txt';
end
% init format stuff:
formatStr = ['(%*d)\n' repmat('%f%f\n', 1, m)];
% Read in the Data:
fid = fopen(aFilename);
data = fscanf(fid, formatStr);
data = data(1:2:end) + data(2:2:end)*1i;
data = reshape(data, n,m);
fclose(fid);
I have large .bin files (10GB-60GB) created by Labview software, the .bin files represent the output of two sensors used from experiments that I have done.
The problem I have is importing the data into Matlab, the only way I have achieved this so far is by converting the .bin files to .txt files in Labview software then Importing the data into MATLAB using the following code:
Nlines = 1e6; % set number of lines to sample per cycle
sample_rate = (1); %sample rate
DECE= 1000;% decimation factor
TIME = (0:sample_rate:sample_rate*((Nlines)-1));%first inctance of time vector
format = '%f\t%f';
fid = fopen('H:\PhD backup\Data/ONK_PP260_G_text.txt');
while(~feof(fid))
C = textscan(fid, format, Nlines, 'CollectOutput', true);
d = C{1}; % immediately clear C at this point you need the memory!
clearvars C ;
TIME = ((TIME(end)+sample_rate):sample_rate:(sample_rate*(size(d,1)))+(TIME(end)));%shift Time along
plot((TIME(1:DECE:end)),(d(1:DECE:end,:)))%plot and decimate
hold on;
clearvars d;
end
fclose(fid);
The basic idea behind my code is to conserve RAM by reading Nlines of data from .txt on disk to Matlab variable C in RAM, plotting C then clearing C. This process occurs in loop so the data is plotted in chunks until the end of the .txt file is reached.
I want to read the .bin file directly into MATLAB rather than converting it to .txt first because it takes hours for the conversion to complete and I have a lot of data. Here are some examples of my data but in manageable sizes:
https://www.dropbox.com/sh/rzut4zbrert9fm0/q9SiZYmrdG
Here is a description of the binary data:
http://forums.ni.com/t5/LabVIEW/Loading-Labview-Binary-Data-into-Matlab/td-p/1107587
Someone has all ready written a Matlab script to import Labveiw .bin files but their script will only work with very small files:
% LABVIEWLOAD Load Labview binary data into Matlab
%
% DATA = LABVIEWLOAD(FNAME,DIM); % Loads the Labview data in binary
% format from the file specified by FNAME, given the NUMBER of
% dimensions (not the actual dimensions of the data in the binary
% file) of dimensions specified by DIM.
%
% LABVIEWLOAD will repeatedly grab data until the end of the file.
% Labview arrays of the same number of dimensions can be repeatedly
% appended to the same binary file. Labview arrays of any dimensions
% can be read.
%
% DATA = LABVIEWLOAD(FNAME,DIM,PREC); % Loads the data with the specified
% precision, PREC.
%
% Note: This script assumes the default parameters were used in the
% Labview VI "Write to Binary File". Labview uses the Big Endian
% binary number format.
%
% Examples:
% D = labviewload('Data.bin',2); % Loads in Data.bin assuming it
% contains double precision data and two dimensions.
%
% D = labviewload('OthereData.bin',3,'int8'); % Loads in
% OtherData.bin assuming it contains 8 bit integer values or
% boolean values.
%
% Jeremiah Smith
% 4/8/10
% Last Edit: 5/6/10
function data = labviewload(fname,dim,varargin)
siz = [2^32 2^16 2^8 1]'; % Array dimension conversion table
% Precision Input
if nargin == 2
prec = 'double';
elseif nargin == 3
prec = varargin{1};
else
error('Too many inputs.')
end
%% Initialize Values
fid = fopen(fname,'r','ieee-be'); % Open for reading and set to big-endian binary format
fsize = dir(fname); % File information
fsize = fsize.bytes; % Files size in bytes
%% Preallocation
rows = [];
columns = [];
I = 0;
while fsize ~= ftell(fid)
dims = [];
for i=1:1:dim
temp = fread(fid,4);
temp = sum(siz.*temp);
dims = [dims,temp];
end
I = I + 1;
% fseek(fid,prod(dims)*8,'cof'); % Skip the actual data
temp = fread(fid,prod(dims),prec,0,'ieee-be'); % Skip the actual data (much faster for some reason)
end
fseek(fid,0,'bof'); % Reset the cursor
data = repmat({NaN*ones(dims)},I,1); % Preallocate space, assumes each section is the same
%% Load and parse data
for j=1:1:I
dims = []; % Actual array dimensions
for i=1:1:dim
temp = fread(fid,4);
temp = sum(siz.*temp);
dims = [dims,temp];
end
clear temp i
temp = fread(fid,prod(dims),prec,0,'ieee-be'); % 11 is the values per row,
% double is the data type, 0 is the bytes to skip, and
% ieee-be specified big endian binary data
%% Reshape the data into the correct array configuration
if dim == 1
temp = reshape(temp,1,dims);
else
evalfunc = 'temp = reshape(temp';
for i=1:1:dim
evalfunc = [evalfunc ',' num2str(dims(dim-i+1))];
end
if dim ~= 2
eval([evalfunc ');'])
else
eval([evalfunc ')'';'])
end
end
data{j} = temp; % Save the data
end
fclose(fid); % Close the file
The code has the following error message, when you try to process even relatively small .bin files:
Error using ones
Maximum variable size allowed by the program is exceeded.
Error in labviewload (line 65)
data = repmat({NaN*ones(dims)},I,1); % Preallocate space, assumes each section is the same
Can you help me modify the code so that I can open large .bin files? Any help will be much appreciated.
Cheers,
Jim